The implementation of sustainable practices, such as the use of renewable sources and efficient technologies, is crucial for reducing climate change. Energy efficiency is highly important on a global scale due to its relationship with climate change, aiming to minimize environmental impact. In Spain, renewable energy policies have increased self-sufficiency and reduced the use of fossil fuels. Optimizing energy consumption in residences, buildings, and industries is essential for improving efficiency. This was taken into consideration for conducting this study, focusing on the residential sector. The desire to understand the level of energy efficiency in Extremadura drove this project, which focuses on collecting and analyzing data on a set of homes located in the au-tonomous community of Extremadura, with the purpose of evaluating their energy efficiency. To achieve this, a computer tool will be employed to provide a detailed view of the different levels of energy efficiency present in the community. In addition to data collection and analysis, research will be conducted to identify areas for improvement. This will allow proposing a series of specific measures that users can implement to optimize energy efficiency in their homes, adapting them to the particular characteristics of each residence.

“Energy” is probably the most important term in science and technology. The reason is energy can be converted while it is overall conserved, and thereby correlates changes of a wide variety. Despite its successful use in many areas over more than a century, an analysis of current literature shows that definitions of what energy is and explanations why it is conserved are inconsistent. With regard to energy forms not even a definition was found, and examples given are often wrong. Looking at two interacting objects in the most simple situations, with energy conservation but without conversion, a consistent understanding of energy and its conservation can be derived. Based on it, the systematic set of energy forms with a clear definition of each is then presented.

In this paper, solar irradiance and wind speed forecasts were performed considering time horizons ranging from 10 min to 60 min, under a 10 min time-step. Global horizontal irradiance (GHI) and wind speed were computed using four forecasting models (Random Forest, k-Nearest Neighbours, Support Vector Regression, and Elastic Net) to compare their performance against two alternative dynamic ensemble methods (windowing and arbitrating). Forecasting models and dynamic forecasting ensembles were implemented in Python for performance evaluation. The performance comparison between the prediction models and the dynamic ensemble methods was carried out by evaluating the RMSE, MAE, R² and MAPE, to evaluate whether the dynamic ensemble forecasting method obtained greater. According to the results obtained windowing dynamic ensemble method was the most efficient among the tested. For the wind speed data, by varying its parameter λ (from 1 to 100), a variable performance profile was obtained, where from λ =1 to λ = 74, windowing proved to be the most efficient, reaching maximum efficiency for λ = 19. Windowing was the best method for the GHI analysis, reaching its best performance for λ = 1. The efficiency gain using windowing was 0.56% when using the wind speed model and 1.96% for GHI.

A Life Cycle Analysis was performed considering three existing power plants of comparable size operating with different sources of renewable energy: geothermal, solar and wind. Primary data were used for building the life cycle inventories. The geothermal power plant includes emissions treatment for removal of hydrogen sulfide and mercury. The scenario about the substitution of natural emissions from geothermal energy, with specific reference to the greenhouse effect, is also investigated performing a sensitivity analysis. The results are characterized employing a wide portfolio of environmental indicators employing the Recipe 2016 and the ILCD 2011 Midpoint+ methods; normalization and weighting are also applied using the Recipe 2016 method at endpoint level. The results demonstrate a good eco-profile of geothermal power plant with respect to other renewable energy systems and allow for a critical analysis to support potential improvements of the environmental performances.

In the Kingdom of Saudi Arabia (KSA), residential buildings’ energy consumption accounts for almost 50% of the building stock electricity consumption. The electricity generation consumes over one-third of the daily oil production. KSA was ranked as one of the highest countries in fossil fuel consumption per capita in 2014. Moreover, the KSA’s economy heavily relies on fossil fuel sources, namely oil reservoirs, whereby depletion will negatively affect the future development of the country. The total electricity consumption is annually growing by approximately 5-8%, which would lead to identical oil consumption to oil production in 2035. Currently, the KSA government is concerned to generate more renewable energy using large renewable energy plants. The government is investing in energy generation through renewable sources, by financing large scale photovoltaic farms to stop an economic crisis that may occur in 2035. The existing building stock consumes around 80% of the total current Saudi electricity that is generated. According to the Saudi energy efficiency report, the primary energy consumption per capita is over three times higher than the world average. Therefore, the residential buildings need further assessment as to their current energy consumption. This research used a survey to explore current user behaviour in residential buildings energy performance in the city of Jeddah, KSA. The findings of the survey showed: • The buildings thermal properties were found to be poorly designed • The majority of users within the buildings prefer a room temperature of below 24 °C, which requires a massive amount of cooling • Due to the climate conditions and the cultural aspects of KSA, housing units are occupied for more than 18 hours per day • An increase in user awareness has helped to slightly improve residential buildings energy efficiency Knowing the current high energy consumption sources and causes and being able to define available opportunities for further developments on building thermal properties enhancements and how to increase user awareness to reach self-sustaining buildings is essential.

An energy diagnosis is a tool used to seek the improvement of energy saving measures, environmental conservation and energy efficiency, making relevant its implementation in any kind of buildings. For this article, an energy diagnosis of third level was carried out in buildings of the Instituto de Energías Renovables (IER) from Universidad Nacional Autónoma de México (UNAM) through survey and census of the 36 buildings in the IER, in order to characterize current patterns of energy consumption and demand, and generating specific strategies towards savings and energy efficiency, such as indicators and corrective proposals within and non-financial investment.

In the face of escalating climate concerns and the push for sustainable development, the global shift towards renewable and decentralized energy systems presents new challenges and opportunities. This study investigates integrating decentralized energy production, particularly photovoltaic (PV) systems, into national energy planning, aiming to optimize energy strategies that balance local production and consumption with national objectives. By analyzing the Swiss energy model, the research employs the EnergyScope and REHO models to assess the strategic implications of decentralized versus centralized energy systems. Results show that a decentralized approach can significantly reduce PV installation needs to 35 GW, about 23% of potential capacity, and decrease annual system costs by 10% to CHF 1230 per capita. This strategy emphasizes local consumption, minimizes grid reinforcement demands, and leverages economic advantages while addressing overproduction challenges through effective energy storage and grid management. Conclusions underline the strategic value of combining centralized and decentralized methods for resilient and sustainable energy planning. The study contributes to the discourse on energy policy and infrastructure planning, advocating for a hybrid model that accommodates both local conditions and broader energy objectives, urging further research into climate impacts and technology integration for a comprehensive energy future.

Energy efficiency is, in principle, a simple idea: an output of human value, for example, vehicle-km traveled, divided by the needed input energy. Efficiency improvements are regarded by many as an important means of mitigating not only climate change, but also other environmental problems. Accordingly, many countries have efficiency ratings for appliances and efficiency standards for road vehicles. Despite the vast number of articles published on energy efficiency, few question whether it is a useful or accurate measure in its present form. This review addresses this lack, by a critical review of the literature, not only in energy efficiency, but in other areas of research, such as ‘energy services’, that can help broaden the scope of this idea, both geographically and conceptually. These shortcomings are illustrated in case studies of road passenger transport and buildings. The main findings are that energy efficiency inevitably has an ethical dimension, that feedbacks are more widespread than generally considered, and that conventional efficiency measures omit important energy input items, particularly those concerned with mining of the materials needed for renewable energy plants. Finally, the key results of this review are summarized, and its limitations are discussed, as is the future research needed to overcome these shortcomings.

In this study, we propose a module-type triboelectric nanogenerator (TENG) capable of harvesting power from a variety of mechanical energy sources. The potential energy and kinetic energy of water are used for the rotational motion of the generator module, and electricity is generated by the contact/separation generation mode between the two triboelectric surfaces inside the rotating TENG. Through the parametric design of the internal friction surface structure and mass ball, we optimized the output of the proposed structure. To magnify the power, experiments were conducted to optimize the electrical output of the series of TENG units. The electrical signal generated by the module-type TENG can be used as a sensor to recognize the strength and direction of various physical quantities, such as wind or earthquake vibrations.

This work proposes a hollow-core photonic crystal fiber-based edible oil sensor in the terahertz (THz) range (e.g., 1.0THz ≤ f ≤ 3.0THz) and different sensing characteristics are numerically analyzed. The suggested sensor’s performance was assessed by means of COMSOL Multiphysics, a commercial program that uses the finite element approach. The computational results indicate that the relative sensitivity is 85.591%, 84.648%, 82.625%, 82.683%, and 79.161%, respectively, at f = 2.2 THz, for several types of sunflower oil, mustard oil, coconut oil, olive oil and palm oil; and the corresponding effective areas are 7.22×10-8 um2, 7.09×10-8 um2, 6.83×10-8 um2,7.09×10-8 um2, 6.5231 ×10-8 um2. In addition, the effective material loss for sunflower oil, muster oil, coconut oil, olive oil, and palm oil has been found to be 0.02561 cm-1, 0.027054 cm-1, 0.030322 cm-1, 0.028854 cm-1 ,0.035427cm-1 respectively. Moreover, the proposed sensor also has low confinement loss are 1.55×10-8 dB/m, 1.63×10-8 dB/m, 1.31×10-8 dB/m, 1.99×10-8 dB/m, 4.0345×10-8 dB/m.This proposed sensor can be fabricated using extrusion and 3D-printing technologies, and due to its augmented detecting capabilities, it can be a vital part of oil sensing devices implemented in real life such as industry fields.

Selection of the most suitable material is one of the key decisions to be taken at the design stage of a manufacturing process. Traditional approaches as Ashby maps based on material properties are widely used in the industry. However, in the production of multimaterial components, the criteria for the selection can include antagonistic approaches. The aim of this work is the implementation of a methodology based on the results of process simulations for several materials and classify them by applying an advanced data analytics method based on Machine Learning (ML), in this case the Support Vector Regression (SVR) and Multi-Criteria Decision Making (MCDM) methodolo-gies, in this case Multi-criteria Optimization and Compromise Solution (VIKOR) combined with Entropy weighting methods. In order to do this, a Finite Element Model (FEM) has been built to evaluate the extrusion force and the die wear in a multi-material co-extrusion process of bimetallic Ti6Al4V-AZ31B billets. After applying SVR and VIKOR combined with Entropy weighting methodologies, a comparison has been established based on the material selection and complexity of the methodology used, resulting that material chosen in both methodologies is very similar and MCDM method is easier to implement because there is no need of evaluate the error of the pre-diction model and the time for data preprocessing is less than the time needed in SVR.

This study investigates the elastic buckling behaviour of skew Functionally Graded Material (FGM) thin plates featuring a circular opening. FGM materials, known for their unique property gradients, have gained prominence in structural engineering due to their mechanical performance and durability. Including a circular opening introduces a critical geometric consideration, influencing the structural stability and load-carrying capacity of FGM plates. The study examines the effects of the skew angle, plate’s aspect ratio, opening position, and size on the critical buckling load, normalized buckling load, and various buckling failure modes through computer modelling and finite element analysis. The results offer valuable insights into the interplay between material heterogeneity, geometric configuration, and structural stability. For instance, the critical buckling load increases by 29%, 82%, and 194% with the increment of skew angle from 0° to 30°, 45°, and 60°, respectively. Moreover, as the opening shifts from the plate’s edge closer to the center, the critical buckling load decreases by 26%. This research contributes to the advancement of understanding FGM thin plates’ behaviour under skew loading conditions, with implications for the design and optimization of innovative structures. The findings presented provide a foundation for further exploration of advanced composite materials and their applications in structural engineering.

Modular high-rise buildings frequently adopt cast-in-place concrete to ensure building integrity. To reduce the material consumption and realize mold-free casting, a 30 mm thick light concrete mold shell wall panel ( MiC wall panel) is set as part of the shear wall. But the concrete casting process is prone to cracking and rising pattern. Its force performance and damage mechanism is not clear. To this end, this paper designs three groups of MiC wall panels with different material component types. The static load test is carried out in a graded partitioned loading mode. The effects of different material components on the mechanical properties of MiC wall panels are systematically investigated and parametrically analyzed by numerical simulation. The results show that the front cracks of the wall slab are mainly distributed under the truss tendons, and the back cracks are mainly distributed in the span position of the adjacent truss tendons. They are both along the span direction of the wall slab. Increasing the strength level of concrete and using steel fiber concrete can improve the mechanical properties of MiC wall panels to different degrees. Among them, increasing the concrete strength has a significant effect on improving the load-bearing capacity of wall panels, while incorporating steel fibers can significantly improve the deformation and crack resistance of wall panels. By building more finite element models, it was verified that the steel fiber admixture has limited effect on the mechanical properties of wall panels as the concrete grade increases. This study aims to summarize the types of wall panels with the best working properties. It provides a practical basis for optimizing the production and fabrication process of MiC wall panels.

Extrusion-based additive manufacturing (AM) technologies (i.e., fused filament fabrication, FFF) mostly produce thermoplastic parts. However, producing metallic or ceramic parts by FFF is also a sintered-based AM process. FFF for metallic parts can be divided into five steps: (1) raw materials selection and feedstock mixture (including palletization), (2) filament production (extrusion), (3) production of AM components using the filament extrusion process, (4) debinding, and (5) sintering. These steps are interrelated, where the parameters interact with the other ones and have a key role in the integrity and quality of the final metallic parts. FFF can produce high-accuracy and complex metallic parts, potentially revolutionizing the manufacturing industry and taking AM components to a new level. In the FFF technology for metallic materials, material compatibility, production quality, and cost-effectiveness are the challenges to overcome to make it more competitive compared to other AM technologies, like the laser processes. This review provides a comprehensive overview of the recent developments in FFF for metallic materials, including the metals and binders used, the challenges faced, potential applications, and the impact of FFF on the manufacturing (prototyping and end parts), design freedom, customization, sustainability, supply chain, among others.

Wearable touch sensors, which can convert force or pressure signals into quantitative electronic signals, have emerged as an essential smart sensing devices and played an important role in various cutting-edge fields, including wearable health monitoring, soft robots, electronic skin, artificial prosthetics, AR/VR, and the Internet of Things. Flexible touch sensors have made significant advancements, while construction of novel touch sensors via mimicking the unique properties of biological materials and biogenetic structures always remains a hot research topic and significant technological pathway. This review provides a comprehensive summary of the research status of wearable touch sensors constructed by imitating the material and structural characteristics in nature, and also summarizes the scientific challenges and development tendency of this aspect. Firstly, the research status for constructing flexible touch sensors based on biomimetic materials is summarized, including hydrogel materials, self-healing materials, and other bioinspired or biomimetic materials with extraordinary properties. Then, design and fabrication of flexible touch sensors based on bionic structures for performance enhancement are fully discussed. These bionic structures include special structures in plants, special structures insects/animal, and special structures in human body. Moreover, a summary of the current issues and future prospects for developing wearable sensors based on bioinspired materials and structures is discussed.

The decreasing width, increasing aspect ratio RDL presents significant challenges to design for reliability (DFR) of advanced package. Therefore, this paper proposes a ML based RDL modeling and simulation method. In the method, RDL is divided into blocks and subdivided into pixels of metal percentage, and the RDL is digitalized as tensors. Then, an ANN-based surrogate model is built and trained by a subset of tensors to predict the equivalent material properties of each block. Lastly, all blocks are transformed into elements for simulations. For validation, line bending simulations were conducted on an RDL, with the reaction force as accuracy indicator. The results show that neglecting layout impact causes critical errors as substrate thins. By the method, the reaction force error is 2.81% and the layout impact can accurately be considered with 200×200 elements. For application, the TCT maximum temperature state simulation was conducted on a CPU chip. The simulation indicates that for advanced package the maximum stress more likely occurs in RDL rather than bumps, both RDL and bumps are critical impacted by layouts, and RDL stress is also impacted by vias/bumps. The proposed method precisely concerns layout impacts with little resources, presents an opportunity of efficiency improvement.

Polymeric composites such as Poly-ether-ether-ketone (PEEK)/carbon fiber (CF) have been widely utilized due to outstanding performances such as high specific strength and specific modulus. The PEEK/CF components via powder-bed fusion additive manufacturing usually show brittle fracture behaviors induced by their poor interfacial affinity and inner voids. These defects are strongly associated with powder packing quality upon deposition. The particle dynamic model has been widely employed to study the interactions of particle motions. Powder property, bulk material property, and interfacial features of composite powders are key factors in the particle dynamic model. In this work, an efficient and systematic material evaluation is developed for composite powders to investigate their deposition mechanism. The discrete element method is utilized to simulate the dynamic behaviors of PEEK/CF composite powders. The powder properties, bulk material properties, and interfacial features of powders are calibrated and justified by experimental measurement, numerical simulation, and design of experiments. The particle dynamic model can well explain the powder flow behaviors and interactions. It reveals that the addition of short CF particles can assist the flow of PEEK powders and improve the packing quality of the composite powders.

Applying of blood biopolymers to regulate the phase composition is promising in designing the hydroxyapatite-based hybrid biomaterials with controllable resorbability. Hybrid materials based on hydroxyapatite and platelet-poor plasma (PPP) were formed in conditions of chemical precipi-tation at pH 11, [Ca2+] / [PO43–] ratio 1.67, PPP volume fraction of 6–24%, maturing time of 4–9 days. Mineral component of the materials was represented as 53% hydroxyapatite / 47% amor-phous calcium phosphate after 4 days of maturation, and 100% hydroxyapatite after 9 days of maturation. Varying PPP content from 6% to 24% provided forming of materials with rather de-fined content of amorphous calcium phosphate and biopolymer component, having desired mor-phology ranging from typical apatitic conglomerates to hybrid apatite-biopolymer fibers. Co-precipitated hybrid materials based on hydroxyapatite and PPP are promising for bone regen-eration in osteoplastic and maxillofacial applications.

Аннотация . Периодически развиваются самоподобные движения структурно-вещественных комплексов (СМК) из состава Солнечной системы в течение периода около 4,5 миллиардов лет земной коры, развития Земли в условиях самоорганизации. Синхронные или близкие во времени ряды генетических или парагенетических групп магматических, рудно-минеральных, метасоматических, осадочных образований, их структур и других сопутствующих им процессов, включают в себя каждый комплекс (ГМК). Каждый комплекс в его пределах ограничен во времени и пространстве, по причине признаков самопроизвольного динамического процесса; распространяется на территорию Земли в текущий исторический период; формирует состав и структуру земной коры на этом этапе, определяя ее полициклическое развитие. Количество циклов около 14,

Magnetoelectric (ME) sensor is a new type magnetic sensor with ultrahigh sensitivity, low power consumption, and suitable for the measurement of low frequency weak magnetic field. In this study, metglas/PZT-5B ME sensor with a mechanical resonance frequency f_res of 60.041 kHz was prepared. It is interesting to note that its magnetic field resolution reaches 0.20 nT at f_res and 0.34 nT for DC field, respectively. In order to measure the ultralow frequency AC magnetic fields, a frequency upconversion technique was employed. Under this technique, a limit of detection (LOD) of AC magnetic field lower than 1 nT at 8 Hz is obtained, and the minimum LOD of 0.51 nT is achieved at 20 Hz. The high resolution ME sensor with sub-pT level is promising in the field of low frequency weak magnetic field measurement technology.

This study employs a high-fidelity numerical framework to determine the plastic material flow patterns and temperature distributions that lead to void formation during friction stir welding (FSW), and to relate the void morphologies to the underlying alloy material properties and process conditions. Three aluminum alloys, viz., 6061-T6, 7075-T6, and 5053-H18 were investigated under varying traverse speeds. The choice of aluminum alloys enables investigation of a wide range of thermal and mechanical properties. The numerical simulations were validated using experimental observations of void morphologies in these three alloys. Temperatures, plastic strain rates, and material flow patterns are considered. The key results from this study are: (1) The predicted stir zone and void morphology are in good agreement with the experimental observations, (2) The temperature and plastic strain-rate maps in the steady-state process conditions show a strong dependency on the alloy type and traverse speeds, (3) The material velocity contours provide a good insight into the material flow in the stir zone for the FSW process conditions that result in voids as well as those that do not result in voids. The numerical model and the ensuing parametric studies presented in this work provide a framework for understanding material flow under different process conditions in aluminum alloys, and potentially in other alloys. Furthermore, the utility of the numerical model for making quantitative predictions and investigating different process parameters to reduce void formation is demonstrated.

Laminate structures composed of stiff plates and thin soft interlayers are widely used in aerospace, automotive and civil engineering encouraging the development of reliable non-destructive strategies for their condition assessment. In the paper, elastodynamic behaviour of such laminate structures is investigated with emphasis on its application in ultrasonic based NDT and SHM for the identification of interlayer mechanical and interfacial contact properties. A particular attention is given to the practically important frequency range, in which the wavelength considerably exceeds the thickness of the film. Three layer model with spring-type boundary conditions employed for imperfect contact simulation is used for numerical investigation. Novel effective boundary conditions are derived via asymptotic expansion technique and used for analysis of the peculiar properties of elastic guided waves in considered laminates. It is revealed that the thin and soft film influences the behaviour of the laminate mainly via the effective stiffnesses being a combination of the elastic moduli of the film, its thickness and interface stiffnesses. To evaluate each of these parameters separately (or to figure out that the available experimental data are insufficient), a step-wise procedure employing the effective boundary conditions is proposed and tested versus the laser Doppler vibrometry data for Lamb waves in Aluminium/Polymer film/Alumunium structure. The possibility of using film-related thickness resonance frequencies to estimate the film properties and contact quality is also demonstrated. Additionally, the rich family of edge waves is also investigated, and the splitting of fundamental edge waves into pairs is revealed.

We report a self-assembly synthesis of silicon nanoparticles/nitrogen-doped reduced graphene oxide/ carbon nanofiber (Si@N-doped rGO/CNF) composites as potential high-performance anodes for rechargeable lithium-ion batteries (LIB) through the electrostatic attraction between amino and carboxyl groups. Nitrogen atoms generate a large number of vacancies or defects on the graphite plane, providing additional transmission channels for the diffusion of lithium ions, and improving the conductivity of the electrode. Carbon nanofiber (CNF) can help maintain the stability of the electrode structure and prevent silicon nanoparticles from falling off the electrode, prevent silicon nanoparticles from being directly exposed to the electrolyte, and can form a stable solid electrolyte interface (SEI) film. The three-dimensional conductive structure composed of Si, nitrogen atom-doped reduced graphene oxide (N-doped rGO), and CNF can effectively buffer the volume changes of silicon nanoparticles, shorten the transmission distance of lithium ions (Li+) and electrons, and make the electrode have good conductivity and stability in mechanical properties. In addition, compared with the Si@N-doped rGO and Si/rGO/CNF composite electrode, the Si@N-doped rGO/CNF composite electrode shows good cycle performance and rate capability, and its reversible specific capacity can reach 1418.8 mAh/g. The capacity retention rate is 64.7%, and the coulomb efficiency is 95%.

Fabric material was coated with Viruferrin™ and tested for its inactivating properties against the pandemic severe acute respiratory syndrome 2 (SARS-CoV-2) and influenza A viruses. A statistically significant (p<0.0001) decrease in the number of infectious virus particles exposed to Viruferrin-treated fabric when compared with the cotton control for both SARS-CoV-2 and influenza A viruses was observed. For both SARS-CoV-2 and influenza A, Viruferrin-treated fabrics experienced a > 99% virus reduction without saliva after five minutes of contact when compared to the positive control at time point 0. Furthermore, the reusability of the Viruferrin treated fabric was demonstrated by stability for up to 10 washes. The level of anti-viral (SARS-CoV-2) activity remained constant from 5 to 10 washes and demonstrated a significant difference (p<0.0001) from the unwashed untreated material. Applications for this treated fabric are far-reaching, and as a biological face covering offers not only a unique 2-way protection but also is unlikely to cause onward touch transmission.

Additive manufacturing (AM) is an emerged layer-by-layer manufacturing process. However, its broad adoption is still hindered by limited material options, different fabrication defects, and inconsistent part quality. Material extrusion (ME) is one of the most widely used AM technologies, and, hence, is adopted in this research. Low-cost metal ME is a new and AM technology used to fabricate metal composite parts using sintered metal infused filament material. Since the involved materials and process are relatively new, there is a need to investigate the dimensional accuracy of ME fabricated metal parts for real-world applications. Each step of the manufacturing process, from the material extrusion to sintering, might significantly affect the dimensional accuracy. This research provides a comprehensive analysis of dimensional changes of metal samples fabricated by the ME and sintering process, using statistical and machine learning algorithms. Machine learning (ML) methods can be used to assist researchers in sophisticated pre-manufacturing planning and product quality assessment and control. This study compares linear regression to neural networks in assessing and predicting the dimensional changes of ME made components after 3D printing and sintering process. The prediction outcomes using a neural network performed the best with the highest accuracy as compared to regression. The findings of this study can help researchers and engineers to predict the dimensional variations and optimize the printing and sintering process parameters to obtain high quality metal parts fabricated by the low-cost ME process.

We investigated the properties of architected materials made from UV-cured urethane elastomers and the use of such materials for insoles. The durability and reliability of various materials currently used in medical insoles were compared with those of architected materials with microlattice. The results show that architected materials made from UV-cured urethane elastomers have high impact resilience and grip, and the hardness can easily be changed by adjusting the column diameter of the unit cell. Compared with the foam materials used for medical insoles today, these architected materials also demonstrate superior UV resistance, suggesting that, after being washed in water, they can be air-dried outdoors.

In this paper, we have numerically investigated a metasurface based perfect absorber design established on the impedance matching phenomena. The paper comprises of two parts. In the first part, the device performance of the perfect absorber is studied which is composed of a silicon Nano-cylindrical meta-atoms periodically arranged on the thin gold layer. The device design is unique which works for both x-oriented and y-oriented polarized light, besides independent of the angle of incidence. In the second part of the paper, CO2 gas sensing application is explored by depositing a thin layer of functional host material polyhexamethylene biguanide polymer on the metasurface. The refractive index of the host material decreases due to the absorption of the CO2 gas. As a result, the resonance wavelength of the perfect absorber performs a prominent blueshift. With the help of the proposed sensor design based on metasurface, the CO2 gas concentration range of 0-524 ppm is detected. The maximum sensitivity of ~17.3 pm/ppm is acquired for the gas concentration of 434 ppm. The study presented in this work explores the opportunity of utilizing metasurface perfect absorber for gas sensing applications by employing the functional host materials.

Thermal interface material (TIM) that can exist as liquid at the service temperature enables efficient heat transfer across two adjacent surfaces in electronic applications. In this work, the thermal conductivities of different phase regions in the Ga-In system at various compositions and temperatures are measured for the first time. A modified comparative cut bar technique is used for the measurement of the thermal conductivities of In_xGa_1-x (x=0, 0.1, 0.214, 0.3, and 0.9) alloys at 40, 60, 80, and 100^oC that are the temperatures commonly encountered in consumer electronics. The thermal conductivity values for the liquid and semi-liquid (liquid+β) Ga-In alloys are higher than the TIM currently used in consumer electronics. These measured quantities, along with the available experimental data from the literature, served as input for the thermal conductivity parameter optimization using the CALPHAD (CALculation of PHase Diagram) method for the pure elements, solution phase, and two-phase region. A set of self-consistent parameters for the description of the thermal conductivity of the Ga-In system is obtained. There is good agreement between the measured and calculated thermal conductivity values for all the phases. Hence, it can be envisaged that liquid/semi-liquid Ga-In alloys can be considered as a potential TIM in consumer electronics due to its high thermal conductivity.

In an attempt to improve the quality of the agricultural drain in Egypt for its reuse again in the irrigation, low cost solution such as sand filter along with/ without other filtration media have been used in this research, As a result of that, pilot plant of sand filter mixed with other filtration media was tested for its ability to improve the sand performance in removing the suspended solids and organic matters from agricultural drain water of the Belbeis drain (in Sharkia governorate in Egypt). Only sand compared with sand with sponge and sand with Liyan Nanfang activated carbon (L.N.A.C) have been tested to find the optimum mixing sand/ medium ratio &optimum infiltration rate. The work has been done on four runs. It was found that sand mixed with sponge gave the best removal efficiency compared to that of the sand only and the sand mixed with L.N.A.C. The results presented that the concentration of CODt, CODsol and TSS was reduced from 125, 47 and 162 mg/l to 44, 34 and 28 mg/l respectively at optimum infiltration rate of 2 m³/m²/d for sand mixed with sponge.

The recycling, incineration, and final disposal rate of municipal solid waste (MSW) are calculated based on the total amount of waste input to each facility in many countries. These statistic data have serious limitation in setting the national goal and policy for effective waste management because it is not considering the amount of foreign objectives in the process of each life-cycle stage. This case study is to estimate the actual rates of recycling, incineration, and final disposal by material flow analysis (MFA) after the collection of MSW in Korea. The actual rates of recycling, incineration and final disposal for MSW in 2016 were 49.9%, 32.9% and 23.1% respectively, indicating that the recycling rate was lower by 10.1%, while the incineration and final disposal rates were raised by 7.6% and 8.4% respectively, compared with the statistics for current MSW. In addition, the changed actual rates of recycling, incineration treatment, and final landfill, and variation of waste treatment charge according to treated amounts per treatment method was analyzed. This results of this study will contribute to establish national level of plan on effective waste management.

The aim of this study is to introduce a novel method which can separate sand or gravel dominated bed load transport in rivers with mixed-size bed material. In engineering practice, the Shields-Parker diagram could be used for such purposes, however, the method has certain applicability limits, due to the fact that it is based on uniform bed material and provides information rather on river-scale, instead of reach or local scale. When dealing with large rivers with complex hydrodynamics and morphodynamics the bed load transport modes can also indicate strong variation even locally, which requires a more suitable approach to estimate the locally unique behavior of the sediment transport. Here, we suggest that the decision criteria utilizes the shear Reynolds number (Re*). The method was verified against field and laboratory measurement data, both performed at non-uniform bed material compositions. The comparative assessment of the results show that the shear Reynolds number based method operates more reliably than the Shields-Parker diagram and it is expected to predict the sand or gravel transport domination with a < 5% uncertainty. The introduced results can greatly contribute to the improvement of numerical sediment transport modeling as well as to the field implementation of bed load transport measurements.

The paper examines the evolution and crucial role of energy communities in the context of the transition to renewable energy sources. Such communities are presented as an innovative and resilient response to the challenges posed by climate change. Their importance emerges from their ability to decentralise energy production, increasing local security and reducing dependence on non-renewable energy sources and external suppliers. However, despite the obvious benefits, the contribution highlights several challenges, such as the need for significant upfront investment and the presence of regulatory barriers that may hinder the integration of these solutions into existing energy systems. A detailed bibliometric analysis is used, focusing on specific research areas and using tools to map the most relevant keywords and emerging trends. The results of the bibliometric analysis highlight how energy communities are emerging as key players in the sustainability landscape, capable of addressing and overcoming contemporary environmental challenges. The research reaffirms the transformative potential of energy communities in promoting a more sustainable and resilient future.

This study explores the crucial roles of energy literacy, transition, and justice in addressing the global climate crisis. Through a systematic bibliometric survey and thematic analysis of existing literature, we identify a scarcity in research (<0.1%, n = 17,773) concurrently integrating the three crucial terms: energy literacy; energy transition; and energy justice. This study emphasizes the importance of energy literacy in empowering societies to make informed decisions, which is essential for facilitating equitable energy transitions and achieving sustainability goals. We delve into the interconnections between energy literacy and energy justice, proposing the integration of these concepts into educational systems, including social media platforms to foster an understanding of energy systems, their environmental impacts, and socio-economic implications. Emphasizing the strategic use of social media, the study also introduces the ‘COMPEL Justice’ framework—Communities Prepared for Energy Literacy and Justice—which aims to enhance public engagement and participation in energy transition initiatives. By analyzing publications from various academic and governmental sources, we provide insights into the challenges and opportunities that lie in promoting energy literacy and justice, particularly in the context of global efforts to mitigate climate change and enhance energy equity. Finally, exemplary application and implications associated with the adoption of the proposed framework within the context of oil-producing regions (e.g., Louisiana in the United States) are presented.

Solar photovoltaic (PV) technology is a cornerstone of the global effort to transition towards cleaner and more sustainable energy systems. This paper explores the pivotal role of PV technology in re-ducing greenhouse gas emissions and combatting the pressing issue of climate change. At the heart of its efficacy lies the efficiency of PV materials, which dictates the extent to which sunlight is transformed into electricity. Over the last decade, substantial advancements in PV efficiency have propelled the widespread adoption of solar PV technology on a global scale. The efficiency of PV materials is a critical factor, determining how effectively sunlight is transformed into electricity. Enhanced efficiency, achieved through a decade of progress, has driven the global expansion of solar PV. Multi-junction photovoltaic materials have now exceeded 40% efficiency in lab tests. China leads the world in solar PV installations, boasting over 253 GW of installed capacity by the end of 2021. Other prominent countries in this sector are the United States, Japan, Germany, and India. Supportive policies like feed-in tariffs, net metering, tax incentives, and cost reductions in PV modules have made solar PV increasingly competitive against fossil fuel-based power generation. Solar PV technology holds immense potential for creating a cleaner, reliable, scalable, and cost-effective electricity system. To expedite its deployment and foster a more sustainable energy future, continued investment in research and development, along with supportive policies and market mechanisms, is essential. This paper underscores the pivotal role of solar PV technology in the global energy transition and advocates for a concerted effort to unlock its full potential in achieving a more sustainable and resilient energy future.

The quickest and easiest way to avoid greenhouse gas (GHG) emissions is to purchase renewable electricity and offset the remaining emissions. However, the industrial sector’s electricity needs already exceed renewable electricity generation. Moreover, electricity accounts for only one third of the industry’s energy needs. Simultaneously, the advance of sectoral coupling and the decarbonisation of industrial processes, as well as the desire to rapidly decrease dependence on fossil fuels, are creating significant additional demand for renewable energy. Neither existing nor planned generation and transmission infrastructure will suffice to meet the expected short-term demand. Based on survey data from the German Industry Energy Efficiency Index, this article therefore examines the share of GHG savings that companies intend to achieve on- and off-site. Understanding how much additional generation and transmission capacity is needed by the industry to decarbonise and by when is crucial to identify and address the extent of excess demand. On average, companies plan to avoid 22 % of their 2019 emissions by 2025 and 27 % by 2030, primarily through on-site measures. In combination with the extrapolation of the entire industry’s needs for off-site capacity, the data calls for a rapid expansion of planning authority and green generation capacities.

This article has been developed to assess the economic feasibility of a roof-top photovoltaic installation of industrial self-consumption. Numerical models that enable an interested person to obtain the main expected parameters will be generated. To do this, a calculation methodology will be generated through which the reader, knowing the location of the facility and dimensions of the roof, will be able to calculate the maximum installable power, the main parameters related to production, the cost of the installation, and the LCOE of the plant. The use of actual costs will be facilitated in case they are known, but it will remain possible to apply the costs of the major equipment (modules, inverter, and structure) considered throughout the article. This developed calculation methodology will also allow a quick comparison of the forecasts of production, CAPEX, and LCOE of plants designed with different inclinations and different types of modules. Consequently, it will be especially useful for decision-making before developing the plant's basic engineering. Moreover, the calculations used for modeling the LCOE will be analyzed in depth. This analysis will allow evaluating how the different technical variables affect the profitability of a photovoltaic installation, such as the selected tilt, the location, the module's technology, or the available area.

The building sector accounts for nearly 40% of total primary energy consumption in the U.S. and E.U. and 20% of worldwide delivered energy consumption. Climate projections predict an increase of average annual temperatures between 1.1-5.4°C by 2100. As urbanization is expected to continue increasing at a rapid pace, the energy consumption of buildings is likely to play a pivotal role in the overall energy budget. In this study we used EnergyPlus building energy models to estimate the future energy demands of commercial buildings in Salt Lake County, Utah, USA, using locally-derived climate projections. We found significant variability in the energy demand profiles when simulating the study buildings under different climate scenarios, based on the energy standard the building was designed to meet, with reductions ranging from 10% to 60% in natural gas consumption for heating and increases ranging from 10% to 30% in electricity consumption for cooling. A case study, using projected 2040 building stock, showed a weighted average decrease in heating energy of 25% and an increase of 15% in cooling energy. We also found that building standards between ASHRAE 90.1-2004 and 90.1-2016 play a comparatively smaller role than variation in climate scenarios on the energy demand variability within building types. Our findings underscore the large range of potential future building energy consumption which depend on climatic conditions, as well as building types and standards.

The conceptual reconstruction of Neiwan powerhouse is one of the key activities under the current ongoing mapping project of Taiwanese hydropower plants that mainly took place between 2013 and 2015 and is now focused on micro, pico, and historical power plants. Judging from the fact that the oldest hydropower plant in Taiwan named Guishan starts its operation in 1905, Neiwan powerhouse was among the very first powerhouses that were built across the island to support the electrification of Taiwan. However, the main function of the single turbine equipped Neiwan micro powerhouse was to support mainly the military needs and protect the territories occupied by Japanese troops. Since the powerhouse was built in 1909 and operates only something about 10 year there are very little physical materials or evidence along with contemporaries. Therefore the further reconstruction is based mainly on physical observation of the remains located at the site, old photographs, related articles, treatises and typology of mechanical and civil constructions of other hydropower plant cases in Taiwan hence this paper´s main intention is to pitch a concept reconstruction rather than definite conclusion.

This research paper is part of the wider project concerning the very first detailed mapping of the overall Taiwanese hydro-power plants that took place from 2013 up to 2015 and it is currently in evaluation and finalization stage. The case of Shanping hydro-power plant has been carefully studied, photographed, documented and mapped in situ. It was one of the isolated hydro-power plant projects originally built to supply the remote area with the specific designation. Shanping hydro-power plant, as well as the other units from the early hydro-power generation era in Taiwan, are considered to be the technological heritage of civil and mechanical engineering that reflects later in all the further projects up to nowadays modern Taiwanese hydro-power plants. Unfortunately, most of the hydro-power houses from the older periods were severely damaged or destroyed by natural causes which were also the case of Shanping unit. The research is trying to reconstruct the original location of the powerhouse and its supporting structures based on available historical documents, previous studies, comparative methodology, and the current on-site observation.

The current energy policy recommends the idea of energy efficiency over fossil energy as a primary matter for the coming years. The kingdom of Morocco requires restructuring of its power equipment by increasing the percentage of renewable energy supplies, optimizing their systems and power storage. Therefore, increasing energy efficiency is an as important obligation as reducing the overall energy consumption. The purpose of this research is to present the energy transition in Morocco towards renewable energies and to assess the diversity of available marine natural resources. Recent research in conversion of ocean thermal energy, wave energy, tidal energy, offshore wind energy, and osmotic energy into power supply has started to encourage different technologies. This research has led to commercial deployment in some cases such as our 550 km long Mediterranean coast and 3000 km long Atlantic. This does not only result in fossil energies independency but also provides advantages like less cost and no pollution.

Many research work has demonstrated that taken the Combined Cooling Heating and Power system (CCHP) as the core equipment, the integrated energy system (IES) can bring obvious benefit to energy efficiency, CO2 emission reduction and operation economy in urban areas. Compared with isolated IES, integrated energy micro-grid (IEMG) which is formed by connecting multiple regions IES together, through distribution and thermal network, can further improve the reliability, flexibility, cleanliness and economy of regional energy supply. Based on the existing IES model, this paper describes the basic structure of IEMG and built a IEMG planning model. The planning based on the mixed integer linear programming, and economically construction planning scheme are calculated by using known electricity, heating and cooling loads information and the given multiple equipment selection schemes. At last, the model is validated by a case study. The results show that the application of IEMG can effectively improve the economy of regional energy supply.

This paper focuses on designing and assessing Pumped Hydroelectric Energy Storage Systems (PHES), connected to the grid and PV system for self-consumption structured at Mutah university in an area of high solar potential. In focusing on PHES and PV literature was made to have data on the field, based on the grid code needed in Jordan. Next, a prospection to find the proper location for the installation was done. Afterward, a load profile was inserted to know the energy demand of the university. Then The productivity of the solar power plant of Mutah University was included. Finally, MATLAB software was used to realize the amount of energy to be stored, this data was used to implement the system which was chosen and sized. PHES layout was created to find the most accurate values for parameters to optimize the system performance, and to investigate the loss analysis. The system attains 9230.89 MWh/year. An annual load yields 4430 MWh/year, which covers the Mutah university demand with an estimated saving of 2039773 JD.

This brief commentary challenges the use of the term "energy deficiency" in nutrition and metabolism, providing a critical examination of its scientific and philosophical aspects. It emphasizes the need to consider rare diseases associated with actual energy deficiency, which extend beyond the scope of everyday tiredness or fatigue. By analyzing energy balance and its complexities, this critique underscores the oversimplification associated with the term and its potential for misleading implications. It highlights the dynamic nature of energy metabolism and the intricate mechanisms involved in maintaining energy equilibrium, including the impact of rare genetic and physiological abnormalities. In addition to the discussion on energy balance, this commentary explores the manifestation of rare diseases that disrupt energy production, utilization, or hormonal regulation. Conditions such as mitochondrial diseases, glycogen storage diseases, adrenal insufficiency, and Prader-Willi syndrome are examined, shedding light on their profound impact on individuals' energy levels and overall health. The distinct time courses, underlying mechanisms, and clinical implications of protein deficiency, energy deficiency, and vitamin C deficiency are also compared, further emphasizing the complexity of energy metabolism and its relationship with various nutrient deficiencies. To foster a more comprehensive understanding of energy metabolism and enhance clarity in communication within the field, the commentary proposes the adoption of alternative terminology, such as "energy flux," to capture the multifaceted nature of energy balance more accurately. By reevaluating the terminology employed, researchers and healthcare professionals can better convey the intricate dynamics of energy metabolism and address the unique challenges faced by individuals with rare diseases causing actual energy deficiency. In conclusion, this commentary serves as a thought-provoking exploration of the concept of energy deficiency in nutrition and metabolism. It highlights the limitations of the term in capturing the complexities of energy balance, particularly in the context of rare diseases. By broadening the discussion to include these rare conditions, it encourages a more comprehensive understanding of energy metabolism and calls for precise and nuanced terminology to facilitate effective communication and advancements in the field.

In 2015, Romania was the first country in Europe that achieved EU targets regarding the share of renewables in the generation mix, far ahead of the 2020 deadline. Starting with the energy structure in Romania, the paper: (1) analyses the evolution of the main indicators in the renewable energy sector, (2) discloses the perspectives of renewable energy in Romania synthesizing the main trends of development in the field and (3) analyses the challenges facing with the development of renewable energy in Romania. Based on analyzing the exploratory data, the paper makes a preliminary prediction of the development of the sector for the future decades and proposes targeted countermeasures and suggestions. Romania still has unexploited potential concerning renewable energy sources. Because Romania registered a continuous economic growth, the demand for electricity is steadily growing, and this trend is expected to continue. Also, Romania could introduce a support mechanism for developing the potential of unexploited potential. The results of the present study may be useful for further research regarding public policies for the development of renewable energy. Also, it can represent a useful analysis in order to identify the future trends of renewable energy in Romania.

Owing to the large ratio of consumption in the building sector, energy saving strategies are required. Energy feedback is an energy-saving strategy that consumers to change their energy-consumption behaviors. The strategy has been principally focused on providing energy-consumption information. However, realization of energy savings using only consumption information remains limited. In this paper, a building-energy three-dimensional (3D) visualization solution is thus proposed. This solution includes the process of diagnosing a building and providing prediction of energy requirements if a building improvement is undertaken. Accurate diagnostic information is provided by real-time measurement data from sensors and building models using a close-range photogrammetry (CRP) method without depending on blueprints. The information is provided by employing visualization effects to increase the energy-feedback efficiency. The proposed strategy is implemented on two testbeds, and building diagnostics are performed accordingly. For the first testbed, the predicted energy improvement amount resulting from the facility upgrade is provided. The second testbed is provided with a 3D visualization of the energy information. The aim is to determine if the building manager will replace the facility after our recommendation is given to improve the building energy efficiency driven from the energy information. Unlike existing systems, which provide only ambiguous data that lack quantitative information, this study is meaningful because it provides energy information with the aid of visualization effects before and after building improvements.

Energy conversion and distribution (heat and electricity) is characterized by long planning horizons, investment periods and depreciation times, and it is thus difficult to plan and tell the technology that optimally fits for decades. Uncertainties include future energy prices, applicable subsidies, regulation, and even the evolution of market designs. To achieve higher adaptability to arbitrary transition paths, a technical concept based on integrated energy systems is envisioned and described. The problem of intermediate steps of evolution is tackled by introducing a novel paradigm in urban infrastructure design.It builds on standardization, modularization and economies of scale for underlying conversion units. Building on conceptual arguments for such a platform, it is then argued how actors like (among others) municipalities and district heating system operators can use this as a practical starting point for a manageable and smooth transition towards more environmental friendly supply technologies, and to commit to their own pace of transition (bearable investment/risk). environmental friendly supply technologies. Merits are not only supported by technical arguments but also by strategical and societal prospects like technology neutrality and availability of real options.

Daylighting has been widely adopted in recent years due to its potential to improve the indoor environment in terms of visual comfort and energy-saving. One of the energy-saving techniques for energy-efficient buildings is the integration of louver systems. Louvers are considered more efficient for providing daylight in the interior as compared to other daylighting systems. Here, this paper presents the design of a louver system for conducting energy simulations for lighting and cooling requirements in office spaces. The simulation results indicate that the use of louvers in different opening configurations can lead to energy savings, particularly in the lighting aspect. The louver system in office spaces with a 50% louver opening leads to 27.0% energy savings. Further, the results are presented for different louver openings to calculate the lighting and cooling energy savings. The overall performance of the system is better in terms of providing consistent daylight, which eventually improves energy saving.

The research introduces the concept of Strong Energy (SE) as a force that encompasses all the different forms of energy in the universe. The study aims to create a mathematical framework that can describe the relationship between these different types of energy and how they can be converted from one form to another. The paper explores the theoretical implications of this model and investigates how it aligns with established physics principles like the conservation of energy and fundamental forces. The paper also discusses potential experiments and the impact this research could have on cosmology, particle physics, and our understanding of energy. This work sets the stage for future research in this area of study.

In 2021 an acute energy crisis inflicted severe damage on the global economy, leading to escalated prices for electricity, gas, and fuel. In order to shield individuals and businesses from the mounting energy expenses, governments have been compelled to implement policy measures, including tax reductions, price restrictions or discounts, and subsidies. This research paper examines these policy responses through the lens of energy sufficiency. Energy poverty poses a significant threat to social cohesion and support for climate-related initiatives. Therefore, it is imperative to employ compensatory measures. However, the design of such solutions must carefully consider the incentives to reduce energy consumption and associated carbon emissions. The findings of the analysis demonstrate that the escalation of energy costs holds promise for achieving energy sufficiency. Nevertheless, the government's response to the surge in energy prices and energy poverty falls short and lacks precision. Most of the policy changes primarily focus on regressive energy cost subsidies and nudging households away from fossil fuels, but they fail to generate the necessary impetus for achieving energy sufficiency, which involves the elimination of energy poverty and excessive energy consumption.

The combined heat and power system is based on the principle of "cascade utilization of thermal energy" for system integration and optimization. The rational utilization of energy, as well as the rational arrangement of energy flow and the process optimization combination of the overall system are taken into account in order to achieve multifunctional goals in the field of thermal engineering. The present paper presents a detailed assessment of combined heat and power systems from above standpoints. This article is divided into two parts “CHP based on thermo-dynamic cycles” and “CHP based on non-thermodynamic cycles”. Each part is then classified based on power subsystem energy consumption efficiency (high or low), including Rankine cycle, ORC, Stirling cycle, gas turbine, reciprocating engine, PVT and fuel cell. The present paper also helps identify the research gaps in this area and provides direction on future studies on combined heat and power systems.

This paper is about energy as viewed through an integrated model that links energy with environment, technology and urbanisation as related areas. Our goal is to empirically investigate the (in)efficient energy use across 30 developed OECD member states during the period from 2001 to 2018. For that purpose, we set up an output-oriented BCC data envelopment analysis that employs a set of input variables with non-negative values to calculate the efficiency scores on minimising energy use and losses as well as environmental emissions. We develop a couple of baseline models for primary energy and secondary energy (electricity) in which we find that countries have mean inefficiency margins of 16.1 per cent for primary energy and from 10.8 to 13.5 per cent for electricity. Then, we extend the baseline models by adding environment as an important closely related concept and confirm the consistency of the baseline findings. In the context of this analysis, however, the inefficiency scores, on the one hand, point out to a mismatch in the utilisation of the inputs to produce efficiency but, on the other hand, they uncover a hidden potential to increasy efficiency through re-allocation under constant inputs.

Although energy management of a microgrid is generally performed using a day-ahead scheduling method, its effectiveness has been questioned by the research community due to the existence of high uncertainty in renewable power generation, power demand and electricity market. As a result, real-time energy management schemes are recently developed to minimise the operating cost of a microgrid while high uncertainty presents in the network. This paper develops modified particle swarm optimisation (MPSO) algorithms to solve optimisation problems of energy management schemes for a community microgrid and proposes a scheduling approach after taking into consideration high uncertainty to effectively minimise the operational cost of the microgrid. The optimisation problems are formulated for real-time and scheduling approaches, and solution methods are developed to solve the problems. It is observed that the scheduling program demonstrates superior performance in all the cases, including uncertainty in prediction, as compared to the other energy management approaches, although solutions have significant deviations due to prediction errors.

Fiber-reinforced mycelium (FRM) composites offer an innovative and sustainable approach to construction materials for architectural structures. Mycelium, the root structure of fungi, can be combined with various natural fibers (NF) to create a strong and lightweight material with environmental benefits. Incorporating NF like hemp, jute, or bamboo into the mycelium matrix enhances mechanical properties. This combination results in a composite that boasts enhanced strength, flexibility, and durability. Natural FRM composites offer sustainability through the utilization of agricultural waste, reducing the carbon footprint compared to conventional construction materials. Additionally, the lightweight yet strong nature of the resulting material makes it versatile for various construction applications, while its inherent insulation properties contribute to improved energy efficiency in buildings. Developing and adopting natural FRM composites showcase a promising step towards sustainable and eco-friendly construction materials. Ongoing research and collaboration between scientists, engineers, and the construction industry will likely lead to further improvements and expanded applications. This article provides a comprehensive analysis of the current research and applications of natural FRM composite for innovative and sustainable construction materials. Additionally, the paper reviews the mechanical properties and potential impacts of these natural FRM composites in the context of sustainable architectural construction practices. Recently, the relevance of mycelium-based materials has extended beyond their original fields of microbiology and mycology to architecture.

The aim of this investigation is focused on the effects of hooked-end steel fibers on both fresh and hardened properties of modified self-compacting concretes (SCC). For this purpose, the steel fibers are associated with other residues contents (i.e. marble, granite and rubber). This concatenated materials contents constitutes a novelty since no investigations are reported. It is found that the increase of rubber content, a better ability to absorb energy is observed. This indicates that a good alternative of structural material is provided. Fresh properties are evaluated by using flow, T500 time, V-funnel, J-ring methods. The mechanical behavior is evaluated in terms of compressive strength, tensile strength, static and dynamic modulus of elasticity, and damping ratio. Experimental results of the water absorption, porosity and density are also attained. It is also found that a SCC mixture containing steel fiber, marble/granite residue and rubber content is a potential mixture to be considered when in SCC designing associated with improved damping ratio. Although the rubber content decreases the mechanical behavior and slump flow, the concatenated utilization of MGR and steel fiber contents provide a slight improve in the damping result. An environmental benefit can also be associated since the cement consumption is decreased with marble additions.

The decarbonization of the built environment, both in new construction and renovation, is crucial to mitigate its relevant impact on climate change and achieve the Paris agreement goals. This study presents a systematic LCA-based methodology to assess the whole life carbon emissions of buildings, applied to a proposal for the regeneration of one of Milan’s disused railway yards. As an entry for the 2020 Reinventing Cities competition, Scalo Lambrate is a project for a mainly residential neighborhood with a public park. Strategies to reduce carbon emissions deriving both from the operational energy and construction and maintenance were evaluated and their effects compared to a reference scenario over a time horizon of 100 years. The results show that, while the opportunities to reduce carbon emissions during the use phase are somehow limited due to the already stringent performance requirements for new builds, the use of fast-growing biogenic materials for construction materials, even if mixed with more traditional ones, can provide a significant reduction of the global warming potential over the whole life cycle, with a reduction of 70% over the baseline. The remaining emissions can be offset with afforestation initiatives that, however, must be assessed against land use issues.

This research work has been based on a previous study by the authors that characterized the behavior of a polyimide-coated FBG sensor in a structural monitoring system. Sensors applied to structural health monitoring are affected in the presence of a state of multidirectional strains simultaneously. The previous study observed the influence of transverse strain (ε_y) while keeping longitudinal strain constant (ε_x), where the direction x is the direction of the optical fiber. The present study developed an experimental methodology which has consisted of carrying out a campaign of biaxial tests on cruciform specimens with three embedded FBG sensors coated with polyimide, acrylate and ORMOCER®. Applying the Strain–Optic Theory as reference, a comparison of the results obtained with the different coatings has been studied. This experimental work has done it possible to study the influence of transverse strain (ε_y) in the longitudinal measurement of each of the FBG sensor and the influence of the coating material. Finally, the calibration procedure as well as the strain sensitivity factor K for each sensor has been defined.

In the case of solid slabs made of reinforced concrete that are usually subjected to bending, large areas of the structure are stressed well below their load-bearing capacity. Contrary to this are shell structures, which can bridge large spans with little material if designed according to the force flow. To improve the efficiency of ceiling slabs, we want to utilize the shell load-bearing behavior on a smaller scale by resolving the solid interior accordingly. In order to be able to study a wide range of such constructions virtually, a parametric multiobjective simulation environment is being developed in an ongoing research project. The basic analysis approaches which were implemented are presented in this paper. The basic workflow, the used programs and material models and their calibration on the tests on textile-reinforced concrete (TRC) samples are described.

Keywords: friction stir processing; additive manufacturing; wire; titanium alloy; material transfer; microstructure; microhardness

Carbon nanomaterial is widely used in structural health monitoring due to the advantage of sensitivity and good mechanical properties. This study presents a novel approach employing carbon nanocomposite materials (CNM) to characterize deformation and damage evolution in physical modelling. As the primary measurement method, the CNM is used to investigate the deformation characteristics of a 200-400 m thick sandstone bed at a 1 km deep longwall mine. The sandstone unit is identified as an ultra-thick key stratum (UTKS), with its thicknesses varying across different mining panels of the UTKS. The results of CNM monitoring show that the UTKS remains stable even after a consecutive excavation of 900 m in width. This stability impedes the upward propagation of overlying strata failure, leading to minimal surface subsidence. The study demonstrates the huge potential of CNM in the mining area, which can be useful for investigating material damage in physical modelling studies. The findings suggest that the cumulative extraction width in individual mining areas of the mine should be controlled to avoid a sudden collapse of the UTKS, and that special attention should be paid to where the UTKS's thickness changes substantially. The substantial variation in UTKS thickness significantly impacts the pattern of overburden subsidence.

Graphene is a two-dimensional carbon atom with a hexagonal honeycomb-like structure in which the sp2 hybridization occurs. GO sheets are highly oxidized and have oxygen-containing groups. Properties of electronics, mechanicals, magnetics, and optics, Oxidized Methods for Brodies, Staudenmaier, Hofmann, Hummers, Improved Hummers, and Tour's Methods Reduction of Graphene oxide methods Chemical Reduction using sodium borohydride, 2,4-dinitrophenylhydrazine, Hydrazine hydrate, Thermal Reduction, Hydrothermal Reduction, Exfoliation Reduction, Catalytic Reduction, and the green synthesis route for reduction, The reduction of graphene oxide has a wide range of applications, including its use in energy storage devices for Solar cells, Supercapacitors, LIG-based sensors, River Water sensors, Battery, hydrovoltaic generators, OLED Screen, and Graphene Shielding. This review will determine the future of a few applications.

The nature of the fracture and fragmentation process of concrete medium under blast loading is the transformation process of the medium from continuum to discontinuity, coupled with the significant rate correlation of concrete medium, its mechanical behavior presents a high degree of complexity. Problems such as grid distortion and even negative volume are often encountered in the finite element method and others when solving this problem, while the material point method can effectively avoid these problems. In addition, the widely used HJC concrete constitutive model does not take into account the segmented characteristics of the calculation function for dynamic increasing factor. Therefore, in this paper, firstly, the calculation function for dynamic increasing factor in the HJC concrete model is modified by SHPB experiment, and the improved HJC concrete model is proposed; secondly, the material point method simulation program is developed, and the improved HJC concrete model is embedded into the simulation program; finally, the simulation program is verified by numerical examples, and the results show that the developed simulation program can better simulate the fracture and fragmentation process of concrete medium under blast loading, especially the pulverization characteristics of the medium in the near zone of the load.

Li-rich manganese-based cathode materials (LRMs) are considered one of the most promising cathode materials for the next generation lithium-ion batteries (LIBs) because of their high energy density. However, there are problems such as capacity decay, poor rate performance, and continuous voltage drop, which seriously limit their large-scale commercial applications. In this work, Li1.2Mn0.54Co0.13Ni0.13O2 coated with Li2MoO4 with unique spinel structure was prepared by wet chemistry method and the subsequent calcination process. The Li2MoO4 coating layer with spinel structure can provide a 3D Li+ transport channel, which is beneficial for improving rate performance, while protecting LRMs from electrolyte corrosion, suppressing interface side reactions, and improving cycling stability. The capacity retention rate of LRMs coated with 3wt% Li2MoO4 increased from 69.25% to 81.85% after 100 cycles at 1C, and the voltage attenuation decreased from 7.06 to 4.98 mV per cycle. The lower Rct also exhibits improved magnification performance. The results indicate that the Li2MoO4 coating effectively improves the cyclic stability and electrochemical performance of LRMs.

Functionally graded materials (FGM) have attracted considerable attention in the field of composite materials and rekindled interest in research on composite materials, due to their unique mechanical response achieved through material design and optimization. Compared to conventional composites, FGMs offer several advantages and exceptional properties, including improved deformation resistance, improved toughness, lightness properties, and excellent recoverability. This study focused on the production of functionally graded (FG) polymer materials by additive manufacturing (AM) method. FG structures were produced by the Fused Deposition Modeling (FDM) method using Acrylonitrile benzidine styrene (ABS) and Polylactic acid (PLA) materials and tensile tests were performed according to ASTM D638. The effects of different layer thicknesses, volume ratios, and total thicknesses on mechanical behavior were investigated. In addition, tensile tests were carried out by producing single-layer samples at certain volume ratios to create a numerical model with the Finite element method to verify the experimental data. As a result of this study, it is presented that the FG structure produced with FDM improves mechanical behavior.

Machining titanium alloy (Ti6Al4V) used in orthopedic implants by conventional metal cutting processes is challenging due to excessive cutting forces, low surface integrity and tool wear. To overcome these difficulties and for ensuring high-quality products, various industries employ wire electrical discharge machining (WEDM) for precise machining of intricate shapes in titanium alloy. The objective is to make WEDM machining parameters as efficient as possible for machining the bio-compatible alloy Ti6Al4V using box-behnken design (BBD) and Non-dominated Sorting Genetic Algorithm II (NSGA II). A quadratic mathematical model is created to represent the productivity and the quality factor (MRR and surface roughness) in terms of varying input parameters, such as pulse active (Ton) time, pulse inactive (Toff) time, peak amplitude (A) current and applied servo (V) voltage. The established regression models and related prediction plots provide a reliable approach for predicting how the process variables affect the two responses viz MRR and SR. The effects of four process variables on both the responses were examined, and the findings revealed that the pulse duration and voltage has a major influence on the rate at which material is removed (MRR) whereas pulse duration influence quality (SR).  The trade-off between MRR and SR, when significant process factors are included emphasizes the need for a reliable multi-objective optimization method. The intelligent metaheuristic optimization method named non-dominated sorting genetic algorithm II (NSGA II) is utilized to provide pareto optimum solutions in order to achieve high material removal rate (MRR) and low surface roughness (SR).

The design and engineering of antibacterial materials is key for preventing bacterial adherence and proliferation in biomedical and house-hold instruments. Silver nanoparticles (AgNPs) and chitosan (CHI) are broad-spectrum antibacterial materials with different properties, whose combined application is currently under optimization. This study proposes the formation of antibacterial films with AgNPs embedded in carboxymethylcellulose/chitosan multilayers by the layer-by-layer (LbL) method. The films were deposited onto nanoporous silicon (nPSi), an ideal platform for bioengineering applications, due to its biocompatibility, biodegradability, and bioresorbability. We focus on two alternative multilayer deposition processes: cyclic dip coating (CDC) and cyclic spin coating (CSC). The physicochemical properties of the films were the subject of microscopic, microstructural and surface-interface analyses. The antibacterial activity of each film was investigated against Escherichia coli (Gram-negative) and Staphylococcus aureus (Gram-positive) bacteria strains as model microorganisms. According to the findings, CDC technique produced multilayer films with higher antibacterial activity for both bacteria compared to the CSC method. Bacteria adhesion inhibition was observed from only 3 cycles. The developed AgNPs-multilayer composite film offers advantageous antibacterial properties for biomedical applications.

A cloud of relativistic material particles is considered, for which the distortions of length and time caused by the presence of the Lorentz factor an order of magnitude greater than curvature of space-time by gravity. The gravitational mass of the cloud is found in the region where its size is insignificant. It is established that the coefficient of dependence of the cloud mass on the total rest mass of its particles includes a complete elliptic integral of the 2nd kind.

The shape memory alloys belong to the smart materials thanks to their thermomechanical proprieties' reply to thermal or to mechanical loading. These materials can change shape, stiffness, displacement, natural frequency, and many mechanical characteristics in response to stress or to heat such as conduction, convection or radiation. However, heating by convection or conduction are the most useful and studied methods unlike radiation. Therefore, this paper aims to study the radiation effect on the shape memory alloy behavior

This article deals with the possibility of partial replacement of blast furnace slag with fly ash after denitrification by the Selective Non-Catalytic Reduction (SNCR) method in alkali-activated materials. In the experiment, the basic physical-mechanical properties and durability properties were tested, the hydration reaction was monitored in a calorimeter and infrared spectroscopy was performed. Results were compared between mixtures prepared with fly ash without denitrification and also with reference mixture based only on alkali-activated blast furnace slag. The basic result is the finding, that hybrid alkali-systems with fly ash after denitrification show similar trends as hybrid alkali-systems with fly ash without denitrification. The significant effect of fly ash is manifested especially in terms of resistance to freeze-thaw. The reactions in the calorimeter show a slower development of reactions with increasing replacement of slag by fly ash. In the case of testing resistance to leaching in demineralised water, a decrease of flexural strength was found, which corresponds to the conclusions of strength testing, that long-term deposition of bodies in water causes deterioration of mechanical properties.

This paper reviews state of the art Additive Manufactured (AM) IN718 alloy intended for high temperature applications. AM processes have been around for decades and have gained traction in the past five years due to the huge economic benefit it brings to manufacturers. It is crucial for the scientific community to look into AM IN718 applicability in order to see a step-change in the production. Microstructural studies reveal that the grain structure plays a significant role in determining the fatigue lifespan of the material. Controlling IN718 respective phases such as the ϒ’', δ and Laves phase is seen to be crucial. Literature reviews have shown that the mechanical properties of AM IN718 were very close to its wrought counterpart when treated appropriately. Higher homogenization temperature and longer ageing were recommended to dissolve the damaging phases. Various surface enhancement techniques were examined to find out their compatibility to AM IN718 alloy that is intended for high temperature application. Laser shock peening (LSP) technology stands out due to the ability to impart low cold work which helps in containing the beneficial compressive residual stress it brings in high temperature fatigue environment.

The application of instrumented indentation to assess material properties like Young’s modulus and micro-hardness has become a standard method. In recent developments, indentation experiments and simulations have been combined to inverse methods, from which further material parameters as yield strength, work hardening rate, and tensile strength can be determined. In this work, an inverse method is introduced by which material parameters for cyclic plasticity, i.e. kinematic hardening parameters, can be determined. To accomplish this, cyclic Vickers indentation experiments are combined with finite element simulations of the indentation with unknown material properties, which are then determined by inverse analysis. To validate the proposed method, these parameters are subsequently applied to predict the uniaxial stress-strain response of a material with success. The method has been validated successfully for a quenched and tempered martensitic steel and for technically pure copper, where an excellent agreement between measured and predicted cyclic stress-strain-curves has been achieved. Hence, the proposed inverse method based on cyclic nanoindentation, as a quasi-non-destructive method, could complement or even substitute the resource-intensive conventional fatigue testing in the future for some applications.

Diffusion bonding is often used on pre-machined parts to generate internal cavities, e.g. for cooling injection molding tools close to the mold cavity. Only then, the workpieces are finished to their final dimensions. In the case of micro-process devices, however, it is essential to precisely control the deformation, as otherwise uncontrollable pressure losses will occur with channel cross-sections in the sub-millimeter range. Post-processing is not possible. The most important process parameters for diffusion bonding are temperature, dwell time and contact pressure, with the bonding temperature and contact pressure acting in opposite directions and showing a strong non-linear dependence on deformation. In addition, the deformation is influenced by a number of other factors such as the absolute size of the cross-section and the aspect ratio of the parts, the dimensions and distribution of the internal cross sections and the overall percentage of the cross-section to be bonded. In micro process engineering, small material cross-sections in the range of the materials microstructure can facilitate additional deformation mechanisms such as grain boundary sliding, which are not relevant at all for larger structures. For parts consisting of multiple layers, tolerances in thickness and roughness of multiple surfaces must be levelled, contributing to the percentaged deformation. This makes it difficult, especially in micro process engineering and in single or small series production, to determine suitable joining parameters in advance, which on the one hand do not cause unforeseen large deformations, but on the other hand reliably produce highly vacuum-tight components. Hence, a definition of a fixed percentaged deformation does not work for all kinds of components. This makes it difficult to specify parameters for surely obtain high-vacuum tight parts. For successful diffusion bonding, atoms must diffuse over the bonding planes, forming a monolithic part in which the original layers are no longer visible. Only then, mechanical properties identical to those of the base material, which has been subjected to identical heat treatment, can be achieved. In this paper, the impacts of different material cross section widths as well as of the aspect ratio on deformation were investigated. By accident, it was found that also accuracy of the temperature measurement may have a serious impact in terms of deformation.

Zirconium based bulk metallic glasses are industrially valuable materials which commercial market grows rapidly. Surface modification of these metallic glasses by high-intensity lasers is relatively new and costly treatment promising great advantages over classical surface processing methods. In this work we perform the case study of surface modification of Zr$_{46}$Cu$_{36.8}$Ag$_{9.2}$Al$_8$ metallic glass by high-intensity millisecond laser beam. Our results suggest chemical deposition of atmospheric oxygen and nitrogen in the laser-melted surface area and its surroundings. Zirconium nitride layer was detected in the middle of laser-irradiated area. Nanocrystals embedded in the amorphous matrix were also formed on the surface. Overall, our findings suggest possibilities for improvement of mechanical characteristics of the studied metallic glass.

The energy efficiency of existing buildings is a crucial factor in addressing Europe’s energy con-sumption challenges, accounting for nearly 40% of the total energy usage. The ongoing energy crisis, driven by the reliance on fossil fuels and increasing prices, has underscored the urgency of adopting sustainable and energy efficient practices especially to the existing building stock. Cyprus is par-ticularly vulnerable due to its heavy dependence on imported fuels for electricity generation and faces significant challenges in transforming its existing building stock into energy-efficient and sustainable structures. Extensive focus has been made by the government on the energy-efficient retrofit of non-residential public buildings. This study examines an existing cultural hall. The case study of the Cultural Hall represents the building stock before 2010 which is lacking thermal in-sulation, double glazing and any energy efficient element. It then offers an ideal case study to ex-plore sustainable solutions which can be easily adopted from the construction industry and from the building owners. The primary objective of this research is twofold: first, to develop a comprehensive retrofit plan to transform the cultural hall into a net-zero energy building; and second, to explore how this transformation can give value back to the local community. After running two simulation scenarios and providing two energy performance certificates, one with at the existing state and one with the intended retrofit measures, it is clear that the building can be a net zero energy consump-tion building. Some interesting results derived, present also how this building can provide value back to the community i.e. through solar carports for EV charging.

Installations of decentralised Renewable Energy Systems (RES) are becoming increasing popular as governments introduce ambitious energy policies to curb emissions and slow surging energy costs. This work presents a novel model for optimal sizing for decentralised renewable generation and hybrid storage system to create a Renewable Energy Community (REC), developed in Python. The model implements PV Solar and Wind Turbines combined with a hybrid battery and Regenerative Hydrogen Fuel Cell (RHFC). The electrical service demand is derived using real usage data from a rural island case study location. Cost remuneration is managed with an REC virtual trading layer, ensuring fair distribution among actors in accordance with the European RED(III) policy. A multi-objective Genetic Algorithm (GA) stochastically determines the system capacities such that the inherent trade-off relationship between project cost and decarbonisation can be observed. The optimal design results in an LCOE of 0.15€/kWh, reducing costs by over 50% compared with typical EU grid power, with a project IRR of 10.8%, simple return of 9.6%/year, and ROI of 9 years. Emissions output from grid only use is reduced by 72% to 69 gCO2e/kWh. Further research of lifetime economics and additional revenue streams in combination with this work could provide a useful tool for users to quickly design and prototype future decentralised REC systems.

In contrast to physical sustainable measures carried out in homes, such as insulation, the installation of a Home Energy Management System (HEMS) has no direct and immediate energy-saving effect. A HEMS gives insight into resident behaviour regarding energy use. When this is linked to the appropriate feedback, the resident is in a position to change his or her behaviour. This should result in reduced gas and/or electricity consumption. The aim of our study is to contribute towards the effective use of home energy management systems (HEMS) by identifying types of homeowners in relation to the use of HEMS. The research methods used were a literature review and the Q-method. A survey using the Q-method was conducted among 39 owners of single-family homes in various Rotterdam neighbourhoods. In order to find shared views among respondents, a principal component analysis (PCA) was performed. Five different types of homeowner could be distinguished: the optimists, the privacy-conscious, the technicians, the sceptics, and the indifferent. Their opinions vary as regards the added value of a HEMS, what characteristics a HEMS should have, how much confidence they have in the energy-saving effect of such systems, and their views on the privacy and safety of HEMS. The target group classification can be used as input for a way in which local stakeholders, e.g. a municipality, can offer HEMS that is in line with the wishes of the homeowner.

Free and open source hardware (FOSH) development has been shown to increase innovation and reduce economic costs. This article reviews the opportunity to use FOSH like a sanction to undercut imports and exports from a target criminal country. A formal methodology is presented for selecting strategic national investments in FOSH development to improve both national security and global safety. In this methodology, first the target country that is threatening national security or safety is identified. Next, the top imports from the target country as well as potentially other importing countries (allies) are quantified. Hardware is identified that could undercut imports/exports from the target country. Finally, methods to support the FOSH development are enumerated to support production in a commons-based peer production strategy. To demonstrate how this theoretical method works in practice it is applied as a case study to the current criminal military aggressor nation, who is also a fossil fuel exporter. The results show there are numerous existing FOSH and opportunities to develop new FOSH for energy conservation and renewable energy to reduce fossil fuel energy demand. Widespread deployment would reduce the concomitant pollution, human health impacts, and environmental desecration as well as cut financing of military operations.

The Smart Energy Research Lab (SERL) Observatory dataset described here comprises half-hourly and daily electricity and gas data, SERL survey data, Energy Performance Certificate (EPC) input data and 24 local hourly climate reanalysis variables from the European Centre for Medium-Range Weather Forecasts (ECMWF) for over 13,000 households in Great Britain (GB). Participants were recruited in September 2019, September 2020 and January 2021 and their smart meter data are collected from up to one year prior to sign up. Data collection will continue until at least August 2022, and longer if funding allows. Survey data relating to the dwelling, appliances, household demographics and attitudes was collected at sign up. Data are linked at the household level and UK-based academic researchers can apply for access within a secure virtual environment for research projects in the public interest. This is a data descriptor paper describing how the data was collected, the variables available and the representativeness of the sample compared to national estimates. It is intended as a guide for researchers working with or considering using the SERL Observatory dataset, or simply looking to learn more about it.

The planning and decision-making for a distributed energy supply concept in complex actor structures like in districts calls for the approach to be highly structured. Here, a strategy with strong use of energetic simulations is developed, the core elements are presented and research gaps are identified. The exemplary implementation is shown using the case study of a new district on the former Oldenburg airbase in northwestern Germany. The process is divided into four consecutive phases, which are carried out with different stakeholder participation and use of different simulation tools. Based on a common objective, a superstructure of the applicable technologies is developed. Detailed planning is then carried out with the help of a multi-objective optimal sizing algorithm and Monte Carlo based risk assessment. The process ends with the operating phase, which is to guarantee a further optimal and dynamic mode of operation. The main objective of this publication is present the core elements of the planning processes and decision-making framework based on the case study and to find and identify research gaps that will have to be addressed in the future.

This paper develops a novel energy universal service bus system (EUSBS) based on emerging energy Internet (E-net) technologies. This EUSBS is a unified identification and plug-and-play interface platform to which high penetration distributed energy and equipment (DEE), including photovoltaic (PV), fans, electric vehicle charging stations (EVCSs), energy storage equipment (ESE), and commercial and residential users (CRUs), can access in a coordinated control and optimized utilization mode. First, the functions design, overall framework and topology architecture design of the EUSBS are expounded, among which the EUSBS is mainly composed of a hardware system and a software platform. Moreover, several future application scenarios are presented. Then, the hardware part of EUSBS is designed and developed, including the framework design of this hardware subsystem, and development of the hardware equipment for PV access, fans access, EVCS access, ESE access, and CRU access. The hardware subsystem consists of smart socket, and household/floor/building concentrators. Based on this, the prototypes development of EUSBS hardware equipment is completely demonstrated. Third, the software part of the EUSBS is developed as a cloud service platform for electricity use data analysis of DEE. This software subsystem contains the power quality & energy efficiency analysis module, optimization control module, information and service module, and data monitoring and electricity behavior analysis module. Based on this design, the software interfaces are developed. Finally, an application study on energy management and optimization of a smart commercial building is conducted to evaluate the functions and practicality of this EUSBS. The EUSBS developed in this paper is able to overcome difficulties in big data collection and utilization on sides of distribution network and electricity utilization, and eventually implement a deep information-energy fusion and a friendly supply-demand interaction between the grid and users. This contribution presents a detailed and systematic development scheme of the EUSBS, and moreover, the laboratory prototypes of the hardware and software subsystems have been developed based on E-net technologies. This paper can provide some thoughts and suggestions for the research of active distribution network and comprehensive energy management and optimization in power systems, as well as references and guidance for researchers to carry out research regarding energy management, optimization and coordinated control of the smart buildings.

The use of energy resources is essential to the survival and development of human civilization. However, inefficient energy use not only has an impact on the economy, but it also has a significant impact on climate change. Studying and analyzing the factors that increase energy consumption is crucial for improving energy management. The aim of this study is to analyze the factors influencing energy savings in a building taken as a study model under two different climatic conditions. Measurements of the building's energy performance were carried out using the EnergyPlus calculation engine, which enabled us to analyze the strengths of building parameters such as the number of lights, the equipment used, occupancy, temperature and the relationships between the factors influenced. EnergyPlus is an important software tool in the field of building energy efficiency, enabling the precise simulation of building energy consumption. Simulation scenarios based on actual consumption data carried out by researchers have made it possible to develop energy management strategies in buildings in order to optimize energy efficiency, and in particular to promote the thermal performance of these buildings. In the present work, EnergyPlus building energy simulation software is used to simulate the energy consumption of the building of the Faculty of Electrical Engineering at the "Gheorghe Asachi" Technical University in Iasi, in order to determine the factors influencing building energy consumption. It has been shown that occupancy and heating and cooling systems are the key factors influencing energy consumption in buildings. The advantage of this study is that it can be used to model the most influential factors in predicting future energy consumption in buildings.

In response to escalating global concerns regarding climate change, nations worldwide have been undertaking structural adjustments in their energy sectors to promote diversification and decarbonization. This study conducts a comparative analysis of the policies and measures adopted by major economies, including the United States, the United Kingdom, Japan, Germany, and France, focusing on climate change, energy structural adjustments, and carbon emission reduction. By analyzing recent carbon emission and highlighting achievements in renewable energy promotion, green industry development, industrial restructuring, and energy production decarbonization, this study aims to provide valuable insights and formulate strategies for constructing an innovative energy system that ensures economic and social development while facilitating rapid growth and wide applications of low-carbon energy sources.

The Internet of Things (IoT) is experiencing exponential growth, revolutionizing various industries with its ability to connect devices and enable advanced applications. In the realm of energy production, IoT offers significant potential for optimizing processes and improving efficiency. This study presents a comprehensive monitoring and energy management strategy for the University of Cuenca's microgrid photovoltaic (PV) system, utilizing IoT and ThingSpeak as key technologies. The proposed strategy leverages intelligent environments and utilizes ThingSpeak as a robust platform for data presentation and analysis. By integrating IoT devices and sensors, real-time monitoring of PV system parameters such as solar radiation and temperature is achieved. The collected data is then analyzed using advanced algorithms and visualized through ThingSpeak, enabling effective energy management and decision-making. The developed monitoring system was rigorously tested in a laboratory microgrid setting, where the PV system is interconnected with other generation and storage systems, as well as the electrical grid. Through the seamless integration of these components, the monitoring system provides enhanced visibility and control over the microgrid's energy production. The results demonstrate the successful implementation of the monitoring system, showcasing its ability to improve the supervision, automation, and analysis of daily energy production. By leveraging IoT technologies and ThingSpeak, stakeholders can access real-time data, analyze performance trends, and optimize energy resources.

$\phi$CDM models provide an alternative to the standard $\Lambda$CDM paradigm, while being physically better motivated. These models lead to a time-dependent speed of sound for dark energy that is difficult to replicate by $w$CDM parametrizations. We review the most up-to-date status of observational evidence for the $\phi$CDM models in this paper. We start with an overview of the motivation behind these classes of models, the basic mathematical formalism, and the different classes of models. We then present a compilation of recent results of applying different observational probes to constraining $\phi$CDM model parameters. Over the last twenty years, the precision of observational data has increased immensely, leading to ever tighter constraints. A combination of the recent measurements favors the spatially flat $\Lambda$CDM model, but a large class of $\phi$CDM models is still not ruled out.

Τhe building automation control is a crucial factor for improving buildings energy efficiency and management, as well as improving the electricity grid's reliability indices. This paper presents the methodology, describes the necessary technology requirements and presents the decentralized building automation novel algorithm for Efficient demand side management in a building. All these are applied in an experimental university microgrid and the results are presented in terms of energy saving in kWh, money in € and working hours.

Energy keeps the global economy alive, whereas it is extensively exposed to various climate change impacts. In this context, severe business competition (e.g., the building sector) and the unwise use of natural resources and ecosystem services (e.g., fossil fuel energy sources) seem to sharpen the relevant effects of climate change. Indicatively, contemporary issues at the interface of building energy performance and environmental quality levels include consequences from global warming, increasing releases of carbon dioxide to peak electrical loads, power grid and building planning, and energy demand and supply issues. In light of such concerns, the present review paper attempts to disclose the multifaceted and multidisciplinary character of building energy use at the interface of the economy, the environment, and society against climate change. This review highlights energy efficiency concepts, production, distribution, consumption patterns, and relevant technological improvements. Interestingly, the reviewed contributions in relevant literature reveal the need and necessity to alter the energy mix used and relevant energy use issues. These include developments in climate-proof and effective systems regarding climate change impacts and shocks. Practical implications indicate that the sustainable development goals for clean energy and climate action should be followed if we wish to bring a sustainable future closer and faster to our reality.

This study investigates the relationship between clean and dirty energy markets, specifically focusing on clean energy stock indexes and their potential as hedging assets and safe havens during periods of global economic uncertainty. The research analyzes five clean energy indexes and five dirty energy indexes from May 2018 to May 2023, considering events like the global pandemic and the Russian invasion of Ukraine. The main objective is to examine the causal relationship among different stock indexes pertaining to dirty and clean energy by using the Granger causality test (VAR Granger Causality/Block Exogeneity Wald Test) to determine whether clean energy indexes can predict future prices of dirty energy indexes. However, the findings reveal that clean and dirty energy indexes do not exhibit hedging characteristics or serve as safe havens during times of economic uncertainty, rejecting the research question. These results have important implications for investment strategies, as assets lacking safe haven characteristics may not preserve portfolio efficiency in uncertain times. The study's insights provide valuable guidance for investors, poli-cymakers, and participants in energy financial markets. It highlights the need to adapt investment approaches and seek alternative options to navigate uncertain economic conditions effectively.

The spiral tube heat exchange is widely used in large-scale liquefaction process. However, the research on the friction pressure drop of the two-phase flow in the spiral tube is limited, especially for the offshore sloshing condition. In this paper, an experimental system is designed and built, and the effects of sloshing form (roll, pitch, heave), sloshing period (5-15s), mass flux (200-800 kg/(m2·s)), vapor quality (0.3-0.9) and operating pressure (2-4 MPa) on friction pressure drop of methane/ethane (C1/C2) mixture in spiral tube are studied. The result shows that the growth rate of time-averaged friction pressure drop during condensation under sloshing condition is less than 0, which indicates that sloshing will lead to drag reduction. And under the three sloshing parameters, the growth rate of time-averaged friction pressure drop of C1/C2 is reduced by-5.99%%, 5.97% and -6.70% respectively.

In this study, a multiobjective, multiperiod, global optimization for design, sizing and dispatch of an islanded, hybrid microgrid was performed using a model built in MATLAB. The system was simulated over one year for sizing and over one day for dispatch, both using hourly time steps. The model minimized lifecycle levelized costs, emissions, lost load and dumped power while maximizing penetration of clean, renewable sources in the microgrid. This found optimal capacities of the renewable, energy storage and backup generation components which provide the best combination of affordability, sustainability, reliability and efficiency. After experimenting with several global solvers, it was determined that particle swarm optimization is most well-suited to solving the sizing optimization problem. The PV-wind microgrid using Li-ion batteries along with diesel engines was found to perform best among all the combinations considered. It was found that in spite of including additional objectives, monetary costs are the primary driver while allocating generation capacity between different renewable sources like wind versus solar PV. Furthermore, the sizing of PV, wind and battery storage depends strongly on the rating of the standby distributed generator, mainly due to reliability consideration. Generating Pareto-optimal sets revealed interesting relationships between different input variables (i.e. PV, wind and battery capacities) as well as trade-offs that arise while pursuing different objectives. Pursuing cost-minimization alone may lead to sub-optimal outcomes in terms of environmental impact, reliability and excess energy production. A sensitivity analysis was also conducted to understand the effects of various parameters like fuel price and energy storage costs on the optimal system's design and operation. Such accurate sizing programs help reduce the extent of oversizing of sub-systems during the design and planning stage, which is usually needed to achieve high reliability with distributed and decentralized energy systems like off-grid microgrids. This reduces the upfront capital investment needed to build the system, making clean electricity access affordable in the short term. The economic-environmental dispatch produced day-ahead scheduling strategies to meet the above mentioned objectives. The system was found to be relatively robust to short-term uncertainties and disturbances in renewable generation and load, although this does cause sub-optimal performance due to increased reliance on fossil fuels. It was found that dispatching of the batteries and backup generators is most critical in minimizing impacts of such events. However, the response to longer-term disturbances still remains to be assessed. The study also includes a comprehensive literature review of tools available for microgrid design as well as different optimization algorithms that have been used to solve microgrid sizing, dispatch and scheduling problems. Additionally, an overview is provided of various control strategies that can be used to improve robustness and resiliency of microgrids.

Renewable Energy Communities (RECs) are emerging as an effective concept and model to empower the active participation of citizens on the energy transition, not only as energy consumers, but also as promoters of environmentally friendly energy generation solutions. This paper aims to contribute to the management and optimization of individual and community Distributed Energy Resources (DER). The solution follows a price and source-based REC management program, in which consumers day-ahead flexible loads (Flex Offers) are shifted according to electricity generation availability, prices and personal preferences, to balance the grid and incentivize user participation. The heuristic approach used in the proposed algorithms allows the optimization of energy resources in a distributed edge and fog approach with a low computational overhead. The simulations performed using real world energy consumption and flexibility data of a REC with 50 dwellings show an average cost reduction of 10.6% and an average increase of 11.4% in individual self-consumption. Additionally, the case-study demonstrates promising results regarding grid load balancing and the introduction of intra-community energy trading.

Explaining the emergence of behavior and understanding on the basis of neuronal mechanisms is still elusive. One renowned proposal is the Free Energy Principle (FEP), which uses an information-theoretic framework derived from thermodynamic considerations to describe how behavior and understanding would emerge. FEP starts from a whole organism approach, based on mental states and phenomena, mapping them into the neuronal substrate. An alternative approach, the Energy Homeostasis Principle (EHP), initiates a similar explanatory effort, but starting from single neuron phenomena and building up to the whole organism’s behavior and understanding. In this work, we develop the EHP as an alternative but complementary vision to FEP and try to explain how behavior and understanding would emerge from the local requirements of the neurons. Based on EHP and a strict naturalist approach that sees living beings as physical and deterministic systems, we explain scenarios where learning would emerge without the need for volition or goals. Given these starting points, we state several considerations of how we see the nervous system, particularly the role of function, purpose, and the conception of goal-oriented behaviors. We problematize these conceptions, giving an alternative teleology-free framework in which behavior and, ultimately, understanding would still emerge. We reinterpret neural processing explaining basic learning situations up to simple anticipatory behavior. Finally, we end the work with an evolutionary perspective of how this non-goal-oriented behavior appears. We acknowledge that in the current form of our proposal, we are still far from explaining the emergence of understanding. Still, we set the ground for an alternative neuron-based framework to ultimately explain understanding.

During the last two decades, energy poverty has captured a growing attention of researchers and policymakers due to its strong association with economic poverty and poor economic performance. This study uses a broad set of macro level indicators and makes the first attempt to measure energy poverty and its impact on economic growth of Pakistan over the period 1990 to 2017. In particular, our energy poverty indicator considers four main dimensions of energy poverty, namely, energy services, clean energy, energy governance and energy affordability. Our main results show that though the overall energy poverty has reduced in Pakistan during the selected sample period, the country shows an increasing dependence on polluted energy supply in order to meet its growing demand of energy. In second stage of the investigation, we test the neoclassical growth theory where we incorporate energy poverty along with human capital as source of economic growth. Our cointegration results reveal a strong relationship between energy poverty and economic growth that is also dynamically stable in short run. These strong negative linkages between energy poverty with economic growth for the sample economy complement the previous literature on the subject.

All over the world energy is used for different purposes and hence its continuous high demand which has brought about an increase in crisis and prices of energy. Ghana has faced a lot of supply and high electricity consumption challenges over a period of time. The Energy Commission of Ghana has developed regulations and guidelines to help reduce high consumption challenges among users, these included the replacement of incandescent bulbs with fluorescent bulbs, ban of importation of low energy efficient appliances. In spite of the effort to reduce electricity wastage, there is still a high increase in electricity consumption. The research investigated what contributed to electricity consumption in Kwame Nkrumah University of Science and Technology with the lecture halls as the main focus, the research also analyzed the current occupant behavior characterized by the electrical energy consumption practices. And investigated how the contemporary theories for reducing energy consumption was used in the lecture halls. A questionnaire survey was conducted to investigate occupants on their energy use practices in lecture halls that causes wastages, observation was made to establish relevant data on the use of contemporary theories for energy reduction in lecture halls. In a total of 110 occupants that responded to the questionnaire, 79 occupants almost always turn off electrical fitting and fixtures when not in use. From the responses, a majority of the occupants claimed to comply to best practices of energy use. The research concluded that some contemporary theories to reduce energy consumptions was not used and considered in the lecture halls.

This study aimed to focus on how to design a low-cost greenhouse for the cultivation of crops, to propose the cost-effectiveness analysis of small agribusiness, and to promote sustainable agricultural production during and after the COVID-19 crisis for helping grassroots and anyone who lost their job. This article is qualitative engineering research, studying of literature reviews of greenhouse farming concept and Micro, Small and Medium Enterprises, then, designing low-cost greenhouse model which was preliminarily adapted for hot climate countries. Three plants that were selected as representative plants of this model include sunflower, water spinach, and wheat. The greenhouse model, measuring 5 x 7 x 4 m (W x L x H), was designed for this mission. The total cost of one building is approximately 97,994 THB. For the worthiness of the investment, farmers should build at least three greenhouse buildings, which will return total income to farmers approximately 34,666.09 THB per month. The suggestion includes further knowledge and financial supports from the government sectors among farmers, then, boost them up using high-level technology and also planting high-price agribusiness production to promote the local economy to be strong and sustainable.

Background: The frequency of visits to restaurants has been suggested to contribute to the pandemic of obesity. However, few studies have examined how individual use of these restaurants is related to BMI using new technology of reminding to avoid memory error. Aim: To investigate the association between the usage of different types of food outlets and BMI among adults in Scotland. Method: The study was cross-sectional. Participants (n = 681) completed an online survey for seven consecutive days where all food purchased at food outlets was reported each day. We explored the relationship between BMI and usage of these restaurants using auto-reminder text system. Results: Body Mass Index (BMI) of both males and females was not related to frequency of use of Full-Service Restaurants (FSRs), Fast Food Restaurants (FFRs), delivery or takeaways, when assessed individually, or combined (TFO= Total Food Outlet). Conclusion: These data do not support the widespread belief that consumption of food out of the home at fast-food and full-service restaurants, combined with that derived from deliveries and takeaways, is a major driver of obesity in UK.

Great Britain’s stocks of coal, natural gas, and petroleum have seen major changes to the levels of stored energy over the years 2005 to 2019, a reduction of 200 TWh (35%) from 570 TWh to 370 TWh. The transformation of its electrical system over this timeframe saw a reduction in coal generation, leading to a corresponding reduction of the levels of stockpiled coal of 85 TWh (68%), partially offset by an increase in the stocks of biomass for electrical generation. The reduction in natural gas storage of 24 TWh (44%) was primarily due to the closure of Britain’s only long-term seasonal natural gas storage facility in January 2018. This was partially offset by the construction of medium-term natural gas storage facilities and the use of LNG storage in the years preceding its closure. For stocks of crude oil and oil products the reduction was 35 TWh (21%), linked to the overall reduction in demand.

Natural gas combined cycle power plants (CCPPs) are widely used to meet peak loads in electric energy production. Continuous monitoring of the output electrical power of CCPPs is a requirement for power performance. In this study, the role of ambient temperature change having the greatest effect on electric production is investigated for a natural gas CCPP. The plant has generated electricity for fourteen years and setup at 240 MW in Aliağa, İzmir, Turkey. Depending on the seasonal temperature changes, the study data were obtained from each gas turbine (GT), steam turbine (ST) and combined cycle blocks (CCBs) in the ambient temperature range of 8-23°C. It has been found that decreases of the electric energy in the GTs because of the temperature increase and indirectly diminishes of the electricity production in the STs. As a result, the efficiency of each GT, ST and CCB reduced, although the quantity of fuel consumed by the controllers in the plant was decreased. As a result of this data, it has been recommended and applied that additional precautions have been taken for the power plant to bring the air entering the combustion chamber to ideal conditions and necessary air cooling systems have been installed.

In a vacuum tube, two identical and parallel Ag-O-Cs surfaces, A and B, with a work function of 0.8eV, ceaselessly emit thermal electrons at room temperature. The thermal electrons are controlled by a static uniform magnetic field (a magnetic demon), and the number of electrons migrate from A to B exceeds the one from B to A, (or vice versa). The net migration from A to B quickly results in a charge distribution: A charged positively and B negatively. A potential difference between A and B emerges, and the tube outputs ceaselessly an electric current and a power to a resistance (a load) and cools itself slightly. The ambient air is a single heat reservoir in the experiment, and all the heat extracted by the tube from the air is converted into electric energy without producing other effect. We believe the experiment is in contradiction to the Kelvin statement of the second law.

The process of modelling energy systems is accompanied by challenges inherently connected with mathematical modelling. However, due to modern realities in the 21st century, existing challenges are gaining in magnitude and are supplemented with new ones. Modellers are confronted with a rising complexity of energy systems and high uncertainties on different levels. In addition, interdisciplinary modelling is necessary for getting insight in mechanisms of an integrated world. At the same time models need to meet scientific standards as public acceptance becomes increasingly important. In this intricate environment model application as well as result communication and interpretation is also getting more difficult. In this paper we present the open energy modelling framework (oemof) as a novel approach for energy system modelling and derive its contribution to existing challenges. Therefore, based on literature review, we outline challenges for energy system modelling as well as existing and emerging approaches. Based on a description of the philosophy and elementary structural elements of oemof, a qualitative analysis of the framework with regard to the challenges is undertaken. Inherent features of oemof such as the open source, open data, non-proprietary and collaborative modelling approach are preconditions to meet modern realities of energy modelling. Additionally, a generic basis with an object-oriented implementation allows to tackle challenges related to complexity of highly integrated future energy systems and sets the foundation to address uncertainty in the future. Experiences from the collaborative modelling approach can enrich interdisciplinary modelling activities. Our analysis concludes that there are remaining challenges that can neither be tackled by a model nor a modelling framework. Among these are problems connected to result communication and interpretation.

Integrating a grid-connected battery into a Renewable Energy Community boosts Collective-Self-Consumption of photovoltaic produced energy and allow to perform Energy Arbitrage in the day-ahead and intraday electricity market. However, is it a cost-effective investment? The proposed analysis relay on Net Present Value assessment. Ageing affects are integrated and sensitivity analyses are conducted: considering community customers number, electricity mar-ket prices, battery cost, size and the decision to engage in energy arbitrage. Each scenario under-goes a 20-year hourly simulation using an ageing aware rolling-horizon 24-hours-looking-ahead scheduling, optimized with Mixed-integer linear Programming. Forecast errors, provid-ing of ancillary services, real time control and grid constrains are not taken into account. Simulations conducted on the Italian market indicates that a battery dedicated solely to collec-tive self-consumption is not economically appealing. However, integrating Energy Arbitrage, despite impact on battery lifespan, halves the payback period and enhances the attractiveness of larger battery investments. The Net Present Value is contingent upon battery size, customer number and market prices. However, if battery cost does not exceed 200 €/kWh the investment become cost-effective across all scenarios.

The transition to sustainable energy systems in the Middle East and North Africa (MENA) region addresses critical challenges of environmental protection, energy security, and socio-economic resilience. Using neo-institutional theory, this paper examines the intricate relationship between formal and informal institutions and their significant impact on the region’s energy transition. Despite the MENA region’s abundant renewable energy resources, numerous institutional barriers, such as governance inefficiencies, regulatory inconsistencies, and entrenched socio-cultural norms, significantly hinder this transition. Through a review of existing literature, this study presents a comprehensive analytical framework designed to overcome these barriers, with a focus on the Just and Sustainable Energy Transition model. This strategic model emphasizes equity, sustainability, and inclusive governance as pillars for reform. The study offers detailed recommendations for institutional change and underscores the importance of collaborative efforts among governments, industry stakeholders, and international partners to unlock the MENA region’s renewable energy potential, advance global sustainability goals, and ensure a more secure and resilient energy future.