Buildings can play an important role in reducing GHG emissions through increased energy efficiency. The European Commission issued a proposal in 2021 suggesting that all new buildings should be “zero-emission Buildings” (ZEB), aiming at a zero GHG emission building stock by 2050.The extent to which ZEB can contribute to reduced GHG emissions, however, varies between countries, due to different energy systems. It is also important to consider other environmental effects to avoid that climate benefits come with unintended consequences.Here, we explore the life-cycle environmental performance for a ZEB in a case where electricity and heating is largely fossil-free. The assessment concentrates on i) environmental impact of the use stage in relation to the product stage, ii) the interrelation between different energy sources, with attention on household electricity, and iii) the performance for more impact categories than primary energy use and climate change. While our results generally support the use of ZEBs from an environmental perspective, they also show that the climate benefit in this setting is marginal. However, given that energy systems are connected and energy savings in one place can reduce the demand for fossil energy elsewhere, the climate benefit of ZEBs is likely underestimated. Besides methdological implications for future studies, this indicates that current EU policy is promising, as incentives for implementation of ZEBs is unaffected by domestic effects.

Kenya’s construction industry is experiencing exponential growth in tandem with construction trends globally. With the growth experienced in the industry, there has been significant growth in the economy and a 50% contribution to the world’s landfill waste and pollution to the adjacent environment. Globally, the construction industry is among the largest consumers of natural resources and significant contributors to pollution. This has given rise to high pressure to adopt environmentally sensitive approaches in the construction industry to present a competitive advantage. It is, therefore, crucial to address the need for sustainability measures for Landscape Architecture projects to increase knowledge and awareness, create incentives geared towards supporting sustainable practices, and leverage legal instruments and policies. Green construction practices and strategies have positively impacted the environment and the Kenyan construction industry’s social and economic performance. However, there are several barriers to the adoption and improvement of monitoring and evaluation of sustainable practices, thus slowing down the industry in taking charge of sustainability.

Shared public buildings have become centers of innovation, integrating advanced technologies to meet evolving societal needs. With a heightened emphasis on occupants’ health and well-being, these buildings serve as hubs for technological convergence, facilitating seamless connectivity and intelligent data analysis and management. Within this context, environmental monitoring emerges as a foundational element, pivotal to all aspects of building management. This article provides findings from the nationally funded RE-START project, which focuses on shared public buildings, with special regard to educational and medical facilities. The project explores enhanced indoor air quality monitoring, focusing in particular on CO2 concentration that is directly correlated with occupancy, as a fundamental element for developing health and safety protocols, energy efficiency strategies, integration of smart building technologies, and data-driven energy management. The intersection of environmental monitoring, energy efficiency, security, and IoT technologies in in indoor spaces are relevant. The outcomes of the study reveal the delicate nature of all the involved components, that need to be carefully developed in an integrated manner.

High-performance insulation and airtight building envelopes are the two most important factors to optimize the building energy efficiency and thermal performance. However, thermal performance of building envelopes can be significantly affected by thermal bridging. Thermal bridges can take place at different locations of the building envelope, causing added transmission losses, increasing heat flow, lower inner surface temperatures. Thermal bridges are regarded in all national regulations for new buildings of all states of European Union (EU) but there are no specifications assessing balconies to wall junctions and the impact on the building thermal performance is not well regulated. In this paper, balcony to wall thermal bridge assessment using infrared thermography is highlighted. The originality is that, infrared thermography, has been applied to a real living latest building in the north east of France showing that there is noncompliance in the national regulations as some exigencies are not met. Thermography of thermal break windows and window doors has also revealed air leakage. The goal, is to illustrate that thermal imaging is a means of quality assurance to new building specifications and should include a clause specifying quality assurance procedure for balconies junction in national building regulations for all states if the EU.

This paper details the comprehensive activities conducted in a laboratory setting to assess the Structural Health Monitoring (SHM) of prefabricated building envelopes. Aimed at enhancing the structural evaluation of buildings, the focus of this research lies in employing nondestructive sensors for SHM with the objective to advance in the understanding and assessment of facade conditions. The paper outlines the methodologies employed, starting with a modal analysis to define the structural vibration's modal frequency. Subsequently, tests were defined and executed to validate building envelope compliance in case of stress typical of high-rise building. Throughout these tests, continuous monitoring of the façade was conducted using both conventional (accelerometers, extensimeter washers) and non-conventional sensors (Fiber Optic Sensing) The gathered data underwent thorough processing and analysis to provide an overall perspective on the structure's behavior during the stress test. The investigation aimed to identify whether specific physical phenomena correlate with distinct signals and to evaluate if continuous façade monitoring over the building's lifespan aids in preventing potential structural damage. Moreover, two modal analyses were conducted to compare final data and frequencies with earlier data, enabling the detection of any structural alterations. The results from compliance testing and structural analysis yielded noteworthy insights contributing to the evolving field of structural health monitoring, offering valuable findings that advance our ability to proactively manage and maintain the integrity of building structures.

This paper presents a study about the integration of Piezoelectric Energy Harvesting Systems (PE-EHS) in building envelopes for powering Fiber Bragg Grating (FBG) sensors, enabling efficient and low-consumption monitoring with the objective to leverage Structural Health Monitoring (SHM). The research includes preliminary tests conducted in a real environment to validate the PE-EHS when fully integrated into the façade, capturing mechanical vibrations generated mainly by wind loads. Based on these activities, the final configuration of PE-EHS is defined to provide a complete system for façade monitoring. This integrated system includes the Piezoelectric Generator (PEG), Supercapacitor (SC), Power Conditioner Circuit (PCC), Fibre Optic Sensing (FOS) Interrogator, and the IoT Gateway trans-mitting measurement data within an Internet of Things (IoT) monitoring platform. This configuration is tailored to address the challenges related to the structural integrity of building envelopes. Results demonstrate a potential for a stand-alone solution in the façade sector, but, raising issues for certain limitations, requiring further investigation. In particular, the study emphasizes constraints related to the energy production of PE-EHS for façade integration. It highlights the necessity to carefully consider these limitations within the broader context of their applicability, providing insights for the informed deployment of Piezoelectric Energy Harvesting technology in building envelope monitoring.

In the scientific community, it is difficult to find a consensus on defining BIM. Just as the acronym BIM is developed in different ways, it is also understood in different ways. Depending on its understanding, different definitions emerge. It is defined differently by organizations and standards, still differently by academics. Many years of academic discourse on the subject have failed to produce a solution. Despite the fact that the acronym BIM has already done its work for the construction industry, it still stirs up excitement. There is still no clear definition, as the view of BIM varies from one perspective to another. This article attempts to sort out the definitions cited so far by important organizations and key academics. The review was based on deep literature study has attempted to be inclusive and consistent. The question still remains open: do we need a single, correct definition of BIM? The aim of the article is to try to answer this question, open up a renewed discussion and come to a satisfactory consensus. BIM can be identified with an activity, product or system. The article breaks down the definitions of BIM, identifies six key attributes of BIM, presents the evolution of the understanding of BIM and proposes new definitions in a narrow and broad approach.

High-rise building machines (HBMs) play a critical role in the successful construction of super-high skyscrapers, providing essential support and ensuring safety. The HBM’s climbing system relies on a jacking mechanism consisting of several independent jacking cylinders. A reliable control system is imperative to maintain a smooth posture of the construction steel platform (SP) under the action of the jacking mechanism. This research introduces three multivariate time series neural network models—namely, Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and Temporal Convolutional Network (TCN)—to predict the posture of HBM. The models take pressure and stroke measurements from the jacking cylinders as inputs, and their outputs determine the levelness of the SP and the posture of the HBM at various climbing stages. The development and training of these neural networks are based on historical on-site data, with the predictions subjected to thorough comparative analysis. All proposed neural network models exhibit the capability to dynamically predict the posture of the HBM during the climbing process, using data from sensors. Notably, the GRU model shows better predictive performance.

In the construction sector, the integration of biobased materials has emerged as a pivotal aspect of EU policies, aimed at promoting sustainable practices throughout the value chain to mitigate resource consumption and carbon emissions. This paper explores the development and validation activities of a bio-based façade system within the Basajaun H2020 project, focusing on enhancing the utilization of biobased components within building envelopes to replace conventional solutions with eco-friendly alternatives. This paper reports the methodologies employed to detect requirements and outline the testing protocols undertaken to validate the façade system design devised within the project focusing on the original façade components as the bio composite profile. Vision and opaque façade modules are prototyped and tested following curtain wall standards standard for performance and acoustic assessments, to showcase the efficacy of the developed solution. The conducted tests demonstrate the feasibility of integrating bio-based components into building envelopes, aligning with project expectations, and prevailing standards for curtain wall façade solutions. Notably, the designed façade system meets technical conditions and project objectives. Nevertheless, the research underscores the need for further refinements to facilitate solution industrialization and explore broader market applicability. Future efforts will focus on addressing these improvements and assessing the scalability of the solution.

Although buildings constitute 35% of global energy use and 38% of carbon emissions from energy, the amount of energy and energy-related carbon emissions are increasing rapidly. On the other hand, non-renewable usable energy resources are decreasing on the contrary. New buildings are being built due to the increasing population and the existing building stock not meeting the needs or losing its lifespan. Some of the existing building stock is demolished and renewed for structural reasons and some for reasons such as usage performance. It is possible to reduce both energy consumption and greenhouse gas emissions with strategic energy uses in existing building stocks. There are various techniques to measure the maximum performance of sustainable and energy-efficient use of existing building stocks with which changes. Building Information Modeling (BIM) technology is one of these techniques that provides wide opportunities to users in recent years, and it is almost a virtual laboratory of structures. Building stocks can be modeled with BIM, and alternative shell and system suggestions can be used to measure how building performance has changed and to achieve the best results. In this research study, improvement scenarios that optimize energy use in existing building stocks are investigated on a sample residential building by using the virtual laboratory facilities of BIM. After measuring the current energy performance of the existing building with BIM tools, 192 alternative results were obtained with 6 variables (external walls, roof, insulation layers, transparent surface materials, lighting, and photovoltaic panels). The obtained alternatives were compared with the current state of the existing building. The material expenditures and amortization periods required for these alternative scenarios are also calculated. The results obtained were evaluated according to annual / lifetime energy consumption, fuel, electricity, initial investment costs, energy use intensity, and carbon emission amounts. With the optimization of the current situation of the sample building, annual fuel consumption decreased by 61% and electricity consumption by 64%. The amortization period of the optimum improvement was determined as 12 years.

eHealth applications are an essential component in achieving Universal Health Coverage. (1) Background: The lack of skilled healthcare personnel has hindered successful integration and use, especially in developing and low and middle-income countries. (2) Methods: A descriptive study was conducted using an online survey to collect quantitative data from 37 organizations to address this issue. (3) Results: The findings showed that there are limited training opportunities available for policymakers and eHealth specialists. Additionally, obstacles such as insufficient funds, inadequate infrastructure, poor leadership, and governance were identified and found to be context specific. To mitigate these challenges, the study proposed continuous in-service training, the implementation of computer-based systems, and the integration of academic modules. The importance of strong eHealth policies and committed leaders was also emphasized. (4) Conclusions: The results of this study support previous research and emphasize the importance of implementing practical and uncomplicated solutions to overcome eHealth barriers to capacity building in low- and middle-income countries. It is essential to recognize that the data collected for this study only pertains to BETTEReHEALTH.

The building and construction sector has a significant impact on CO2 emissions and pollutants released into the atmosphere, which contribute to climate change. The EPDB Directive mandates the achievement of a minimum energy class E for all residential buildings by 2030 and an energy class D by 2033. Particularly, in Italy, about 86% of the existing building stock predates the enactment of any energy laws and regulations, making it imperative to apply the energy efficiency interventions. This paper provides a support decision tool for the identification of standardized interventions on the envelope, air conditioning system and domestic hot water production. The study is focused on a specific construction period class (1976 - 1990) in six different climatic zones. The methodological approach is based on a cataloguing phase and definition of Ante Operam energy classes, on the case study identification, the energy requalification interventions identification, solutions simulations, cost estimation. By simulating standardized interventions for each climatic zone, a range of possible combinations will be identified. The most advantageous ones will be determined based on a cost-benefit analysis, considering the potential class jump achieved. The research result is a matrix of energy efficiency interventions that is applicable to each climatic zone and can be extended to the existing housing stock.

The aim of this study is to propose and validate the state space mode decomposition technique for precise mode separation of non-classical damping systems and closely distributed modal systems. To assess the reliability and applicability of this technique, a 40-story building with a tuned mass damper is investigated, and acceleration responses measured by the building's health monitoring system are used for the verification of the technique. The mode separation results reveal that the separated modal power spectrum becomes distorted at neighboring natural frequency ranges when the performance index only considers the concentration of power spectral energy at the target natural frequency. However, by introducing an augmented performance index that includes a constraint condition to account for distortion, more accurate mode decomposition can be achieved.

Implementing net-zero building design is a crucial step towards decarbonizing the built environment during the entire lifecycle of a building, encompassing both embodied and operational carbon. This paper presents a novel computational approach to design Life Cycle Zero-Carbon Building (LC-ZCB), utilizing parametric integrated modeling through the versatile Grasshopper platform and its plug-ins. The Department of Energy’s prototype residential building at New York Institute of Technology, optimized to fulfill the LC-ZCB target, serves as the base building for this comprehensive study. Four main influencing design parameters, namely geometry, construction technology, thermal resistance of the envelope, and on-site renewable energy production, are defined and three-hundred design combinations are evaluated through the assessment of the operational carbon (OC) and embodied carbon (EC). By incorporating bio-based materials in the design options, the influence of biogenic carbon on the whole carbon footprint of the building case study is addressed by utilizing the GWPbio dynamic method, which assumes 100-year time horizon and incorporates dynamic characterization factors based on time of pulse emissions and two variables: rotation of the biomass and storage period of carbon in products. Finally, to account for potential climate changes, future climate data and 2099 weather conditions are considered during the scenarios assessment. The results demonstrate the potential for achieving LC-ZCB when fast growing biobased materials are largely used as construction materials, fostering a more environmentally responsible future for the construction industry.

The increased focus on sustainability in response to climate changes has given rise to many new initiatives to meet the rise in building load demand. The concept of distributed energy resources (DER) and optimal control of supply to meet power demands in buildings have resulted in growing interest to adopt microgrids for a precinct or a university campus. In this paper, a model for an actual physical microgrid has been constructed in OPAL-RT for real-time simulation studies. The load demands for SIT@NYP campus and its weather data are collected to serve as input to run on the digital twin model of DERs of the microgrid. The dynamic response of the microgrid model in response to fluctuations in power generation due to intermittent solar PV generation and load demands are examined via real-time simulation studies and compared with the response of the physical assets. It is observed that the simulation results match closely to the performance of the actual physical asset. As such, the developed microgrid model offers plug-and-play capability which will allow power providers to better plan for on-site deployment of renewable energy sources and energy storage to match the expected building energy demand.

This paper reports aligned activities to promote energy and resource-efficient construction practice in Vietnam. First, the governance framework is introduced, including government decrees and technical standards. Then, a laboratory with building physics measurement technology is designed and partly set up at the local partner Vietnam Institute for Building Materials (VIBM), which can be used to determine the essential characteristic values required for the implementation of energy standards. The basis for the prioritization of the characteristic values are the requirements of the National technical regulation on energy efficient buildings of Vietnam – QCVN09:2017/BXD. Furthermore, basic characteristic values from international standards are described, which can also be used for calculations to optimize the energy consumption of buildings. In order to be able to carry out transient hygrothermal computer simulations, special characteristic values were also included. These are particularly useful for the research and development of new building materials and the evaluation of entire buildings in terms of thermal and moisture protection In order to communicate the material properties to the market and enable informed decision making by the stakeholders, a labeling system has been developed. Thereby, the practical means for implementing governance instruments are provided, and the related technical applications are supported.

In recent years, due to the low energy utilization of the whole life-cycle of buildings and the di-minished indoor and outdoor comfort of buildings and the impact on the surrounding environ-ment caused by the carbon emissions of the building life-cycle, the establishment of a whole life- cycle carbon emission model for buildings to improve their energy utilization at all stages of their life-cycle has received unprecedented attention. In China, the construction industry has become a major carbon emitter, and traditional houses, as a green development building type, are an effec-tive way to achieve carbon neutrality in buildings, but the existing green building evaluation system lacks quantitative indicators of carbon emissions in the building life-cycle. The exclusive evaluation indexes for regional and characteristic buildings, such as traditional houses, are ne-glected; This study explored the formula for calculating the life-cycle carbon emissions model of traditional residential houses under a carbon emission intervention and used real measurements of the physical environment and comparative analysis of the limitations of existing local stand-ards; The results showed that the carbon emission calculation formulas for each stage of the life-cycle of traditional residential houses must be established by combining the selection of local building materials, and the materials for sustainable energy and carbon sinks of green systems. Based on the results of indoor and outdoor heat and humidity environmental tests of residential houses and an analysis of the limitations of existing evaluation indexes due to locality, four im-portant factors affecting locality green buildings in terms of energy utilization, site ecology and landscape, land saving and material saving were extracted; on this basis, the whole life-cycle carbon emission model of traditional residential houses is constructed by combining the existing green building evaluation standards with the carbon emission indexes of the life-cycle of tradi-tional residential houses.

2,7-bis(pyridin-4-ylethynyl)-9H-carbazole (1) was synthesized by reacting 4-ethynylpyridine hydrochloride with 2,7-dibromo-9H-carbazole. The full characterization of compound 1 is presented, and the crystal structure of its monohydrate co-crystal was determined by single-crystal XRD analysis.

This paper presents a numerical study on the vertical (axial) and lateral (flexure) behavior of CFST (Concrete-Filled Steel Tube) columns with active hoop prestress; this transverse prestressing effect is achieved by bolting together two steel half-tubes. This study refers to new construction only (i.e., no retrofit). 12 prototype CFST column specimens (segments) are analyzed. These specimens differ in the prestressing force (3 levels) and in the gravity loading ratio (4 levels); they are selected to represent typical ground columns of mid-rise buildings. The structural behavior of these column specimens is simulated with a nonlinear model implemented in Abaqus; the concrete and steel behavior are described with a damage-plasticity and a plasticity model, respectively. Finally, the interface concrete-steel interaction is represented by a hard (compression-only) surface-to-surface contact model. The calculations involve three consecutive loading steps: (i) transverse prestress, (ii) axial force, and (iii) lateral loading (shear force and bending moment). The structural behavior of the CFST columns is deeply examined and discussed; the results show that their axial-flexural capacity is adequate. Noticeably, it is concluded that the overall benefits of prestressing the columns are only modest. Preliminary studies on the aforementioned mid-rise buildings equipped with the CFST columns show that their gravity and wind capacities are largely enough; conversely, their seismic capacity is sufficient for moderate seismic ground motions only.

Dealing with and maintaining high-quality standards in the design and construction phases is challenging, especially for on-site construction. Issues like improper implementation of building components and poor communication can widen the gap between design specifications and actual conditions. To prevent this, particularly for energy-efficient buildings, it's vital to develop resilient, sustainable strategies. These should optimize resource use, minimize environmental impact, and enhance livability, contributing to carbon neutrality by 2050 and climate change mitigation. Traditional post-occupancy evaluations, which identify defects after construction, are impractical for addressing energy performance gaps. A new, real-time inspection approach is necessary throughout the construction process. This paper suggests an innovative guideline for prefabricated buildings, emphasizing digital 'self-instruction' and 'self-inspection'. These procedures ensure activities impacting quality adhere to specific instructions, drawings, and 3D models, incorporating relevant acceptance criteria to verify completion. This methodology, promoting alignment with planned energy-efficient features, is supported by BIM-based software and Augmented Reality (AR) tools, embodying Industry 4.0 principles. BIM and AR bridge the gap between virtual design and actual construction, improving stakeholder communication and enabling real-time monitoring and adjustments. This integration fosters accuracy and efficiency, key for energy-efficient and Nearly Zero-Energy Buildings, marking a shift towards a more precise, collaborative, and environmentally sensible construction industry.

In Germany, as in many developed countries, over 60% of buildings were constructed before 1978, where most are in critical condition, requiring either demolition with plans for redevelopment or renovation and rehabilitation. Given the urgency of climate action and relevant sustainable development goals set by the United Nations, more attention must be shifted toward the various sustainability aspects when deciding on the strategy for renovation or redevelopment of existing buildings. To this end, this study focused on developing a smart decision support framework for aging buildings based on lifecycle sustainability considerations. The framework integrated digital technological advancements, such as building information modeling (BIM), point clouds processing with field information modeling (FIM)®, and structural optimization, together with life-cycle assessment to evaluate and rate the environmental impact of different solutions. Three sustainability aspects, namely, cost, energy consumption, and carbon emissions, were quantitatively evaluated and compared in two scenarios, namely, renovation, and demolition or deconstruction combined with redevelopment. A real building constructed in 1961 was the subject of the experiments to validate the framework. The result outlined the limitations and advantages of each method in terms of economics and environmental impact. It was further observed that optimizing the building design with the goal to reduce embodied energy and carbon in compliance with modern energy standards, was crucial to improve overall energy performance. This work demonstrated that the developed BIM-based framework to assess the environmental impact of rehabilitation work in aging buildings can provide effective ratings to guide decision-making in real-world projects.

Introductions- Liveable housing environments face the menace of global climate change. In-frastructure (including buildings and houses) continuously experiences significant impacts ex-acerbated by natural variability in climate. The study addressed how climate change impacts the resilience of residential buildings, increased maintenance frequency, and the wellbeing and comfort of residents in UK residential buildings. Design/Methodology/Approach: This study used deductive reasoning and an empirical epis-temological methodology as a data-collecting basis to evaluate primary information obtained via a questionnaire. Regression analysis was ultimately employed to analyse the collected da-ta. Result/Discussions: The findings show a significant relationship between climate change and the wellbeing of the occupants of UK residential buildings. Also, the results show that social wellbeing is more important to the occupants than mental and physical wellbeing. It reveals that residential buildings in the UK suffer the cost of maintenance due to continuous reduc-tion in the building fabric's resilience to the impacts of climate change; for instance, a recent increase in rainfall/storms results in unprecedented flooding, which continues to damage the UK residential building fabrics.

The thermal properties of a building envelope are key indicators of the energy performance of the building. Therefore, methods are needed to determine quantities like U-values or heat capacitance in a fast, reliable way and with as little impact on the use of the building as possible. In this paper a technique is proposed that relies on a simplified electrical analogical model of building envelope components which can cover their dynamic thermal behavior. The parameters of this model are optimized to produce the best fit between simulated and measured outside surface temperatures. As the temperatures can be measured remotely with an infrared camera this approach requires significantly less installation effort and intrusion in the building than other methods. At the same time, a single measurement provides data for a large range of locations on a facade or a roof. The paper describes the method and a first experimental implementation of it. The experiment indicates that this method has the potential to produce results which have an accuracy that is comparable to standardized reference methods.

The response of structures under pulse-like ground motions is characterized by the large amount of energy input in a few cycles. Consequently, structures with insufficient strength may suffer severe damage owing to excessive deformation. In a previous paper, the energy-based prediction procedure for the peak and cumulative response of a reinforced concrete (RC) frame building with steel damper columns was proposed (Fujii and Shioda, 2023). Although this procedure was verified by comparison to the nonlinear time-history analysis (NTHA) results, the performance of the proposed procedure with pulse-like ground motion records has not been verified yet. In this study, the accuracy of the energy-based prediction procedure for an RC frame building with steel damper columns was investigated by considering pulse-like ground motions. The numerical analysis results reveal that the accuracy of the predicted peak response is satisfactory, which agrees with the results of the author’s previous study. However, the accuracy of the predicted total input energy to the building model depends on the ratio of the pulse period of the ground motion to the effective fundamental period of the building model. The reasons for this underestimation of the total input energy are discussed in this paper.

Building energy demand impacts a myriad of interconnected economic, societal, and environmental aspects. As a result, Buildings Energy Models (BEM) play an important role in the process of urban design and planning. While previous studies have investigated the effects of building interventions on energy efficiency, their applicability may be limited due to the BEM’s high computational complexity. This limits their ability to systematically study important aspects of energy demand on a large scale. The development of Machine Learning Models (MLM) allows to design the required detailed analysis and solutions, while reducing the computational burden, making MLM attractive for urban designers. The capability of MLM to generalize well for multiple contexts (in our case, multiple buildings) is a crucial contributor to their applicability. However, the validation process in a wider context is often overlooked, therefore its generalization capabilities are not quantified. In this paper, we present a framework to train and validate a surrogate model derived from a physics-based BEM. Our method employs a Multiple Linear Regression model to predict Energy Use Intensity (EUI) for office buildings in Singapore using 36 input parameters (covariates), based on a training dataset of 23,000 samples. Model validation is performed by comparing the results of the Surrogate Model (SM) to a widely used BEM for a sample of 120 buildings. Our results indicate that the SM has an accuracy of NRMSE of 13%, NMBE of −3.56%, and R2 of 0.92, which suggests it can effectively and accurately predict building EUI. We also conduct a sensitivity analysis, which indicates that the parameters associated with internal loads and internal space usage are the most influential. Additionally, we present a reduced order model trained with only the 11 most influential parameters, which exhibits negligible loss in accuracy compared to the full SM while providing reduced complexity. Finally, we demonstrate an application of our SM to evaluate energy efficiency under uncertainty scenarios. The analytically derived results indicate a potential reduction of EUI of offices in Singapore from 227kWh/m2 to 99kWh/m2 by altering the building parameters that were identified as most influential.

This paper proposes an active-reactive power collaborative scheduling model with cluster division for the flexible distributed energy resources (DERs) of smart building system to resolve the high complexity of centralized optimal scheduling of massive dispersed DERs in the distribution network. Specifically, the optimization objective of each cluster is to minimize the operational cost, the power loss cost, and penalty cost for the flexibility deficiency, and the second-order cone-based branch flow method is utilized to convert the power flow equations into the linearized cone constraints, reducing the nonlinearity and heavy computation burden of the scheduling model. Customized virtual battery models for the building-integrated flexible DERs are developed to aggregate the power characteristics of flexible resources while quantifying their regulation capacities with time-shifting power and energy boundaries. Moreover, a cluster division algorithm considering the module degree index based on the electrical distance and flexible balance contribution index is formulated for cluster division to achieve the information exchange and energy interaction in the distribution network with high proportion of building-integrated flexible DERs. Comparative studies have demonstrated the superior performance of the proposed methodology on the economic merits and voltage regulation.

The study aims to analyze the characteristic parameters of rooftop photovoltaic (PV) power generation on industrial plant buildings in the Ningxia region of China, in order to evaluate the impact of passive design characteristic parameters on the benefits of PV power generation and determine the degree of impact of different passive design characteristic parameters. The methodology involves analyzing the characteristics of existing industrial plant buildings in Ningxia, China, and conducting a series of regional studies on the parameters of plant PV power generation influencing factors. The simulation results revealed that five features, including roof form, PV panel laying pattern, PV panel laying area, azimuth angle, and PV module material, have a significant impact on PV power generation benefits of industrial plant buildings.The study further uses MATLAB 2022b to build a backpropagation neural network model with 5 neurons in the implicit layer to predict the PV power generation benefits. The model calculates the whole-life cycle power generation benefits and the whole-life cycle reduction of carbon emissions as output data. Finally, the Mean Impact Value (MIV) method is employed to select the feature parameter values one by one within their range, and the passive design feature parameters that have the greatest influence on the prediction results are identified as the PV panel laying method, the PV panel tilt angle, and the PV material parameters, respectively.

This study focuses on the increased risk of high heat release and asphyxiation (toxic gas poisoning) in the event of a fire of polyurethane (PU) and MDF-based building materials, which are commonly used in building fires. Among them, polyurethane (PU) building materials are essential for buildings except in Europe and some other countries due to their excellent thermal insulation performance, but problems of short-term heat release and spread of toxic gases in the event of a fire continue to occur. To overcome these problems, researchers are actively working on introducing various flame retardants into building materials. Therefore, in this study, we produced a laboratory-sized (500mm*500mm) plate flame retardant board that can be utilized as a building material with a lower heat release rate and a lower toxicity index by mixing expanded graphite and ceramic binder as flame retardants in a main material based on the cellulose of waste paper by replacing the existing building materials with a hot-press method. According to the ISO-5660-1 test on the heat release rate of the plate flame retardant board, the THR value was 2.9 (MJ/m2) for 10 minutes, showing an effect of reducing the THR value by 36.3 (MJ/m2) compared to the THR value of 39.2 (MJ/m2) of the specimen made using only paper. In addition, the toxicity index of the flame retardant board was checked through the NES 713 test. As a result, the test specimen showed a toxicity index of 0.7, which is 2.4 lower than the toxicity index of 3.1 of MDF, which is utilized as a conventional building material. Based on the results of this study, the cellulose fire retardant board showed the effect of reducing the heat release rate and toxicity index of building materials in a building fire, which reduces the risk of rapid heat spread and smoke toxicity. This has the potential to improve the evacuation time (A-SET) of evacuees in fires. It is also important to show that recycling waste paper and utilizing it as the main material for building materials can be an alternative in terms of sustainable development.

The main development direction of energy efficiency technologies in construction is the creation of various materials with a complex structure and unique strength, thermal and other properties. The aerogel is a material with high porosity and excellent thermal insulation properties. This paper provides the state-of-the-art of aerogel applications for the additive manufacturing of energy efficient buildings. This work provides the experimental and numerical assessment results of thermal conductivity of aerogel-enhanced blanket, the experimental assessment results of thermal performance of aerogel-enhanced building structure, the experimental assessment results of the aerogel application as mixture powder component of the concrete mixture to printing building and the experimental assessment results of the aerogel application as parget powder component. Experimental results show the effect of aerogel powder component application: thermal conductivity decreased by 25%.

The research on the distribution of rural buildings is one of the fundamental works of urban-rural development in Vietnam. Adopting Mask R-CNN deep learning framework and collecting sub-meter remote sensing images, this research used a remote sensing interpretation model of rural buildings trained based on East Asian characteristics of rural buildings and successfully recognized about 2.87 million rural buildings in 34 Vietnamese provincial administrative districts with a total area of rural buildings of 2,492 million square meters. The reliability of the identification results was verified by manual detection and quantitative statistics, and a multi-scale database of rural buildings in Vietnam based on individual rural buildings was created. Based on the database, this paper analyzes the distribution characteristics of rural buildings and summarizes characteristics of rural buildings distribution at the country, regional, and provincial scales. The identification results lay the foundation for the next study of urban-rural relations in Southeast Asia and the construction of a basic database on villages.

In order to foster a more sustainable and eco-friendly trajectory for the construction industry, while concurrently mitigating environmental pollution and energy inefficiency, it is imperative to cultivate an environmentally conscious building and urban environment. Under the background of carbon peak and carbon neutrality, green building evaluation system (GBRS) has become a research hotspot in the field of green building. This paper systematically summarizes the current research progress based on GBRS, focuses on the current weight and indicators setting, analyzes it with Cite Space software, and puts forward its future development direction. The results show that the weight setting method of green building evaluation system is determined by multidimensional and multi-method. From the perspective of environment, society and economy, the scope of indicators setting is expanding. The green building evaluation system will play a guiding role in green building design, and the evaluation process will continue to be optimized and developed in the direction of intelligence and automation.

This research paper examines the role of mass media in fostering positivity for the purpose of nation building. The mass media, including television, radio, print, and online platforms, holds significant influence over public opinion and societal attitudes. However, in recent years, there has been a growing concern about the predominance of negative news and content, which can have detrimental effects on the overall well-being of individuals and the development of a cohesive society. This study explores strategies and approaches to enhance positivity in mass media for the betterment of nations. It investigates the potential benefits, challenges, and ethical considerations associated with promoting positivity through various media channels. This paper provides recommendations for media organizations, policymakers, and society at large to cultivate a more positive media landscape that contributes to nation building.

Scaffoldings play a critical role as temporary structures in supporting construction processes. Accidents at construction sites frequently stem from issues related to scaffoldings, including insufficient support caused by deviations from the construction design, insecure rod connections, or absence of cross bracing, which result in uneven loading and potential collapse, leading to casualties. In this study, we introduce a deep-learning-based, augmented reality (AR)-enabled system called scaffolding assembly deficiency detection system (SADDS) to assist field inspectors in identifying deficiencies in scaffolding assemblies. Inspectors have the flexibility to utilize SADDS through various devices, such as video cameras, mobile phones, or AR goggles (i.e., Microsoft HoloLens 2), for automated detection of deficiencies in scaffolding assemblies. The training test yielded satisfactory results, with a mean average precision of 0.89 and individual precision values of 0.96, 0.82, 0.90, and 0.89 for “qualified” frames and frames with the “missing cross-tie rod,” “missing lower-tie rod,” and “missing footboard” deficiencies, respectively. Field tests conducted at two construction sites demonstrated improved system performance compared to that in the training test. However, these field tests also revealed certain limitations of the SADDS system.

In the field of adaptive building technologies, this research introduces the development of a self-regulating solar shading actuator, that utilizes the thermal shape memory effect. The study places its focus on addressing the actuator’s performance under diverse environmental conditions. Thermal simulations were carried out during the development of the individual components of the actuator and for the prediction of specific switching temperatures. The investigation includes an analysis of the sunshade’s response to varying environmental conditions, emphasizing its effectiveness on clear summer days and identifying challenges during overcast periods. The critical coordination between the solar collector and the shape memory alloy (SMA) wire is examined, shedding light on the impact of SMA temperature dynamics on the actuation performance. Through the integration of simulation data and real-world measurements, the study validates the thermal model for the solar collector, establishing the robustness of the system’s operation. This research work contributes significantly to the development of intelligent actuators and outlines the importance of validation of SMA-based applications under real conditions.

Efficient fixed crane position analysis is critical in precast buildings construction to maximize lifting efficiency for precast elements. The primary objective is to minimize the travel distances of fixed cranes, thereby enhancing operational efficiency and cost control. This involves strategically reducing the distances between the transport truck parking, where elements are stored, the fixed crane, and the construction installation point. Despite its significance, existing studies often overlook the dynamic movement efficiency of transport trucks, particularly when dealing with multiple transport trucks and various models of fixed cranes, rendering the opti-mization of this scenario a challenging NP-hard problem susceptible to combinatorial explosion. This study presents a novel mathematical model leveraging the Genetic Algorithm (GA). The model aims to solve optimal model and position of fixed cranes, along with identifying ideal positions for transport truck parking. The study's methodology is validated and demonstrated through a project case study. Comparative analyses between the proposed model and the original planning underscore a noteworthy 6% reduction in both duration and costs when lifting elements directly from transport trucks, as opposed to establishing an on-site stock yard. Furthermore, the developed GA exhibits a substantial improvement in final solutions, achieving a remarkable 30% reduction in both operational duration and costs. This research contributes valuable insights into fixed crane position analysis of precast building construction, providing foundation for enhanced operational efficiency and cost-effectiveness in the industry.

Matrix-variate Gaussian type or Wishart type distributions in the real domain are widely used in the literature. When the exponential trace has an arbitrary power and when a factor involving a determinant enters into the model or a matrix-variate gamma type or Wishart type model with exponential trace having an arbitrary power, is extremely difficult to handle. Evaluation of the normalizing constant in such a model is the most important part because when studying the properties of such a model, the method used in the evaluation of the normalizing constant will be the relevant steps in all the computations involved. One such model with a factor involving a trace and the exponential trace having an arbitrary power, in the real domain, is known in the literature as Kotz' model. No explicit evaluation of the normalizing constant in the model involving trace with an exponent and determinant with an exponent entering into the model and at the same time the exponential trace having an arbitrary exponent seems to be available in the literature. The normalizing constant widely used in the literature and interpreted as the normalizing constant in the general model and refers to as a Kotz' model does not seem to be correct. Corresponding model in the complex domain, with the correct normalizing constant, does not seem to be available in the literature. One of the main contributions in this paper is the matrix-variate distributions in the complex domain belonging to Gaussian type, gamma type, type-1 and type-2 beta type when the exponential trace has an arbitrary power. All these models are believed to be new. A second main contribution is the explicit evaluation of the the normalizing constants, in the real and complex domains especially in the complex domain, in a matrix-variate model involving a determinant and a trace as multiplicative factors and at the same time the exponential trace having an arbitrary power. Another main contribution is the introduction of matrix-variate models with exponential trace having an arbitrary exponent, in the categories of type-1 beta, type-2 beta and gamma distributions or in the family of Mathai's pathway models [1], both in the real and complex domains. Another new contribution is the logistic-based extensions of models in the real and complex domains with exponential trace having an arbitrary exponent and connecting to extended zeta functions introduced by this author recently. Some properties of such models are indicated but not derived in detail in order to limit the size of the paper. The techniques and steps used at various stages in this paper will be highly useful for people working in multivariate statistical analysis as well as people applying such models in engineering problems, communication theory, quantum physics and related areas, apart from statistical applications.

The aim of this study is to develop an African Neutral Network (ANN) model for predicting temperature and relative humidity in the greenhouse during the calendar year. Input data are ambient temperature and relative humidity outside of the greenhouse chosen for a typical meteorological year for the location of the object and the values of temperature and relative humidity of the air in the greenhouse, obtained as a result of a TRNSYS dynamic simulation of the thermal load of the facility. The goal was to show that our ANN model is capable of making predictions over extended time period. The TRNSYS model was created on a real object, taking into account all relevant parameters, in order to describe the dynamic behavior of the object as good as possible. The ANN model is formed of 3 layers, where the number of neurons in the hidden layer is obtained by training different types in order to reach the optimal number of neurons, and the values of the learning rate and epochs are also varied. The activation functions were respectively the hyperbolic tangent in the hidden layer and the linear function in the output layer. The Root Mean Square Error (RMSE), Mean Absolute Error (MAE) and Correlation Coefficient were chosen as the statistical criteria for measuring of the network performance. MAE and RMSE showed that the model with 6 neurons in the hidden layer gave the best results of data prediction in relation to the input data. Statistical analysis of output shows that, the RMSE and Mean Absolute Error (MAE) between the measured and predicted temperature was 0.3166 °C and 0.1002°, and the relative humidity RMSE and MAE was 5.9% and 3.4%, respectively, which can satisfy the demand of greenhouse climate control. The results of the study showed that the model can be used with satisfactory accuracy to predict the parameters of the internal environment, in relation to the complex simulation of the thermal load of the object.

In the context of the French tertiary decree, it is crucial to reduce the energy consumption of buildings by first addressing the design of the electrical architecture. Implementing Direct Current (DC) nanogrids in buildings could offers a promising advantage for energy efficiency, significantly impacting overall energy consumption and sustainability goals. For an insulated area with a subtropical climate, such as La Réunion island, DC nanogrids could also facilitate the insertion of local renewable energy sources, especially solar energy. This article presents the deployment and efficiency evaluation of an end-to-end Low Voltage Direct Current (LVDC) nanogrid, from conception to real-world installation within a company. The nanogrid consists of a photovoltaic power plant, a Lithium-Iron-Phosphate (LFP) battery, and DC end-use equipment such as LED lighting and DC fans for two individual offices. An innovation is provided for the power supply and energy management of terminal equipment using the Power Over Ethernet (PoE) standard IEEE 802.3bt. The efficiency of the nanogrid is measured to be 40% higher than the efficiency of an installation powered by PV and distributed at 230 VAC. These results are obtained under certain deployment conditions, which are discussed in this article, in order to enhance the energy efficiency of buildings by using 48VDC. The nanogrid hardware and software infrastructure, the methodology employed for efficiency quantification and the measurement results are described in the paper.

The benefits of cycling as a sustainable transportation mode are widely recognized. Cycling to work offers numerous advantages for individuals, employers, the environment, and society, ranging from improved physical health, wellbeing, and productivity to enhanced public health and reduced carbon emissions. Many governments around the world have implemented various policy measures, interventions, and initiatives to promote cycling. Some cities and towns have encouraged workplaces to provide bike-friendly amenities, such as secure bike parking/storage and shower and changing facility (referred to as end-of-trip facilities), to accommodate cyclists and motivate more employees to embrace sustainable transportation options. However, the presence or absence of such amenities has been found to both positively influence cycling behavior or deter some individuals from cycling to work. Despite the desirability of these amenities, the number of office buildings equipped with bike storage and shower/changing facility remains small, and their economic value is not well understood. In this paper, we aim to investigate whether the presence of cycling-supportive facilities could add value to office buildings. Specifically, we conduct a study using data from office buildings across England as of the end of 2021. We employ hedonic techniques to examine whether office buildings with bike storage and/or shower facility command a rent premium and whether the existence of a rent premium for bike storage and/or shower facility vary by location and across regions in England, independently from any premium associated with BREEM certification. We find that the buildings with bike storage and shower facility secure rent premiums respectively. The level of rent premiums varies with location and regions. The variations of premium are driven by the shortage of the supply of these facilities.

Enhancing energy efficiency within the building sector is imperative to curbing energy losses, given that this sector alone contributes to over 34% of global energy consumption. Employing a building management system, along with its regular updates, presents a strategic avenue to decrease energy usage, enhance building energy efficiency, and more. Tailored control strategies, aligned with the unique characteristics and usage patterns of each building, are essential for achieving energy savings. This article presents an evaluation of HVAC system efficiency in office buildings, utilizing a data-driven approach coupled with simulations conducted in IDA ICE software. The research explores the control strategy of an office building equipped with a constant air volume HVAC system, featuring a regularly controlled air handling unit. The objective is to boost energy efficiency while striking a balance between occupant comfort and energy consumption. Findings indicate that by analyzing measured data and adjusting configurable parameters, building energy consumption can be significantly reduced. Close monitoring of indoor parameters by building operators and corresponding adjustments to the HVAC system can yield energy savings of up to 16%. Leveraging these insights, the paper suggests integrating data-driven and dynamic simulation methods into building management system models to optimize HVAC systems, enhance energy efficiency, and advance ambitious carbon neutrality objectives.

Earth is a complex material with a mechanical and physical behavior that differs from modern building materials. The conservation of rammed earth (RE) constructions presents specific difficulties that are challenging to overcome. The lack of knowledge about RE due to its abandonment for decades and attempts to adopt materials and repair methodologies designed for new building products has led to inadequate interventions. In the case of historic defensive constructions, the doubts and technical difficulties are even greater due to the nature of the so called military RE (with physical and mechanical characteristics significantly different from those of civil, more common, RE) and, not least, due to the historical and cultural heritage value of these constructions. Some important interventions have been carried out recently and others are underway or in the planning stage, and there is a constant lack of information and technical data on the best ways to intervene. To fill this gap, the state of conservation of the RE defensive structures and the results of interventions carried out throughout history in the southwest of the Iberian Peninsula are being assessed. This article sets out the framework of the subject, identifies the material and construction techniques, and recognizes the main causes of its deterioration and decay. With special focus on the most frequent damages detected in historic military defensive structures built with RE, it analyses and discuss the most common techniques that have been used for the repair and conservation of these particular structures.

European cities are motivated to act towards the achievement of climate-neutral mobility solutions. Often, though, they are facing many challenges when bringing (innovative) sustainable mobility solutions forward. Capacity building that fills skills gap and/or enables acquisition of new ones related to the planning and implementation of such solutions can empower local/ regional authorities to identify them, adopt them and eventually deliver them properly. The aim of this paper is to present the Key Performance Indicator (KPI) framework that has been used for the assessment of the effectiveness of the Learning and Exchange Programme applied in an EU-funded project. It presents the methodological steps for the adoption of the KPIs, as well as the tools used for the selection of the KPI data and the KPI monitoring at project level. It also presents the results from the application of the framework for assessing the knowledge performance towards the deployment of sustainable mobility solutions. It finally reflects on recommendations for applying the KPI framework to other cases and thematic contents.

There is a substantial lack of data relating to the hygrothermal traits of existing buildings and building materials. Moisture analysis in building envelopes is 1D (one-dimensional), and 2D and 3D effects and feedback can be neglected. Many European standards treat a moisture percentage in building envelopes as surface and interstitial moisture condensation, such as BS EN ISO 10211, BS EN ISO 13788, BS EN ISO 15148, and BS EN 15026. In this manuscript, there was a tendency to capture a relative quantity of superficial moisture, by metering spots on the inner and outer surface of wall lining systems with a moisture meter. The metering specimens were the buildings with different envelopes: a wooden hut-house, a masonry building and a building partially sheeted in stone. The referent heights on wall linings, for taking the moisture data were specified as 50 cm for a wooden and masonry building and 80 cm for a stone-sheeted building, from the ground. The obtained numeric results were palpable with no regard to the current state of the weather outside. The listed conclusions highlight the significance of a well-tailored building envelope, and its dependence on weather, junctions, gaskets, appropriate materials, etc.

The utilization of primary school buildings is multifaceted, primarily due to the high occupancy density, varying thermal preferences among occupants, diverse indoor activities (such as walking, sports, and conversation), and a constant flow of individuals entering and exiting the building. This results in frequent opening and closing of external windows and doors and fluctuations in internal heat gain. Consequently, frequent interactions between the indoor and outdoor microenvironments lead to energy losses. This study conducts a comprehensive literature review on building energy loss stemming from occupant behavior and the interactions between indoor and outdoor microenvironments. Furthermore, it proposes a dynamic real-time monitoring system based on a computer data capture and visualization platform foundation for building energy loss. The research methods include data crawling, data association rule mining, and data association analysis. The research findings yield a universally applicable and informative building energy-saving design theory based on extensive data analysis. Additionally, the system presents information on occupants' behavior and the microclimate data of indoor and outdoor environments on a computer screen, facilitating human-machine communication and enabling timely adjustments to design strategies for new buildings and operation and maintenance strategies for existing buildings.

The wind flow patterns and pressure distribution around a plus-shaped building are significantly influenced by the dimensions of its re-entrant corners and the overall building height. The present study aims to find the wind effects and study of the pressure distribution with different flow patterns. Plan area of the building is around 300 square meter while the height of the building is 50 meters by keeping the equal length of the re-entrant corners. The research is performed using ANSYS CFX academic version and the results are depicted in various forms such as pressure coefficient (Cpe), stream lines in both vertical as well as in specific surface and pressure contours. The analysis is carried out by varying the wind incident angles, from 0° to 90° at the interval of 15°. The building dimension are scale down to perform the test on length scale of 1:100. Since the considered building model exhibits symmetry along both the axes, present study mostly emphasis on examining re-entrant corners located in the building. This method yields valuable information about how air circulates and how pressure is distributed across a broad spectrum of wind angles. This study provides valuable insights into flow circulation and pressure distribution for a wide range of wind angles.

In China's mountainous coastal terrain, the storm badly damaged low-rise buildings. At present, it is not clear how the relative position of buildings and mountains affects the surface of a low-rise building’s fluctuating coefficient. The study compared these results with the wind pressure distribution without the surrounding environment. The primary objective of this study is to examine the fluctuating coefficient variation rule based on the spacing between hillsides and buildings under 0° wind angle. Additionally, the study analyzes the fluctuating wind pressure coefficient across wind angles between 0°~90°. The distribution of wind pressure in different common hillside landforms was examined through a wind tunnel experiment, which also compared with the distribution in an open environment. The study examined the fluctuating coefficient as the distance between the building and the hillside changed, specifically for wind blowing at a 0° angle. Next, an analysis is conducted on the changing pattern of the fluctuating coefficient for low-rise buildings ranging from a wind angle of 0° to 90°. Simultaneously, the investigation examined the power spectrum and wind pressure’s probability distribution, while considering the proximity of the building to an adjacent hill. The findings indicated that the changing wind pressure factor on the surface of the structure differed based on the relative location of the hillside and the building. The roof's wind pressure coefficient fluctuated and gradually increased until it reached its peak, unaffected by the surroundings. The low-frequency energy decreased in windward eaves, while the high-frequency energy progressively rose as the distance between the hillside and the building increased. The wind pressure on the leeward side exhibited Gaussian characteristics in its probability distribution.

This paper undertakes a comprehensive review to underscore the central role of sustainability in the evaluation and innovation of jet grouting technologies. It meticulously traces the evolution of evaluation methodologies, emphasizing the imperative of sustainable practices throughout history. Traditional evaluation paradigms are examined alongside contemporary trends, with a particular focus on sustainability metrics and visualization techniques. Through an examination of innovative jet grouting technologies, this paper illustrates how sustainability principles have driven advancements aimed at improving the efficiency and environmental impact of jet grouting methods. Central to this review is an assessment of sustainability across multiple dimensions, including method applicability, installation and operational compatibility, and the performance of the resulting jet grouted piles. By emphasizing sustainability considerations, the paper highlights the intrinsic link between environmental integrity and technological innovation in the field of jet grouting. In addition, it discusses analytical evaluation methods designed to proactively address sustainability concerns prior to construction, thereby promoting a more environmentally responsible approach. Finally, this paper presents a pioneering evaluation framework that integrates real-time monitoring and visualization tools, allowing stakeholders to track sustainability milestones throughout the construction process. By emphasizing sustainability as a guiding principle, this review advocates for a paradigm shift toward more ecologically sound and resilient jet grouting practices.

The benchmarking of hotel energy use comprehensively identifies the controllable and uncontrollable factors affecting energy performance, including building characteristics, management strategies, operations, and maintenance systems. Other factors include climatic conditions, floor areas, operating hours, occupancy rates, and guest populations. A benchmarking study on energy consumption patterns in significant hotels (each with less than 100 rooms and an average staff strength of 40 employees), situated in the university town of Nsukka (longitude 70 23' E, latitude 60 52' N), Nigeria, was performed using the data envelopment analysis (DEA) methodology. DEA, a linear programming technique that measures the relative performances of units, was chosen as a benchmarking methodology due to its ability to handle multiple inputs and outputs. Following a correlation test, energy use intensity, diesel consumption, and the number of employees were selected as the analysis inputs, while the occupancy rate was chosen as the output variable. Data on these variables spanning 12 months were collected using questionnaires, interviews, site visits, and oral conversations with hotel managers to ensure validity. Grid-supplied electricity accounted for most of the hotels' energy needs, followed by diesel used in generators. More than 70% of the electricity use was for HVAC. From the DEA, Hotel 3 (DMU H3) had a technical efficiency score of 1, whereas adjustments were recommended for improving the efficiency scores of the other hotels, which were deemed inefficient. DMU H7 had the lowest efficiency score (0.474) and the highest identified savings for electricity and diesel. The analysis also revealed that occupancy rates were generally low in the months of June and July, coinciding with the high rainfall season with its accompanying decline in outdoor activities. Consistent with this, electricity consumption was highest in the Christmas and Easter holiday months of December, January, and April following increased travel-related activities.

Smelting used to be less efficient in the past; therefore, wastes obtained from historical processing at smelter plants usually contain certain quantities of valuable metals. Upon the extraction of useful metal elements, metallurgical slag can be repurposed as an alternative mineral raw material in the building sector. A case study was conducted, which included an investigation of the physico-chemical, mineralogical, and microstructural properties of Pb-Zn slag found at the historic landfill near the Topilnica Veles smelter in North Macedonia. The slag was sampled using drill holes. The mineralogical and microstructural analysis revealed that the Pb-Zn slag is a very complex and inhomogeneous alternative raw material with utilizable levels of metals, specifically Pb (2.3 wt%), Zn (7.1 wt%), and Ag (27.5 ppm). Crystalline mineral phases wurtzite, sphalerite, galena, cerussite, akermanite, wüstite, monticellite, franklinite, and zincite were identified in the analyzed samples. The slag’s matrix consisted of alumino-silicates, amorphous silicates, and mixtures of spinel and silicates. Because the extraction of Pb, Zn, and Ag has economic potential, the first reutilization stage will be to convert metal concentrates into their collective concentrate, from which the maximum amount of these valuable elements may be taken out. This will include combination of gravity concentration and separation techniques. The next step is to assess the Pb-Zn slag’s potential applications in civil engineering based on its mineralogical and physico-mechanical properties. Alumino-silicates, amorphous silicates, and mixtures of spinel and silicates present in Pb-Zn slag, which contain high concentrations of SiO2, Al2O3, CaO, and Fe2O3, are suitable for use in cementitious building composites. The goal of this research is to suggest a solution for closing the circle of slag's reutilization in terms of Zero Waste principles, so it is critical to thoroughly investigate the material and establish methods and preparation processes, as well as ways of concentrating useful components into commercial products.

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.

A comprehensive evaluation system of rural building energy consumption from a innovative composite perspective is established, which is suitable for southwest China. the brainstorming method and Delphi method were used to establish the indicator system, the ANP method was applied to calculate the weights of the comprehensive evaluation model, the scoring criteria of all evaluation indexes are constructed based on fuzzy evaluation theory, the applicability of the model is verified by an example of the countryside around Chengdu. The results showed that the score of some factors is low, whole or part area, just like the percentage of clean energy use(C24), the thermal performance of external walls(E21), the implementation of energy-saving measures(S22), were key factors affecting the target level, which has greater potential for improvement. The distribution of comprehensive indicators and evaluation factors have certain spatial distribution characteristics, the overall spatial distribution shows the characterwastic of "high in the southeast and low in the northwest". The key factors and spatial distribution characteristics found can be used as an important basis for the improvement of green energy-saving promotion measures, energy-saving retrofit programmes were proposed in terms of additional solar room, energy-saving of external walls and air-conditioning temperature setting guidance.

Smelting used to be less efficient in the past, so wastes obtained from historical processing at smelter plants usually contain certain quantities of valuable metals. A case study was conducted, which included an investigation of the physicochemical, mineralogical, and microstructural properties of raw material found at the historic slag pond near the Topilnica Veles smelter in North Macedonia. The Pb-Zn slag was sampled using traditional geophysical methods such as drill holes and pitholes. The mineralogical and microstructural analysis revealed that the Pb-Zn slag is a very complex and inhomogeneous alternative raw material with utilizable levels of metals, specifically Pb (2.24 wt%), Zn (7.10 wt%), and Ag (27.53 ppm). Amorphous phase, lead alloys, zinc alloys, wurtzite, sphalerite, galena, cerussite, elemental silver, elemental copper, elemental iron, magnetite, spinel, rutile, hematite, and troilite were also identified through qualitative mineralogical analysis. The glassy matrix composed of spinel, silicates, and mixed spinel-silicate is the most abundant constituent in slag composition. The various potential applications of the slag are possible based on its mineralogical and geochemical properties. Because the extraction of Pb, Zn, and Ag has certain economic potential, the next step, which will include gravity concentration and magnetic separation procedures, will be to form metal concentrates into their collective concentrate, from which the maximum amount of silver can be extracted. Slag's amorphous spinel, silicate, and mixed spinel-silicate phases, which contain high concentrations of SiO2, Al2O3, CaO, and Fe2O3, are suitable for use in building materials such as cement clinker, filler, or aggregate for concrete or mortar. The goal of this research is to close the circle of slag's reutilization potential in terms of Net Zero and Zero Waste principles, so it is critical to thoroughly investigate the material and establish methods and preparation processes, as well as ways of concentrating useful components into commercial products.

Within the context of sustainable material development for the construction sector, this study explores the viability of panels composed of recycled newspaper-derived cellulose (9%), rice husk (14%), borax (15%), and polyvinyl acetate-based glue (62%). The methods employed involve water absorption and density tests, following ASTM C-1763 and C-303 standards. The fire resistance test conforming to the European standard UNE 23-725-90, and a mold growth test using AOAC 2002.11. The composite is prone to absorbing a significant amount of water when exposed to humid conditions. However, the incorporation of rice husk and borax can provide benefits such as improved moisture resistance compared to other cellulitic insulators, which may be advantageous in specific climates. Also, the developed composite has an intermediate density compared to other polymeric materials. This characteristic presents advantages in applications that demand a balance between strength and lightness. During the fire resistance tests, the samples with borax presented less fire propagation, and superficial damage compared with the specimens without borax. This is important, considering the fireproofing property, required in building materials. The presence of borax in the composite has an inhibitory effect on the growth of fungi and yeasts. These findings are consistent with previous research. Nevertheless, further research and testing are imperative to assess its viability and performance for commercial applications.

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.

The construction sector of the Kingdom of Saudi Arabia (KSA), valued at USD 152 billion and employing 2.54 million people by 2023, is crucial to its economy. However, it faces challenges such as delays, disputes, and cost overruns. This study aims to address these issues by implementing Building Information Modeling (BIM) in the KSA, based on an extensive literature review highlighting the role and significance of BIM in mitigating construction claims. BIM improves collaboration, communication, and data integration among stakeholders. Hence, this study proposes a comprehensive BIM package framework comprising Revit Architecture, Microsoft Project, and Cost-X to reduce claims effectively. Validated through a KSA claims case study with a USD 1,870,000 claims value and 360-day delay, the BIM package significantly reduced the claims value to USD 188,000 and saved 275 days. Interview sessions were conducted to validate the effectiveness of the BIM package; 95% favored the use of BIM, 86% supported NEC4 contract adoption alongside BIM, 100% acknowledged BIM's potential in reducing design errors, 95% were confident in the case study's accuracy, and 82% were satisfied with data accuracy. This study confirms that BIM is an effective approach for minimizing construction claims in the KSA.

The Western Balkans region is persistently vulnerable to natural hazards, inadequate infrastructure, and limited institutional capacities, necessitating a collaborative approach to disaster risk management. This paper presents a comprehensive project led by the Scientific-Professional Society for Disaster Risk Management (NSD-URVs) in Belgrade, aiming to establish and strengthen a regional network of experts in disaster risk management. The project focuses on building expertise, facilitating knowledge exchange, promoting expert coordination, and enhancing cross-border collaboration. Key activities include developing a web platform, organising an international conference, and advocating for regional policies that integrate best practices and innovations in disaster risk management. The expected outcomes are the establishment of a cohesive network, enhanced expertise and coordination, and improved preparedness and responsiveness to disasters. By leveraging collective expertise and resources, this initiative aims to fortify the region's resilience against potential disasters. Addressing the identified gaps and implementing the proposed policy recommendations can significantly enhance the region's resilience to natural hazards. Future research should focus on the implementation and impact of these recommendations to ensure continuous improvement in disaster preparedness and response.

The domain of construction engineering and management is evolving rapidly. Optimizing resource positioning is crucial for meeting the challenges of efficiency and productivity. This research presents a novel methodology that incorporates Agent-Based Modeling (ABM), Building Information Modeling (BIM), and Bluetooth Low Energy (BLE) technologies, augmented with a Client Early Warning System (CEWS) and a Decision Support System (DSS). What makes this study unique is that it provides a real-time methodology for resource allocation and project management, tailored to address the complexities of modern construction projects. The application of this integrated technological framework marks a significant leap in construction management, empowering data-driven decision-making and significantly improving project efficiency. Empirically validated through a case study at Helwan University's College of Engineering and substantiated by expert surveys, this research showcases a transformative model for resource management. The findings not only underscore the practical applicability of this approach but also open new horizons for its adoption in global construction practices, offering insights for future research endeavors focused on expanding these methodologies to a wider range of resources.

The integration of digital technologies into construction practices has emerged as a pivotal area of interest, reflecting its substantial influence on the future trajectory of the construction industry. This study undertakes a comprehensive bibliometric analysis of literature on construction digitalization spanning from 2013 to 2023, sourced from the Elsevier Scopus database. Employing key terms such as "construction digitalization," "BIM," "construction 4.0," and "digital construction methodologies," the research methodically extracts and scrutinizes relevant articles. Advanced tools like the VOS viewer were utilized to delve into the bibliometric networks, offering insights into prevailing research trends within the built environment sector. The findings reveal a pronounced emphasis on digital modeling, automation, blockchain technologies, and emerging paradigms such as smart contracts and modular construction. This investigation enriches the academic discourse by elucidating the varied subtleties, ongoing shifts, and prospective directions in the ever-evolving landscape of construction digitalization research.

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.

Western countries are experiencing an increasing aging population, resulting in heightened disability and mobility issues. This trend is expected to escalate in the coming decades. Therefore, ensuring adequate accessibility in collective residential housing –where individuals spend much of their daily lives– is of paramount importance. This paper presents a case study focused on the accessibility of building entrances in collective residential housing in Southeast Spain, specifically in the Region of Murcia. In this region, 9.8% of the population has disabilities, and 15.75% were over 64 years old in 2020. The study began by compiling the relevant national and regional accessibility regulations for existing buildings. Subsequently, extensive fieldwork was conducted, analyzing 150 collective residential housing buildings. Based on this analysis, a set of recommendations to enhance accessibility was formulated for buildings not complying with the regulations. The results are presented and discussed in detail. The most frequent recommendation was the construction of accessible ramps, identified as the primary solution in over 40% of cases, either alone or in conjunction with other measures. In 54% of the cases, multiple interventions were necessary to achieve effective accessibility adaptation. The findings of this study could inform the development of public policies aimed at improving accessibility conditions in urban areas.

Low energy consumption is a significant contribution of new and retrofitted buildings that place an emphasis on energy efficiency. Although the mandatory requirements of the U-factor and R-value are described in the Vietnamese National Technical Regulation on the energy efficiency of buildings—QCVN09:2017/BXD, these values are not widely publicized, leading to designers facing difficulties when choosing suitable materials at the design stage. This study focuses on the method used to declare the heat transfer values of building materials based on the energy labeling process in order to create an energy labeling program for building materials. To accomplish this objective, criteria and labeling procedures for windows, doors, walls, and building roofs have been developed. In addition, a case study of insulation product labeling was used to evaluate the applicability of the developed labeling program in the implementation phase.

The built environment sector’s growing impact on climate change is becoming increasingly important due to its share in energy consumption and greenhouse gas emissions. Global efforts have been undertaken to design and develop residential dwellings that aim towards zero energy and carbon emission, but there remains a multitude of obstructions to efficient construction processes. This study is focused on the gaps and barriers that have emerged during the pre-construction phase of a low-environmental-impact Passive House in Fayetteville, Arkansas. The technical, management, regulatory, and supply chain obstacles to the construction of a new three-story residential Passive House are documented to engage knowledge transformation in the design and construction of sustainable buildings of interest to developers and property owners. Primary data are collected by direct observation as well as open-ended interviews and secondary data collected through a literature review to understand the barriers and gaps faced by different key actors during the pre-construction phase in different regions. This local study highlighted the lack of interest, knowledge, and experience in sustainable building design among professionals having a significant influence on the project goals and timeline and was mentioned by participants as a common barrier as well as the inconsistency and inadequacy of regulatory framework of existing building codes to implement sustainable building design. These barriers along with other identified barriers are discussed and recommendations to overcome these barriers are provided.

To enable net zero sustainable thermal building energy this study develops an open-source thermal house model to couple solar photovoltaic (PV) and heat pumps (HP) for grid-connected residential housing. The calculation of both space heating and cooling thermal loads and the selection of HP is accomplished with a validated Python model for air-source heat pumps. The capacity of PV required to supply the HPs is calculated using an System Advisor Model integrated Python model. Self-sufficiency and self-consumption of PV and the energy imported/exported to the grid for a case study are provided, which shows that simulations based on the monthly load profile have a significant reduction of 43% for energy sent to/from the grid compared to the detailed hourly simulation and an increase from 30% to 60% for self-consumption and self-sufficiency. These results show the importance of more granular modeling and also indicate mismatches of PV generation and HP load based on hourly simulation datasets. The back-calculation PV sizing algorithm combined with HP and thermal loads presented in this study exhibited robust performance. The results indicate this approach can be used to accelerate the solar electrification of heating and cooling to offset the use of fossil fuels in northern climates.

This paper presents a methodology for the integration of Building Information Modeling (BIM) and Life Cycle Cost Analysis (LCCA) to assess the economic implications of designing aging-in-place (AIP) homes at the conceptual stage. With the global increase in the aging population, there is an increased demand for housing solutions tailored to the needs of elderly individuals. Focusing on the importance of the early phase of design, this study aims to improve the process of making efficient decisions by providing a comprehensive assessment of the life cycle costs associated with AIP homes. The study introduces a semi-automated model for the economic evaluation of AIP homes, enabling the estimation of costs throughout the houses’ entire life cycle, from design and construction to operation, maintenance, and eventual renovation or disposal. The said model facilitates the exploration of the long-term economic feasibility of design’s related decisions with an emphasis on the importance of considering the life cycle costs early during the design process to optimize the functionality and economic viability. By investing in accessible and universal design features upfront, the initial costs for modifications can lead to long-term savings by reducing the need for extensive retrofits. The model can easily do comparison between different design alternatives in terms of their lifecycle costs, allowing designers to assess the financial impact of using important features in their design such as wider doorways, accessible bathrooms, and elevators. Overall, this study provides valuable insights for designers and homeowners about the economic aspects of designing AIP homes as a support for efficient decision-making during the early stages of the design process.

In the ambitiously evolving construction industry of Kuwait, characterized by its vision 2035 and rapid technological integration, there exists a pressing need for advanced analytical frameworks. This research paper introduces a groundbreaking deep learning approach utilising an autoencoder neural network to analyse the complexities of the Kuwait Construction Market and identify data irregularities. The construction sector’s significant investment influx and project expansion make it an ideal candidate for deploying sophisticated analytical techniques to detect anomalous patterns indicating inefficiencies or unveiling potential opportunities. Our approach leverages the capabilities of autoencoder architectures to delve into and understand the prevalent patterns in market behaviours. This meticulous analysis allows for the detection of deviations that may lead to operational or financial consequences. We elucidate the mathematical foundations of autoencoders, highlighting their proficiency in managing the complex, multidimensional data typical of the construction industry. Through training on an extensive dataset—comprising variables like market sizes, investment distributions, and project completions—our model demonstrates its ability to pinpoint subtle yet significant anomalies. The outcomes of this study enhance our understanding of deep learning’s pivotal role in construction and building management. Additionally, our findings proactively sketch the future market trajectory and facilitate anomaly detection, thereby contributing substantially to the academic discussion on integrating machine learning into construction management. This research offers valuable insights for professionals within Kuwait, aiming to harness deep learning techniques to boost operational efficiency and strategic foresight in the construction sector.

Effective waste elimination is critical for the success of construction projects. Although several studies have focused on various aspects of construction waste, limited efforts have investigated the dynamic effect of Making-Do (MD) practices on productivity, rework, defects, and materials wastage. From a lean construction perspective, this study aims to address MD waste using the Last Planner System (LPS) and BIM. First, the casual structure that can cause MD in construction projects was expressed in a casual loop diagram (CLD), and thematic analysis uncovered the strategies of LPS-BIM to eliminate MD identified by reviewing the literature. Secondly, twenty-five strategies from the LPS and BIM strategies to address MD using Structural Equation Modeling (SEM) were assessed. Subsequently, a system dynamics model (SDM) for investigating LPS-BIM strategies on MD decisions in a construction project was formulated based on the underlying causal loop diagrams and the mathematical relations among the variables. Finally, the model was applied to three projects, and simulations for four LPS-BIM scenarios were carried out. The findings show that dynamic interactions among diverse production planning and control factors are critical in evaluating MD impacts on a construction project. The results demonstrate that the LPS-BIM approach resulted in an average 43.8% reduction in the tasks performed with MD, 45.3% of constraints, 66.5% of construction waste, increasing 13.7% completion rate, and 29.3% cost reduction, demonstrating that LPS-BIM as a more efficient solution for MD mitigation and construction planning.