The operation of electricity and natural gas transmission networks in the U.S. are increasingly interdependent, due to the growing number of installations of gas fired generators and the penetration of renewable energy sources. This development suggests the need for closer communication and coordination between gas and power transmission system operators in order to improve the efficiency and reliability of the combined energy system. In this paper, we present a co-simulation platform for examining the interdependence between natural gas and electricity transmission networks based on a direct current unit-commitment and economic dispatch model for the power system and a transient hydraulic gas model for the gas system. We analyze the value of day-ahead coordination of power and natural gas network operations and show the importance of considering gas system constraints when analyzing power systems operation with high penetration of gas generators and renewable energy sources. Results show that day-ahead coordination contributes to a reduction in curtailed gas during high stress periods (e.g., large gas offtake ramps) and a reduction in energy consumption of gas compressor stations.

Water soluble polymers have gained an increasing interest in enhanced oil recovery (EOR) processes, especially as polymer flooding. Despite the fact that the flow of polymer in porous medium has been a research subject for many decades with numerous publications, there are still some research areas that need progress. The prediction of polymer injectivity remains elusive. Polymers with similar shear viscosity might have different in-situ rheological behaviors and may be exposed to different extent of mechanical degradation. Hence, determining polymer in-situ rheological behavior is of great significance for defining its utility. In this study, an investigation of rheological properties and mechanical degradation of different HPAM (partially hydrolyzed polyacrylamide) polymers was performed using Bentheimer sandstone outcrop cores. Results show that, HPAM in-situ rheology is different from bulk rheology measured in rheometer. Specifically, shear thickening behavior occurs at high rates, and near-Newtonian behavior is measured at low rates in porous media. This deviates strongly from measurements in the rheometer. Polymer molecular weight and concentration influence its viscoelasticity and subsequently its flow characteristics in porous media. Exposure to mechanical degradation by flow at high rate through porous media leads to significant reduction in shear thickening and thereby improved injectivity. More importantly, the degraded polymer maintained in-situ viscosity at low flow rates indicating that improved injectivity can be achieved without compromising viscosity at reservoir flow rates. This is explained by reduction in viscoelasticity. Mechanical degradation also leads to reduced residual resistance factor (RRF), especially for high polymer concentrations. For some of the polymer injections, successive degradation (increased degradation with transport length in porous media) was observed. The results presented here may be used to optimize polymer injectivity.

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

This paper aims to analyze the effects of Covid-19 on financial markets from the perspective of Complexity. The Covid-19 pandemic has caused turmoil in financial markets and is already one of the most important financial crises in history, causing a fall in several stock markets as well as great volatility. Unlike past crises, which in most cases were caused either by problems of fiscal deficits or in the financial system, this crisis has its origin in an epidemic disease, which occurred in Wuhan, China, and quickly spread across the globe affecting transport networks, commerce and finance, and will affect the public debt of many countries. This is a systemic situation in which there is a need to consider several interconnected systems, financial instability and high financial risk, something that econophysics and some complexity theorists already do. Therefore, this paper intends to show, theoretically, the systemic and complex character of the recent financial crisis caused by Covid-19.

The Doubly-Fed Induction Generator (DFIG) has significant features in comparison with Fixed Speed Wind Turbine (FSWT), which has popularized its application in power system. Due to partial rated back-to-back converters in the DFIG, Fault Ride-Through (FRT) capability improvement is one of the great subjects regarding new grid code requirements. To enhance the FRT capability of the DFIG, many studies have been carried out. Fault current limiting devices as one of the techniques are utilized to limit the current level and protect switches of the back-to-back converter from over-current damage. In this paper, a review is done based on fault current limiting characteristic of the proposed fault current limiting devices Therefore, Fault Current Limiters (FCLs) and Series Dynamic Braking Resistors (SDBRs) are mainly taken into account. Operation of all configurations including their advantages and disadvantages is explained. Impedance type and the fault current limiting devices’ location are two important factors, which significantly affect the DFIG behaviour in the fault condition. These two factors are basically studied by the simulation and their effects on the key parameters of the DFIG are investigated. Finally, future works in respect to the FCL application in the FRT improvement of the DFIG have also been discussed.

The propeller jet from a ship has a significant component directed upwards towards the free surface of the water, which can be used for ice management. This paper describes a comprehensive laboratory experiment where the influences of operational factors affecting a propeller wake velocity field were investigated. The experiment was done on a steady wake field to investigate the characteristics of the axial velocity of the fluid in the wake and the corresponding variability downstream of the propeller. The axial velocities and the variability recorded were time-averaged. Propeller rotational speed was found to be the most significant factor, followed by propeller inclination. The experimental results also provide some idea about the change of the patterns of the mean axial velocity distribution against the factors considered for the test throughout the effective wake field, as well as the relationships to predict the axial velocity for known factors.

Three-phase to single-phase matrix converter (TSMC) is used as the transmitter for transient electromagnetic method (TEM) instrument, instead of an AC-DC converter and an H-bridge inverter. The transmitter produces excitation current for primary field. The output current has a waveform with a bipolar square of half duty cycle, which is required by TEM. The space vector PWM based on input currents is discussed in detail. The control method of input power factor is proposed for TSMC. The simulation model of TSMC is established and the simulations of different conditions are completed. The simulation results show the controllability of the input power factor is illustrated.

The analogy between the theory of phase transitions in simple fluids and vehicular traffic flow has long been suspected, promising a new level of understanding of urban congestion by standing on one of the firmer foundations in physics. The obstacle has been the interpretation of the thermal energy of the gas-particle system, which remains unknown. This paper proposes the flow of cars through the network as a viable interpretation, where the fundamental diagram for traffic flow would be analogous to the coexistence curve in gas-liquid phase transitions. Thanks to the power-law form of the coexistence curve, it was possible to formalize that the resulting network traffic model belongs to the Kardar-Parisi-Zhang universality class. The scaling relationships arising in this universality class are found to be consistent with West's scaling theory for cities. It is shown that congestion costs (delays + fuel consumption) scale superlinearly with city population, possibly and worryingly more so than predicted by West's theory. Implications for sustainability and resiliency are discussed.

This article reports a novel and efficient method to synthesize graphene by thermal decomposition process. In this method, silicon carbide (SiC) thin films grown on Si(100) wafers with an AlN buffer layer were used as substrates. A CO₂ laser beam heating without vacuum or controlled atmosphere was applied for SiC thermal decomposition. The physical, chemical, morphological, and electrical properties of the laser-produced graphene were investigated for different laser energy densities. The results demonstrate that graphene was produced in form of small islands with quality, density and properties depending on the applied laser energy density. Furthermore, the produced graphene exhibits a sheet resistance characteristic similar to graphene grown on mono-crystalline SiC wafer, which indicates its potential for electronic device applications.

Directional protective relaying based on amplitude comparison of traveling wave on continuous co-phase auto-transformer(AT) power transmission system was proposed. Phase-model transformation is used for decoupling transient fault signals and get aerial mode component. The forward and backward traveling wave are obtained by calculating aerial mode component, then the intrinsic mode function(IMF) components can be obtained through Variational Mode Decomposition(VMD), the module maxima are obtained through calculating the IMF components. The fault direction is determined by the ratio of fault components. If two faults relays at the ends of electric traction networks detect a fault to be in the forward direction, the fault occurred in the internal area, the protection would operate properly. The simulation tests indicate that the protection scheme is feasible, and the proposed protection method can discriminate internal faults from external faults under various fault types, and its performances are immune to fault initial angle, ground resistance, etc.

This study analyses the short-run hydro generation scheduling for the wind power differences from the contracted schedule. The approach for construction of the joint short-run marginal cost curve for the hydro-wind coordinated generation is proposed and applied on the real example. This joint short-run marginal cost (SRMC) curve is important for its participation in the energy markets and for economic feasibility assessment of such coordination. The approach credibly describes the short-run marginal costs which this coordination bears in “real life”. The approach is based on the duality framework of a convex programming and as a novelty combines the shadow price of risk mitigation capability and the water shadow price. The proposed approach is formulated as a stochastic linear program and tested on the case of the Vinodol hydropower system and the wind farm Vrataruša in Croatia. The result of the case study is a family of 24 joint short-run marginal cost curves.

This paper aims to propose a new approach of territorial competitiveness assessment revisited from the resource-based view, as the combination of location-specific resources and capabilities can improve the territorial socio-economic development. A territorial competitiveness index is calculated in order to assess the potential of renewable energy sources to improve the sustainable development in islands. Different sources of information and methodologies have been employed to measure the variables included in the model, thus ensuring a rigorous process in the index calculation. In order to quantify the basic resources, for example, a methodology based on a multicriteria analysis (MCA) with geographic information system (GIS) is suggested, with the objective of obtaining an indicator called index of available territorial resources. This index synthesizes the map information through a numerical value that allows integrating the territorial resource with other indicators of the model. The results of the study show that capability development is a key factor to better exploit the territorial resource endowment in order to achieve a competitive advantage.

In this paper, we studied and analyzed the behavior of velocity profiles and the distribution of pressures in a pipe connected to an accessory. In this case, it was a 90º elbow fitting in which water flows as an incompressible flow. This study was developed numerically through the fluent program of ANSYS. It is of practical interest in engineering because it is based on results regarding the internal structure of a model of incompressible flows. In the same way, it provides a basis for the proper design and implementation of velocity profiles within an elbow.In the agricultural industry, suitable systems can be implemented for crop irrigation in this way with the results obtained to improve the design in the fluid distribution system.We used a feasible κ-ε turbulence model because this model causes less turbulence than the standard κ-ε model. A mesh independence study was developed, in which it was observed that combining different densities of meshes for the same geometry causes some variables, so a fine meshing was used to carry out the study so that the results are as close to reality as possible.

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

We introduce firm solar forecasts as a strategy to operate optimally overbuilt solar power plants in conjunction with optimally sized storage systems so as to make up for any power prediction errors, hence entirely remove load balancing uncertainty emanating from grid-connected solar fleets. A central part of this strategy is plant overbuilding that we term implicit storage. We show that strategy, while economically justifiable on its own account, is an effective entry step to least-cost ultra-high solar penetration where firm power generation will be a prerequisite. We demonstrate that in absence of an implicit storage strategy, ultra-high solar penetration would be vastly more expensive. Using the New York Independent System Operator (NYISO) as a case study, we determine current and future cost of firm forecasts for a comprehensive set of scenarios in each ISO electrical region, comparing centralized vs. decentralized production and assessing load flexibility’s impact. We simulate the growth of the strategy from firm forecast to firm power generation. We conclude that ultra-high solar penetration enabled by the present strategy, whereby solar would firmly supply the entire NYISO load, could be achieved locally at electricity production costs comparable to current NYISO wholesale market prices.

In this study, regression analyses were used to find a relationship between the rain gauge rainfall rate R and radar reflectivity Z for the urban catchment of the Służewiecki Stream in Warsaw, Poland. Rainfall totals for 18 events which were measured at two rainfall stations were used for these analyses. Various methods for determining calculational values of radar reflectivity in reference to specific rainfall cells with 1-km resolution within an event duration were applied. The influence of each of these methods on the Z-R relationship was analyzed. The correction coefficient for data from the SRI (Surface Rainfall Intensity) product was established, in which the values of rainfall rate are calculated based on parameters a and b determined by Marshall and Palmer. Relatively good agreement between measured and estimated rainfall totals for the analyzed events was obtained using the Z-R relationships as well as the correction coefficient determined in this study. Rainfall depths estimated from radar data for two selected events were used to simulate flow hydrographs in the catchment using the SWMM (Storm Water Management Model) hydrodynamic model. Different scenarios were applied to investigate the stream response to changes in rainfall depths, in which the data both for 2 existing as well as 64 virtual rain gauges assigned to appropriate rainfall cells in the catchment were included.

A non-Newtonian fluid model is used to investigate the two-dimensional pulsatile blood flow through a tapered artery with a stenosis. The mixed convection effects of heat and mass transfer are also taken into account. By applying non-dimensionalization and radial coordinate transformation, we simplify the system in a tube. Under the finite difference scheme, numerical solutions are calculated for velocity, temperature concentration, resistance, impedance, wall shear stress and shearing stress at the stenosis throat. Finally, Quantitative analysis is carried out.

A portable urea sensor for use in the fast flow condition was fabricated using porous polytetrafluoroethylene (PTFE) membranes coated with amine-functionalized parylene, parylene-A, by vapor deposition. To generate a specific electrochemical sensor signal from urea, the urea-hydrolyzing enzyme urease was immobilized on the parylene-A-coated PTFE membranes via chemical crosslinking using glutaraldehyde. The urease-immobilized membranes were assembled in a polydimethylsiloxane (PDMS) fluidic chamber, and a screen-printed carbon three-electrode system was used for electrochemical measurements. The success of urease immobilization was confirmed using fluorescence microscopy, scanning electron microscopy, and Fourier-transform infrared spectroscopy. The optimum concentration of urease for immobilization on the parylene-A-coated PTFE membranes was determined to be 48 mg/mL, and the optimum number of membranes in the PDMS chamber was found to be 8. Using these optimized conditions, we fabricated the urea biosensor and monitored urea samples under various flow rates ranging from 0.5 to 10 mL/min in the flow condition using chronoamperometry. To test the applicability of the sensor for physiological samples, we used it for monitoring urea concentration in the waste peritoneal dialysate of a patient with chronic renal failure, at a flow rate of 0.5 mL/min.

This paper presents a complete control strategy of the active return-to-center (RTC) control for electric power steering (EPS) systems. We first establish the mathematical model of the EPS system and analyze the source and influence of the self-aligning torque (SAT). Second, based on the feedback signals of steering column torque and steering wheel angle, we give the trigger conditions of a state switch between the steering assist state and the RTC state. In order to avoid the sudden change of the output torque for the driving motor when the state switches frequently between the steering assist state and the RTC state, we design an undisturbed state switching logic algorithm. This state switching logic algorithm ensures that the output value of the RTC controller is set to an initial value and increases in given steps up to a maximum value after entering the RTC state, and the output value of the RTC controller will reduce in given steps down to zero when exiting the RTC state. This therefore ensures smooth switch control between the two states and improves the driver’s steering feeling. Third, we design the RTC controller, which depends upon the feedback signals of the steering wheel angle and the angular velocity. In addition, the controller increases the auxiliary control function of the RTC torque based on vehicle speed. The experimental results show that the active RTC control method does not affect the basic assist characteristics, which effectively reduces the residual angle of the steering wheel at low vehicle speed and improves the RTC performance of the vehicle.

An optimal scheduling strategy for cooling, heating and power (CCHP) joint-power-supply system is proposed to improve energy utilization and minimize costs in this paper. Firstly, the mathematical model of CCHP system is established. Particle swarm optimization (PSO) is used to optimize the regularization coefficient C and the kernel parameter λ which can affect the prediction accuracy of KELM(PSO-KELM). Then PV generation and load prediction model are established by PSO-KELM. In order to jump out of local optimal solution, Cauchy variation is introduced in SFLA local update, and adaptive mutation operation is carried out on SFLA individuals. The predictions of PV generation and load power by PSO-KELM are imported into the objective function, and the microgrid dispatching model is solved by the improved SFLA algorithm. Compared with the traditional GA-KELM and KELM, PSO-KELM has faster convergence and prediction accuracy. Compared with the power supply division, the operation cost of the power grid is reduced by the proposed optimization dispatching strategy of CCHP micro-grid.

Computationally modelling a nuclear reactor startup core for a benchmark against the existing models is highly desirable for an independent assessment informing nuclear engineers and energy policymakers. This work presents a startup core model of the UK’s first Evolutionary Pressurised Water Reactor (EPR) based on Monte Carlo simulations of particle collisions using Serpent 2, a continuous-energy Monte Carlo reactor physics burnup code. Coupling between neutronics and thermal-hydraulic conditions with the fuel depletion is incorporated into the multi-dimensional branches, obtaining the thermal flux and fission rate (power) distributions radially and axially from the three dimensional (3D) single assembly level to a 3D full core. Shannon entropy is employed to characterise the convergence of the fission source distribution, with 3 billion neutron histories tracked by parallel computing. Source biasing is applied for the variance reduction. Benchmarking the proposed Monte Carlo 3D full-core model against the traditional deterministic transport computation suite used by the UK Office for Nuclear Regulation (ONR), a reasonably good agreement within statistics is demonstrated for the safety-related reactivity coefficients, which creates trust in the EPR safety report.

In this paper, the current technologies of the regenerative shock absorber systems have been categorized and evaluated. Three drive modes of the regenerative shock absorber systems, namely the direct drive mode, the indirect drive mode and hybrid drive mode are reviewed for their readiness to be implemented. The damping performances of the three different modes are listed and compared. Electrical circuit and control algorithms have also been evaluated to maximize the power output and to deliver the premium ride comfort and handling performance. Different types of parameterized road excitations have been applied to vehicle suspension systems to investigate the performance of the regenerative shock absorbers including that of the nonlinear regenerative shock absorber. The research gaps for comparison of the different drive modes and the nonlinearity analysis of the regenerative shock absorbers are identified and, the corresponding research questions have been proposed for future work.

Modeling fluid flow in three-dimensional (3D) Discrete Fracture Networks (DFNs) is of relevance in many engineering applications, such as hydraulic fracturing, oil/gas production, geothermal energy extraction, nuclear waste disposal and CO₂ sequestration. A new Boundary Element Method (BEM) technique with discontinuous quadratic elements and a parallel Domain Decomposition Method (DDM) is presented herein for the simulation of the steady-state fluid flow in 3D DFN systems with wellbores, consisting of planar fractures having arbitrary properties and wellbore trajectories. Numerical examples characterized by DFNs of increasing complexity are investigated to evaluate the accuracy and efficiency of the presented technique. The results show that accurate solutions can be obtained with less nodes than with mesh-based methods (e.g. Finite Element Method). In addition, the DDM algorithm used provides a quite fast convergence. The simulation results of the fluid flow around intersections among traces (linear intersections between fractures), intersections between traces and a fracture boundaries, and wellbore intersections is accurate. Source code is available at : https://github.com/BinWang0213/PyDFN3D.

Plants Microbial Fuel Cells (PMFC) is a new technology that generates electricity in a renewable, clean and sustainable way. In spite of these advantages, it still faces limitations in power generation and current density, reaching lower production values than other renewable technologies. Different studies maintain that the high resistivity of the cathode is the main limitation in the generation of energy; therefore, non-metallic materials to obtain a better performance are replacing the metallic electrodes. The implementation of these materials applied to PMFC requires a complex interdisciplinary work. Through three experimental tests using metallic electrodes for the extraction of electrons, this research study shows that the treatment of the substrate with natural materials, the volume plant roots, and substrate temperature and humidity control have a significant influence in the increase of the electric potential and the generated current.

Fossil fuels are non-renewable sources of energy, used particularly in developing countries. There are insufficient fossil fuels and their availability is gradually declining. This leads to a steady increase in prices. Renewable energy is clean, cost-effective and limitless. The considerable population growth and industrial growth have made the construction of solar power plants essential in developing countries. The study used Boolean logical-AHP techniques to select a suitable site for solar power in Duhok Governorate. The result indicated that 68.5% of the area in the governorate of Duhok is available for solar power station construction, especially the most appropriate zone which has 132.2 sq. km and can provide more than 8000 megawatts of solar energy. Most of the appropriate areas are in the south and southwest regions of the governorate, located mostly in the districts of Bardarash, Shekhan and Semel, situated between the major cities of Mosul, Erbil and Duhok. These locations can supply a significant amount of clean, renewable energy for these areas.

The presence of wireless communication grows undeniably more prevalent each year. Since the introduction of the IEEE 802.11 standard for Wireless Local Area Networks (WLAN) in 1997, technologies have progressed to provide wireless accessibility to industries and consumers with growing ease and convenience. As the usage of personal devices, such as phones and watches, that connect to the Internet through Wi-Fi increases, wireless attacks on users are becoming more critical. This paper provides a novel attack model to offer an organized and comprehensive view of the possible attacks on WiFi latest security standards. All exiting attacks will be investigated, with emphasis on more recent attacks, such as the KRACK and PMKID Dictionary attacks. This paper will then analyze the technology offered in the new Wi-Fi Protected Access III (WPA3) security scheme and provide a comprehensive security analysis and discussion to determine whether it has addressed the vulnerabilities of its predecessor. An interesting finding of this paper is that WPA3 still lacks to address all the issues existed in WPA2 and explore other mitigations for future research.

Sediment transport is highly sensitive to flow conditions, showing significant increase during flood events. Based on this principle, this study set out to rank flood events occurring along river Trotuș (Romania) based on the amount of transported sediment and event duration. The 77 flood events recorded from 2000 to 2017 were ranked into 4 classes: type A (4%); type B (16%), type C (14%) and type D (66%). The sediment transport specific for the 4 types of flood events was related to the flow discharge (sediment rating curve and hysteresis effect), the specific stream power and the energy expenditure of these events. More than 60% of the hysteresis loops typical for flood events were clockwise, thus singling out the channel as the main sediment source. Ca. 74% of the total sediment yield was transported at stream power values higher than the 300 Wm-2 threshold, which was exceeded in less than 1% of the investigated timeframe. The changes occurring in the sediment transport rates after major floods show that these events are significant thresholds in the hydrogeomorphic evolution of river channels.

This paper considers a hybrid relay network consisting of the source, the amplify-and-forward (AF) relay, the decode-and-forward (DF) relay, and the destination. We propose the optimal power allocation schemes between two different relays which maximize the achievable rate under a sum relay power constraint for given channel gains and transmit power from source. By solving the optimization problem to maximize the achievable rate for each relay network, the transmit power values in closed-form are derived. When the channel gains are the same, the optimal power allocation scheme for AF-DF relay network proves that a more power should be allocated at the first relay to maximize the achievable rate. In case of the DF-AF relay network, we derive the optimal power allocation scheme for the possible four cases. Under the same SNR condition at the first hop, we show that the achievable rate of AF-DF relay network is greater than that of DF-AF relay network when the channel gain between two relays is higher than that between the second relay and destination. Simulation results show that the proposed power allocation schemes provide a higher achievable rate than the equal power allocation schemes.

Renewable energy sources (RES) will play a crucial role in future sustainable energy systems. In scenarios analyzing future energy system designs, a detailed spatial and temporal representation of renewable-based electricity generation is essential. For this, sufficiently representative weather data are required. Most analyses performed in this context use the historical data of either one specific reference year or an aggregation of multiple years. In contrast, this study analyzes the impact of different weather years based on historical weather data from 1980 through 2015 in accordance with the design of an exemplary future energy system. This exemplary energy system consists of on- and offshore wind energy for power-to-hydrogen via electrolysis, including hydrogen pipeline transport for most southwestern European countries. The assumed hydrogen demand for transportation needs represents a hypothetical future market penetration for fuel cell-electric vehicles of 75%. An optimization framework is used in order to evaluate the resulting system design with the objective function of minimizing the total annual cost (TAC) of the system. For each historical weather year, the applied optimization model determines the required capacities and operation of wind power plants, electrolyzers, storage technologies and hydrogen pipelines to meet the assumed future hydrogen demand in a highly spatially- and temporally-detailed manner, as well as the TAC of the system. Following that, the results of every individual year are compared in terms of installed capacities, overall electricity generation and connection to the transmission network, as well as the cost of these components within each region. The results reveal how sensitive the final design of the exemplary system is to the choice of the weather year. For example, the TAC of the system changes by up to 20% across two consecutive weather years. Furthermore, significant variation in the optimization results regarding installed capacities per region with respect to the choice of weather years can be observed.

According to the Water Framework Directive, the Ecological Flow (Eflow) is assumed to be the minimum water discharge required to achieve and maintain the environmental objectives of “good quality status” in a natural water body. It is highly recognized that, the hydrological regime of natural flow plays a primary and crucial role influencing the physical conditions of habitats, which in turn determines the biotic composition and sustainability of aquatic ecosystems. Furthermore, the simple assumption to supply a minimum instream during dry periods is not enough any longer in order to protect the river environment. The recent hydro-ecological understanding states that all flow components might be considered as operational targets for water management, starting from base flows (including low flows) to high and flood regimes in terms of magnitude, frequency, duration, timing and rate of change. Several codes have been developed and applied on different case studies in order to define common tools to be implemented for the Eflow assessment. The study proposes the application of the Indicators of Hydrologic Alteration methodology (IHA by TNC) coupled to the valuation of the Index of Hydrological Regime Alteration (IARI by ISPRA) as an operative tool to define the ecological flow in each monitoring cross section to support the sustainable water resources management and planning. The case study of Agri River, in Basilicata (Southern Italy) is presented. The analyses have been carried out on monthly discharge data derived applying the HEC-Hydrological Modelling System at the basin scale using the daily rain data measurements obtained by the regional rainfall gauge stations and calibrated through the observed inlet water discharge registered at the Lago del Pertusillo reservoir station.

In ultra-relativistic collisions of heavy ions, the strongly interacting Quark Gluon Plasma (sQGP) is created. The fluid nature of the sQGP was one of the important discoveries of high energy heavy ion physics in the last decades. Henceforth the explosion of this matter may be described by hydrodynamical models. Besides numerical simulations, it is important to study the analytic solutions of the equations of hydrodynamics, as these enable us to understand the connection of the final and initial states better. In this paper we present a perturbative, accelerating solution of relativistic hydrodynamics, on top of a known class of solutions describing Hubble-expansion. We describe the properties of this class of perturbative solutions, and investigate a few selected solutions in detail.

This paper presents findings of a study on continuous feed-in management and continuous synthetic inertia contribution with wind turbines. A realistic case study, based on real measurements, is outlined. A wind turbine feeds into a weak feeder, such that its power has to be adapted to the permissible loading of this feeder. At the same time the wind turbine is to provide inertia to the grid by applying the previously published variable inertia constant controller. It is discussed that optimal grid utilisation and simultaneous inertia contribution are mandatory for the frequency control in power systems that are heavily penetrated with renewable energies. The study shows that continuous feed-in management can be combined well with continuous inertia provision. There are hardly any negative consequences for the wind turbine. The benefits for the grid are convincing, both in terms of increased system utilisation and in terms of provided inertia. It is concluded that wind turbines can enhance angular stability in a power system to a larger extent than conventional power plants.

The trafficking of illegal drugs by criminal networks at borders, harbors, or airports is an increasing issue in public health as these routes ensure the main supply of illegal drugs. The prevention of drug smuggling, including the installation of scanners and other analytical devices to detect ultra-small traces of drugs within a reasonable time frame, remains a challenge. The presented immunosensor is based on a monolithic affinity column with a large excess of immobilized hapten, which traps fluorescently labeled antibodies as long as the analyte cocaine is absent. In the presence of the drug, some binding sites of the antibody will be blocked, which leads to an immediate breakthrough of the labeled protein, detectable by highly sensitive laser-induced fluorescence with the help of a Peltier-cooled complementary metal-oxide-semiconductor (CMOS) camera. Liquid handling is performed with high-precision syringe pumps and microfluidic chip-based mixing devices and flow cells. The biosensor achieved limits of detection of 23 pM (7 ppt) of cocaine with a response time of 90 seconds and a total assay time below 3 minutes. With surface wipe sampling, the biosensor was able to detect 300 pg of cocaine. This immunosensor belongs to the most sensitive and fastest detectors for cocaine and offers near-continuous analyte measurement.

Several transgenic rice lines have been developed and are currently under field trials around the world. There are future plans for the commercial release of transgenic rice into the environment. Rice is an autogamous plant and therefore not perceived to be a very high candidate for pollen mediated gene flow to wild and weedy relatives. However, in a tropical environment like Ghana, where sexually compatible wild Oryza species which belongs to the AA genome are present within the ecology of cultivated rice, the possibility of gene flow to wild species cannot be overlooked. There is little evidence on gene flow and its consequences on the wild rice species should they acquire useful genes through gene flow. This review discusses the chances of cultivated to wild rice gene flow in Ghana and the biosafety considerations that should be put in place before the commercial release of genetically modified (GM) rice.

Self-organized criticality (SOC) is a celebrated paradigm from the 90’s for understanding dynamical systems naturally driven to its critical point, where the power-law dynamics taking place make predictions practically impossible, such as in stock prices, earthquakes, pandemics and many other problems in science related to phase transitions. Shortly thereafter, it was realized that traffic flow might be in the SOC category, implying that conventional traffic management strategies seeking to maximize the local flows can become detrimental. This paper shows that the Kinematic Wave model with triangular fundamental diagram, and many other related traffic models, indeed exhibit SOC, thanks in part to the fractal nature of traffic exposed here on the one hand, and our need to get to our destinations as soon as possible, on the other hand. Important implications for congestion management of traffic near the critical region are discussed, such as: (i) Jam sizes obey a power-law distribution with exponent 1/2, implying that both its mean and variance become ill-defined and therefore impossible to estimate. (ii) Traffic in the critical region is chaotic in the sense that predictions becomes extremely sensitive to initial conditions. (iii) However, aggregate measures of performance such as delays and average speeds are not heavy tailed, and can be characterized exactly by different scalings of the Airy distribution, (iv) Traffic state time-space “heat maps” are self-affine fractals where the basic unit is a triangle, in the shape of the fundamental diagram, containing 3 traffic states: voids, capacity and jams. This fractal nature of traffic flow calls for analysis methods currently not used in our field.

One of the major problem of photovoltaic grid integration is limiting the solar-induced imbalances since these can undermine the security and stability of the electrical system. Improving the forecast accuracy of photovoltaic generation is becoming essential to allow a massive solar penetration. In particular, improving the forecast accuracy of large solar farms generation is important both for the producers/traders to minimize the imbalance costs and for the Transmission System Operators to insure stability. In this article, we provide a benchmark for the day-ahead forecast accuracy of utility scale PV plants in 1325 locations spanning the country of Italy. We then use these benchmarked forecasts and real energy prices to compute the economic value of forecast accuracy and accuracy improvement in the context of the Italian energy market regulatory framework. Through this study, we further point out some several important criticisms of the Italian “single pricing” system that brings to paradoxical and counterproductive effects regarding the need to reduce the imbalance volumes. Finally, we propose a new market-pricing rule and innovative actions to overcome these undesired effects of the current dispatching regulations.

This paper presents a control algorithm for soft-switching series LC converters. The conventional voltage-to-voltage controller is split into a master and a slave controller. The master controller implements constant-current-constant-voltage (CCCV) control, required for demanding applications, i.e. lithium battery charging or laboratory power supplies. It defines the set-current for the open-loop current slave controller, which generates the PWM parameters. The power supply achieves fast large-signal responses, e.g. from 5 V to 24 V, where 95% of the target value is reached in less than 400 µs. The design is evaluated extensively in simulation and on a prototype. A consensus between simulation and measurement is achieved.

Accurate diagnosis at an early stage of infection is essential for the successful management of any contagious disease. The COVID-19, caused by the SARS-CoV-2 virus is a pandemic that has affected 214 countries affecting more than 30.8 million people causing 0.957 million deaths as of third week of September, 2020. The primary diagnosis of the infection is done either by the molecular technique of RT-qPCR by detecting portions of the RNA of the viral genome or through immunodiagnostic tests by detecting the viral proteins or the antibodies produced by the host. As the demand for the test increased rapidly many naive manufacturers entered the market with novel kits and more and more laboratories also entered the diagnostic arena making the test result more error-prone. There are serious debates globally and regionally on the sensitivity and specificity of these tests and about the overall accuracy and reliability of the tests for decision making on control strategies. The significance of the test is also complexed by the presence of asymptomatic carriers, re-occurrence of infection in cured patients as well as by the varied incubation periods of the infection and shifting of the viral location in the host tissues. In this paper, we review the techniques available for SARS-CoV-2 diagnosis and probable factors that can reduce the sensitivity and specificity of the different test methods currently in vogue. We also provide a check-list of factors to be taken care to avoid fallacious practices to reduce false positive and false negative results by the clinical laboratories

Building a new power plant to address the growing demand for power due to population concentration in the metropolitan area is one of the world's major concerns. However, since a large power plant can not be located around the city due to burden of economic cost, building power plant outside metropolitan and cities is necessary. Therefore, new power generation facilities are promoting policies to provide distributed generator(DG) with a small capacity relatively near the metropolitan. When the DG (photovoltaic, wind farm, etc.) is connected with the grid using medium voltage direct current (MVDC) system, voltage sourced converter(VSC) should supply reactive power to the grid, because of fault ride through(FRT) operation in grid fault. If the voltage drop is severe, the converter should be disconnected from the grid immediately without supplying the reactive power, resulting in a considerable economic loss. In general, superconducting fault current limiter(SFCL) is introduced as a measure to enhance FRT capability. In this paper, we use trigger type SFCL which protects superconducting element and reduces low voltage. On the other hand, the active power unbalance of the DC-link and the DC voltage rise due to the reactive power supply of the grid-side converter. The rise of the DC voltage causes the P (active power), Q (reactive power) control of the converter to deviate, causing malfunction and damage of the DC equipment. Therefore, the rise of the DC voltage must be prevented. In this paper, we consider the suppression the DC voltage rising caused by the FRT operation through the active power tracking control (APTC).

In the context of video background-foreground separation, we propose a compressive online Robust Principal Component Analysis (RPCA) with optical flow that separates recursively a sequence of video frames into foreground (sparse) and background (low-rank) components. This separation method can process per video frame from a small set of measurements, in contrast to conventional batch-based RPCA, which processes the full data. The proposed method also leverages multiple prior information by incorporating previously separated background and foreground frames in an n-l₁ minimization problem. Moreover, optical flow is utilized to estimate motions between the previous foreground frames and then compensate the motions to achieve higher quality prior foregrounds for improving the separation. Our method is tested on several video sequences in different scenarios for online background-foreground separation given compressive measurements. The visual and quantitative results show that the proposed method outperforms other existing methods.

A modular switched-capacitor (SC) DC-DC converter (MSCC) is introduced in this paper. It is designed to boost a low input voltage to a high voltage level and can be applied for photovoltaics and electric vehicles. This topology has high extensibility for high voltage gain output. The merits of the converters also lie in the fault tolerance operation and the voltage regulation with a minimum change in the duty ratio. Those features are built in when designing the modules and then integrating these into the DC-DC converter. Converter performance including voltage gain, voltage and current stress are focused and tested. The converter is modelled analytically, and its control algorithm is analyzed in detailed. Both simulation and experiment are carried out to verify the topology under normal operation and fault mode operation.

A four-parameter kinematic model for the position of a fluid parcel in a time-varying ellipse is introduced. For any ellipse advected by an arbitrary linear two-dimensional flow, the rates of change of the ellipse parameters are uniquely determined by the four parameters of the velocity gradient matrix, and vice-versa. This result, termed ellipse/flow equivalence, provides a stronger version of the well-known result that a linear velocity field maps an ellipse into another ellipse. Moreover, ellipse/flow equivalence is shown to be a manifestation of Stokes' theorem. This is done by deriving a matrix-valued relationship, called the geometric Stokes' theorem, that involves a spatial integral over the velocity gradient tensor, thus accounting for the two strain terms in addition to the divergence and vorticity. General expressions for various physical properties of an elliptical ring of fluid are also derived. The ellipse kinetic energy is found to be composed of three portions, associated respectively with the circulation, the rate of change of the moment of inertia, and the variance of parcel angular velocity around the ellipse. A particular innovation is the use of four matrices, termed the IJKL basis, that greatly facilitate the required calculations.

To reduce solar power production invariance, it is critical to study varying patterns of power production in the concerned region. Analyzing the patterns of past power production trends can help simulate power production scenarios for future. The current study area is around Amsterdam, located in Netherlands. PVoutput.org website is used to mine 6 months of solar power production data for 120 stations around Amsterdam city. FME Workbench software is used to actively fetch the data from the mentioned website and manage in a MySQL database. Solar attenuation maps created using ArcGIS, helped to graphically visualize the variations in solar power production at different times and locations. Further, spatial autocorrelation is checked between the stations using semi-variograms in geostatistical tool of ArcMap. This feature allows to check whether the stations located close to each other are more correlated to each other rather than stations which are far apart. The statistical data analysis of power production can aid solar power production companies to better interpolate and predict solar power in advance for the concerned study region.

Trends such as Industrial Internet of Things (IIoT) and Industry 4.0 have increased the need to use powerfull network technologies in industrial automation. The growing communication in industrial automation is harnessing the productivity and efficiency of manufacturing and process automation with minimum human intervention. Due to the ongoing evolution of industrial networks from Fieldbus technologies to Ethernet, the new opportunity has emerged to integrate the Software Defined Networking (SDN) technique. In this paper, we provide a brief overview of SDN in the domain of industrial automation. We propose a network architecture called Software Defined Industrial Automation Network (SDIAN), with the objective of improving network scalability and efficiency. To match the specific considerations and requirements of having a deterministic system in an industrial network, we propose two solutions for flow creation: Pro-active Flow Installation Scheme (PFIS) and Hybrid Flow-Installation Scheme (HFIS). We analytically quantify the proposed solutions in alleviating the overhead incurred from the flow setup cost. The analytical model is verified through monte carlo simulations. We also evaluate the SDIAN architecture and analyze the network performance of the modified topology using an emulator called Mininet. We further list and motivate SDIAN features and in particular report on an experimental food processing plant demonstration featuring Raspberry PIs (RPIs) instead of traditional Programmable Logic Controllers (PLCs). Our demonstration exemplifies the characteristics of SDIAN.

Many studies, which try to analyze conditions for debris flow development, ignore the type of initiation. Therefore this paper deals with the following questions: What type of hydro-mechanical triggering mechanisms for debris flows can we distinguish in upstream channels of debris flow prone gullies? Which are the main parameters controlling the type and temporal sequence of these triggering processes and what is their influence on the meteorological thresholds for debris flow initiation? A series of laboratory experiments were carried out in a flume, 8 m long and with a width of 0.3 m. to detect the conditions for different types of triggering mechanisms. The flume experiments show a sequence of hydrological processes triggering debris flows, namely erosion and transport by intensive overland flow and by infiltrating water causing failure of channel bed material. On the basis of these experiments an integrated hydro-mechanical model was developed, which describes Hortonian and Saturation overland flow, maximum sediment transport, through flow and failure of bed material. The model was calibrated and validated using process indicator values measured during the experiments in the flume. Virtual model simulations, carried out in a schematic hypothetical source area of a catchment show that slope angle and hydraulic conductivity of the bed material determine the type and sequence of these triggering processes. It was also clearly demonstrated that the type of hydrological triggering process and the influencing geometrical and hydro-mechanical parameters may have a great influence on rainfall intensity-duration threshold curves for the start of debris flows.

In this article we present a deployment of 11 nodes using the three different SUN (Smart Utility Network) modulation schemes, as defined in the IEEE 802.15.4-2015 standard. The nodes were deployed in a 110.044 m2 warehouse for 99 days, and the resulting dataset contains a total of 10.710.868 measurements with RSSI (Received Signal Strength Indicator), CCA (Clear Channel Assessment) and PDR (Packet Delivery Ratio) values. The analyzed results show a high variability in average RSSI (i.e., between -82.1 dBm and -101.7 dBm) and CCA (i.e., between -111.2 dBm and -119.9 dBm) values, which are caused by the effects of multi-path propagation and external interference. Despite being above the sensitivity limit for each modulation, this values result in poor average PDR values (i.e., from 65.9% to 87.4%), indicating that additional schemes are required for low-power wireless communications to meet the dependability requirements of industrial applications. For that purpose, we also introduce the concept of modulation diversity, which can be combined with packet repetition to meet such requirements (i.e., PDR>99%) while minimizing the energy expenditure of nodes and meeting regulatory constraints.

The physical and economic sustainability of using Built Environment Wind Turbine (BEWT) systems depends on the wind resource potential of the candidate site. Therefore, it is crucial to carry out a wind resource assessment prior to deployment of the BEWT. The assessment results can be used as a referral tool for predicting the performance and lifespan of the BEWT in the given built environment. To date, there is limited research output on BEWTs in South Africa with available literature showing a bias towards utility-scale or conventional ground based wind energy systems. This study aimed to assess wind power generation potential of BEWT systems in Fort Beaufort using the Weibull distribution function. The results show that Fort Beaufort wind patterns can be classified as fairly good and that BEWTs can best be deployed at 15m for a fairer power output as roof height wind speeds require BEWT of very low cut-in speed of at most1.2ms⁻¹.

The matrix converter converts the input line voltage into a variable voltage with an unrestricted output frequency without using an intermediate circuit, dc link circuit. A pure sine in and pure sine out is the unique feature of the matrix converter. This research paper also analyzes the basic operating principle and the simulation modeling of the direct matrix converter, which is controlled by the Space Vector Pulse Width Modulation technique by using the software which is known as MATLAB/Simulink. The most desirable features in the power frequency changes can be fulfilled by using the matrix converters, and this is the reason for the tremendous interest in the topology. Since the power electronic circuits which is known as the motor drives are used to operate the AC motors at the frequencies other than that of the supply.

Biosensors are essential tools which have been traditionally used to monitor environmental pollution, detect the presence of toxic elements and biohazardous bacteria or virus in organic matter and biomolecules for clinical diagnostics. In the last couple of decades, the scientific community has witnessed their widespread application in the fields of military, health care, industrial process control, environmental monitoring, food-quality control, and microbiology. Biosensor technology has greatly evolved from the in vitro studies based on the biosensing ability of organic beings to the highly sophisticated world of nanofabrication enabled miniaturized biosensors. The incorporation of nanotechnology in the vast field of biosensing has led to the development of novel sensors and sensing mechanisms, as well as an increase in the sensitivity and performance of the existing biosensors. Additionally, the nanoscale dimension further assists the development of sensors for rapid and simple detection in vivo as well as the ability to probe single-biomolecules and obtain critical information for their detection and analysis. However, the major drawbacks of this include, but are not limited to potential toxicities associated with the unavoidable release of nanoparticles into the environment, miniaturization induced unreliability, lack of automation, and difficulty of integrating the nanostructured-based biosensors as well as unreliable transduction signals from these devices. Although the field of biosensors is vast, we intend to explore various nanotechnology enabled biosensors as part of this review article and provide a brief description of their fundamental working principles and potential applications.

This paper presents a study on optimization of Overcurrent relay (OCR) coordination protection scheme for Sustainable Standalone Hydrokinetic Renewable Energy (SHRE) distribution network at Batang Rajang river, located at Kapit Sarawak, Malaysia by turning river stream into power generation source. The purpose of the project is to develop rural electrification system for native long houses along the river. The research study is tested on a DigSILENT develop model of the SHRE distribution network and in accordance with all respectively unique parameters and relevant standards. Since this is a new standalone distribution system, an efficient and properly coordinated overcurrent protection system must be provided. Improper and miscoordination among OCRs result in maloperation of the protection system that can lead to false tripping and an unnecessary outage and power system instability. Thus, the objective of this work is to employ Genetic Algorithm (GA) technique in Matlab/Simulink for optimal overcurrent coordination and settings among all OCRs in the proposed distribution network in order to improve the speed of OCR tripping operation. The GA is used because the project is fast track and requiring the simplest method available. In this strategy, time dial setting (TDS) is optimized by using plug setting multiplier (PSM) as the constraint. The obtained results show a significant improvement of the relay operating time of 36.01% faster than that of conventional numerical technique during fault occurrence. Thus, an efficient and reliable overcurrent protection scheme has been achieved for the SHRE distribution network.

The main objective was to determine the effect of mobile phone radiation on general health and electrolytes among students who use mobile phones. A questionnaire was designed and applied to 103 healthy and 36 deaf female students to select cases that meeting the inclusion criteria. For assessment of salivary parameters, the participants were classified into three groups. Group I was the control group, which included 17 deaf students. Group II was healthy students who have mobile phone for less than 5 years. Group III was healthy students who have mobile phone for 5 years or more. The results showed that the participants who use mobile phone had several problems in their health including dry mouth, bad odor from mouth, drooling of saliva, as well as ear and eye pain. The participants who use mobile phone complained of headache, anxiety and forgetfulness as compared to deaf participants. The study showed that there was no significant difference between pH and flow rate of saliva in all tested groups. This study has also shown that salivary level of Na+ and K+ were significantly lower in mobile phone users when compared to non users of mobile phone.

The dynamics of a spherical particle in an asymmetric serpentine is studied by finite element method (FEM) simulations in a physically unconstrained system. The two-way coupled time dependent solutions illustrate the path of the particle along a curve where a secondary flow (Dean flow) has developed. The simulated conditions were adjusted to match those of an experiment for which particles were focused under inertial focusing conditions. The obtained rotational modes allowed to infer the influence of the local flow around the particle. We propose a new approach to find the decoupled secondary flow contribution employing a quasi-Stokes flow.

Objective: To investigate the effects and mechanisms of different concentrations of CCCP on mitophagy in human peripheral blood regulatory T cells. Methods: Tregs were isolated, identified and then grouped, treating with CCCP at a concentration of 2.5 μM, 5 μM, 10 μM, 20 μM and 40 μM for 24h in an incubator. Flow cytometry detected the reactive oxygen species (ROS), mitochondrial membrane potential (MMP), mitochondrial quality, and fluorescence microscopy observed the co-localization of mitochondria and lysosomes in each group. Results: The purity of CD4⁺CD25⁺Tregs was (93.36 ± 1.87) %. With the increase of CCCP concentration, the level of ROS gradually increased, while the MMP decreased gradually. About the mitochondria and lysosome fusion, the fluorescence intensity of orange (yellow) was the highest when the concentration of CCCP was in the range of 5-10 μM while decreased with the CCCP concentration continually increasing. The mitochondrial quality decreased with the increase of CCCP concentration. However, there was no significant difference between groups C, D and E. The mitochondrial quality of groups F and G were significantly lower than that of group E. Conclusions: With the concentration of CCCP gradually increased, the level of ROS in Treg cells increased, and MMP decreased, which promoted the mitophagy, mitochondrial quality maintains homeostasis; When ROS accumulated, and MMP decreased significantly, the mitophagy was inhibited, and the mitochondrial quality was significantly decreased.

Non-linear loads in circuits cause the appearance of harmonic disturbances both in voltage and current. In order to minimize the effects of these disturbances and, therefore, to control over the flow of electricity between the source and the load, they are often used passive or active filters. Nevertheless, determining the type of filter and the characteristics of their elements is not a trivial task. In fact, the development of algorithms for calculating the parameters of filters is still an open question. This paper analyzes the use of genetic algorithms to maximize the power factor compensation in non-sinusoidal circuits using passive filters, while concepts of geometric algebra theory are used to represent the flow of power in the circuits. According to the results obtained in different case studies, it can be concluded that the genetic algorithm obtain high quality solutions that could be generalized to similar problems of any dimension.

On 5-7 April 2018 a landfalling atmospheric river resulted in widespread heavy precipitation in the Sierra Nevada of California and Nevada. Observed snow levels during this event were among the highest snow levels recorded since observations began in 2002 and exceeded 2.75 km for 31 hours in the northern Sierra Nevada and 3.75 km for 12 hours in the southern Sierra Nevada. The anomalously high snow levels and over 80 mm of precipitation caused flooding, debris flows, and wet snow avalanches in the upper elevations of the Sierra Nevada. The origin of this atmospheric river was super typhoon Jelawat, whose moisture remnants were entrained and maintained by an extratropical cyclone in the northeast Pacific. This event was notable due to its April occurrence, as six other typhoon remnants that caused heavy precipitation with high snow levels (mean = 2.92 km) in the northern Sierra Nevada all occurred during October.

Compared with conventional methods of fault diagnosis for power transformers, which have defects such as imperfect encoding and too absolute encoding boundaries, this paper systematically discusses various intelligent approaches applied in fault diagnosis and decision making for large oil-immersed power transformers based on dissolved gas analysis (DGA), including expert system (EPS), artificial neural network (ANN), fuzzy theory, rough sets theory (RST), grey system theory (GST), swarm intelligence (SI) algorithms, data mining technology, machine learning (ML), and other intelligent diagnosis tools, and summarizes existing problems and solutions. From this survey, it is found that a single intelligent approach for fault diagnosis can only reflect operation status of the transformer in one particular aspect, causing various degrees of shortcomings that cannot be resolved effectively. Combined with the current research status in this field, the problems that must be addressed in DGA-based transformer fault diagnosis are identified, and the prospects for future development trends and research directions are outlined. This contribution presents a detailed and systematic survey on various intelligent approaches to faults diagnosing and decisions making of the power transformer, in which their merits and demerits are thoroughly investigated, as well as their improvement schemes and future development trends are proposed. Moreover, this paper concludes that a variety of intelligent algorithms should be combined for mutual complementation to form a hybrid fault diagnosis network, such that avoiding these algorithms falling into a local optimum. Moreover, it is necessary to improve the detection instruments so as to acquire reasonable characteristic gas data samples. The research summary, empirical generalization and analysis of predicament in this paper provide some thoughts and suggestions for the research of complex power grid in the new environment, as well as references and guidance for researchers to choose optimal approach to achieve DGA-based fault diagnosis and decision of the large oil-immersed power transformers in preventive electrical tests.

Empirical Colebrook equation from 1939 is still accepted as an informal standard to calculate friction factor during the turbulent flow (4000 < Re < 10⁸) through pipes from smooth with almost negligible relative roughness (ε/D→0) to the very rough (up to ε/D = 0.05) inner surface. The Colebrook equation contains flow friction factor λ in implicit logarithmic form where it is, aside of itself; λ, a function of the Reynolds number Re and the relative roughness of inner pipe surface ε/D; λ = f (λ, Re, ε/D). To evaluate the error introduced by many available explicit approximations to the Colebrook equation, λ ≈ f(Re, ε/D), it is necessary to determinate value of the friction factor λ from the Colebrook equation as accurate as possible. The most accurate way to achieve that is using some kind of iterative methods. Usually classical approach also known as simple fixed point method requires up to 8 iterations to achieve the high level of accuracy, but does not require derivatives of the Colebrook function as here presented accelerated Householder’s approach (3^rd order, 2^nd order: Halley’s and Schröder’s method and 1^st order: Newton-Raphson) which needs only 3 to 7 iteration and three-point iterative methods which needs only 1 to 4 iteration to achieve the same high level of accuracy. Strategies how to find derivatives of the Colebrook function in symbolic form, how to avoid use of the derivatives (Secant method) and how to choose optimal starting point for the iterative procedure are shown. Householder’s approach to the Colebrook’s equations expressed through the Lambert W-function is also analyzed. One approximation to the Colebrook equation based on the analysis from the paper with the error of no more than 0.0617% is shown.

This work aims to develop an integrated fault location and restoration approach for microgrids (MGs). This work contains two parts. Part I presents the fault location algorithm, and Part II shows the restoration algorithm. The proposed algorithms are implemented by particle swarm optimization (PSO). The fault location algorithm is based on network connection matrices, which are the modifications of bus-injection to branch-current and branch-current to bus-voltage (BCBV) matrices, to form the new system topology. The backward/forward sweep approach is used for the prefault power flow analysis. After the occurrence of fault, the voltage variation at each bus is calculated by using the Zbus modification algorithm to modify Zbus. Subsequently, the voltage error matrix is computed to search for the fault section by using PSO. After the allocation of the fault section, the multi-objective function is implemented by PSO for optimal restoration with its constraints. Finally, the IEEE 37-bus test system connected to distributed generations is utilized as the sample system for a series simulation and analysis. The outcomes demonstrated that the proposed optimal algorithm can effectively solve the fault location and restoration problem in MGs.

The purpose of this article is to simulate data transmission and calculate traffic parameters in SAGIN air segment for which Ad Hoc network of flying drones is considered as a model. Traffic modeling is based on the manet-routing-compare example from the ns3 simulator library, which has been supplemented with the code for calculation packet losses, throughput/goodput, and message transmission delays. The program allowed considering drones movement at both low and high speeds from 3.6 km/h to 72 km/h. The dependences of traffic losses on data transmission power, transaction sizes and data transmission rate are obtained and analyzed. The distribution of the average effective arrival rate λ and the throughput/goodput for drones has been studied. Comparing traffic characteristics in models with different numbers of drones allows judging how the required quality of service can be achieved by choosing the right transmission parameters.

Over the years, sustainability, impact on the environment, as well as the operation expenditure have been a major concern to the deployment of mobile cellular base stations worldwide. This is because the mobile cellular base stations are known to consume a high percentage of power within the mobile cellular network. Such energy consumption contributes to the emission of Greenhouse Gases (GHG) through the use of conventional diesel generating a set. As a result, the mobile cellular operators are faced with the dilemma of minimising the power consumption, GHG emission, and the operation cost, while improving the Quality of Service of the networks. In attempting to find a solution, this study presents the feasibility and simulation of a solar photovoltaic (PV) with battery hybrid power system (HPS) as a predominant source of power for a specific mobile cellular base station site situated in Soshanguve area of the city of Pretoria, South Africa. It also presents the technical development, showed the environmental advantage and cost benefits of using a solar PV-battery HPS to power a base station site of a 24 hrs daily load of 241.10 kWh/d and the peak load of 20.31 kW as compared to using the HPS of solar PV-diesel generating set-battery. The solar resource pattern for the city of Pretoria was collected from The National Aeronautics and Space Administration and modelled statistically. Thus, the statistical modelling done using solar radiation resource exposure characteristic patterns of Pretoria, South Africa, revealed an average annual daily solar radiation of 5.4645 Wh/m2/d and 0.605 clearness index. The simulation and the design were done using the Hybrid Optimization Model for Electric Renewables and Matlab/Simulink software. The simulation finding shows that the HPS of solar PV-battery combination has about 59.62 % saving on Net Present Cost, Levelized Cost of Energy, and 80.87% saving on Operating cost as against conventional BS powered with Gen Set-Battery.

The ecological background condition of the semi-arid steppe region (SASR) is extremely fragile. It is recognized that the development of coal and electricity power is a kind of strong human interference behavior for regional landscape ecology. Landscape ecological classification (LEC) is the premise of landscape ecology research of the mining area. The current research on the SASR and grassland LEC of coal-power base is relatively less, but still remains uncertainty concerning how to stratify and classify urban mining landscapes into units of ecological significance at spatial scales appropriate for management. This study is based on hierarchy theory, scale theory, landscape process, the patch-corridor-matrix model, the network, the theory of multiple planning integration and the principle of remote sensing. According to the comprehensive principle, principles of the combining of structure and function, principle of the combining human-ominated and natural landscape, principle of emphasis, and principle of combining qualitative analysis with quantitative research of LEC in large-scale coal-power base(LSCPB). On the basis of occurrence method land classification, fully consider the ecological attributes of the land, integration pattern, processes and function theory of the landscape ecology, the LEC system of the LSCPB in the SASR has been constructed by using top-down decomposition classification method. Empirical research of the Victory and Mindong No.1 mining areas of Shenhua Group shows that the classification system constructed in this paper can meet the requirements of LEC and fully reflect the status of landscape ecology of LSCPB in SASR. This study can provide theoretical guidance for the landscape ecology of LSCPB, while also supporting a theoretical reference for the LEC research.

Power quality is a major concern in electrical power systems. The power quality disturbances such as sags, swells, harmonic distortion and other interruptions have impact on the electrical devices and machines and in severe cases can cause serious damages. Therefore it is required to recognize and compensate all types of disturbances at an earliest to ensure normal and efficient operation of the power system. To solve these problems, many types of power devices are used. At the present time, one of those devices, Dynamic Voltage Restorer (DVR) is the most efficient and effective device used in power distribution system. In this paper, design and modeling of a new structure of multifunctional DVR for voltage correction is presented. The performance of the device under different conditions such as voltage swell, voltage sag due to symmetrical and unsymmetrical short circuit, starting of motors, and voltage distortion are described. Simulation result shows the superior capability of proposed DVR to improve power quality under different operating conditions. The proposed new DVR controller is able to detect the voltage disturbances and control the converter to inject appropriate voltages independently for each phase and compensate to load voltage through three single- phase transformers.

With a relatively small population, Russia accesses huge oil, natural gas, coal and uranium resources, and hosts advanced nuclear energy, oil and natural gas industries. However, the combined effect of today’s low cost electricity generation via photovoltaic modules, water and wind turbines and similarly low cost storage in Li-ion battery and solar hydrogen obtained via water electrolysis will have a profound impact on Russia’s energy and automotive industries.

Adequate knowledge about the development and operation of the components of water systems is of high importance in order to optimize them. For this reason, forecasting of future events becomes greatly significant due to making the appropriate decision. Moreover, operational river management severely depends on accurate and reliable flow forecasts. In this regard, current study inspects the accuracy of support vector regression (SVR), and SVR regulated with fruit fly optimization algorithm (FOASVR) and M5 model tree (M5), in river flow forecasting. Monthly data of river flow in two stations of the Lake Urmia Basin (Vaniar and Babarud stations on the Aji Chay and the Barandouz Rivers) were utilized in the current research. Additionally, the influence of periodicity (π) on the forecasting enactment was examined. To assess the performance of mentioned models, different statistical meters were implemented, including root mean squared error (RMSE), mean absolute error (MAE), correlation coefficient (R), and Bayesian information criterion (BIC). Results showed that the FOASVR with RMSE (4.36 and 6.33 m3/s), MAE (2.40 and 3.71 m3/s) and R (0.82 and 0.81) values had the best performances in forecasting river flows in Babarud and Vaniar stations, respectively. Also, regarding BIC parameters, Q_t-1 and π were selected as parsimonious inputs for predicting river flow one month ahead. Overall findings indicated that, although both FOASVR and M5 predicted the river flows in suitable accordance with observed river flows, the performance of FOASVR was moderately better than the M5 and periodicity noticeably increased the performances of the models; consequently, FOASVR can be suggested as the accurate method for forecasting river flows.

The Unmanned Aerial Vehicles (UAVs), used in civilian applications such as emergency medical deliveries, precision agriculture, wireless communication provisioning, etc., face the challenge of limited flight time due to their reliance on the on-board battery. Therefore, developing efficient mechanisms for in-situ power transfer to recharge UAV batteries hold potential in extending their mission time. In this paper, we study the use of far-field wireless power transfer (WPT) technique from specialized, transmitter UAVs (tUAVs) carrying Multiple Input Multiple Output (MIMO) antennas for transferring wireless power to receiver UAVs (rUAVs) in a mission. The tUAVs can fly and adjust their distance to the rUAVs to maximize energy transfer. The use of MIMO antennas further boost the energy reception by narrowing the energy beam toward the rUAVs. The complexity of their dynamic operating environment increases with the growing number of tUAVs, and rUAVs with varying levels of energy consumption and residual power. We propose an intelligent trajectory selection algorithm for the tUAVs based on a deep reinforcement learning model called Proximal Policy Optimization (PPO) to optimize the energy transfer gain. Simulation results demonstrate that with the use of PPO, the system achieves a tenfold flight time extension compared to no wireless recharging. Further, PPO outperforms the benchmark movement strategies of ’Traveling Salesman Problem’ and ’Low Battery First’ when used by the tUAVs.

Volcanic fumaroles are openings in the earth's surface, where volcanic gases discharge to the atmosphere. Metallic and non-metallic elements contained in gases form specific mineral precipitates upon cooling. Although the presence of metals in fumarolic gases has long been known, their concentrations are generally low and difficult to measure directly. A laboratory model of a fumarole may resolve the situation if the complex gas composition could be accurately reproduced. Here we describe a new experimental approach that allows accurately simulating fumarolic gases in terms of their main components (H₂O, CO₂, S, HCl), as well as adding volatile metal compounds. Gas is generated inside a special flow-through reactor, at the outlet of which the elements contained in the gas form temperature-dependent mineral sequence inside the attached silica-glass tube. Using this installation, we obtained laboratory sublimates from reducing (H₂S-rich) gases similar to natural ones in terms of mineral composition and mineral habits. Twenty-one phases have been identified in sublimates, among which are simple and complex chlorides, simple sulfides and six sulfosalts. Comparison of the sublimate deposition from H₂O-rich gas at 1 bar with similar works performed in evacuated ampoules at low pressure showed that fumarolic gases behave like an ideal gas, in which molecules do not interact with each other, and reactive compounds in the gas serve in fact as an inert carrier of volatile metals species. Changing the composition of the gas at the outlet of the installation, its flow rate and temperature, we can observe the corresponding changes in mineral precipitates and in such a way study the factors affecting mineral formation on natural fumarolic fields.

Laser-induced breakdown spectroscopy (LIBS) is an important analysis technique with applications in many industrial branches and fields of scientific research. Nowadays, the advantages of LIBS are impaired by the main drawback in the analysis of collected data. This procedure is essentially based on the comparison of lines present in the spectrum with a literature database. This paper proposes the use of various computational intelligence methods to develop a reliable and fast classification of non-destructively acquired LIBS spectra into a set of predefined classes. We focus on a specific problem of classification of paper-ink samples into 30 separate, predefined classes. For each of 30 classes (10 pens of each of 5 ink types combined with 10 sheets of 5 paper types plus empty pages) 100 LIBS spectra are collected. Four variants of preprocessing, seven classifiers (Decision trees, Random forest, k-Nearest Neighbour, Support Vector Machine, Probabilistic Neural Network, Multi-Layer Perceptron, and Generalized Regression Neural Network), 5-fold stratified cross-validation and test on an independent set (for methods evaluation) scenarios are employed. Our developed system yielded an accuracy of 99.08% with average classification time of about 0.12 s is obtained using the random forest classifier. Our results clearly demonstrates that machine learning methods can be used to identify the paper-ink samples based on LIBS reliably at a faster rate.

Gas embolism is a medical condition leading to the blockage of blood flow in the microvasculature by gas bubbles. While reported as rare, gas embolism often has devastating, fatal physiological consequences. Despite this acute importance, the genesis and evolution of air bubbles in blood vessels under different physiological conditions, such as blood viscosity and blood flow rate, is still understudied, largely because of difficult experimentation and in situ visualization. The objective of this work was to study the gas embolism phenomenon in vitro, using a microfluidic system that mimicked the architecture of microvasculature. The microfluidic systems comprised linear channels with two different air inlet types, namely, T- and Y-junctions with three different widths (20 µm, 40 µm, and 60 µm), and a 30 µm width honeycombed network with three bifurcation angles (30°, 60°, and 90°). Three synthetic liquids equivalent to 0%, 20%, and 46% hematocrit that mimicked the physiological blood viscosity and hematocrit concentrations were used. Our results show that: (i) 20 µm and 40 µm width channels had an elevated risk of gas embolism due to wide fluctuations in the total slug sizes; (ii) the resistance to the flow of air bubbles increased with the increase in the equivalent concentration of hematocrit; (iii) gas bubbles causing blockages and dampening of the flow velocity were frequently observed in 20 µm channels, and lastly (iv) increased risk of gas embolism was observed in the honeycomb architecture with 60° and 30° bifurcations. This work suggests that in vitro experimentation using microfluidic devices with microvascular tissue-like structures opens the possibility of studying this medical condition with high reproducibility and impacts the fact-based medical guidelines for preventing or mitigating iatrogenic occurrences.

Oil immersed paper insulation condition is a crucial aspect of power transformer’s life condition diagnostic. The measurement testing database collected over the years made it possible for researchers to implement classification analysis to in-service power transformer. This article presents classification analysis of transformer oil-immersed paper insulation condition. The measurements data (dielectric characteristics, dissolved gas analysis, and furanic compounds) of 149 transformers with primary voltage of 150 kV had been gathered and analyzed. The algorithm used for developing classification model is Support Vector Machine (SVM). The model has been trained and tested using different datasets. Different models have been created and the best chosen, resulting in 90.63% accuracy in predicting the oil-immersed paper insulation condition. Further implementation was executed to classify oil-paper condition of 19 Transformers which Furan data is not available. The classification results combined, reviewed, and compared to conventional assessment methods and standards, confirming that the model developed has the ability to do classification of current oil-paper condition based on Dissolved Gasses and Dielectric Characteristics.

Recent advancements in Software Defined Networking (SDN) makes it possible to overcome the management challenges of traditional network by logically centralizing control plane and decoupling it from forwarding plane. Through centralized controllers, SDN can prevent security breach, but it also brings in new threats and vulnerabilities. Central controller can be a single point of failure. Hence, flow-based anomaly detection system in OpenFlow Controller can secure SDN to a great extent. In this paper, we investigated two different approaches of flow-based intrusion detection system in OpenFlow Controller. The first of which is based on machine-learning algorithm where NSL-KDD dataset with feature selection ensures the accuracy of 82% with Random Forest classifier using Gain Ratio feature selection evaluator. In the later phase, the second approach is combined with Gated Recurrent Unit Long Short-Term Memory based intrusion detection model based on Deep Neural Network (DNN) where we applied an appropriate ANOVA F-Test and Recursive Feature Elimination feature selection method to improve the classifier performance and achieved an accuracy of 88%. Substantial experiments with comparative analysis clearly show that, deep learning would be a better choice for intrusion detection in OpenFlow Controller.

Background: This study aims to investigate the effects of visual neurofeedback stimulation on the brain activity in overweight cases. The neuroscience studies indicated the personal decision about eating under the impact of environmental factors such as (visually, smelling, tasting) is related to neural activity of the prefrontal lobe of the brain. Therefore, there were many attempts to modify the food intake behavior in overweight cases through the stimulation of the prefrontal cortex. However, the empirical viewing of EEG-neurofeedback experiments has not explicated the details about the effect of the EEG-NF, the specificity of positive treatment effects remains in a challenging scope.Methods: This study is a cue-exposure EEG-NF experiment to verify the hypothesis of effecting the EEG-NF on the electrical activity of PFC and modifying the general symptoms of food intake behavior in overweight cases. Twenty-four individuals were recruited as participants for this study. These participants were assigned randomly into two groups; the EX-Group (N=12) enrolled in 8 sessions of the EEG-NF experiment, and the C-Group (N=12) was listed in no EEG-NF sessions. The participants provided researchers with a self-report questionnaire relating to their observation of general symptoms of food intake behavior, and EEG signals recordings into the pre and posts stimulation phase. The power spectral density (PSD) method was applied for EEG parameters extraction.Results: The results of a two-way analysis of variance (ANOVA) explained that a significant variation in variables between the two groups after the EEG-NF experiment. The analysis of the quantitative variables indicated that the effect of EEG-NF experiment was a significant decrement in EEG power bands which significantly influenced changing the median of self-report questionnaire responses that is related to general symptoms of food intake behavior.Conclusions: This study provides preliminary support for the therapeutic potential of EEG-NF experiment that targets the prefrontal cortex, to influence neural processes underlying food intake behavior in overweight cases.

The coronavirus disease 2019 (COVID-19) has spread over the world for more than one year. COVID-19 often develops life-threatening hypoxemia. Endothelial injury caused by the viral infection leads to intravascular coagulation and ventilation-perfusion mismatch. However, besides above pathogenic mechanisms, the role of alveolar edema in the disease progression has not been discussed comprehensively. Since the exudation of pulmonary edema fluid was extremely serious in COVID-19 patients, we bring out a hypothesis that severity of alveolar edema may determine the size of poorly-ventilated area and the blood oxygen content. Treatments to pulmonary edema (alcohol-oxygen vapor therapy and fluid management) may be great helpful for reducing occurrence of severe cases. Given that late mechanical ventilation may cause mucus (edema fluid) to be blown to the deep of the small airways, oxygen therapy should be given at the early stages. The optimal time and SpO₂ threshold for oxygen therapy are also discussed.

A method of solution to solve the compressible unsteady 3D Navier-Stokes Equations in cylindrical co-ordinates coupled to the continuity equation in cylindrical coordinates is presented in terms of an additive solution of the three principle directions in the radial, azimuthal and z directions of flow. A dimensionless parameter is introduced whereby in the large limit case a method of solution is sought for in the boundary layer of the tube. A reduction to a single partial differential equation is possible and integral calculus methods are applied for the case of a body force directed to the centre of the tube to obtain an integral form of the Hunter-Saxton equation. Also an extension for a more general body force is shown where in addition there is a rotational force applied.

Background: A malfunction of the innate immune response in COVID-19 is associated with eosinopenia particularly in more severe cases. This study tested the hypothesis that this eosinopenia is COVID-19 specific and is associated with systemic activation of eosinophils.. Methods: Blood of 15 healthy controls and 75 adult patients with suspected COVID-19 at the ER were included before PCR testing and analyzed by point-of-care automated flow cytometry (CD10, CD11b, CD16 and CD62L) in the absence or presence of a formyl peptide (fNLF). 45 SARS-CoV-2 PCR positive patients were grouped based on disease severity. PCR negative patients with proven bacterial (n=20) or other viral (n=10) infections were used as disease controls. Eosinophils were identified with the use of the FlowSom algorithm. Results: Low blood eosinophil numbers (<100 cells/microL; p<0.005) were found both in patients with COVID-19 and with other infectious diseases albeit less pronounced. Two discrete eosinophil populations were identified in healthy controls both before and after activation with fNLF based on the expression of CD11b. Before activation, the CD11bbright population consisted of 5.4% (CI95% = 3.8, 13.4) of total eosinophils. After activation, this population of CD11bbright cells comprised nearly half the population (42.21%, CI95% = 35.9, 54.1). Eosinophils in COVID-19 had a similar percentage of CD11bbright cells before activation (7.6%, CI95% = 4.5, 13.6), but were clearly refractory to activation with fNLF as a much lower percentage of cells end up in the CD11bbright fraction after activation (23.7%, CI95% = 18.5, 27.6; p<0.001). Conclusion: Low eosinophil numbers in COVID-19 are associated with refractoriness in responsiveness to fNLF, which is likely caused by migration of fully functional cells to the tissue. Such homing might be beneficial as eosinophils have been implicated in viral killing.

Presently power control and management play a vigorous role in information technology and power management. Instead of non-renewable power manufacturing, renewable power manufacturing is preferred by every organization for controlling resource consumption, price reduction and efficient power management. Smart grid efficiently satisfies these requirements with the integration of machine learning algorithms. Machine learning algorithms are used in a smart grid for power requirement prediction, power distribution, failure identification etc. The proposed Random Forest-based smart grid system classifies the power grid into different zones like high and low power utilization. The power zones are divided into number of sub-zones and map to random forest branches. The sub-zone and branch mapping process used to identify the quantity of power utilized and the non-utilized in a zone. The non-utilized power quantity and location of power availabilities are identified and distributed the required quantity of power to the requester in a minimal response time and price. The priority power scheduling algorithm collect request from consumer and send the request to producer based on priority. The producer analysed the requester existing power utilization quantity and availability of power for scheduling the power distribution to the requester based on priority. The proposed Random Forest based sustainability and price optimization technique in smart grid experimental results are compared to existing machine learning techniques like SVM, KNN and NB. The proposed random forest-based identification technique identifies the exact location of the power availability, which takes minimal processing time and quick responses to the requestor. Additionally, the smart meter based smart grid technique identifies the faults in short time duration than the conventional energy management technique is also proven in the experimental results.

China combines green energy and industrial policy in its power market reform with various policy initiatives, including price support scheme for electricity from renewable sources and subsidies in the push for broader use of greener energy. This study focuses on the impacts of power market reform on the stock price volatility of listed power companies: 1) we use the Iterative Cumulative Sums of Squares (ICSS) algorithm to identify structural break points in stock prices; 2) we analyze the characteristics of stock price volatility based on the GARCH model; 3) we report the impact of power regulation on stock price fluctuations based on the Autoregressive Distributed Lag (ARDL) model. The result suggests three structural breaks in China’s power stock price volatility were related to the promulgation of power market reform policies. We find that industrial policies promote the reduction of power stock price fluctuations and its impact on power stock price volatility is consistent in the long run. However, our study also indicates the recent policies related to renewable energy do not have a very significant impact on the power stock market.

In most studies reported in literature, a flat, constant coefficient is used to convert the amount of optical power required at the input of an optical link into the effective power consumption. This constant coefficient approach is very simple to apply but not accurate, since laser efficiencies are dependent on the optical output power in addition to the operating temperature. In this paper the relationship between laser wall plug efficiency and optical power output is investigated and the effect of this variance on optical links and on-chip laser source electric power consumption is presented

The vision of the community around Geothermal Power Plant (GPP) is the development of GPP should be based on sustainable development principles, without jeopardizing the quality of life and justice for communities surrounding the power plant. This research aims to: (i) identifying issues that arise as an impact of the development of GPP in the rural Tompaso, and (ii) finding solutions to the issues to minimize the conflict that arises from further GPP development in rural Tompaso and its surroundings. This study is based on the competitive intelligence (CI) research method. The results show that the development of GPP in Tompaso has a negative impact on the natural environment and social environment. The technical solutions offered include: (i) bioremediation by cultivating plants that absorb arsenic; (ii) biosulfurization and desulfurization for reducing air pollution, especially sulfur; (iii ) floods and extreme drought are managed by improving infrastructure and reforestation; (iv) social conflicts (land acquisition, working days, labor recruitment and settlement security) are solved by intensifying program dissemination to the community and involving local communities in decision making. The recommended policy is providing incentives to the local community through strategic programs for the development of human and natural resources.

Active flow control of canonical laminar separation bubbles by steady and harmonic vortex generator jets (VGJs) was investigated using direct numerical simulations. Both control strategies were found to be effective in controlling the laminar boundary-layer separation. However, the present results indicate that using the same blowing amplitude, harmonic VGJs were more effective and efficient in reducing the separated region than the steady VGJs considering the fact that the harmonic VGJs use less momentum than the steady case. For steady VGJs, longitudinal structures formed immediately downstream of injection location led to formation of hairpin-type vortices causing an earlier transition to turbulence. Symmetric hairpin vortices were shown to develop downstream of the forcing location for the harmonic VGJs as well. However, the increased control effectiveness for harmonic VGJs flow control strategy is attributed to the fact that shear-layer instability mechanism was exploited. As a result, disturbances introduced by VGJs were strongly amplified leading to development of large-scale coherent structures, which are very effective in increasing the momentum exchange, thus, limiting the separated region.

This paper shows that the percolation clusters from elementary cellular automata {30, 45, 60, 86, 99, 105, 129, 150, 153, 169, 182, 183, 184, 195 and 225 exhibit strong power law behavior, either under random initial conditions, a single occupied cell, or both. Most of the tail exponents are less than unity, implying diverging means and variances of cluster sizes. The analysis presented here is admittedly coarse in an effort to expedite its dissemination.

Abstract Due to the relatively low efficiency of thermoelectric (TE) generators, they have mostly been used in niche applications where the unique properties of TE generators outweigh their lack of efficiency, or conditions where it is more reasonable to base the optimal design on maximum generated power rather than maximum efficiency. The aim of this work is to investigate how the different fundamental transport properties (Seebeck coefficient, thermal conductivity and electrical resistivity) in materials with equal figure of merit (ZT) impact TE module design and maximum power output. Further, we discuss and review the strategies to enhance material properties and the latest studies on the TE module performance. It is shown, that by increasing the power factor by a factor of 15 and decreasing the thermal conductivity by 13.33 in order to maintain ZT=1, power output is increased by 45%. This effect is stronger in lower module fill factor and thermal resistance of the heat source and heat sink.

In this paper, a further mathematical analysis of some previous results of the author’s ongoing investigation regarding Prandtl’s equations is accomplished. In particular, the objective of the present work is the performance of an approximate explicit solution to Prandtl’s system of equations for a laminar, isothermal, incompressible and steady boundary layer flow of a Newtonian fluid, over an infinite horizontal flat plate.

Chinese investors are easily affected by hot topics on the media and Internet and likely take irrational behavior. They tend to consume rationally and invest emotionally. This research aims to analyze the Baidu index’s effect on share price of solar power industry in China. Three main models are established to identify the correlation between Baidu index and stock price of solar industry. The media index and searching index of Baidu are chosen as an independent variable to measure the influence from media and Internet, and stock price as the dependent variable. To improve and complete the analysis, Hexun index is taken into consideration as mediator variable. This study applied Multiple Linear Regression Model and VAR (Vector auto-regression) Model. The research mainly uses the tools of SPSS, Eviews and Excel to conduct data analysis. The test is based on the theories of Granger Causality, unit root test, F-test, and t-test. The research proves the relationship between the close price of stock and Baidu index, and it also created a model for further forecasting.

This paper proposes the impact of plug-in electric vehicles integrated into power distribution system based on voltage dependent control. The plug-in electric vehicles was modeled as the static load model in power distribution systems under balanced load condition. The power flow analysis is determined by using the basic parameters of the electrical network. The main point of this study are compare with voltage magnitude profiles, load voltage deviation, and total power losses of the electrical power system. There are investigating the affected from constant power load, constant current load, constant impedance load and plug-in electric vehicles load, respectively. The IEEE 33 bus test system is used to test the proposed method by assigning each load type to a balanced load in steady state and applied the solving methodology based on the bus injection to branch injection matric, branch current to bus voltage matrix, and current injection matrix to solve the power flow problem. The simulation results showed that the plug-in electric vehicles load had the lowest impact compared to other loads. The lowest plug-in values for the electric vehicle loads were 0.062, 119.67 kW and 79.31 kVar for the load voltage deviation, total active power loss and total reactive power loss, respectively. Therefore, this study can be verified that the plug-in electric vehicles load were affected to the lowest of the electrical power system in condition to same sizing and position. So that, in condition to the plug-in electric vehicles load added into the electrical power system with the conventional load type or complex load type could be considered that the affected from the plug-in electric vehicles load in next study.

The calculation of power flow in power systems with the presence of harmonics has been properly studied in the scientific literature. However, power flow calculation considering interharmonic components is still an open question. Traditional methods based on the IEEE1459 standard have proven to be valid and accurate only for linear and sinusoidal systems, but have been criticized for non-linear and non-sinusoidal systems because they are not able to explain correctly the current and voltage interactions beyond the active power. This paper proposes the use of a novel mathematical framework called geometric algebra (GA) to study the power flow considering the interaction of current and voltage harmonics and interharmonics. The use of GA enables the precise determination of the direction and magnitude of the total and single active power flow for each component, as well as other power elements related to the non-active power due to cross interaction. Moreover, this paper makes a novel contribution to the definition of interharmonics in geometric algebra space that has not been done before. To test the validity of the method, both linear and non-linear circuits are proposed and solved by applying voltages and currents with harmonic and interharmonic components. The results obtained show that power flow can be analyzed under the prism of the principle of energy conservation (PoCoE) in a way that allows a better understanding of the power spectrum due to the interaction of harmonics and interharmonics of voltage and current.

The construction industry is one of the most fatal industries, so it is important to pay more attention to safety solutions. Even though work-related accidents are known as major waste in construction projects, little attention has been paid so far to incorporating safety into the lean construction framework. In this research, lean construction theory is reviewed through the lens of safety. That being so, the identified challenges in previous research on improving safety in construction projects are categorized and those related to the concept of lean project delivery are introduced. Then, the principles of the lean construction framework are explained and the relevant changes for incorporating safety into the framework are introduced and discussed. It is expected that this hybrid model would further enrich the lean construction framework. The careful attention of project executives to this model may improve the safety situation in construction projects.

This paper addresses the effects of electric power quality on robotics operation. A general overview is reported to highlight the main characteristics of electric power quality and their effects on a powered system by considering an end-users viewpoint. Then, authors outline the influence of voltage dip effects by focusing at robotic grasping applications. A specific case of study is reported as referring to LARM Hand IV, a three-fingers robotic hand, which has been designed and built at LARM in Cassino. A dedicated test rig has been settled up for generating predefined voltage dips. Experimental tests are carried out for evaluating the effects of different types of voltage dips on the grasping of objects.

The aim of this work is to evaluate the impact of proposed modifications to conventional capturing and discharging effluents devices in Subsurface Flow Wetland (SSFW) systems. Main modifications proposed consist on extending the influence of the capture and discharge device in such a way that the SSFW width and height are fully covered. Additionally an SSFW prototype was built as pilot including the proposed modifications and the impact of the innovative device is measured based on the efficiency of the Chemical Oxygen Demand (COD) removal as compared to a traditionally built SSFW. The results show that for the innovative device, the COD removal was 10% higher than for the conventional device.

In this paper, a study of modeling PV cell (solar cell), PV module (solar modules) and PV array solar array) using Matlab/Simulink software is presented. This study is focused on the study to design photovoltaic cell, photovoltaic modules, photovoltaic panels and PV array (solar array) and to analyze the change in PV performance according to changes in different parameters such temperature, solar irradiation, reverse saturation current, series resistance and shunt resistance. This study shows the PV and IV characteristics curve for each model from which MPP (maximum power point) is determined. In this study, different PV and IV characteristic curves are gained for varying temperatures with specified solar irradiation conditions,s and then the MPP is tracked. The highest power output is also compared between the designed PV module and the selected PV module (MX Solar USA MX60-245)

Coal combustion in thermal power plants releases ash. Ash is reported to cause different adverse health hazards in humans and other organisms. Owing to the presence of radionuclides, it is also considered as a potential radiation hazard. In this study, based on the surface radiation measurements and relevant ancillary data, expected radiation risk zones were identified with regard to the human population residing near the Thermal Power Plant. With population density as the risk determining criteria, about 20% of the study area was at ‘High’ risk and another 20% of the study area was at ‘Low’ risk zone. The remaining 60% was under medium risk zone. Based on the findings remedial measures which may be adopted have been suggested.

As a consequence of the increasing share of renewable energies and sector coupling technologies, new approaches are needed for the study, planning, and control of modern energy systems. Such new structures may add extra stress to the electric grid, as is the case with heat pumps and electrical vehicles. Therefore, the optimal performance of the system must be estimated considering the constraints imposed by the different sectors. In this research, a dispatch optimization method with an iterative grid constraint generation, decoupled from the linear unit commitment problem, is employed. From the considered scenarios, it was found that in a typical German neighborhood with 150 households, PV penetration of ∼5kWp per household can lead to curtailment of ∼60MWh per year due to line loading. Furthermore, the proposed method eliminates grid violations due to the addition of new sectors reducing the curtailment up to 60%. With the optimization of the heat pump operation, an increase of 7% of the self-consumption was achieved with similar results for the combination of battery systems and electrical vehicles. In conclusion, a safer and optimal operation of a complex energy system is fulfilled. Safer control strategies and more accurate plant sizing could be derived from this work.

For the particular selected type of fractals, i.e., the Kronecker product based fractals, the introductory common classification is proposed. It essentially relies on the size and content of the initial fractal matrix. In turn, it gives one of the possible explanation of the phenomenal ability to produce a few of the most popular fractals using many different algorithms, languages and tools. Also, it paves the way to discover on the regular basis thousands of the new fractals, and this gives researchers a wider range of fractal models to choose from.

Yam (Dioscorea spp.) is a monocotyledonous herbaceous vine plant grown in the tropics and subtropics. It is a multi-species plant with varied intra- and interspecific ploidy levels. Of the 600 species, 11 are cultivated staple supporting the livelihood of over 300 million people. The paucity of information on ploidy and the genomic constitution is a significant challenge to the crop’s genetic improvement through crossbreeding. The objective of this study was to investigate the ploidy levels of 236 accessions across six cultivated and two wild species using chromosome counting, flow cytometry and genotyping-based ploidy determination methods. Results obtained from chromosome counting and genotyping-based ploidy determination were in agreement. In majority of the accessions, chromosome counting and flow cytometry were congruent, allowing future rapid screening of ploidy levels using flow cytometry. Among cultivated accessions, 168 (71%) were diploid, 50 (21%) were triploid, and 12 (5%) were tetraploid. Two wild species included in the study were diploids. Resolution of ploidy level in yams offers opportunities for implementing successful breeding programmes through intra- and inter-specific hybridization.

While the demand in reduction of CO₂ increases, the need for CO₂ sequestration processes is very high. One promising technology is the Carbon Capture and Storage (CCS). In this paper we refer to several papers which study the three main steps in CCS chain. CO₂ capture technologies, CO₂ transportation to the storage sites and the very critical step the CO₂ storage. Recently a novel method (mineral carbonation) for CO₂ sequestration has been proposed which is based in the reaction of CO₂ with calcium or magnesium oxides or hydroxides to form stable carbonate materials. Greece is a country that emits CO₂ mainly from the lignite fired power plant in Western Greece. After the study of the bibliographic references about the use of mineral carbonation process while injecting CO₂ in the appropriate geological forms we concluded that there are also these forms in our country and mainly in the area near to the power plant such as in sites Vourinos and Pindos. In these sites exist minerals rich in oxides and hydroxides of Ca, Mg and Fe representing the perfect materials for mineral carbonation.

In this study, a tuned mass damper is proposed as a seismic acceleration mitigating technique of an electrical cabinet inside the nuclear power plant. In order to know the mitigation performance, the electrical cabinet and the tuned mass damper were modeled using SAP2000. The sine sweep wave was used to confirm the vibration characteristics of the cabinet over a wide frequency range, and the several various earthquakes were applied to the cabinet to verify the control performance of the tuned mass damper. After analyzing the numerical results, it is summarized that the application of the proposed technique can reduce the acceleration response of the cabinet.

The research is designed for developing the pilot small-scale clean development mechanism bundled project activities in Vietnam electricity/ energy sector. Its overall purpose is to assess the potential of rice husk - fuelled bio-power development projects in Mekong delta. Based on estimating the electricity potential of a bundle of rice husk-fuelled bio-power development projects in Mekong delta with the capacity of 11 MW per project, assessing their CO₂ emission reductions (CERs) and CER credits, calculating and comparing their financial indices (NPV, B/C, IRR) in two cases: W/O CDM and W/CDM, the research expects to establish a rice husk energy balance flowchart for the whole Mekong delta in the year 2021 and recommend policies to use for bio-power generation the unused rice husk that is dumped and discharged from local paddy milling centers into rivers and canals, as well as, to put forward a safe and environmentally friendly solution to minimize thoroughly the current serious pollution of rivers and canals in Mekong delta with the increasing unused rice husk quantity in the context is where the sea level rise phenomenon is the strongest in the world .

In this study an adjusting post-processing approach is implemented for improving intra-hourly forecasts of solar power and ramp events of PV solar power systems at different locations in the United States. This study also serves as an out-of-sample test to evaluate the performance of the adjusting approach with different locations and timescales. Thus, various individual intra-hourly forecasts of solar power are combined and adjusted by applying the adjusting approach. Both point and probabilistic forecasts of solar power are included. After that, solar power ramp event forecasting by the adjusting approach is carried out.

In this paper, a new approach is proposed for designing ultra-low-power FFT (Fast Fourier Transform) system suitable for use in energy harvesting powered sensors. Bit-serial architecture is adopted to reduce the power consumption of butterfly operation. Simulation results show that, compared with state-of-the-art bit-serial and conventional parallel processors, the proposed technique is superior in terms of silicon area, power consumption, dynamic energy use due to variable precision arithmetic. A sample design of a 64-point FFT shows that the implementation can save about 40% area and 36% leakage power compared with a conventional parallel counterpart, accordingly achieving significant power benefits at a low sample rate and low voltage domain. The dynamic variation of the arithmetic precision can be achieved through a simple modification of the controller with hardware area overhead of 10% gate count.

The Abdominal Aortic Aneurysm (AAA) is a local dilation of the abdominal aorta and it is a cause for serious concern because of the high mortality associated with its rupture. Consequently, the understanding of the phenomena related to the creation and the progression of an AAA is of crucial importance. In this work the complicated interaction between the blood flow and the AAA wall is numerically examined using a fully coupled Fluid-Structure Interaction (FSI) method. The study investigates the possible link between the dynamic behaviour of an AAA and the blood viscosity variations attributed to the haematocrit value, while it also incorporates the pulsatile blood flow, the non-Newtonian behaviour of blood and the hyperelasticity of the arterial wall. It was found that blood viscosity has no significant effect on von Mises stress magnitude and distribution, whereas there is a close relation between the haematocrit value and the Wall Shear Stress (WSS) magnitude in AAAs. This WSS variation can possibly alter the mechanical properties of the arterial wall and increase its growth rate or even its rupture possibility. The relationship between haematocrit and dynamic behaviour of an AAA can be helpful in designing a patient specific treatment.

The decarbonization of the electrical energy sector is in progress for contrasting the climate changes, with a relevant increase of the Renewable Energy Sources (RES) power plants, mostly in Dispersed Generation (DG). The adequacy and the security of power systems, with a huge penetration of RES in DG is possible with a suitable integration of energy storage. In fact, energy storages are able to provide many different services for long-term adequacy and real time security. In this framework the present paper deals with a Thermal Energy Storage (TES) proposed for power system services. The technology presented is made up of modules containing a bed of fluidizable solid particles, which can store thermal energy from waste heat, process heat and/or from electricity. Stored thermal energy can be released, e.g. as superheated steam, for thermal uses or converted into electricity, by means of steam turbines. Some possible applications are then reported explaining advantages and limits.