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Developing cost-effective and stable materials for the electrocatalysis of hydrogen evolution reaction (HER) remains challenging. In this study, efficient catalysts for HER were synthesized by integrating the cobalt and molybdenum oxides via electrodeposition, followed by subsequent sulfurization of the as-prepared oxides using chemical vapor deposition (CVD). This methodology allowed the incorporation of both cobalt and molybdenum components into the catalyst in a single step. The as-synthesized CoSx@MoSx/MoOx-based catalysts exhibited excellent hydrogen production performance in acidic media owing to the presence of Co-S and Mo-S bonds in the hybrid structure. Particularly, CoSx@MoSx/MoOx(90@360) and MoSx@CoOx(180@180) displayed the best HER performances with low overpotentials of 80 mV and 150 mV, respectively. The catalysts were highly stable, with their stability preserved for over 1000 cycles with marginal reduction in overall efficiency. Therefore, these findings suggest the potential of CoSx@MoSx/MoOx and MoSx@CoOx composites as ideal candidates for developing low-cost catalysts for electrochemical hydrogen production. [ABSTRACT FROM AUTHOR]

Summary: In the pulp and paper industry, black liquor, which is a biomass resource, is burned to produce electricity. Black liquor is concentrated to 21 wt% water through an evaporator before being burned in a boiler. For the evaporator, a multiple‐effect evaporator (MEE) is mainly used, but it requires a large amount of energy and cost. Therefore, it is crucial to reduce energy and cost of evaporation process. Hence, this study suggested a novel process model that integrated mechanical vapor recompression (MVR) with MEE to increase the energy efficiency. The suggested MVR‐assisted evaporation process was composed of preheating and evaporation processes to effectively concentrate black liquor. In addition, it reduced the steam consumption of MEE by using MVR, which uses relatively inexpensive electric energy in the pre‐evaporation process. In the simulation results, the steam, electricity consumption, and the latent heat recovered from the secondary vapor of the suggested process were quantitatively analyzed to verify the energy efficiency. The results indicate that the proposed process increases substantial energy efficiency compared to the conventional process. Then, the appropriateness of the suggested process was evaluated by the techno‐economic analysis. The total annualized cost (TAC) is determined for both current and potential future economic benefits. TAC of the MVR‐assisted MEE configuration can be reduced by up to 77.54%. [ABSTRACT FROM AUTHOR]

Integrating more active components into a catalyst material could facilitate the development of multifunctional electrocatalysts for energy conversion and storage applications. In this study, we developed a multifunctional electrocatalyst, namely, Pd alloyed with Co-Fe deposited on N-doped mesoporous carbon derived from tissue paper (Pd@Co-Fe/N-TDC). The synergism in Pd@Co-Fe/N-TDC, stemming from the interatomic alloy between Pd and Co-Fe, N-doped mesoporous carbon with defective surfaces, distribution of polyhedral Pd nanoparticles, and strong metal-support interfacial interaction, resulted in significantly high electrocatalytic performance for both oxygen reduction reaction (ORR) and oxygen evolution reaction (OER). Pd@Co-Fe/N-TDC was found to be an efficient bifunctional oxygen electrocatalyst, and this was evidenced by a high onset potential (1.01 V) and kinetic current density (2.6 mA/cm2) for the ORR and by a low overpotential (296 mV) and a low Tafel slope value (38 mV/dec) for the OER, along with a small Δ E of 736 mV. The catalyst also exhibited high durability for both ORR and OER, even after 10000 and 5000 cycles, respectively. Theoretical assessment provides an insight into the synergism of active metal sites in Pd@Co-Fe/N-TDC, which showed its potential for use as a non-Pt electrocatalyst for energy applications. [ABSTRACT FROM AUTHOR]

Summary: Microfluidic fuel cell (MFC) stacking is a prerequisite to enhance its power output for practical applications. However, most MFC stacks reported in the present literature require external pumps to maintain the co‐laminar flow and complex fluidic management networks for homogeneous flow and reactant distributions. To address these issues, a novel paper‐based self‐pumping MFC stack with potassium formate as the fuel and hydrogen peroxide as the oxidant is proposed in this study. The capillary action is employed to achieve passive liquid flow. A vertical stack structure with the unit cells piled one above another compactly is adopted to reduce the volumetric costs. The experimental results show that the maximum power outputs of the two‐cell and three‐cell stack prototypes are 4.01 and 7.26 mW cm−2, outperforming the MFC unit by 5.81 and 10.52 times, respectively. The superior performance is attributed to its distinct vertical stacking structure, which brings the enhanced capillary flows in the paper wicks and reduced ohmic losses in comparison with the unit cell. Further, effects of the filter paper and reactant concentrations on the stack performance were examined, and mass transfer of the fuel and/or oxidant to the electrode/electrolyte interface was identified as the main limiting factor. A loose microstructure of the paper wick was found beneficial in enhancing the mass transfer. The potential applications of the MFC stack in a variety of portable electronics are broad. [ABSTRACT FROM AUTHOR]

Summary: Tremendous research has focused on the wearable electronic device, leading to the basic requirement of suitable power sources. Herein, we report one bendable paper‐based zinc‐air battery with a novel hollow channel structure. It achieves a maximum power density of 138 mW/cm2, outperforming the state‐of‐art paper‐based batteries reported previously. The boosted performance is assigned to the low charge transfer resistance and facilitated mass transfer from the hollow structure. It demonstrates the positive design of microchannel structure is profitable for the power‐generation enhancement, and offers a possible route to commercialize the paper‐based power generators. [ABSTRACT FROM AUTHOR]

Summary: Direct liquid fuel cell (DLFC) and membraneless fuel cell using the anode consisting of buckypaper (BP) and vitamin B12 (Vit B12) (BP/Vit B12) is introduced in physiological condition, while vitamin C (Vit C) is used as anodic fuel. Due to the high sensitivity of Vit B12 and the inherent feature of BP, the onset potential for the oxidation reaction of Vit C catalyzed by BP/Vit B12 is −0.1 V (vs Ag/AgCl), and its anodic current density measured at 0.3 V (vs Ag/AgCl) is 1.82 mA cm−2 even in a low Vit C concentration (10 mM). Regarding performance in fuel cells, maximum power density (MPD) of Vit C fuel cell containing membrane and Pt‐based air cathode is 0.62 ± 0.067 mW cm−2 in 0.01 M Vit C, and this is 3.1 times higher than that of fuel cell containing pristine BP. In addition, in a paper‐based flexible membraneless fuel cell using BP/bilirubin oxidase as cathode and the concentration of cerebrospinal fluid within the human body (0.35 mM Vit C), its MPD is 57.7 ± 4.02 μW cm−2. This means this suggested Vit C fuel cell system can replace the conventional primary batteries considered as the power source of implantable sensors and stimulation devices to treat neurological disorders. [ABSTRACT FROM AUTHOR]

Summary: Coronavirus disease (COVID‐19) has spread all across the world. Low‐ and medium‐income countries are more affected economically and socially compared to developed countries due to the lack of a rapid, robust, and affordable testing infrastructure. Furthermore, the high cost of real‐time polymerase chain reaction (PCR) system, sophisticated user‐handling procedure, and high expense of the conventional clinical tests are the root causes of the less accessibility of the testing systems to the users. In this study, a COVID‐19 Point‐of‐Care (POC) ecosystem model is proposed for the low‐ and medium‐income countries (or energy deprived countries) that will facilitate the technological development with locally available fabrication components. In addition, the nontechnological development phases have also been discussed, which encompasses the collaboration among academia, local as well as government bodies, and entrepreneurial ventures. In addition, a hypothetical design of a microfluidic paper‐based analytical (μPADs) POC platform is proposed to detect COVID‐19 analyte using unprocessed patient‐derived saliva, which is a miniaturized form‐factor of conventional real‐time polymerase chain reaction (PCR) technique. The device contains four major reaction zones, which are sample zone, buffer zone, loop‐mediated isothermal amplification (LAMP) Master Mix zone, Ethylenediamine tetraacetic acid (EDTA) zone, and sensor zone. To obtain quicker test results and easier operation, a handheld image acquisition technique is introduced in this study. It is hypothesized that in a remote setting, the proposed design could be used as an initial guideline to develop a POC COVID‐19 testing system, which may be simple, easy‐to‐use, and cost‐effective. [ABSTRACT FROM AUTHOR]

The through-plane permeability of the gas diffusion media (GDM) is investigated experimentally with regard to the microporous layer (MPL) composition and the gas diffusion layer (GDL) composition and structure. The MPL composition is held constant at 80% carbon powder and 20% polytetrafluorethylene (PTFE) (by weight) for various carbon loadings. The decrease or increase in GDM permeability was found to be dependent on the structure of the GDL used in conjunction with the type of carbon powder. It was found that low-surface- area carbon powder (Vulcan XC-72R) forms thin, dense MPLs with small cracks when compared to high-surface-area powder (Ketjenblack EC-300J), which creates thick, rough MPLs with large cracks with increased carbon loadings. For most cases, the permeability decreases with increasing carbon loading; however, the non-woven, straight fibre carbon papers using Ketjenblack EC-300J show the lowest permeability at the lowest carbon loading. Furthermore, the percentage reduction from the GDL substrate permeability appears to be predictable for similar structures with increasing carbon loading. The increase in PTFE loading from 10% to 30% in the GDL was shown to have a significant impact on the percentage reduction from the original GDL permeability of ~9% to 15% for the GDM composed of Vulcan XC-72R as carbon powder; however, such effects are insignificant when using Ketjenblack EC- 300J carbon powder. [ABSTRACT FROM AUTHOR]

The increasing environmental consideration and the growth of instability of the energy market call for methods that can process the organic fraction of municipal solid waste (OFMSW) into fuel instead of disposal. Due to the pyrolysis and gasification that are efficient procedures to achieve valuable products, gasification of OFMSW with different particle sizes and compositions was carried out in the presence of Ni and Ni-Ce-loaded Y-zeolite in a multizone tubular kiln reactor. During the experiments, 500°C was applied in the first reactor zone, while the 2nd zone was at an elevated temperature of 600°C or 900°C in the presence of steam. The combined pyrolysis and gasification experiments were also carried out without a catalyst with the same operating conditions. The feedstock was collected from the organic fraction of a Hungarian mechanical-biological treatment (MBT) plant and was separated into four different fractions based on particle size: <1 cm dry biomass and fine particles, 1-2 cm paper-rich, 2-6 cm paper and plastic-rich feedstocks, and <6 cm mixture of these fractions. During the experimental work, product yields; gaseous product composition; the ratio of H2/CO, CO2/CO, and CH4/CO; and lower heating value were determined in the function of feedstock composition, the applied temperature, and catalysts. It was found that the hydrogen content and H2/CO ratio of gaseous products were increased due to catalyst application and temperature elevation in the 2nd reactor zone. The addition of Ce to the Ni/Y-zeolite catalyst was advantageous in the case of hydrogen formation at a lower temperature (600°C). The hydrogen and methane content of products obtained from the catalytic pyrolysis-gasification of paper and plastic-rich OFMSWs on elevated temperatures were higher, which increased the lower heating value of those products. Based on the elemental analysis of the obtained solid residues, it was found that paper/plastic-rich feedstock released hydrogen and carbon with a higher extent. 1-2 cm feedstock-related solid residues had the highest H/C ratio which caused a 12.5-12.8 MJ/kg gross heating value. As a result, combined pyrolysis and gasification appear to be an efficient method to attain valuable outputs from OFMSW not only in gas but also in solid products. [ABSTRACT FROM AUTHOR]

The fabrication of heterostructures via solution process is one of the essential technologies for realizing efficient advanced-generation optoelectronics. Hybrid structures comprising colloidal quantum dots (CQD) and organic semiconducting molecules are garnering considerable research interest because of their complementing optical and electrical properties. However, blending both the materials and forming a stable electronic ink are a challenge owing to the solubility mismatch. Herein, a CQD:organic ternary-blended hybrid solar ink is devised, and efficient hybrid solar cells are demonstrated via single-step spin coating under ambient conditions. Specifically, the passivation of the benzoic acid ligand on the CQD surface enables the dissolution in low-polar solvent such as chlorobenzene, which yields a stable CQD:organic hybrid ink. The hybrid ink facilitates the formation of favorable thin-film morphologies and, consequently, improves the charge extraction efficiency of the solar cells. The resulting hybrid solar cells exhibit a power conversion efficiency of 15.24% that is the highest performance among all existing air-processed CQD:organic hybrid solar cells. [ABSTRACT FROM AUTHOR]

Energy consumption has risen much more while the economy has expanded so quickly. As a result, significant environmental contamination is created, which causes public worry. Under this background, enhancing energy efficiency and lowering pollution is particularly crucial for the fulfillment of sustainable economic development. Efficiency evaluation for energy and environment is an effective measure to achieve both energy saving and emission reduction as well as sustainable social development. In this paper, energy and environmental efficiency consists of energy utilization efficiency and pollution treatment efficiency. An improved two‐stage DEA model is proposed, which takes into account how stochastic and environmental factors affect decision‐making units (DMUs). Finally, the author analyses the panel data of 15 cities in Southwest China from 2010 to 2018, which proves the feasibility and effectiveness of this study. The results show Southwest China's poor energy and environmental efficiency as well as the stark differences among its cities. The scientific value revealed by this paper is as follows: (1) for the study of energy and environmental efficiency, this paper is more targeted at the differences between cities and (2) using an improved two‐stage DEA model to consider the effects of stochastic factors on DMUs. [ABSTRACT FROM AUTHOR]

Summary: The purpose of this paper is to investigate the perspective of using wood waste, especially the one that resulted from the construction and demolition activities, to produce sustainable bioenergy. The context of this research is characterized by a more accelerated need for development, a growing need for energy to fuel all human activities, and a greater awareness of the pressure on the environment and the negative effects produced. One of the major challenges for environmental protection is the issue of mitigating CO2 emissions, and among the biggest contributors to the CO2 emissions is the construction industry. Given the current rhythm of society development, a decrease in construction activities is not possible so a solution can be better management of the waste produced in various stages. If the need for better waste management is joined with the need for more sustainable energy, then using waste to produce bioenergy seems like a good solution. This study focuses mainly on wood waste and to respond to the research purpose it uses bibliometric literature search, scientometric analysis, and in‐depth discussions. The data were obtained by interrogating the ISI Web of Science database using the keywords "bioenergy", "wood waste" and "construction and demolition" as search criteria. The extraction of data was done using the PRISMA method and processed with VOSviewer and Bibliometrix software. The processing of the data was done so to obtain information related to the importance of the research topic given by the number of publications, the most studied topics revealed by a keywords co‐occurrence analysis and a trend topic plot, as well as the world scientific productions on the studied topics. The main results indicate a significant increase, in the last years, of the interest in the studied topics, all over the world. Wood waste is considered as a direct combustion fuel or as a raw material for components of fuels used to produce energy, as well as components for new building materials. Given the limitations of other renewable energy sources, wood biomass is a subject that must be considered more in the future. The use of wood waste as biomass for the production of bioenergy can be a very good solution that will bring the advantage of both ensuring a renewable source of energy and at the same time decreasing the impact of the building industry on the environment. [ABSTRACT FROM AUTHOR]

Summary: Lateral flow test assay requires integrated micro power sourcesto realize quantitative testing as well as to enhance accuracy. Conventional dry batteries generally havepollution issues for this task, while the recently emerged paper‐based fuel cells are both expensive and low‐voltage that restrict their usage. In comparison, the metal‐air battery (MAB) using a metal anode and an air‐breathing cathode could be a much better solution. In this study, different micro metal‐air batteries are integrated onto paper substrates, producing micro power sources that are low‐cost, high‐voltage and environmentally friendly. Their performances are compared under both alkaline and salt electrolytes in terms of power output, fabrication cost and specific energy. Among them, the Al‐air battery with an alkaline electrolyte and the Mg‐air battery with a salt electrolyte are more advantageous than others, achieving high voltage outputs of 1.55 V and 1.53 V at 1 mA cm−2, respectively. By using acarbon grid instead of asilver grid as current collector, and nitrogen‐doped carbon nanotubesinstead of MnO2 as oxygen reduction catalyst, the as‐fabricated micro MABs can be much cheaper and greener for disposable lateral flow test devices. Finally, a two‐cell micro Al‐air battery pack, which is integrated into a digital pregnancy tester, provides powersuccessfully for its operation for more than 5 minutes. [ABSTRACT FROM AUTHOR]

Summary: The object of this study is the manufacturing processes and fluorinated ethylene propylene (FEP) contents on the cell performance of the proton exchange membrane fuel cell (PEMFC). These results are useful for optimizing gas diffusion layer (GDL) fabrication processes and the operating conditions of the PEMFC. A traditional GDL with a micro porous layer (MPL) can enhance the water management ability. For the case of the one‐stage GDL manufacturing process, carbon paper with an FEP content of 10 wt% has the best fuel cell performance and limiting current density. Besides, in the two‐stage GDL fabrication process, when the cathode fuel is air, carbon paper with the same 10 wt% FEP content can delay the occurrence of limiting current density. The types of carbon black have remarkable influences on water management capabilities. It is noted that the XC‐72R carbon powder has a relatively appropriate pore volume to have enough water to keep the membrane moist and avoid water flooding. The higher the gas humidification temperature, the faster the electrochemical reaction rate. But when the operating current density is high, it will generate too much water, resulting in water flooding and a decrease in the PEMFC performance. Therefore, when the cathode fuel is air and the inlet humidification temperature is 80°C for the anode and 50°C for the cathode, the limiting current density can be effectively extended to maintain the cell performance. [ABSTRACT FROM AUTHOR]

This paper reviews the current state of microbial fuel cell (MFC) technology for energy generation. It begins by exploring clean energy alternatives, focusing on waste‐to‐energy solutions, and introduces the concept, applications, and advantages of MFCs. The biochemical processes within MFCs are explained, highlighting how microorganisms metabolize substrates through glycolysis, the Krebs cycle, and the electron transport chain to generate electrons. These electrons flow through an external circuit and combine with protons and oxygen at the cathode to produce water or reduced forms of nitrogen and sulfur. This paper also analyzes 10 key parameters affecting MFC performance: coulombic efficiency, pH, temperature, substrates, organic loading rate, electrode potential, open circuit voltage, treatment efficiency, organic removal rate, and hydraulic retention time. Recent advancements in MFC technology are also discussed, including innovations in reactor configuration and scaling, the development of new membrane materials like earthen and ceramic, and improvements in wastewater treatment methods. The advancements also extend to genetic engineering techniques to enhance microbial efficiency and component modifications, such as the use of carbon‐based nanomaterials and metal catalysts for improved performance, innovations in proton transfer membranes, and mediator‐less MFCs utilizing metal‐reducing bacteria. Challenges facing MFC technology, such as cost, scalability, and environmental sensitivity, are mentioned. The paper concludes with future directions, including the use of advanced materials, integration with wastewater treatment infrastructure, and the potential for nutrient recovery and chemical synthesis. This comprehensive review aims to provide knowledge into optimizing MFCs for sustainable energy generation and environmental benefits. [ABSTRACT FROM AUTHOR]

Summary: Pristine WSe2 based electrocatalyst shows poor reaction kinetics in electrochemical hydrogen evolution reaction due to a lack of active atomic sites and an inert basal plane. Herein, we report an active system of non‐metallic plasmonic WSe2/WO3−x, supported by highly conductive and eco‐friendly Ag/cellulose paper electrodes. An air thermal annealing technique is used to enrich the p‐WO3−x dopants in WSe2, which is significant for substantially improving electrocatalytic behaviour as well as photo responsive performance in the near‐infrared (NIR) region. The WSe2/WO3−x dramatically decreases the overpotential of HER from −330 to −150 mV (at 10 mA/cm2) owing to homo doping and generation of Se‐vacancies. Surface plasmons resonances of p‐WO3−x give the contributions to injection of photogenerated electrons and overpotential as low as −120 mV can be achieved under the illumination of NIR light. These results represent significant advances in light‐enhanced electrocatalysis and would provide potential applications for commercial hydrogen generation. Novelty Statement: Novel WSe2/WO3−X hybrid nanosheets‐based electrocatalysts exhibit the light‐enhanced hydrogen evolution reaction. WO3−X enriched WSe2 nanosheets exhibit rapid electrochemical charge transport due to p‐homodoping and Se‐vacancies. Overall, the 3D‐porous structure of cellulose paper and 2D‐ WSe2/WO3−X leads the promising optimisation. [ABSTRACT FROM AUTHOR]

Why Hydrogen. Nowadays, the energy industry and research laboratories are heavily working on developing ideas and methods to reduce and/or eliminate the carbon dioxide emission to control the problem of global warming. The solution relies on finding alternative green energy resources to reduce the world's dependence on conventional fossil hydrocarbon energy. Green hydrogen gas from water stands on the top of the alternative resources since it does not produce carbon dioxide when burned and in return does not add to global warming. Since seawater is the largest resource on earth, this makes the hydrogen production from seawater the most economically attractive solution. It is very important to avoid using fresh water as a source of hydrogen energy due to the dependence of all living creatures, humans, animals, plants, etc., on such very limited resources. In this paper, the applications of the proposed novel solution of green hydrogen production directly from seawater relies on solving one of the major problems, electrode corrosion. Generating Hydrogen. The direct method to produce green hydrogen from seawater is the electrolysis technique. This technique requires a direct current power supply for the positive and the negative electrodes. The outcome of the electrolysis is decomposing the saltwater to its positively charged hydrogen and sodium ions at the negative electrode and its negatively charged oxygen and chlorine ions at the positive electrode. The Real Challenge. Traditionally in the electrolysis analysis of water, both electrodes are made of metals. At the positive electrode, both the oxygen and the chlorine cause a high rate of corrosion to that electrode. This results in the interruption of the electrolysis process, bad water condition due to the corrosion deposits, and cost burden due to the need to periodically replace the corroded electrodes and/or use high-cost corrosion-resistant alloys. The Novel Solution. A low-cost but powerful solution to the corrosion problem is introduced, tested, and experimentally proved. The novelty of the solution relies on replacing the classic special high-cost metallic positive electrode with a nonmetallic, no-cost, one. The nonmetallic electrode is made of surface rock portions that have high porosity and pore volume and high permeability and pore connectivity and is saturated with saline water. Surface rocks with the above properties exhibit very low resistivity and hence conduct electricity like metallic electrodes. The voltage and the current conducted by such electrode are controlled by the electrode geometry, connectivity, and physical properties. Results and Discussions. Multiple experiments using the proposed nonmetallic high-porosity and high-permeability positive electrode are conducted and presented in this paper. The experimental work is based on testing multiple rock electrodes with different rock properties, sizes, and connectivity in comparison to the metallic ones. The comparison showed that the novel solution solved the corrosion challenges of the metallic electrodes with excellent efficiency. [ABSTRACT FROM AUTHOR]

Optimal sizing and management of hybrid wind turbine-diesel-battery system for reverse osmosis seawater desalination in NEOM city is the objective of the paper. Therefore, the paper explored the different factors to optimize and introduce a technoeconomic evaluation and energy management of a stand-alone wind turbine (WT) system, diesel generator (DG), and battery storage (BS). The suggested WT/DG/BS system is implemented to feed seawater reverse osmosis (SWRO) unit in NEOM. The necessitated desalinated water per day is 100 m3. To determine the optimal size of WT/DG/BS corresponding to the minimum cost of energy (COE) and net present cost, two different ratings of the SWRO units (SWRO-100 and SWRO-150), three control dispatch strategies (load following, cycle charging, and combined dispatch), and five types of batteries are considered. HOMER software is performed to simulate and optimize the WT/DG/BS. The optimization results indicated that the best battery storage is the Trojan SAGM battery. In this case, the COE ranged between $0.337/kWh and $0.564/kWh. The lowest COE of $0.377/kWh is obtained when using a combined control strategy and SWRO-100 unit, whereas the worst COE of $0.564/kWh is obtained when using load following control strategy and SWRO-150 unit. The best option of the WT/DG/BS system to supply the SWRO unit is option number 26. This system includes one wind turbine of 90 kW, DG of 25 kW, 47 Trojan SAGM batteries, a 23.8 kW converter, a SWRO-100 unit, and a combined control strategy. The net present cost and the initial cost are $950,725 and $221,495, respectively. The annual operating cost and annual consumed fuel are $56,409 and 36,396 L, respectively. Compared with using only a 25 kW diesel generator, the COE reduced from $0.373/kWh (using only DG/BS) to $0.337/kWh (using the best option) by around 9.65%. Under this condition, the values for the internal rate of return, return on investment, and simple payback are 11%, 7.8%, and 8.3 years, respectively. [ABSTRACT FROM AUTHOR]

Nowadays, most of the works are based on electric vehicle usage for sustainable transportation using traditional energy storage device, such as battery. Usage of batteries in electric vehicles is having several disadvantages, for example, life span, temperature, and charge estimation. In this paper, a novel control scheme for battery and supercapacitor- (SC-) based hybrid energy storage system (HESS) using hybrid proportional and integral- (PI-) sliding mode control (SMC) for electric vehicle (EV) applications is introduced and implemented. This HESS with hybrid controller proves the usage of batteries in EVs to its fullest potential. The conventional control strategy for HESS follows two-loop voltage and current PI controllers with low-pass filter (LPF) and involves tuning of multiple control parameters with variations of source and load disturbances. Performance of the system is affected by tuning PI controller constants. A slow response time with linear PI controllers is long which is not advisable for starting and sudden jerk conditions of EVs. Moreover, the PI controller performance is affected by the system parameter variations during load changes. And these parameters are dynamic in nature due to nonideal conditions. In this paper, a hybrid PI-sliding mode controller (SMC) scheme is designed to control the bidirectional DC-DC converters to overcome the drawbacks of aforementioned issues. The combined PI-SMC controller reduces the tuning effort and reduces the effect of shift in operating point in controller performance. Linear modeling is done using small signal analysis for each subsystems. Permanent magnet synchronous machine (PMSM) is used as electric vehicle. The entire system and its controllers are simulated using MATLAB-Simulink, and detailed comparison is carried between conventional PI and proposed hybrid PI-SMC scheme to regulate the DC link voltage. The results are tabulated and show that the hybrid PI-SMC scheme outperforms in transient and steady-state conditions than the traditional PI controller. A scaled hardware prototype of 48 W set-up is developed using dSPACE-1104, and the experimental results have been carried out to verify the proposed system's feasibility. [ABSTRACT FROM AUTHOR]

Machine learning (ML) algorithms are increasingly used in power systems applications. One important application is the classification and localization of various types of transmission line faults. Using voltage and current measurements from phasor measurement units (PMUs), a number of useful features can be extracted, which can form the basis of a ML-based prediction of the fault type, line, and distance on the line. This paper proposes a technique to find the optimal number and placement of PMUs by performing thorough feature selection. The features are selected to maximize the accuracy of the ML classification and regression algorithms. The results show that for the IEEE 14 bus system, the use of only five PMUs is sufficient to obtain high levels of accuracy. For example, a testing accuracy of 99.0% and 97.1% can be achieved for the fault type and fault line location, respectively. As for the fault distance along the line, the testing MAE of 3.1% can be obtained along with an R 2 score of 94.4%. Adding more PMUs does not provide any additional value in terms of accuracy. [ABSTRACT FROM AUTHOR]

This paper is aimed at performing a comprehensive review of the approaches employed in nanosatellite platforms, specifically 1 U and 3 U, for electrical power systems (EPS). Moreover, it seeks to develop a robust maximum power point tracking (MPPT) controller using the sliding mode control (SMC) method. The proposed control strategy is intended to monitor the solar panel's maximum power point (MPP) and adapt to changes in temperatures and solar irradiance in low Earth orbit (LEO). The EPS model, designed with the proposed sizing method, is built in MATLAB-Simulink and integrates a solar panel, battery storage, and power converters controlled by diverse MPPT methods. Then, simulation results demonstrate the effectiveness of the proposed SMC approach compared to other conventional control methods for the designed EPS under varying LEO conditions. To achieve a robust validation of the most appropriate MPPT control method under steady-state conditions, this paper presents an experimental investigation into the proposed EPS hardware design. The proposed SMC method achieved an increase in power generation from 10% to 12% for buck and boost power converters, respectively, compared to traditional control methods. [ABSTRACT FROM AUTHOR]

This paper introduces a novel concept of a TRISO-fueled salt-cooled reactor (TFSCR). The core contains circulating pipes filled with molten salt carrying TRISO particles. The reactor achieves online refueling by slowly circulating the molten salt through the pipeline. The reactor utilizes the same molten salt as the coolant and graphite as the moderator. The reactor design has the characteristics of safety, economy, and nonproliferation. TRISO particles exhibit greater resistance to neutron irradiation, corrosion, oxidation, and high temperatures compared to conventional fuels. A molten salt-cooled reactor can also operate at higher temperatures, consequently enhancing power generation efficiency. Furthermore, lower operating pressures can mitigate the risk of significant damages and loss of coolant caused by accidents, thereby enhancing reactor safety. This paper presents the basic nuclear design of TFSCR under the assumptions concerning the average fuel power density, the volumetric core power density, and the core temperature. At the same time, the feasibility of online refueling and long-life operation was evaluated by fuel burnup calculation. [ABSTRACT FROM AUTHOR]

This paper presents a performance analysis and optimization of heat exchanger fin shapes in a thermoelectric power generation system for ship waste heat recovery. It proposes a new curved fin design aimed at enhancing heat transfer efficiency and maximizing thermoelectric power generation capacity. Numerical analysis and response surface methodology (RSM) focused on 225 parameters to identify the optimal fin shape. Computational analysis using CFX was conducted on the thermoelectric module system with curved fins. The methodology was verified by comparing and analyzing CFD and PIV experimental results for a curved fin. The paper comprehensively compares the fluid dynamics of curved fins and straight fins, highlighting how curved fins improve heat exchange by creating a tip leak vortex. The results demonstrate the superiority of the curved fin design in terms of heat transfer efficiency and net power generation over the conventional straight fin design. [ABSTRACT FROM AUTHOR]

Predictive energy-saving control (PEC) is aimed at reducing energy consumption by designing the vehicle speed while considering future road and traffic information. In particular, the slope of the road ahead is necessary and critical for PEC. This paper proposes a road slope prediction method for production vehicles that uses the nonlinear autoregressive (NAR) neural network model based on road slope sensors. To adaptively balance the energy savings and trip time, this paper proposed a real-time variable weight PEC method for a four-wheel-drive (4WD) intelligent electric vehicle. The weight coefficients are automatically changed according to the characteristics of the road slope, where the vehicle energy-saving rate on the steep downhill road can be maximized. The results of real-time simulation on the dSPACE platform indicated that the road slope predictive model can be run in real time and adapted to changes in road slope and speed. The root mean square error (RMSE) of the predictive results is 0.3063. On a steep downhill road, the energy-saving rate of the proposed PEC method can reach 30.87% at a small expense of time of 3.75%. On uphill and flat roads, energy can be saved by 6.35% at a time cost of 3.0%. Compared with the PEC with constant weight factors, the two control objectives of energy savings and traveling time can be better balanced on various types of roads. [ABSTRACT FROM AUTHOR]

This paper presents a multistrategy fusion particle swarm optimization model for dynamic economic dispatching of renewable energy in distribution networks. The objective is to minimize active network losses and system voltage deviation while considering the integration of distributed energy sources and static reactive power compensators. The algorithm incorporates specific strategies, including a particle position change strategy based on the midpipeline convergence approach, a strategy for generating exploding particles near the optimal particles, and a particle velocity update strategy relying on the global optimal particle position. The inertia weights and particle position update methods of the simplified particle swarm optimization algorithm are also utilized. Simulation experiments are conducted on an IEEE 33 bus radial distribution system, demonstrating the effective optimization of system losses while ensuring system voltage stability. This research contributes to the scientific understanding of renewable energy integration in distribution networks and its economic dispatching. [ABSTRACT FROM AUTHOR]

In recent years, the proportion of wind power in new energy generation has gradually increased. The natural wind in wind farms is subject to velocity attenuation by the wake effect, so improving the efficiency of wind farm power generation has become a problem that must be solved for wind power generation. Considering the uncertainty of wind farms, we regard wind farm layout optimization (WFLO) as a strongly nonlinear problem. In this paper, we improve the sparrow search algorithm (SSA) using dynamic opposite learning (DOL) strategy. Twenty-eight benchmark test results prove that compared with other algorithms, the improved algorithm DOLSSA has excellent robustness and the ability of searching for a better solution when solving a strongly nonlinear optimization problem, and the DOL strategy effectively improves the shortcomings of the original algorithm which is prone to local optimization and space limitation. In this paper, the authors establish the dynamic rotational coordinates of wind farms and set six different physical scenarios by considering the wind direction and wind speed variables, and the results prove that the performance of DOLSSA is optimal. [ABSTRACT FROM AUTHOR]

The bioeconomy model provides an alternative view of global economic systems by putting sustainable practices combined with digital approaches at the forefront to tackle issues such as climate change. To address this new business trends, financial institutions began to set up the environmental, social, and governance (ESG) business units to evaluate their business strategies. This paper is aimed at examining the nonfinancial effect created by the digital transformation (DT) activities, highlighting the role of enterprise heterogeneity after the implementation of Environmental Protection Law (EPL) in China. We employ the panel data of A-share listed companies from 2010 to 2020, selecting DT and ESG indicators as the important representations of "Industry 5.0." Our empirical results demonstrate a positive impact of EPL on the ESG performance in sight of resource enterprises (REs), environmental enterprises (EEs), and polluting enterprises (PEs), but a negative impact of EPL on the DT indicators among those environmental related industries. Additional causal relationship regression reveals that enterprise DT has an intrinsic promoting effect on the ESG performance, emphasizing on the high risk of digitization process being the shock transmitters to enterprise nonfinancial indices. Notably, the connectedness of environmental policy illustrates dynamic patterns by parallel trend test and propensity score matching (PSM) DID regression. This paper is prone to benefit lawmakers, regulators, and firm executives responsible for analyzing and assessing enterprise digitization behavior by exploring the influence of macrolevel environmental policy. [ABSTRACT FROM AUTHOR]

In recent times, the significance of renewable energy generation has increased and photovoltaic-thermoelectric (PV-TE) technologies have emerged as a promising solution. However, the incorporation of these technologies still faces difficulties in energy storage and optimization. This review paper addresses these challenges by providing a comprehensive overview of the latest advancements in PV-TE technologies. The paper emphasizes the integration of phase change materials (PCMs) for thermal energy storage, also buttressing the use of encapsulated PCM for thermal storage and efficiency, and the use of hybrid PCM to enhance overall performance. Furthermore, reviews on the use of machine learning techniques for efficient optimization and the integration of thermoelectric modules into tandem perovskite silicon solar cells have been comprehensively analyzed. The advancements in photovoltaic-thermoelectric systems, as reviewed in this article, signify significant progress in attaining sustainable and effective energy production and storage. This review comprehensively addresses the 4Es, underlining their importance. It not only consolidates recent developments but also charts a path for future research in the field of PV-TE technologies, offering precise insights to guide upcoming studies and innovations. [ABSTRACT FROM AUTHOR]

Vibration control has been of great interest to scientists and engineers for many years. Although linear vibration absorbers have been shown to be effective in mitigating vibrations at specific frequencies, their vibration reduction effect is usually limited to a narrow frequency bandwidth. Nonlinear energy sinks have attracted attention due to their better vibration reduction effect over a wider frequency bandwidth. In practical applications, the nonlinear energy sink devices can effectively absorb, dissipate, and convert energy from broadband excitation, so as to achieve vibration reduction and energy harvesting. However, research on energy harvesting based on the nonlinear energy sink is less mature than in linear systems. Multiple parameters of device design (e.g., damping size) affect the actual performance of the nonlinear energy sinks, but there is no exact method to simplify the design of the multiparameter nonlinear energy sinks. Since it is more difficult to implement electromagnetic and electrostatic energy harvesters, more research has focused on piezoelectric energy harvesters. This paper summarizes the research on the nonlinear energy sink and energy harvesting technology, including the introduction of the nonlinear energy sink, energy harvesting based on the nonlinear energy sink, and its application in various fields of energy harvesting. The paper also summarizes some important methods for solving the dynamical equations, as well as their advantages and disadvantages. The conclusions provide an outlook on the subsequent research of the nonlinear energy sink technology, such as the introduction of piezoelectric materials with high energy density, the benefits of balanced vibration suppression and harvesting of vibration energy, and the self-tuning of parameters in complex environments. It provides a powerful reference for the popularization and application of energy harvesting technology based on nonlinear energy sinks. [ABSTRACT FROM AUTHOR]

This paper presents a measurement method that utilizes object recognition technology for continuous and quantitative real‐time monitoring of water levels in industrial boilers. Real‐time videos of water levels were monitored using a small camera, and the YOLO algorithm, a single‐stage detector, was employed to use the bounding boxes of detected objects within the video as variables, directly measuring the length ratio for each frame. The method demonstrated a high level of accuracy in water‐level measurement, with an average of 99.02%, and a stable performance, with a fluctuation of 0.13% in continuous measurements. Consequently, the proposed measurement method proves feasible for quantifying continuous water levels in industrial inspection systems even in low‐resource environments. These results demonstrate a new mechanism for monitoring technology, without requiring text detection, showing the potential for improving efficiency in complex boiler systems and the feasibility of reliable water‐level measurement and control. [ABSTRACT FROM AUTHOR]

China's renewable energy products have an important place in international trade, and the conclusion of the RCEP agreement can create favourable external conditions for China's renewable energy product exports. This paper measures the export potential of China's renewable energy products to other RCEP countries through a trade gravity model. The results show that (1) the GDP of the importing and exporting countries, the energy consumption of the importing countries, and the particulate emissions damage significantly enhance China's renewable energy product exports; (2) among the RCEP countries, China has a greater potential to export renewable energy products to five countries in 2020, which are mainly located in East and Southeast Asia; and (3) from a dynamic perspective, China's renewable energy trade potential is increasing, while in the Oceania region it is weakening, while trade links to Southeast Asian countries are developing in a more mature direction. Based on the above research, this paper puts forward corresponding policy recommendations. [ABSTRACT FROM AUTHOR]

The conventional overcurrent protection is ineffective in isolating faults in microgrids due to the low fault current levels contributed by inverter-interfaced distributed generations (IIDGs). To extend the microgrid protection methods, the distance protection is considered as a common alternative to detect faults. However, the fault-ride-through (FRT) requirements and the high impedance fault (HIF) detection challenge the application of the conventional distance protection. To solve the two problems, a new inverse-time distance (ITD) protection for medium-voltage AC microgrids was proposed in this paper. The primary ITD protection was designed to meet the FRT requirements, and the backup protection was coordinated to isolate faults. The fault resistance and distributed generation infeed effect on the measured impedance were mitigated by a communication-assisted method proposed in this paper. Owing to the shorter communication channel time in distribution feeders and lower communication investments without a synchronous clock, the proposed method can be used to improve the ITD protection performance. An 11 kV AC microgrid was simulated with different fault types in the islanded mode and grid-connected mode. Time domain simulation verified the effectiveness of the proposed ITD protection. [ABSTRACT FROM AUTHOR]

Industrial and energy-related industries are major sources of carbon dioxide emissions, and their interdependence, as reflected in the financial field, has attracted the attention of scholars. For the purpose of exploring the evolutionary characteristics of the short-term dynamic correlation coefficient between the EU carbon futures price and the industrial and energy-related indices, this paper selected the settlement price of EU carbon emission quota futures, the MSCI energy I index on three dimensions, and the Dow Jones industrial index and West Texas crude oil futures price, as sample data. Using the time-varying t-copula model to measure the dynamic correlation coefficient between variables, the time-sliding window idea and coarse-grained method were combined to establish the correlation fluctuation mode, and a complex network theory and analysis methods were used to study the evolutionary traits of the time-varying network structure between the EU carbon price and the industrial and energy-related index. The results show that the transmission objects of the key correlation fluctuation modes in the network are stable and maintain their own state with a high probability. Second, the clustering effect exists in the transmission process. Some nodes with high mediating abilities are also the key correlation wave modes in the dynamic correlation evolution network. This study provides ideas for the study of the correlations between multiple variables and is also a useful reference for international investors. [ABSTRACT FROM AUTHOR]

The rapid deployment of electric vehicles (EVs) in Jordan requires massive efforts to prepare the infrastructures that serve the transportation sector. The lack of EV charging stations is the major obstacle that faces EV drivers. Utilizing renewable energy in EV charging stations contributes to the spread of these stations. Renewable energy technologies are environmentally friendly as they mitigate greenhouse gases that cause the global warming phenomenon. In this paper, an EV charging station, based on a PV-biodiesel-battery hybrid system, is investigated. The importance of this article is to discuss the hybrid system of PV and waste vegetable oil (WVO) along with storage that applies the maximum reliability supply, having an environmentally friendly supply and achieving the lowest energy cost of charging. This station is designed based on renewable and WVO utilization. In fact, WVO, coming from restaurants, is exploited to produce electricity by a diesel generator through direct burning after converting it into biodiesel. The capacity of each station is 14 cars/day with a medium-speed charger of 7 kW. The system is simulated and optimized using iHOGA software where multiobjective optimization is applied to achieve the minimum net present cost (NPC) and CO2 emissions considering three cases, PV-diesel, PV-biodiesel, and PV-WVO, all with battery-hybrid system. These values for the EV charging station that uses the PV-biodiesel-battery hybrid system are 624408 € and 15.4 tons/year, respectively. The corresponding values are 781473 € and 15.14 tons/year and 615310 € and 18.84 tons/year for the systems that work with diesel and WVO, respectively, and energy cost is achieved in best solution to be 0.11 Euro/kWh. Simulation results show that the proposed technique led to enhanced operational efficiency in terms of both NPC and annual CO2 emissions. [ABSTRACT FROM AUTHOR]

In this paper, a new simultaneous framework of distribution network operation is proposed based on the scheduling of photovoltaic/wind/battery multi-microgrids with network reconfiguration considering self-healing. The objective function is considered to minimize the energy losses, and multi-microgrids cost and improve the reliability indices including minimization of energy not-supplied (ENS) and minimizing system average interruption duration (SAIDI) and system average interruption frequency (SAIFI) indices. The optimization variables are defined as the situation of the distribution network switches to find the network's optimal configuration with the installation location and size of renewable resources and battery energy storage during 24 hours. An improved beluga whale optimization (IBWO) based on a nonlinearly diminishing inertia weight (NDIW) approach is used to find the optimal variable set of the problem. The recommended methodology is implemented on 33-bus and real 59-bus distribution networks. The results demonstrated that by obtaining an optimal state of the network switches in the event of a fault, as well as the optimal scheduling of the two microgrids, the energy losses have decreased and the reliability indices have improved. The outcomes of the proposed methodology based on the hybrid multi-microgrid allocation and network reconfiguration are stated that the losses, ENS, SAIDI, and SAIFI are reduced by 66.39%, 54.00%, 50.24%, and 33.61%, respectively, for 33-bus network and are declined by 65.29%, 57.44%, 48.63%, and 62.33%, respectively, for the real 59-bus Ahvaz network in comparison with the base network. The obtained results illustrated that in the condition of the network line outage, by simultaneously implementing the reconfiguration with the change of network switches and the optimal allocation and scheduling of HMGs in the network, self-healing is provided to prevent a significant weakening of the network performance so that the resilience is improved in addition to minimizing the energy losses and the cost of HMG energy injection compared to the base network. The findings revealed that the objectives including losses, ENS, SAIFI, and SAIDI are increased by 78.29%, 33.00%, 83.33%, and 35.11%, respectively, due to outage of line 22 of the 33-bus network and these objectives are increased by 52.32%, 10.30%, 32.29%, and 79.66%, respectively, due to outage of line 12 of the 59-bus network compared with not considering the line outage. Moreover, the superior capability of the recommended NDIW-based IBWO has been confirmed in comparison with the well-known particle swarm optimizer (PSO) and ant lion optimizer (ALO) in solving the problem to achieve better objective value. [ABSTRACT FROM AUTHOR]

The increasing global dependence on fossil fuels for energy has prompted researchers to explore alternative power generation sources that offer higher efficiency, cost-effectiveness, and low environmental impact. Developed countries have been making continuous efforts to reduce their reliance on depleting fossil fuel sources to curb carbon emissions. As a result, hydrogen has gained significant attention among researchers as a potential future fuel that meets all the necessary criteria. Many countries aiming for a hydrogen economy have invested in research on fuel cells. Among various fuel cells, the solid oxide fuel cell (SOFC) has emerged as a commercially viable power source at a small scale. This paper provides an extensive review of the components, materials, design, operation, and integration strategies of SOFCs with existing thermal-based power plants. The performance and prospects of various SOFCs in standalone and hybrid modes are summarized, along with the limitations. Additionally, the research and commercialization efforts that can enhance the potential applications of SOFCs as a sustainable and reliable system in the long term are outlined. [ABSTRACT FROM AUTHOR]

In the past few years, there has been a notable interest in the application of machine learning methods to enhance energy efficiency in the smart building industry. The paper discusses the use of machine learning in smart buildings to improve energy efficiency by analyzing data on energy usage, occupancy patterns, and environmental conditions. The study focuses on implementing and evaluating energy consumption prediction models using algorithms like long short-term memory (LSTM), random forest, and gradient boosting regressor. Real-life case studies on educational buildings are conducted to assess the practical applicability of these models. The data is rigorously analyzed and preprocessed, and performance metrics such as root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE) are used to compare the effectiveness of the algorithms. The results highlight the importance of tailoring predictive models to the specific characteristics of each building's energy consumption. [ABSTRACT FROM AUTHOR]

Energy storage systems (ESS) are seeing rapid market growth due to the changing worldwide landscape of electricity distribution and consumption. An ESS must possess the capability to oversee the functioning of the system's modules under abnormal circumstances, while also having the ability to supervise, manage, and optimize the performance of one or more battery modules. At present, the condition of batteries is assessed based on two factors: the level of charge (SOC) and the overall condition (SOH). By using these two characteristics, it becomes feasible to compute the anticipated battery lifespan and evaluate a battery's efficiency. The assessment of SOH is a crucial determinant in guaranteeing the effectiveness, dependability, and security of batteries in electric vehicles (EVs). Nevertheless, the safety issues resulting from the imprecise estimation and forecasting of battery health status have garnered significant attention in academic circles. This study presents a comprehensive evaluation of several SOH monitoring techniques. In order to achieve this objective, various scientific and technical literatures are examined and the corresponding methodologies are categorized into distinct groupings. The groupings are categorized based on the manner in which the procedure is executed: methods and techniques used in experiments and models. This paper provides a comprehensive overview of the benefits and drawbacks of several SOH assessment and prediction techniques, along with the associated obstacles in SOH estimation. [ABSTRACT FROM AUTHOR]

During the development of oil reservoirs, a rapid increase in water cut following reservoir flooding leads to inefficient or ineffective circulation of injected water, rendering a significant portion of the remaining oil in the reservoir inaccessible. The displacement method using polymer particle dispersion systems effectively solves the issue of rapid water breakthrough in oil reservoirs. Owing to the particle phase separation phenomenon, polymer particles can selectively penetrate into the larger pores where water circulation is inefficient, enhance their flow resistance, and thereby achieve equilibrium displacement along with an increased swept volume. This paper investigates the heterogeneous distribution of polymer particles within a porous medium, incorporates the red blood cell dendrite concentration distribution theory from biological fluid mechanics, and develops a mathematical model to delineate the viscosity characteristics of polymer particle dispersion systems, taking into account the phase separation phenomenon. Building on this foundation, it formulates a capillary bundle model for the polymer particle dispersion system specifically designed for oil displacement and proceeds to determine its relative permeability curve. Simulation outcomes reveal that at a water saturation level of 0.063, the concentration of polymer particles in fractured large pore capillaries is markedly elevated, yet capillaries with a pore size under 26 µm remain devoid of polymer particles. With the increase of water saturation, the concentration of polymer particles in large pore capillaries reduces, whereas it progressively augments in medium pore capillaries. Upon reaching a peak water saturation of 0.751, capillaries smaller than 18 µm are entirely free of polymer particles. These findings suggest that the heterogeneous distribution of polymer particles markedly inhibits the percolation capabilities of the dispersed system following a water phase breakthrough, facilitating the entry of more dispersion into oil-laden capillaries and thus enhancing the flow capacity of the oil phase. [ABSTRACT FROM AUTHOR]

In pressurized water reactor accident scenarios, the injection of water from the emergency core cooling system (ECCS) (ECC injection) might induce a pressurized thermal shock (PTS), affecting the reactor pressure vessel (RPV) integrity. Therefore, PTS is a vital research issue in reactor safety, and its analysis is essential for evaluating the integrity of RPVs, which determines the reactor life. The PTS analysis comprises a coupled analysis between thermal–hydraulic and structural analyses. The thermal–hydraulic approach is particularly crucial, and reliable computational fluid dynamic (CFD) simulations should play a vital role in the future because predicting the temperature gradient of the RPV wall requires data on the transient temperature distribution of the downcomer (DC). Since one-dimensional codes cannot predict the complex three-dimensional flow features during ECC injection, PTS is one reactor safety issue where CFD simulation can benefit from complement evaluations with thermal–hydraulic system analysis codes. This study reviewed from the viewpoint of the turbulence models most affecting PTS analysis based on papers published since 2010 on single- and two-phase flow CFD simulation for the experiment on PTS performed in the Rossendorf coolant mixing model (ROCOM), transient two-phase flow (TOPFLOW), upper plenum test facility (UPTF), and large-scale test facility (LSTF). The results revealed that in single-phase flow CFD simulation, where knowledge and experience are sufficient, various turbulence models have been considered, and many analyses using large eddy simulation (LES) have been reported. For two-phase flow analysis of air–water conditions, interface capturing/tracking methods were used in addition to two-fluid models. The standard k – ε and shear stress transport (SST) k – ω models were still in the validated phase, and various turbulence models have yet to be fully validated. In the two-phase flow analysis of steam–water conditions, many studies have used two-fluid models and Reynolds-averaged Navier-Stoke (RANS), and NEPTUNE_CFD, in particular, has been reported to show excellent prediction performance based on years of accumulated validation. [ABSTRACT FROM AUTHOR]

Recent experience with the strongest earthquakes greater than magnitude 5.4 in Korea leads to public interest in the safety and resilience of critical infrastructures. There are many nuclear power plants near the epicenters of the earthquakes. Nuclear power plants are essential infrastructures that provide stable and enough energy for human life, and simultaneously, control systems for the safety and security of nuclear power plants are critical due to the risk of nuclear accidents on public health and the environment. The nuclear area uses probabilistic risk assessment to estimate the risk of structures, systems, and components in nuclear power plants, and the evaluation of the fragility curve is a key process for probabilistic risk assessment. The challenges of a seismic fragility analysis lie in estimating the influence of various uncertainties in material, geometry, and earthquake and improving the existing fragility analysis methods, which require time-consuming nonlinear time history analysis. Thus, this paper conducts a multivariate seismic fragility analysis using surrogate models for reinforced concrete squat shear walls and proposes a simplified closed form equation for a chosen surrogate seismic demand model. The surrogate models are trained and validated by several approaches: response surface method, support vector machine, Gaussian process regression, and neural network. In addition, a correlation analysis is used to evaluate the relative importance of the variables to the seismic demand to simplify the surrogate model further. Finally, simplified surrogate models based on the importance of the variables are proposed as closed form of polynomials, and the performance of these models on the fragility analysis is evaluated. [ABSTRACT FROM AUTHOR]