bluuebunny/crossref_metadata_2025 huggingface dataset:
Using Shannon Entropy to Improve the Identification of MP-SBM Models with Undesirable Output
Authors: Ma Zhanxin , Yin Jie , Yang Lin , Li Yiming , Zhang Lei , Lv Haodong
Published: November 2022

In the context of the COVID-19 global epidemic, it is particularly important to use limited medical resources to improve the systemic control of infectious diseases. There is a situation where a shortage of medical resources and an uneven distribution of resources in China exist. Therefore, it is important to have an accurate understanding of the current status of the healthcare system in China and to improve the efficiency of their infectious disease control methods. In this study, the MP-SBM-Shannon entropy model (modified panel slacks-based measure Shannon entropy model) was proposed and applied to measure the disposal efficiency of the medical institutions responding to public health emergencies (disposal efficiency) in China from 2012 to 2018. First, a P-SBM (panel slacks-based measure) model, with undesirable outputs based on panel data, is given in this paper. This model measures the efficiency of all DMUs based on the same technical frontier and can be used for the dynamic efficiency analysis of panel data. Then, the MP-SBM model is applied to solve the specific efficiency paradox of the P-SBM model caused by the objective data structure. Finally, based on the MP-SBM model, undesirable outputs are considered in the original efficiency matrix alignment combination for the deficiencies of the existing Shannon entropy-DEA model. The comparative analysis shows that the MP-SBM-Shannon model not only solves the problem of the efficiency paradox of the P-SBM model but also improves the MP-SBM model identification ability and provides a complete ranking with certain advantages. The results of the study show that the disposal efficiency of the medical institutions responding to public health emergencies in China shows an upward trend, but the average combined efficiency is less than 0.47. Therefore, there is still much room for improvement in the efficiency of infectious disease prevention and control in China. It is found that the staffing problem within the Center for Disease Control and the health supervision office are two stumbling blocks.
First-Principle Derivation of Single-Photon Entropy and Maxwell–Jüttner Velocity Distribution
Authors: Li Changhao , Li Jianfeng , Yang Yuliang
Published: November 2022

This work is devoted to deriving the entropy of a single photon in a beam of light from first principles. Based on the quantum processes of light–matter interaction, we find that, if the light is not in equilibrium, there are two different ways, depending on whether the photon is being added or being removed from the light, of defining the single-photon entropy of this light. However, when the light is in equilibrium at temperature T, the two definitions are equivalent and the photon entropy of this light is hν/T. From first principles, we also re-derive the Jüttner velocity distribution showing that, even without interatomic collisions, two-level atoms will relax to the state satisfying the Maxwell–Jüttner velocity distribution when they are moving in blackbody radiation fields.
Isotropization of a Rotating and Longitudinally Expanding ϕ4 Scalar System
Authors: Carrington Margaret E. , Kunstatter Gabor , Phillips Christopher D. , Rubio Marcelo E.
Published: November 2022

We study numerically the evolution of an expanding system of scalar fields. The initial configuration is non-isotropic and rotating. We calculate the energy–momentum tensor and angular momentum vector of the system. We compare the time scales associated with the isotropization of the transverse and longitudinal pressures, and the decay of the initial angular momentum. We show that even a fairly large initial angular momentum decays significantly faster than the pressure anisotropy.
The Extended Linguistic Hellwig’s Methods Based on Oriented Fuzzy Numbers and Their Application to the Evaluation of Negotiation Offers
Authors: Roszkowska Ewa , Wachowicz Tomasz , Filipowicz-Chomko Marzena , Łyczkowska-Hanćkowiak Anna
Published: November 2022

This study proposes a novel fuzzy framework for eliciting and organizing the preference information of the negotiator to allow for the evaluation of negotiation offers. The approach is based on verbal evaluation of negotiation options that operates with linguistic variables to handle vague preferences and operationalizes them through oriented trapezoidal fuzzy numbers. Two variants of the linguistic method based on Hellwig’s approach and oriented fuzzy numbers are proposed, which can be applied to building a scoring system for the negotiation template. Then, an example of determining such a scoring system and using it to evaluate the negotiation offers in typical multi-issue negotiation is shown. The results are discussed and compared with other methods known from the literature, in which the preference information is organized similarly but processed differently. The comparison shows that the presented methods can be an alternative to Simple Additive Weighting or TOPSIS methods that may also operate with oriented fuzzy numbers, but some of their characteristics may be problematic from the viewpoint of data interpretation. The former requires defuzzification of the global scores determined, while the latter requires the compulsory use of two reference points derived mechanically out of the negotiation space. By applying modified Hellwig’s approaches, the former and the latter may be easily avoided.
Transformer-Based Model with Dynamic Attention Pyramid Head for Semantic Segmentation of VHR Remote Sensing Imagery
Authors: Xu Yufen , Zhou Shangbo , Huang Yuhui
Published: November 2022

Convolutional neural networks have long dominated semantic segmentation of very-high-resolution (VHR) remote sensing (RS) images. However, restricted by the fixed receptive field of convolution operation, convolution-based models cannot directly obtain contextual information. Meanwhile, Swin Transformer possesses great potential in modeling long-range dependencies. Nevertheless, Swin Transformer breaks images into patches that are single-dimension sequences without considering the position loss problem inside patches. Therefore, Inspired by Swin Transformer and Unet, we propose SUD-Net (Swin transformer-based Unet-like with Dynamic attention pyramid head Network), a new U-shaped architecture composed of Swin Transformer blocks and convolution layers simultaneously through a dual encoder and an upsampling decoder with a Dynamic Attention Pyramid Head (DAPH) attached to the backbone. First, we propose a dual encoder structure combining Swin Transformer blocks and reslayers in reverse order to complement global semantics with detailed representations. Second, aiming at the spatial loss problem inside each patch, we design a Multi-Path Fusion Model (MPFM) with specially devised Patch Attention (PA) to encode position information of patches and adaptively fuse features of different scales through attention mechanisms. Third, a Dynamic Attention Pyramid Head is constructed with deformable convolution to dynamically aggregate effective and important semantic information. SUD-Net achieves exceptional results on ISPRS Potsdam and Vaihingen datasets with 92.51%mF1, 86.4%mIoU, 92.98%OA, 89.49%mF1, 81.26%mIoU, and 90.95%OA, respectively.
Comparative Analysis of Socioeconomic Models in COVID-19 Pandemic
Authors: Vasin Sergey Mikhailovich
Published: November 2022

Certain features of socioeconomic models can be distinctly determined in different countries and regions. However, such models are quite flexible under external and internal influences. Their changes can be observed under the impact of unpredictable factors, the COVID-19 pandemic being one. The aim of the work is to identify differences in the structure of socioeconomic models under the influence of the pandemic. The object of the study is the socioeconomic models of various states. The subject of the study is the transformation of socioeconomic models at different stages of the pandemic. Research methods include analysis of statistical data, correlation and comparative analysis, and graphical methods of presenting results. A comparison of data from the most well-known socioeconomic models was carried out for the first time. It is determined that the countries of the Chinese model adopted restrictive measures of high Stringency Index. The countries of the Japanese model used unique crowd management methods, and the countries of the Scandinavian, German and Anglo-Saxon models resorted to unprecedented monetary injections into the social and economic spheres. It was revealed that quarantine measures eventually cost countries less than monetary injections. It was shown that a decrease in the Pandemic Uncertainty Index stabilized the economic behavior of the population and businesses and increased the volume of export-import operations. It was found that the pandemic affected the economy indirectly through the level of uncertainty and rigidity of preventive measures. It is assumed that the intensity and severity of measures could be influenced by global trends leading to certain types of preventive measures rather than by the COVID-19 statistics of a particular country.
Modelling and Analysis of Adaptive Cruise Control System Based on Synchronization Theory of Petri Nets
Authors: Guo Qi , Yu Wangyang , Hao Fei , Zhou Yuke , Liu Yuan
Published: November 2022

The ACC (adaptive cruise control) system has developed rapidly in recent years, and its reliability and safety have also attracted a lot of attention. The ACC system can realize automatic driving following the vehicle in the longitudinal range, and its reliability is closely related to the synchronization between two vehicles. Combined with formal modelling methods, this paper analyzes and detects the logical flaw that is poor synchronization in the following process of the ACC system from the perspective of synchronization. Aiming at avoiding this kind of logical flaw, this paper presents a novel optimized modelling solution based on the synchronization theory of Petri nets and further improves the calculation method of the synchronic distance. The simulation results reduce the token accumulation by an average of 91.357%, which demonstrates that the improved model can effectively improve reliability and reduce the risk of rear-end collision.
Intelligent Fault Detection in Hall-Effect Rotary Encoders for Industry 4.0 Applications
Authors: Agarwal Ritik , Bhatti Ghanishtha , Singh R. Raja , Indragandhi V. , Suresh Vishnu , Jasinska Laura , Leonowicz Zbigniew
Published: November 2022

Sensors are the foundational components of any smart machine system and are invaluable in all modern technologies. Consequently, faults and errors in sensors can have a significant negative impact on the setup. Intelligent, lightweight, and accurate fault diagnosis and mitigation lie at the crux of modern industries. This study aimed to conceptualize a germane solution in the domain of fault detection, focusing on Hall-effect rotary encoders. Position monitoring through rotary encoders is essential to the safety and seamless functioning of industrial equipment such as lifts and hoists, and commercial systems such as automobiles. This work used multi-strategy learners to accurately diagnose quadrature and offset faults in Hall-effect rotary encoders. The obtained dataset was then run through a lightweight ensemble classifier to train a robust fault detection model. The complete mechanism was simulated through interconnected models simulated in a MATLAB Simulink™ environment. In real time, the developed fault detection algorithm was embedded in an FPGA controller and tested with a 1 kW PMSM drive system. The resulting system is computationally inexpensive and achieves an accuracy of 95.8%, making it a feasible solution for industrial implementation.
Cost-Effective and Energy-Aware Resource Allocation in Cloud Data Centers
Authors: Sabyasachi Abadhan Saumya , Muppala Jogesh K.
Published: November 2022

Cloud computing supports the fast expansion of data and computer centers; therefore, energy and load balancing are vital concerns. The growing popularity of cloud computing has raised power usage and network costs. Frequent calls for computational resources may cause system instability; further, load balancing in the host requires migrating virtual machines (VM) from overloaded to underloaded hosts, which affects energy usage. The proposed cost-efficient whale optimization algorithm for virtual machine (CEWOAVM) technique helps to more effectively place migrating virtual machines. CEWOAVM optimizes system resources such as CPU, storage, and memory. This study proposes energy-aware virtual machine migration with the use of the WOA algorithm for dynamic, cost-effective cloud data centers in order to solve this problem. The experimental results showed that the proposed algorithm saved 18.6%, 27.08%, and 36.3% energy when compared with the PSOCM, RAPSO-VMP, and DTH-MF algorithms, respectively. It also showed 12.68%, 18.7%, and 27.9% improvements for the number of virtual machine migrations and 14.4%, 17.8%, and 23.8% reduction in SLA violation, respectively.
A Novel Mutation Analysis-Based Approach for Testing Parallel Behavioural Scenarios in Multi-Agent Systems
Authors: Dehimi Nour El Houda , Benkhalef Abdelhamid Haithem , Tolba Zakaria
Published: November 2022

In this work, we propose a new test case generation approach that can cover behavioural scenarios individually in a multi-agent system. The purpose is to identify, in the case of the detection of an error, the scenario that caused the detected error, among the scenarios running in parallel. For this, the approach used, in the first stage, the technique of mutation analysis and parallel genetic algorithms to identify the situations in which the agents perform the interactions, presented in the sequence diagram, of the scenario under test only; these situations will be considered as inputs of the test case. In the second stage, the approach used the activities presented in the activity diagram to identify the outputs of the test case expected for its inputs. Subsequently, the generated test cases will be used for the detection of possible errors. The proposed approach is supported by a formal framework in order to automate its phases, and it is applied to a concrete case study to illustrate and demonstrate its usefulness.
A Critical Review on Charging Technologies of Electric Vehicles
Authors: Shahjalal Mohammad , Shams Tamanna , Tasnim Moshammed Nishat , Ahmed Md Rishad , Ahsan Mominul , Haider Julfikar
Published: November 2022

The enormous number of automobiles across the world has caused a significant increase in emissions of greenhouse gases, which pose a grave and mounting threat to modern life by escalating global warming and polluting air quality. These adverse effects of climate change have motivated the automotive sector to reform and have pushed the drive towards the transformation to fully electric. Charging time has been identified as one of the key barriers in large-scale applications of Electric Vehicles (EVs). In addition, various challenges are associated with the formulation of a safe charging scheme, which is concerned with appropriate charging converter architecture, with the aim of ensuring a safe charging protocol within a range of 5–10 min. This paper provides a systematic review of thharging technologies and their impacts on battery systems, including charger converter design and associated limitations. Furthermore, the knowledge gap and research directions are provided with regard to the challenges associated with the charger converter architecture design at the systems level.
Development of PMU-Based Transient Stability Detection Methods Using CNN-LSTM Considering Time Series Data Measurement
Authors: Azhar Izzuddin Fathin , Putranto Lesnanto Multa , Irnawan Roni
Published: November 2022

The development of electric power systems has become more complex. Consequently, electric power systems are operating closer to their limits and are more susceptible to instability when a disturbance occurs. Transient stability problems are especially prevalent. In addition, the identification of transient stability is difficult to achieve in real time using the current measurement data. This research focuses on developing a convolutional neural network—long short-term memory (CNN-LSTM) model using historical data events to detect transient stability considering time-series measurement data. The model was developed by considering noise, delay, and loss in measurement data, line outage and variable renewable energy (VRE) integration scenarios. The model requires PMU measurements to provide high sampling rate time-series information. In addition, the effects of different numbers of PMUs were also simulated. The CNN-LSTM method was trained using a synthetic dataset produced using the DigSILENT PowerFactory simulation to represent the PMU measurement data. The IEEE 39 bus test system was used to simulate the model under different loading conditions. On the basis of the research results, the proposed CNN-LSTM model is able to detect stable and unstable conditions of transient stability only from the magnitude and angle of the bus voltage, without considering system parameter information on the network. The accuracy of transient stability detection reached above 99% in all scenarios. The CNN-LSTM method also required less computation time compared to CNN and conventional LSTM with the average computation times of 190.4, 4001.8 and 229.8 s, respectively.
Balanced-Scorecard-Based Evaluation of Knowledge-Oriented Competencies of Distributed Energy Investments
Authors: Carayannis Elias , Kostis Pantelis , Dinçer Hasan , Yüksel Serhat
Published: November 2022

Since the global warming problem threatens the whole world, it is understood that countries should develop energy policies that will increase their sustainable and clean energy investments. Compared to other alternatives, the high cost of renewable energy projects is an essential obstacle in this process. Therefore, priority should be given to developing distributed energy projects to minimize this problem. The scope of the present paper is to identify the most critical items that affect the performance of distributed energy projects to have knowledge-oriented competencies. In this way, companies can focus on more critical items to provide efficiency for distributed energy projects. As a result, clean energy usage is improved, and the global warming problem is handled more successfully. A novel decision-making model is generated to examine the competencies of the knowledge economy based on collaborative filtering and bipolar q-rung orthopair fuzzy sets (q-ROFSs) with the golden ratio. The analysis concludes that learning and growth are the most critical balanced scorecard perspectives. Moreover, it was also determined that information and communication technology is the most critical competency of the knowledge economy. Therefore, it would be appropriate for investors who plan to invest in distributed energy projects to form a research and development team. Hence, new technologies will be followed instantly. In this way, companies will be able to gain a cost advantage. In this context, improving distributed energy projects is important to increase efficiency in clean energy investments.
Green Hydrogen Production Technologies from Ammonia Cracking
Authors: Yousefi Rizi Hossein , Shin Donghoon
Published: November 2022

The rising technology of green hydrogen supply systems is expected to be on the horizon. Hydrogen is a clean and renewable energy source with the highest energy content by weight among the fuels and contains about six times more energy than ammonia. Meanwhile, ammonia is the most popular substance as a green hydrogen carrier because it does not carry carbon, and the total hydrogen content of ammonia is higher than other fuels and is thus suitable to convert to hydrogen. There are several pathways for hydrogen production. The considered aspects herein include hydrogen production technologies, pathways based on the raw material and energy sources, and different scales. Hydrogen can be produced from ammonia through several technologies, such as electrochemical, photocatalytic and thermochemical processes, that can be used at production plants and fueling stations, taking into consideration the conversion efficiency, reactors, catalysts and their related economics. The commercial process is conducted by using expensive Ru catalysts in the ammonia converting process but is considered to be replaced by other materials such as Ni, Co, La, and other perovskite catalysts, which have high commercial potential with equivalent activity for extracting hydrogen from ammonia. For successful engraftment of ammonia to hydrogen technology into industry, integration with green technologies and economic methods, as well as safety aspects, should be carried out.
Statistical Safety Factor in Lightning Performance Analysis of Overhead Distribution Lines
Authors: Sarajcev Petar , Lovric Dino , Garma Tonko
Published: November 2022

This paper introduces a novel machine learning (ML) model for the lightning performance analysis of overhead distribution lines (OHLs), which facilitates a data-centrist and statistical view of the problem. The ML model is a bagging ensemble of support vector machines (SVMs), which introduces two significant features. Firstly, support vectors from the SVMs serve as a scaffolding, and at the same time give rise to the so-called curve of limiting parameters for the line. Secondly, the model itself serves as a foundation for the introduction of the statistical safety factor to the lightning performance analysis of OHLs. Both these aspects bolster an end-to-end statistical approach to the OHL insulation coordination and lightning flashover analysis. Furthermore, the ML paradigm brings the added benefit of learning from a large corpus of data amassed by the lightning location networks and fostering, in the process, a “big data” approach to this important engineering problem. Finally, a relationship between safety factor and risk is elucidated. THe benefits of the proposed approach are demonstrated on a typical medium-voltage OHL.
Experimental Study on the Effect of Inclination Angle on the Heat Transfer Characteristics of Pulsating Heat Pipe under Variable Heat Flux
Authors: Zhang Dong , Li Haixia , Wu Jianghao , Li Qingliang , Xu Baorui , An Zhoujian
Published: November 2022

This paper aims to deeply explore the influence of different inclination conditions on the heat transfer characteristics and broaden the application scene of a pulsating heat pipe. A test device for the heat transfer performance of a pulsating heat pipe under different inclination angles is designed and built. Under the condition of 70% liquid filling rate, ethanol and HFE-7100 are selected to carry out the experimental test with heating power of 40–140 W and dimensionless thermal difference of 0–0.56. The heat transfer performance, the temperature in the evaporation section and the internal pressure fluctuation of the pulsating heat pipe were experimentally studied. The results show that under the condition of uniform heat flux, for ethanol working medium, when the pulsating heat pipe is heated at 40 W, the operating thermal resistance varies significantly with different installation angles. At this time, the operating thermal resistance of a pulsating heat pipe with installation angles of 45°, 70°, 90° and D90° is 1.38 °C/W, 1.60 °C/W, 1.73 °C/W and 2.07 °C/W, respectively. With the increase in installation angle, the operating thermal resistance also increases gradually, reaching the maximum at 90°. At low heating power, the effect of the installation angle on the ethanol working medium is significantly greater than that of HFE-7100 working medium. The HFE-7100 working medium showed lower operating thermal resistance at low heating power, but with the increase in heating power, the operating thermal resistance of the two working medium gradually approached a 70% filling rate. Under non-uniform heating conditions, when HFE-7100 is used as a working fluid, the operating thermal resistance of a pulsating heat pipe under different heating power was lower than that of the ethanol working medium. The operating thermal resistance is less affected by the installation angle, and the overall heat transfer performance is better. The phenomenon in which the ethanol working medium is obviously affected by the installation angle can be improved by non-uniform heating conditions. For ethanol working medium, when the dimensionless heat difference reaches 0.33 under the condition of a 45° installation angle, the average temperature fluctuation in the evaporation section appears gentle. At this installation angle, the internal working medium of the four elbow pulsating heat pipe devices used in this research more easily forms a cycle in the pipe than the 90° installation angle.
Optimal Design of Asymmetric Rotor Pole for Interior Permanent Magnet Synchronous Motor Using Topology Optimization
Authors: Wu Huihuan , Niu Shuangxia , Fu Weinong
Published: November 2022

As asymmetric interior permanent magnet synchronous motor (AIPMSM) has excellent performance but complicated topological structure, a novel high-resolution encoding and edge smoothing method is proposed for topology optimization of the asymmetric rotor of interior permanent magnet synchronous motor (IPMSM) in this study. This method aims to solve complex electromagnetic design problems with time-dependent performance through a multi-objective genetic algorithm (MOGA) integrated with a high-resolution encoding and edge smoothing method. The complex structure is represented by a high-resolution image-like matrix and then vectorized by the edge smoothing method. Therefore, the commonly used discrete binary encoded variables related to the finite element (FE) model are replaced with a vectorized topological structure and other control variables. In this sense, high-resolution matrix and edge smoothing methods are used for the first time to represent the rotor topology of AIPMSMs. Compared with the traditional topology optimization method, the proposed method has the advantage of expressing more complex and vectorized topological structures; meanwhile, the obtained performance is accurate and trustworthy using conventional FE simulation. Numerical results show that a stable convergence is achieved with the avoidance of checkerboards and material overlapping. It is shown that the proposed method can find solutions with better performances, in comparison with the reference model.
Study on the Influence and Control of Stress Direction Deflection and Partial-Stress Boosting of Main Roadways Surrounding Rock and under the Influence of Multi-Seam Mining
Authors: Chen Dongdong , Guo Fangfang , Li Zijian , Ma Xiang , Xie Shengrong , Wu Yiyi , Wang Zhiqiang
Published: November 2022

A large coal pillar (usually more than 90 m) is generally left in place to ensure the stability of main roadway groups, due to its long service lifespan, which commonly also causes a significant loss of coal resources. The design of the width of the protective coal pillar and the control system of the surrounding rock are directly determined by the characteristics of the stress field and the damage mechanism under the influence of the mining activities. However, there are few studies on the effects of the partial-stress boosting and the direction deflection of the stress field on the failure evolution of the surrounding rock (especially in multi-seam mining). In this paper, theoretical analysis and numerical simulation are used to investigate the direction evolution of the maximum principal stress in front of the working face with malposition distances between the upper and lower working faces during the influence of double coal seams mining. Furthermore, a large-scale numerical model is used to study the deviatoric stress evolution of the surrounding rock and the propagation process of the plastic zone in the main roadway group with different widths of protective coal pillars. Then, an asymmetric cooperative anchoring classification method is proposed to strengthen the roadway support, depending on the critical area of the deviatoric stress in the roadway surrounding rock. The peak zone deflection of the deviatoric stress determines the evolution direction of the plastic area, and the peak value of the deviatoric stress presents a typical asymmetric stress boosting on both sides of the roadway. These findings are validated by the on-site ground pressure monitoring results and the practical failure modes of the surrounding rock.
Numerical Study on Transverse Jet Mixing Enhanced by High Frequency Energy Deposition
Authors: Cai Zilin , Gao Feng , Wang Hongyu , Ma Cenrui , Yang Thomas
Published: November 2022

Supersonic incoming flow has a large momentum, which makes it difficult for transverse jets to have a large penetration depth due to the strong compression of the incoming flow. This impacts the mixing efficiency of the jet in the supersonic combustor. This paper proposes a method to improve the mixing efficiency of a rectangular flow field model using pulsed energy deposition, which is verified numerically. In the simulations, the Navier–Stokes equations with an energy source are solved to simulate the effects of energy deposition with various distributions on the fuel mixture. The results show that the energy deposition increases the turbulent kinetic energy, which enlarges the scale of the flow vortex and improves the fuel mixing performance. The energy deposition is distributed upstream and significantly improves the mixing performance. Energy deposition can improve the penetration depth of fuel, which is more significant when the energy deposition is distributed downstream of the jet orifice. The energy deposition also slightly reduces the total pressure recovery coefficient. In general, an energy deposition that is distributed upstream of the jet has the best effect on the mixing efficiency.
Compact Thermal Storage with Phase Change Material for Low-Temperature Waste Heat Recovery—Advances and Perspectives
Authors: Dzhonova-Atanasova Daniela , Georgiev Aleksandar , Nakov Svetoslav , Panyovska Stela , Petrova Tatyana , Maiti Subarna
Published: November 2022

The current interest in thermal energy storage is connected with increasing the efficiency of conventional fuel-dependent systems by storing the waste heat in low consumption periods, as well as with harvesting renewable energy sources with intermittent character. Many of the studies are directed towards compact solutions requiring less space than the commonly used hot water tanks. This is especially important for small capacity thermal systems in buildings, in family houses or small communities. There are many examples of thermal energy storage (TES) in the literature using the latent heat of phase change, but only a few are commercially available. There are no distinct generally accepted requirements for such TES systems. The present work fills that gap on the basis of the state of the art in the field. It reviews the most prospective designs among the available compact latent heat storage (LHS) systems in residential applications for hot water, heating and cooling and the methods for their investigation and optimization. It indicates the important characteristics of the most cost- and energy-efficient compact design of an LHS for waste heat utilization. The proper design provides the chosen targets at a reasonable cost, with a high heat transfer rate and effective insulation. It allows connection to multiple heat sources, coupling with a heat pump and integration into existing technologies and expected future scenarios for residential heating and cooling. Compact shell-tube type is distinguished for its advantages and commercial application.
Experimental Study and Optimisation of a Non-Conventional Ignition System for Reciprocating Engines Operation with Hydrogen–Methane Blends, Syngas, and Biogas
Authors: De Simio Luigi , Iannaccone Sabato , Masi Massimo , Gobbato Paolo
Published: November 2022

The paper deals with the experimental study of a medium-load spark ignition engine under operation with different fuel mixtures among those deemed as promising for the transition towards carbon-free energy systems. In particular, the performance of a non-conventional ignition system, which permits the variation of the ignition energy, the spark intensity and duration, was studied fuelling the engine with 60–40% hydrogen–methane blends, three real syngas mixtures and one biogas. The paper is aimed to find the optimal ignition timing for minimum specific fuel consumption and the best setup of the ignition system for each of the fuel mixtures considered. To this end, a series of steady-state tests were performed at the dynamometer by varying the parameters of the ignition system and running the engine with surrogate hydrogen–methane–nitrogen mixtures that permit the simulation of hydrogen–methane blends, real syngas, and biogas. The results quantify the increase of spark advance associated with the decrease of the fuel quality and discuss the risk of knock onset during methane–hydrogen operation. It was demonstrated that the change of the ignition system parameters does not affect the value of optimum spark advance and, except for the ignition duration, all the parameters’ values are generally not very relevant at full load operation. In contrast, at partial load operation with low-quality syngas or high exhaust gas recirculation rate, it was found that an increase of the maximum ignition energy (to 300 mJ) allows for operation down to approximately 66% of the maximum load before combustion becomes incomplete. Further reductions, down to 25% of the maximum load, can be achieved by increasing the gap between the spark plug electrodes (from 0.25 to 0.5 mm).
Price-Guided Peer-To-Peer Trading Scheme and Its Effects on Transaction Costs and Network Losses
Authors: Kim SungJoong , Yoon YongTae , Jin YoungGyu
Published: November 2022

Distributed energy resources (DERs), such as small-scale renewable energy generators, storage systems, and controllable loads, have been attracting great attention. Accordingly, interest in peer-to-peer (P2P) energy trading between prosumers with DERs is growing. The prosumers may perform the P2P electricity trading within the loss-guided framework, where network losses are primarily considered during the peer matching process. However, the loss-guided framework has limitations in that prosumer welfare is neglected in favor of prioritizing the network losses caused by the P2P transactions. Thus, in this study, a price-based framework for P2P electricity trading is suggested, where the prosumer welfare is considered by including not only network loss costs but also energy costs in the matching procedure. The effects of the suggested price-based framework on network efficiency, prosumer welfare, and social welfare are examined by comparing simulation results with the loss-guided framework and the random transactions. Further, how those three properties are affected by the change in loss price is analyzed and a guideline for the suitable choice of the loss price is suggested.
A Numerical Investigation of the Energy Efficiency Enhancement of Oscillating Water Column Wave Energy Converter Systems
Authors: Ramezanzadeh Shayan , Ozbulut Murat , Yildiz Mehmet
Published: November 2022

This work focuses on the geometry effects over the performance of oscillating water column (OWC)-type wave energy converter (WEC) systems and searches for the OWC geometries that enhance the energy efficiencies under the same wave conditions. To analyze the hydrodynamic performances of the WEC systems, an in-house smoothed particle hydrodynamics (SPH) code based on weakly compressible fluid approach is utilized. The energy efficiency enhancement studies of the determined OWC device are carried out with a two-step geometry modification procedure. The first step starts with the validation of the free-surface elevation and orbital velocity time histories. Then, a three-by-three simulation matrix that depends on the geometrical design parameters of chamber length and front wall draft is run at three different wave conditions, and the OWC geometry that produces the maximum energy efficiency is determined. In the second step, the corner regions of the obtained optimal geometry are chamfered, and another simulation matrix is tested at the wave condition that yields maximum wave energy. It is observed in this step that the energy efficiency index can still be improved by 4.3% by only chamfering the back face of the OWC chamber. To scrutinize the physical grounds of this increase, the correlation between the time-averaged vorticity and energy efficiency is presented. Finally, the performance of the best configuration is also examined in three different wave periods, where the suggested geometry shows better performance with respect to base geometry results in all wave conditions.
Steam Gasification of Refuse-Derived Fuel with CaO Modification for Hydrogen-Rich Syngas Production
Authors: Ren Ranwei , Wang Haiming , You Changfu
Published: November 2022

Steam gasification of refuse-derived fuel (RDF) for hydrogen-rich syngas production was investigated in a lab-scale gasification system with CaO modification. A simulation model based on Aspen Plus was built to study the characteristics and the performance of the RDF gasification system. The influences of gasification temperature, steam to RDF ratio (S/R), and CaO adsorption temperature on the gas composition, heating value, and gas yield were evaluated. Under the gasification temperature of 960 °C and S/R of 1, H2 frication in the syngas increased from 47 to 67% after CaO modification at 650 °C. Higher syngas and H2 yield were obtained by increasing both S/R and gasification temperature. However, as the CaO adsorption temperature increased, a lower H2 fraction was obtained due to the limitation of the CaO adsorption capacity at high temperatures. The highest H2 fraction (69%), gas yield (1.372 m3/kg-RDF), and H2 yield (0.935 m3/kg-RDF) were achieved at gasification temperature of 960 °C, S/R of 2, and CaO modification temperature of 650 °C. The variation trends of simulation results can match well with the experiment. The deviation was mainly because of the limitation of contact time between the gasification agent and RDF, uneven temperature distribution of the reactors, and the formation of tar during the experiment.
Human Capital as a Source of Energy for Rural Areas’ Socio-Economic Development—Empirical Evidence for Rural Areas in Poland
Authors: Klonowska-Matynia Maria
Published: November 2022

This article deals with the issue of human capital as a factor responsible for the emergence of development inequalities in rural areas. Its main goal is to analyze and evaluate the existing differences in the distribution of human capital resources in rural areas in Poland in relation to their socio-economic situation. The essence of human capital is expressed through the analogy of energy and capital in relation to the concept of homo energeticus. The essence of human capital is also expressed in terms of two components of its structure, i.e., health and the labor market. The level of human capital was expressed using two synthetic measures, i.e., the human capital ratio in the field of health (HCH) and the labor market (HCLM). The obtained research results indicate the existing differences in the spatial distribution of human capital, resulting in a polarization effect in the center-periphery system, and showing relations with the socio-economic structure of rural areas, their agricultural function, and the ongoing population processes. The assumption about the existing relations between the individual components of the structure of human capital, i.e., health and the labor market, with the socio-economic situation of individual communes should be considered correct. The obtained results of the empirical analysis constitute an important contribution to the description of the mechanism explaining the causes of the existing disproportions in the level of rural development; they allow for a more optimal planning of the instruments supporting their development at the local level. The empirical analysis was carried out in spatial terms with regard to rural areas in Poland defined in accordance with the administrative criterion of the Central Statistical Office at the lowest local (rural) level of data aggregation. The analysis covers rural and urban-rural communes in Poland, i.e., 2172 spatial units. The source of data for the synthetic measures (HCH and HCLM) was Local Data Bank Statistics Poland (LDB SP), and that for the indicator of the level of socio-economic development for rural areas (S-EDI) was the European Fund for Polish Rural Development (EFRWP).
Sustainable Development of Road Transport in the EU: Multi-Criteria Analysis of Countries’ Achievements
Authors: Siksnelyte-Butkiene Indre , Streimikiene Dalia
Published: November 2022

One quarter of global energy consumption goes towards meeting transport needs. In Europe, the share of energy for transport is much higher and accounts for about a third. Therefore, it is very important to monitor the sustainable development and progress of the sector. This paper seeks to develop a framework for the sustainability assessment of road transport in EU countries and to evaluate the countries’ achievements in the last decade. The research adheres to the provision that the developed framework should be easily applied in future studies. Therefore, significant attention is paid to the selection of indicators and their availability, as well as the selection of the research instrument itself. The multi-criteria decision-making (MCDM) technique TOPSIS has been applied for calculations and countries’ ranking, in order to compare countries’ achievements in the last decade (2010–2020). The last ten years’ analysis allows us to identify the direction of individual countries in developing road transport.
A Composite Variable Structure PI Controller for Sensorless Speed Control Systems of IPMSM
Authors: Feng Weidong , Bai Jing , Zhang Zhiqiang , Zhang Jing
Published: November 2022

In the speed control system of an Interior Permanent Magnet Synchronous Motor (IPMSM) without a speed sensor, PI controllers using only a fixed set of parameters cannot achieve accurate tracking of the estimated speed in a wide speed domain and also suffer from step response overshoot. This paper proposes a Compound Variable Structure PI (CVSPI) controller to improve the system control performance. It can choose whether to include an integral term according to the size of the system deviation to speed up the response. It also introduces a Model Reference Adaptive System (MRAS) speed observer in the controller to estimate the speed and adaptively adjust the size of the anti-integration saturation gain to improve the dynamic response following performance and immunity of the system. A feed-forward link is added for a given input differential to achieve an accurate answer to time-varying inputs. As the linear compensation matrix of the conventional MRAS is a unit matrix, the speed can only be accurately observed in a specific speed range. In this paper, a new linear compensation matrix is designed, and a new speed adaptive law is derived, allowing the improved MRAS to measure speed over a wide range accurately. Simulation results validate the excellent control performance of the CVSPI and the accuracy of the enhanced MRAS over a wide speed range.
A Review of Molten Salt Reactor Multi-Physics Coupling Models and Development Prospects
Authors: Wu Jianhui , Chen Jingen , Cai Xiangzhou , Zou Chunyan , Yu Chenggang , Cui Yong , Zhang Ao , Zhao Hongkai
Published: November 2022

Molten salt reactors (MSRs) are one type of GEN-IV advanced reactors that adopt melt mixtures of heavy metal elements and molten salt as both fuel and coolant. The liquid fuel allows MSRs to perform online refueling, reprocessing, and helium bubbling. The fuel utilization, safety, and economics can be enhanced, while some new physical mechanisms and phenomena emerge simultaneously, which would significantly complicate the numerical simulation of MSRs. The dual roles of molten fuel salt in the core lead to a tighter coupling of physical mechanisms since the released fission energy will be absorbed immediately by the molten salt itself and then transferred to the primary heat exchanger. The modeling of multi-physics coupling is regarded as one important aspect of MSR study, attracting growing attention worldwide. Up to now, great efforts have been made in the development of MSR multi-physics coupling models over the past 60 years, especially after 2000, when MSR was selected for one of the GEN-IV advanced reactors. In this paper, the development status of the MSR multi-physics coupling model is extensively reviewed in the light of coupling models of N-TH (neutronics and thermal hydraulics), N-TH-BN (neutronics, thermal hydraulics, and burnup) and N-TH-BN-G (neutronics, thermal hydraulics, burnup, and graphite deformation). The problems, challenges, and development trends are outlined to provide a basis for the future development of MSR multi-physics coupling models.
Co-Torrefaction Progress of Biomass Residue/Waste Obtained for High-Value Bio-Solid Products
Authors: Waheed Abdul , Naqvi Salman , Ali Imtiaz
Published: November 2022

The co-torrefaction of several biomasses may be a viable solution in the study area, as it produces biofuels and addresses waste-treatment concerns. This review evaluates biomass through ultimate, proximate, and FTIR analyses, and the mechanism of the co-torrefaction process is observed for product quality with a synergistic effect. Furthermore, the parameters of co-torrefaction, including temperature, reaction time, mass yield, energy yield, and the composition of the H/C and O/C ratio of the co-torrefied materials, are similar to those for coal composition. Different reactor types, such as fixed-bed, fluidized-bed, microwave, and batch reactors, are used for co-torrefaction, in which biomass blends with optimized blend ratios. The co-torrefaction process increases the bio-solid yield and heating value, the capacity to adsorb carbon dioxide, and the renewable fuel used for gasification. One of the objectives of this study is to adopt a process that must be viable, green, and sustainable without generating pollution. For this reason, microwave co-torrefaction (MCT) has been used in many recent studies to transform waste and biomass materials into an alternative fuel using a microwave reactor.