bluuebunny/crossref_metadata_2025 huggingface dataset:
Energy, Waves, and Forces in Bilateral Fracture of the Femoral Necks: Two Case Presentations and Updated Critical Review
Authors: Baciu Cosmin Constantin
Published: October 2022

Two case reports and an updated critical review on bilateral fractures of the femoral neck are presented. Bilateral fractures of the femoral neck have been investigated for at least 80 years and are treated as rare cases. The primary cause is usually considered an external shock; however, aside from high energy shocks (e.g., falling and impact with hard, rigid surfaces, traffic accidents, etc.) the underlying causes of femoral neck frailty have not yet been fully understood. Although not exhaustive, the review spans cases reported as early as 1944 and compares their conclusions in line with medicine developments at the time of the reports until present. The discussion is perhaps controversial at times; it brings to the fore the energy balance between shock waves and stress waves. The two cases reported here add to the review, one highlighting the biomechanics, and the other supporting more recent findings on metabolic disorders, which ultimately lead to enhanced frailty of the femoral neck. Investigation of the fractures has been performed with X-ray radiographs, MRI, and CT, with a follow up using a Doppler US to check blood flow in the lower zone of the limbs. The second case was investigated both for fractures and metabolic diseases, e.g., type I diabetes and kidney failure (dialysis). In Case 1 the second fracture was not observable at the time of admission, and therefore two surgery operations were performed at seven days interval. Taperloc Complete prostheses (Zimmer Biomet) were applied. Case 2 suffered a second fracture in the right hip in the segment above the knee and required better fixation with cables. Despite this, she returned one month later with a new crack in the femur. Case 1 is a typical case of wear consequences on the biomechanics of the hill pad-tibia-femur-femoral neck system, where tension of the neck occurred due to a stress wave rather than a shock wave. This can be proven by the absence of a second fracture from the images first acquired, the only evidence being pain and walking difficulty. Case 2 shows that metabolic diseases can dramatically enhance the frequency of bilateral femoral neck fractures.
Graphene-Based Sensor for the Detection of Cortisol for Stress Level Monitoring and Diagnostics
Authors: Zubarev Alexei , Cuzminschi Marina , Iordache Ana-Maria , Iordache Stefan-Marian , Rizea Constantin , Grigorescu Cristiana E. A. , Giuglea Carmen
Published: October 2022

In this work, we study the sensing properties of multi-layer graphene combined with pyrrole in order to elaborate low-cost, high-sensitive material for cortisol detection. Graphene nanoplatelets and pyrrole were dispersed in a solution containing 1M HNO3 by using a powerful ultrasound probe for 10 min, then centrifuged for 30 min at 4000 rpm; polymerization was performed by cyclic voltammetry. The graphene–pyrrole composite was tested to ultra-low levels of cortisol in artificial saliva, consistent to the levels excreted in human salivary samples. The composite was further investigated by Raman spectroscopy and we modeled the interaction between the sensitive layer and cortisol using MarvinBeans software. It shows a good sensitivity for salivary values of cortisol cyclic voltammetry being able to detect a level down to 0.5 ng/mL cortisol.
PSMA PET-CT in the Diagnosis and Staging of Prostate Cancer
Authors: Combes Alexander D. , Palma Catalina A. , Calopedos Ross , Wen Lingfeng , Woo Henry , Fulham Michael , Leslie Scott
Published: October 2022

Prostate cancer is the most common cancer and the second leading cause of cancer death in men. The imaging assessment and treatment of prostate cancer has vastly improved over the past decade. The introduction of PSMA PET-CT has improved the detection of loco-regional and metastatic disease. PSMA PET-CT also has a role in the primary diagnosis and staging, in detecting biochemical recurrence after curative treatment and in metastasis-directed therapy. In this paper we review the role of PSMA PET-CT in prostate cancer.
How to Evaluate Theory-Based Hypotheses in Meta-Analysis Using an AIC-Type Criterion
Authors: Kuiper Rebecca M.
Published: October 2022

Meta-analysis techniques allow researchers to aggregate effect sizes—like standardized mean difference(s), correlation(s), or odds ratio(s)—of different studies. This leads to overall effect-size estimates and their confidence intervals. Additionally, researchers can aim for theory development or theory evaluation. That is, researchers may not only be interested in these overall estimates but also in a specific ordering or size of them, which then reflects a theory. Researchers may have expectations regarding the ordering of standardized mean differences or about the (ranges of) sizes of an odds ratio or Hedges’ g. Such theory-based hypotheses most probably contain inequality constraints and can be evaluated with the Akaike’s information criterion type (i.e., AIC-type) confirmatory model selection criterion called generalized order-restricted information criterion (GORICA). This paper introduces and illustrates how the GORICA can be applied to meta-analyzed estimates. Additionally, it compares the use of the GORICA to that of classical null hypothesis testing and the AIC, that is, the use of theory-based hypotheses versus null hypotheses. By using the GORICA, researchers from all types of fields (e.g., psychology, sociology, political science, biomedical science, and medicine) can quantify the support for theory-based hypotheses specified a priori. This leads to increased statistical power, because of (i) the use of theory-based hypotheses (cf. one-sided vs. two-sided testing) and (ii) the use of meta-analyzed results (that are based on multiple studies which increase the combined sample size). The quantification of support and the power increase aid in, for instance, evaluating and developing theories and, therewith, developing evidence-based treatments and policy.
Digital Quantum Simulation and Circuit Learning for the Generation of Coherent States
Authors: Liu Ruilin , V. Romero Sebastián , Oregi Izaskun , Osaba Eneko , Villar-Rodriguez Esther , Ban Yue
Published: October 2022

Coherent states, known as displaced vacuum states, play an important role in quantum information processing, quantum machine learning, and quantum optics. In this article, two ways to digitally prepare coherent states in quantum circuits are introduced. First, we construct the displacement operator by decomposing it into Pauli matrices via ladder operators, i.e., creation and annihilation operators. The high fidelity of the digitally generated coherent states is verified compared with the Poissonian distribution in Fock space. Secondly, by using Variational Quantum Algorithms, we choose different ansatzes to generate coherent states. The quantum resources—such as numbers of quantum gates, layers and iterations—are analyzed for quantum circuit learning. The simulation results show that quantum circuit learning can provide high fidelity on learning coherent states by choosing appropriate ansatzes.
Efficient Power Characteristic Analysis and Multi-Objective Optimization for an Irreversible Simple Closed Gas Turbine Cycle
Authors: Qiu Xingfu , Chen Lingen , Ge Yanlin , Shi Shuangshuang
Published: October 2022

On the basis of the established irreversible simple closed gas turbine cycle model, this paper optimizes cycle performance further by applying the theory of finite-time thermodynamics. Dimensionless efficient power expression of the cycle is derived. Effects of internal irreversibility (turbine and compressor efficiencies) and heat reservoir temperature ratio on dimensionless efficient power are analyzed. When total heat conductance of two heat exchangers is constant, the double maximum dimensionless efficient power of a cycle can be obtained by optimizing heat-conductance distribution and cycle pressure-ratio. Through the NSGA-II algorithm, multi-objective optimizations are performed on the irreversible closed gas turbine cycle by taking five performance indicators, dimensionless power density, dimensionless ecological function, thermal efficiency, dimensionless efficient power and dimensionless power output, as objective functions, and taking pressure ratio and heat conductance distribution as optimization variables. The Pareto frontiers with the optimal solution set are obtained. The results reflect that heat reservoir temperature ratio and compressor efficiency have greatest influences on dimensionless efficient power, and the deviation indexes obtained by TOPSIS, LINMAP and Shannon Entropy decision-making methods are 0.2921, 0.2921, 0.2284, respectively, for five-objective optimization. The deviation index obtained by Shannon Entropy decision-making method is smaller than other decision-making methods and its result is more ideal.
Quantum Information Scrambling in Non-Markovian Open Quantum System
Authors: Han Li-Ping , Zou Jian , Li Hai , Shao Bin
Published: October 2022

In this paper, we investigate the dynamics of a spin chain whose two end spins interact with two independent non-Markovian baths by using the non-Markovian quantum state diffusion (QSD) equation approach. Specifically, two issues about information scrambling in an open quantum system are addressed. The first issue is that tripartite mutual information (TMI) can quantify information scrambling properly via its negative value in a closed system, whether it is still suitable to indicate information scrambling in an open quantum system. We find that negative TMI is not a suitable quantifier of information scrambling in an open quantum system in some cases, while negative tripartite logarithmic negativity (TLN) is an appropriate one. The second one is that up to now almost all information scrambling in open quantum systems reported were focus on a Markovian environment, while the effect of a non-Markovian environment on information scrambling is still elusive. Our results show that the memory effect of an environment will be beneficial to information scrambling. Moreover, it is found that the environment is generally detrimental for information scrambling in the long-term, while in some cases it will be helpful for information scrambling in the short-term.
A Comprehensive Experimental Investigation of Additives to Enhance Pool Boiling Heat Transfer of a Non-Azeotropic Mixture
Authors: Xu Chen , Qian Zuoqin , Ren Jie
Published: October 2022

Adding nanoparticles or surfactants to pure working fluid is a common and effective method to improve the heat transfer performance of pool boiling. The objective of this research is to determine whether additives have the same efficient impact on heat transfer enhancement of the non-azeotropic mixture. In this paper, Ethylene Glycol/Deionized Water (EG/DW) was selected as the representing non-azeotropic mixture, and a comparative experiment was carried out between it and the pure working fluid. In addition, the effects of different concentrations of additives on the pool boiling heat transfer performance under different heat fluxes were experimentally studied, including TiO2 nanoparticles with different particle diameters, different kinds of surfactants, and mixtures of nanofluids and surfactants. The experimental results showed that the nanoparticles deteriorated the heat transfer of the EG/DW solution, while the surfactant enhanced the heat transfer of the solution when the concentration closed to a critical mass fraction (CMC). However, the improvement effect was unsteady with the increase in the heat flux density. The experimental results suggest that the mass transfer resistance of the non-azeotropic mixture is the most important factor in affecting heat transfer enhancement. Solutions with 20 nm TiO2 obtained a steady optimum heat transfer improvement by adding surfactants.
Non-Separability of Physical Systems as a Foundation of Consciousness
Authors: Arkhipov Anton
Published: October 2022

A hypothesis is presented that non-separability of degrees of freedom is the fundamental property underlying consciousness in physical systems. The amount of consciousness in a system is determined by the extent of non-separability and the number of degrees of freedom involved. Non-interacting and feedforward systems have zero consciousness, whereas most systems of interacting particles appear to have low non-separability and consciousness. By contrast, brain circuits exhibit high complexity and weak but tightly coordinated interactions, which appear to support high non-separability and therefore high amount of consciousness. The hypothesis applies to both classical and quantum cases, and we highlight the formalism employing the Wigner function (which in the classical limit becomes the Liouville density function) as a potentially fruitful framework for characterizing non-separability and, thus, the amount of consciousness in a system. The hypothesis appears to be consistent with both the Integrated Information Theory and the Orchestrated Objective Reduction Theory and may help reconcile the two. It offers a natural explanation for the physical properties underlying the amount of consciousness and points to methods of estimating the amount of non-separability as promising ways of characterizing the amount of consciousness.
Epileptic Seizure Detection Using Geometric Features Extracted from SODP Shape of EEG Signals and AsyLnCPSO-GA
Authors: Wang Ruofan , Wang Haodong , Shi Lianshuan , Han Chunxiao , Che Yanqiu
Published: October 2022

Epilepsy is a neurological disorder that is characterized by transient and unexpected electrical disturbance of the brain. Seizure detection by electroencephalogram (EEG) is associated with the primary interest of the evaluation and auxiliary diagnosis of epileptic patients. The aim of this study is to establish a hybrid model with improved particle swarm optimization (PSO) and a genetic algorithm (GA) to determine the optimal combination of features for epileptic seizure detection. First, the second-order difference plot (SODP) method was applied, and ten geometric features of epileptic EEG signals were derived in each frequency band (δ, θ, α and β), forming a high-dimensional feature vector. Secondly, an optimization algorithm, AsyLnCPSO-GA, combining a modified PSO with asynchronous learning factor (AsyLnCPSO) and the genetic algorithm (GA) was proposed for feature selection. Finally, the feature combinations were fed to a naïve Bayesian classifier for epileptic seizure and seizure-free identification. The method proposed in this paper achieved 95.35% classification accuracy with a tenfold cross-validation strategy when the interfrequency bands were crossed, serving as an effective method for epilepsy detection, which could help clinicians to expeditiously diagnose epilepsy based on SODP analysis and an optimization algorithm for feature selection.
Factors Influencing Students’ Attitudes and Readiness towards Active Online Learning in Physics
Authors: Uden Lorna , Sulaiman Fauziah , Lamun Ronald Francis
Published: October 2022

Many factors can influence students’ attitudes and their readiness to learn, especially with respect to learning physics online. Traditional online learning, where the teacher is the sole speaker, is inappropriate for learning physics because there must be live demonstrations and activities connecting theories with real world experiences. Online learning for physics must be active and engaging. Students would find the traditional form of online instruction difficult, because there is no physical social interaction between teacher and students. In our teaching work, we have found that factors such as computer skills/ICT skills, learning preferences, prior knowledge and motivation are important for students’ learning. What are the perceptions and attitudes of learners regarding these factors? The aim of this paper is to investigate the attitudes of students’ responses to computer/ICT skills, learning preferences, prior knowledge, and motivation pre-online learning and post-online learning in a case study. The research used a hierarchical regression for data analysis across a sample of young respondents who studied physics at Labuan Matriculation College, i.e., pre-university, in year one of their enrolment. The study involved two phases. A survey was conducted to assess the attitudes of the students prior to the implementation of active online learning. The pre-survey results showed that students considered learning preference and motivation to be important factors that would influence their active online learning. Post-survey responses and views communicated after completion of the learning revealed that all four factors have positive influence in their learning. Principles from neuroscience were used to explain why these four factors were important. The paper also provides guidelines on how teachers can use principles from neuroscience to help students to improve active online learning based on these four factors.
The Relationship between Teacher Leadership and School Climate: Findings from a Teacher-Leadership Project
Authors: Gningue Serigne Mbaye , Peach Roger , Jarrah Adeeb M. , Wardat Yousef
Published: October 2022

A positive school climate and teacher leadership have both been shown to have beneficial effects on student achievement. This study was part of a wider research effort designed to assess the effects of a teacher-leadership development project. We hypothesized that there was a positive relationship between teacher leadership development and school climate. Seventy project participants from two cohorts responded to a teacher-leadership survey and 891 personnel from 42 schools from which participant teachers were drawn responded to a school climate survey. We found that, generally, there was little relationship between school climate and teacher-leadership development. However, a more fine-grained analysis showed that, for Cohort 2, schools that encourage teacher-to-teacher interactions are likely to see personal growth and development in teacher leaders in their staff. Additional findings suggest that if teacher-to-teacher interactions are encouraged, then teachers will increase their development as teacher leaders. However, as the results are correlational and not causal, it may be that, as teachers engage more in professional development activities, they encourage more positive teacher-to-teacher interactions in their school.
Quantum Chaotic Honey Badger Algorithm for Feature Selection
Authors: Alshathri Samah , Abd Elaziz Mohamed , Yousri  Dalia , Hassan  Osama Farouk , Ibrahim  Rehab Ali
Published: October 2022

Determining the most relevant features is a critical pre-processing step in various fields to enhance prediction. To address this issue, a set of feature selection (FS) techniques have been proposed; however, they still have certain limitations. For example, they may focus on nearby points, which lowers classification accuracy because the chosen features may include noisy features. To take advantage of the benefits of the quantum-based optimization technique and the 2D chaotic Hénon map, we provide a modified version of the honey badger algorithm (HBA) called QCHBA. The ability of such strategies to strike a balance between exploitation and exploration while identifying the workable subset of pertinent features is the basis for employing them to enhance HBA. The effectiveness of QCHBA was evaluated in a series of experiments conducted using eighteen datasets involving comparison with recognized FS techniques. The results indicate high efficiency of the QCHBA among the datasets using various performance criteria.
Feasible Evaluation and Implementation of Shunt Active Filter for Harmonic Mitigation in Induction Heating System
Authors: Raman Rahul , Sadhu Pradip Kumar , Kumar Ritesh , Rangarajan Shriram Srinivasarangan , Subramaniam Umashankar , Collins Edward Randolph , Senjyu Tomonobu
Published: October 2022

This paper proposes a shunt active filter (SAF) for harmonic mitigation and reactive power compensation in an induction heating (IH) system. The high-frequency switching in the resonant inverter of the IH system generates a considerable number of high-frequency harmonics. The latter flow back to the supply side and causes a wide variety of problems. The predominant ones are the deterioration of the power quality, distortion in the grid voltage, and malfunctioning of the protective equipment. These harmonics need to be attenuated as per the IEEE 519-1992 and IEEE 519-2014 standards. To overcome these problems, an SAF based on the modified version of instantaneous power theory was placed between the power supply and the IH equipment. Moreover, the proposed model could work in unbalanced and non-sinusoidal input voltage conditions, as well as dynamic conditions with changing reference currents. The feasibility of the proposed SAF-based IH system was verified by a series of simulation results and a comparative analysis of the THD of the input currents. The power quality issues were successfully addressed, which signifies the ability and effectiveness of the proposed model to mitigate the problems caused by harmonics and enhance the power factors.
Generating Synthetic Images for Healthcare with Novel Deep Pix2Pix GAN
Authors: Aljohani Abeer , Alharbe Nawaf
Published: October 2022

Due to recent developments in deep learning and artificial intelligence, the healthcare industry is currently going through a significant upheaval. Despite a considerable advance in medical imaging and diagnostics, the healthcare industry still has a lot of unresolved problems and unexplored applications. The transmission of a huge number of medical images in particular is a difficult and time-consuming problem. In addition, obtaining new medical images is too expensive. To tackle these issues, we propose deep pix2pix generative adversarial networks (GAN) for generating synthetic medical images. For the comparison, we implemented CycleGAN, Pix2Pix GAN and Deep Pix2Pix GAN. The result has shown that our proposed approach can generate a new synthetic medical image from a different image with more accuracy than that of the other models. To provide a robust model, we trained and evaluated our models on a widely used brain image dataset, the IXI Dataset.
CLSTM-AR-Based Multi-Dimensional Feature Fusion for Multi-Energy Load Forecasting
Authors: Ren Bowen , Huang Cunqiang , Chen Laijun , Mei Shengwei , An Juan , Liu Xingwen , Ma Hengrui
Published: October 2022

Integrated Energy Systems (IES) are an important way to improve the efficiency of energy, promote closer connections between various energy systems, and reduce carbon emissions. The transformation between electricity, heating, and cooling loads into each other makes the dynamic characteristics of multiple loads more complex and brings challenges to the accurate forecasting of multi-energy loads. In order to further improve the accuracy of IES short-term load forecasting, we propose the Convolutional Neural Network, the Long Short-Term Memory Network, and Auto-Regression (CLSTM-AR) combined with the multi-dimensional feature fusion (MFFCLA). In detail, CLSTM can extract the coupling and periodic characteristics implied in IES load data from multiple time dimensions. AR takes load data as the input to extract features of sequential auto-correlation over adjacent time periods. Then, the diverse and effective features extracted by CLSTM, LSTM, and AR can be fused using the multi-dimensional feature fusion technique. Ultimately, the model achieves the accurate prediction of multiple loads. In conclusion, compared with other forecasting models, the case study results show that MFFCLA has higher forecasting precision compared with the comparable model in the short-term multi-energy load forecasting performance of electricity, heating, and cooling. The accuracy of MFFCLA can help to optimize and dispatch IES to make better use of renewable energy.
Environmentally and Socially Sustainable Behaviors of Generation Z in Poland Stimulated by Mobile Applications
Authors: Jaska Ewa , Werenowska Agnieszka , Balińska Agata
Published: October 2022

The aim of this study was to identify environmentally and socially sustainable behaviors and explore the role of mobile applications in encouraging them among young residents of Poland. The study involved a literature review and a survey carried out on a sample of 772 representatives of Generation Z (through the use of CAWI method). The collected material was subjected to quantitative and qualitative analyses involving factor analysis and statistical tests. The analysis of the obtained dataset shows that there is a significant difference between pro-environmental behaviors assigned to the following areas: (I) purchasing activity enhanced by visual identification, (II) sustainable consumption, (III) behavior stimulated by legal regulations and economic factors. The research revealed a statistically significant difference between the sustainable behaviors of men and women, and a slight difference between the behaviors of people from different places of residence and with different levels of income. It was also shown that respondents using the three analyzed mobile applications: Vinted (an online marketplace and community that allows its users to sell, buy, and swap new or secondhand items, mainly clothing and accessories), Veturilo (an app for users of city bike system) and GdzieWyrzucić (an app helping with waste sorting) rated their pro-environmental activities significantly higher in almost all areas covering socially and environmentally sustainable behaviors.
The Recent Development of Power Electronics and AC Machine Drive Systems
Authors: Habibullah Al Faris , Yoon Seung-Jin , Tran Thuy Vi , Kim Yubin , Tran Dat Thanh , Kim Kyeong-Hwa
Published: October 2022

Currently, power electronics and AC machine drive systems are employed in numerous areas, such as in industrial processes, consumer electronics, electric vehicles (EVs), renewable-energy-source (RES)-based distributed generation (DG) systems, and electric power generation systems. As RESs such as wind and solar are attracting relatively more attention due to environmental issues caused by fossil fuel use, various RESs have been integrated into the utility grid (UG) as DG systems. As a result, the concept of a microgrid (MG), which constructs an electrical power system with DGs, energy storage systems (ESSs), and loads, has emerged. Recently, the DG-based MG has been regarded as a promising and flexible technology for those involved in constructing electric power systems. This article presents future technology and recent developments in applied power electronics. In this Special Issue, “The Recent Development of Power Electronics and AC Machine Drive Systems”, four papers were published highlighting recent developments in this field. In addition, other topics beyond the coverage of the published articles are highlighted by a guest editor to address other trends and future topics related to the Special Issue. Through an in-depth investigation of recent development trends, this article seeks to encourage related studies in power electronics.
Interconnecting Power-Electronic Buck Converter Modules in a Novel High-Power Test Bench for MVDC Circuit Breakers
Authors: Langenberg Nils , Kimpeler Simon , Moser Albert
Published: October 2022

Advances in medium voltage direct current (MVDC) technologies and the penetration of extended MVDC systems are still significantly hindered by the lack of adequate direct current (DC) switching equipment. The fundamentally different fault current behavior in case of a DC fault, compared to faults in alternating current (AC) systems, with regard to the characteristics and development of fault currents and their interruption make dedicated test procedures necessary. One testing approach is the application of a power-electronic buck converter (PEBC) to simulate relevant stresses on DC switching equipment during a DC fault current interruption. Since the associated requirements, especially regarding current ratings of several kiloamperes, cannot be fulfilled by using a singular PEBC, a modularization becomes necessary. However, particularly in high-power applications, the interconnection of several PEBC modules poses significant challenges. In this article, a demonstrator PEBC-based high-power test circuit for the provision of relevant testing parameters is presented. The underlying challenges and respective solutions with regard to the interconnection of, in total, 120 individual PEBC modules are discussed. It can be shown that the harmonization of connection busbar inductances is the main contributor towards a stable and safe test circuit operation.
Eco-Efficient Vehicle Cooling Modules with Integrated Diffusers—Thermal, Energy, and Environmental Analyses
Authors: Faraj Jalal , Chahine Khaled , Mortada Mostafa , Lemenand Thierry , Ramadan Haitham S. , Khaled Mahmoud
Published: October 2022

The automotive domain is a very good candidate for energy management, particularly due to the huge amounts of energy lost by heat through exhaust and water-cooling systems. This makes the optimization of vehicle cooling modules directly related to energy consumption and carbon dioxide emission. In this context, contemporary designs that employ diffusers between the forward-facing of an automobile and its heat exchanger subjected to airflow are presented in this work. The ultimate aim is to reduce the fuel consumption and carbon dioxide emissions of vehicles. Based on the aforementioned design, the intensity of the air velocity would be decreased but distributed over a larger exchanger surface. Consequently, the velocity non-uniformity of the airflow upstream would decrease and therefore, the thermal performance would increase. The above-mentioned conclusion is a result of parametric numerical analysis and its associated numerical results that disclosed the enhancement of water-air heat exchanger thermal performance. To perform a parametric numerical analysis of the heat exchanger thermal performance for the new suggested configurations, a computational code was developed and validated to estimate the thermal performance for a known set of parameters. It was shown that for an automobile, with engine power ranging from 100–200 kW that is utilized for three hours a day and equipped with a diffuser, reduction of up to 2.91 kg (3.89 L) of gasoline consumption and 9.51 kg of CO2 emission can be achieved per day. The originality of the present work resides in the use of diffusers in cooling modules of vehicles, the thermal modeling of heat exchanger’s thermal performance along with its associated code, and the parametric analysis performed to prove the potential enhancement related to the use of diffusers in the cooling modules.
Electric Bus Scheduling and Timetabling, Fast Charging Infrastructure Planning, and Their Impact on the Grid: A Review
Authors: Alamatsaz Kayhan , Hussain Sadam , Lai Chunyan , Eicker Ursula
Published: October 2022

Transit agencies are increasingly embracing electric buses (EB) as an energy-efficient and emission-free alternative to the conventional bus fleets. They are rapidly replacing conventional buses with electric ones. As a result, emerging challenges of electrifying public transportation bus networks in cities should be addressed. Introducing electric buses to the bus transit system would affect the public transit operation planning steps. The steps are network design, timetabling, bus scheduling, and crew scheduling. Regarding the functional and operational differences between conventional buses and electric buses, such stages should be changed and optimized to enhance the level of service for the users while reducing operating costs for service providers. Many mathematical optimization models have been developed for conventional buses. However, such models would not fit the electric buses due to EBs’ limited traveling range and long charging time. Therefore, new mathematical models should be developed to consider the unique features of electric buses. We present a comprehensive literature review to critically review and classify the work done on these topics. This paper compares the studies that have been done in this field and highlight the missing links and gaps in the considered papers, and the potential future studies that could be done. The considered papers cover the integration of timetabling and vehicle scheduling, recharging scheduling planning, and fast charging infrastructure location planning and its impacts on the grid. The main goal of this research is to highlight the research gaps and potential directions for future studies in this domain to encourage more realistic and applicable models and solution approaches for fully electric bus transit systems.
Sectoral Analysis of Energy Transition Paths and Greenhouse Gas Emissions
Authors: Csalódi Róbert , Czvetkó Tímea , Sebestyén Viktor , Abonyi János
Published: October 2022

The Paris Climate Agreement and the 2030 Agenda for Sustainable Development Goals declared by the United Nations set high expectations for the countries of the world to reduce their greenhouse gas (GHG) emissions and to be sustainable. In order to judge the effectiveness of strategies, the evolution of carbon dioxide, methane, and nitrous oxide emissions in countries around the world has been explored based on statistical analysis of time-series data between 1990 and 2018. The empirical distributions of the variables were determined by the Kaplan–Meier method, and improvement-related utility functions have been defined based on the European Green Deal target for 2030 that aims to decrease at least 55% of GHG emissions compared to the 1990 levels. This study aims to analyze the energy transition trends at the country and sectoral levels and underline them with literature-based evidence. The transition trajectories of the countries are studied based on the percentile-based time-series analysis of the emission data. We also study the evolution of the sector-wise distributions of the emissions to assess how the development strategies of the countries contributed to climate change mitigation. Furthermore, the countries’ location on their transition trajectories is determined based on their individual Kuznets curve. Runs and Leybourne–McCabe statistical tests are also evaluated to study how systematic the changes are. Based on the proposed analysis, the main drivers of climate mitigation and evaluation and their effectiveness were identified and characterized, forming the basis for planning sectoral tasks in the coming years. The case study goes through the analysis of two counties, Sweden and Qatar. Sweden reduced their emission per capita almost by 40% since 1990, while Qatar increased their emission by 20%. Moreover, the defined improvement-related variables can highlight the highest increase and decrease in different aspects. The highest increase was reached by Equatorial Guinea, and the most significant decrease was made by Luxembourg. The integration of sustainable development goals, carbon capture, carbon credits and carbon offsets into the databases establishes a better understanding of the sectoral challenges of energy transition and strategy planning, which can be adapted to the proposed method.
Analyzing the Impact of EV and BESS Deployment on PV Hosting Capacity of Distribution Networks
Authors: Filip Robin , Püvi Verner , Paar Martin , Lehtonen Matti
Published: October 2022

The current article analyzes the impact of charging electric vehicles and battery energy storage systems on the photovoltaic hosting capacity of low-voltage distribution networks. A Monte Carlo-based simulation is used to analyze predominantly rural, intermediate and predominantly urban residential regions facing different penetrations of electric vehicles utilizing uncontrolled and controlled charging, and evaluate their impact on photovoltaic hosting capacity. Subsequently, electric vehicles are replaced or supplemented by residential battery energy storage systems, and their combined impact on the hosting capacity is studied. The results revealed that electric vehicles solely do not improve the hosting capacity unless they are connected to the network during sunshine hours. However, controlled storage provides a remarkable increase to the hosting capacity and exceptional contribution in combination with electric vehicles and customers with high loads. Finally, a feasibility analysis showed that controlled charging of the storage has a lower marginal cost of increasing hosting capacity as compared to network reinforcement.
An Asymptotic Energy Equation for Modelling Thermo Fluid Dynamics in the Optical Fibre Drawing Process
Authors: Luzi Giovanni , Lee Seunghyeon , Gatternig Bernhard , Delgado Antonio
Published: October 2022

Microstructured optical fibres (MOFs) are fibres that contain an array of air holes that runs through the whole fibre length. The hole pattern of these fibres can be customized to manufacture optical devices for different applications ranging from high-power energy transmission equipment to telecommunications and optical sensors. During the drawing process, the size of the preform is greatly scaled down and the original hole pattern result might be modified, potentially leading to unwanted optical effects. Because only a few parameters can be controlled during the fabrication process, mathematical models that can accurately describe the fibre drawing process are highly desirable, being powerful predictive tools that are significantly cheaper than costly experiments. In this manuscript, we derive a new asymptotic energy equation for the drawing process of a single annular capillary and couple it with existing asymptotic mass, momentum, and evolution equations. The whole asymptotic model only exploits the small aspect ratio of a capillary and relies on neither a fitting procedure nor on any empirical adjustable parameters. The numerical results of the simplified model are in good accordance with experimental data available in the literature both without inner pressurization and when internal pressure is applied. Although valid only for annular capillaries, the present model can provide important insights towards understanding the MOF manufacturing process and improving less detailed approaches for more complicated geometries.
Inhibition Mechanism of EMIM-Cl to Methane Gas Hydrate by Molecular Dynamics Simulation
Authors: Xin Guizhen , Xu Na , Li Hongwei , Yin Faling , Qi Yaqiang , Li Shaoqiang , Su Xinyao , Chen Ye , Sun Baojiang
Published: October 2022

Deep-water gas well testing is a key technology for obtaining reservoir production and physical property parameters. However, gas hydrates could easily form and cause blockage in the low-temperature and high-pressure environment on the seafloor. Therefore, it is extremely important to inhibit hydrate growth in deep-water operations. Ionic liquid is a type of hydrate inhibitor with both thermodynamic and kinetic effects. However, its intrinsic inhibiting mechanism is still unclear. By using molecular dynamics simulation, the growth process of methane hydrate in the 1-ethyl-3-methylimidazole chloride (EMIM-Cl)-containing system at the pressure of 15 MPa and temperature of 273.15 K was studied. The system energy and angular order parameters (AOP) were extracted as the evaluation indicators. It was found that the time for the complete growth of methane hydrate in the EMIM-Cl-containing system was about 10 ns, longer than that in the pure water, indicating that EMIM-Cl showed an obvious inhibition effect to hydrate growth. The results also implied that the joint action of hydrogen bond and steric hindrance might be the inhibition mechanism of EMIM-Cl. Some six-membered rings in hydrate crystal large cage structures evolved from five-membered rings under the effect of EMIM, which partly contributed to the delay of hydrate formation.
Hybrid Switched Reluctance Motors for Electric Vehicle Applications with High Torque Capability without Permanent Magnet
Authors: Abhijith Vijina , Hossain M. J. , Lei Gang , Sreelekha Premlal Ajikumar , Monichan Tibinmon Pulimoottil , Rao Sree Venkateswara
Published: October 2022

In electric vehicle (EV) applications, hybrid excitation of switched reluctance motors (HESRMs) are gaining popularity due to their advantages over other EV motors. The benefits include control flexibility, simple construction, high torque/power density, and the ability to operate over a broad speed range. However, modern HESRMs are constructed by increasing the air gap flux density with permanent magnets (PMs) in the excitation system in order to generate more electromagnetic torque. This study aims to investigate a new topology for increasing the torque capabilities of HESRM without the use of permanent magnets (PMs) or other rare-earth components. This paper provides a comprehensive evaluation of the static and dynamic characteristics, software analysis using the Ansys 2D finite element method (FEM), and an experimental demonstration of the real-time motor with an advanced control strategy in MATLAB/Simulink. Our simulation and experimental results for a machine with 12/8 poles and a machine rating of 1.2 kW indicate that the HESRM designed without PMs has greater torque capability and efficiency than the conventional SRM. The proposed HESRM without PMs has a high torque/power density and a higher torque per ampere across the entire speed range, making it suitable for EV applications.
Experimental Study on the Catalyst-Coated Membrane of a Proton Exchange Membrane Electrolyzer
Authors: Rocha Amadeu Gomes , Ferreira Rui , Falcão Daniela , Pinto Alexandra M. F. R.
Published: October 2022

Proton exchange membrane (PEM) technology may regulate the electrical grid connected to intermittent power sources. The growing pace of R&D in alternative components is widening manufacturing methods and testing procedures across the literature. This turns the comparison between performances into a more laborious task, especially for those starting research in this area, increasing the importance of testing components accessible to all. In this study, an electrochemical characterization is performed on a commercial single-cell PEM water electrolyzer with commercial catalyst-coated membranes (CCMs) and one prepared in-house. Two membrane thicknesses and the effect of different catalysts are assessed. The thicker membrane, Nafion 117, operates with 5% greater ohmic overvoltage than the thinner Nafion 115, resulting in up to 1.5% higher voltage for the former membrane. Equivalent Ir black CCMs provided by different suppliers and one prepared in-house perform similarly. Regarding the influence of the anode catalyst, Ir black, IrRuOx and IrRuOx/Pt have similar performance, whereas IrOx has worse performance. Compared with Ir black, the mix of IrRuOx/Pt operated with 1.5% lower voltage at 2.6 A cm−2, whereas IrRuOx performed with 2% lower voltage at 0.3 A cm−2. A temporary increase in performance is observed when the anode is purged with hydrogen gas.
Fracture Mechanism of Crack-Containing Strata under Combined Static and Harmonic Dynamic Loads Based on Extended Finite Elements
Authors: Zhang Haiping , Li Siqi , Chen Zhuo , Tong Yeshuang , Li Zhuolun , Wang Siqi
Published: October 2022

Based on the existing research results, a theoretical fracture model of strata under the compound impact of static and harmonic dynamic load is improved, and the fracture characteristic parameters (stress intensity factor, T-stress, and fracture initiation angle) under the two far-field stress are determined according to the crack dip angle. Additionally, the effects of harmonic dynamic load on the distribution of the stress field and the fracture characteristic (the crack initiation angle, the fracture degree, the number of fracture units, and the fracture area) are further calculated and discussed by theoretical model solution, extended finite element simulation, and the secondary development of the simulation module, respectively. The research results show that the far-field stress, stress intensity factor, and T-stress vary in harmonic form with time under the compound impact of static and harmonic dynamic loads. The frequency of dynamic load affects the number of reciprocal fluctuations of stress intensity factor and T-stress as well as the crack initiation time, but has less influence on the crack initiation angle and fracture degree. While the amplitude of dynamic load affects the stress intensity factor, the extreme value of T-stress and fracture characteristics of the crack. This study has theoretical guiding significance for parameters’ optimization and realization of resonance impact drilling technology.
Performance Analysis of a Hydrogen-Doped High-Efficiency Hybrid Cycle Rotary Engine in High-Altitude Environments Based on a Single-Zone Model
Authors: Yang Zhenghao , Du Yang , Geng Qi , Gao Xu , Er Haonan , Liu Yuanfei , He Guangyu
Published: October 2022

The power attenuation of internal combustion engines in high-altitude environments restricts the performance of unmanned aerial vehicles. Herein, a single-zone model of a hydrogen-doped high-efficiency hybrid cycle rotary engine that considers high-altitude environments was proposed. The indicated values for power, thermal efficiency, and specific fuel cost were used to evaluate the power performance, energy conversion efficiency, and economic performance of the engine, respectively. Then, the effects of adjusting the hydrogen fraction, ignition angle, and rotational speed on high-altitude performance were analyzed. The results showed that high-altitude environments prolonged combustion duration and reduced in-cylinder pressure, thereby causing power attenuation; however, increasing the hydrogen fraction can increase the indicated power. At an altitude of 6 km, the indicated power with a hydrogen fraction of 0.3 was approximately 20.7% higher than that obtained with pure gasoline. The ignition angle and hydrogen fraction corresponding to the optimal indicated thermal efficiency increased with increasing altitude. At an altitude of 6 km, the indicated thermal efficiency reached its maximum (36.4%) at an ignition angle of 340 [CA°] and a hydrogen fraction of 0.15. At high altitudes, rotational speeds below 6000 rpm and ignition angles of 340–345 [CA°] were beneficial in reducing indicated specific fuel costs.
Impact of Geometry on a Thermal-Energy Storage Finned Tube during the Discharging Process
Authors: Privitera Emanuela , Caponetto Riccardo , Matera Fabio , Vasta Salvatore
Published: October 2022

This work focused on the modelling of latent heat thermal energy storage systems. The mathematical modelling of a melting and solidification process has time-dependent boundary conditions because the interface between solid and liquid phases is a moving boundary. The heat transfer analysis needs the interface position over time to predict the temperature inside the liquid and the solid regions. This work started by solving the classical two-phase (one-dimensional) Stefan problem through a Matlab implementation of the analytical model. The same physical problem was numerically simulated using ANSYS FLUENT, and the good match of analytical and numerical results validated the numerical model, which was used for a more interesting problem: comparing three different latent heat TES configurations during the discharging process to evaluate the most efficient in terms of maximum average discharging power. The three axial heat conduction structures changed only for the fin shape (rectangular, trapezoidal and fractal), keeping constant the volume fractions of steel, aluminium and PCM to perform a proper comparison. Results showed that the trapezoidal fin profile performs better than the rectangular one, and the fractal fin profile geometry was revealed as the best for faster thermal exchange when the solidifying frontier moves away from the steel ring. In conclusion, the average discharging power for the three configurations was evaluated for a time corresponding to a reference value (10%) of the liquid fraction: the rectangular fin profile provided 950.8 W, the trapezoidal fin profile 979.4 W and the fractal fin profile 1136.6 W, confirming its higher performance compared with the other two geometries.