bluuebunny/crossref_metadata_2025 huggingface dataset:
Learning Clinical Skills Using Haptic vs. Phantom Head Dental Chair Simulators in Removal of Artificial Caries: Cluster-Randomized Trials with Two Cohorts’ Cavity Preparation
Authors: San Diego Jonathan P. , Newton Tim J. , Sagoo Anika K. , Aston Tracy-Ann , Banerjee Avijit , Quinn Barry F. A. , Cox Margaret J.
Published: October 2022

Dental task trainer simulators using haptics (virtual touch) offers a cost-effective method of teaching certain clinical skills. The purpose of this study is to evaluate students’ performance in removing artificial caries after training with either a haptic dental chair simulator with virtual reality or a traditional dental chair simulator with a mannequin head. Cluster Randomized Controlled Trials in two cohorts, both Year 1 dental students. Students taught using traditional dental chair simulators were compared with students taught using haptic-based simulators on their ability to cut a cavity in a plastic tooth following training. Across both cohorts, there was no difference in the quality of cavity cut, though students’ technique differed across the two simulator groups in some respects. No difference was seen across both cohorts in the quality of cavity cut for a simple preparation, though students in the haptic condition performed less well in the more demanding task. Moreover, students in the haptic group were also less likely to be perceived to be ‘holding the instrument appropriately’. These findings suggest further investigation is needed into the differences in handling of instruments and level of clinical task difficulty between the simulators.
Finite-Time Neuro-Sliding-Mode Controller Design for Quadrotor UAVs Carrying Suspended Payload
Authors: Bingöl Özhan , Güzey Hacı Mehmet
Published: October 2022

Due to the quadrotor’s underactuated nature, suspended payload dynamics, parametric uncertainties, and external disturbances, designing a controller for tracking the desired trajectories for a quadrotor that carries a suspended payload is a challenging task. Furthermore, one of the most significant disadvantages of designing a controller for nonlinear systems is the infinite-time convergence to the desired trajectory. In this paper, a finite-time neuro-sliding mode controller (FTNSMC) for a quadrotor with a suspended payload that is subject to parametric uncertainties and external disturbances is designed. By constructing a finite-time sliding mode controller, the quadrotor can follow the reference trajectories in finite time. Furthermore, despite time-varying nonlinear dynamics, parametric uncertainties, and external disturbances, a neural network structure is added to the controller to effectively reduce chattering phenomena caused by high switching gains, and significantly reduce the size of the control signals. Following the completion of the controller design, the system’s stability is demonstrated using the Lyapunov stability criterion. Extensive numerical simulations with various scenarios are run to demonstrate the effectiveness of the proposed controller.
Is It Possible to Compromise Forest Conservation with Forest Use?
Authors: Sierota Zbigniew , Miścicki Stanisław
Published: October 2022

A variety of elements in nature, from a pine cone’s bracts to a spiral galaxy, are described by a unique mathematical relationship described by Fibonacci as adhering to the “golden ratio”. In forest management, various models are used to achieve a balance between forest use and conservation that meets societal expectations in both ecological and economic terms. In Central European countries, where forest management has been subordinated to the timber industry, such a transition is still in progress, and people continue to look for an acceptable balance between forest conservation and management. The main objective of this paper is to review approaches to forest management in Central Europe with the aim of contributing to current discussions on forest management models in Europe. We anticipate that the new EU Biodiversity Strategy for 2030 will implement the billion-tree afforestation program with appropriate consideration of forest potential based on the tenets of sustainable management and that the future climate will be neutral. We hope that the forestry aspects of the strategy will provide a positive impetus to forest management by finding effective compromises between forest conservation and forest use in furthering the aims of sustainable development.
Corporate Dividend Policies during the COVID-19 Pandemic
Authors: Ali Nasir , Rehman Muhammad , Ashraf Badar , Shear Falik
Published: October 2022

In this paper, we examine the changes in corporate dividend policies during the COVID-19 shock. For empirical analysis, we employ annual data of 360 companies from the Pakistan Stock Exchange over the period 2015–2020. Using descriptive analysis and Logit regression models, we find that firms were more likely to either omit or reduce dividend payments during the pandemic year of 2020 as compared to the trends in pre-COVID-19 years of 2015–2019. Further, firms with higher profitability, asset turnover and size were less likely to opt for dividend omissions. On the contrary, dividend omissions were more likely among firms with higher debt ratios. The findings of this study helps to understand firm dividend policies during crisis periods.
Learning to Teach as a Spectator or a Participant—Ideas of Vocational Learning in Policy on Teacher Education
Authors: Jederud Sandra
Published: October 2022

This article explores how ideas about teacher student learning are expressed in policy documents, especially the school-based part of teacher education in the Swedish educational system. The study concerns how these parts of the education process are outlined through two reforms, one in 2001 and one in 2011. Of particular interest in the article is how these reforms represent, and to some extent, produce ideas for learning the teaching profession in relation to the specific context of practicum, and that this context pertains to specific knowledge, theoretical and practical knowledge. However, the analysis of the documents points towards a tension between theory and practice. By additionally analyzing policy documents on a local level, where the national policy is operationalized, the tension between theory and practice becomes more explicit. By introducing the notion of spectatorship knowledge and participatory knowledge, two different visions of students’ learning emerge in policy. However, the relation between these two perspectives is problematic, as will be shown in the concluding part of the article. In conclusion, it is suggested that rather than muddling spectatorship knowledge and participatory knowledge together, teacher education programmes should provide for conditions where these knowledge forms are better taken care of.
STEM Education in Australia: Impediments and Solutions in Achieving a STEM-Ready Workforce
Authors: Bentley Brendan , Sieben Rob , Unsworth Paul
Published: October 2022

Recent government and industry priorities have led to a call to raise the quality of STEM learning to meet the future needs of industry and workforce skills. In Australia, education jurisdictions have responded to this challenge. Consequently, education is now considered critical in developing the skills required to meet these future needs. However, several significant issues have hindered STEM education’s advancement. These impediments if not resolved may impact Australia’s future STEM workforce and subsequent economic prosperity. This paper seeks to address some of the key impediments identified within the research literature by making a series of recommendations that provide insight into possible improvement to help recalibrate future STEM education initiatives and support Australia’s long-term economic growth.
Does the Cards against Calamity Learning Game Facilitate Attitudes toward Negotiation, Civics, and Sustainability? Empirical Findings from Greek Graduates
Authors: Makri Eleni G.
Published: October 2022

Learning games for instruction constitute a progressively important, mutually universal challenge for academics, researchers, and software engineers worldwide. Embracing no definite rules for encouraging negotiation, civics, and sustainability game-based learning and agency decisions, this study investigates negotiation/conflict and civics/sustainability-related attributes, as examined through the use of a learning game in a college environment. The author elaborates on the negotiation/conflict and civics/sustainability-related knowledge, attitudes, and skills of 60 Greek non-public college post-graduate students, explored post-gaming, and compared with classroom instruction as part of a negotiation/conflict management module in business psychology sessions in 2019/2020. The findings indicate the integrative negotiation/conflict resolution management and positive civics/sustainable development-associated attitudes of learners post-gaming when compared with lecture instruction. Cooperation, civic action, seeking knowledge about political/societal issues, and gains in problem-solving skills predicted civic responsibility attributes post-gameplay. Non-working status significantly affected the “argument”/verbal fight negotiation/conflict management perceptions of students with non-voting in elections status post-gaming, while working significantly influenced “walk away”/neutral negotiation/conflict resolution attitudes in participants with non-voting in elections status after gameplay. Non-voting in elections attributes significantly impinged on “argument”/verbal fight negotiation/conflict management attitudes for Athens municipality students after gaming. The learning game-based negotiation/conflict management- and civic/sustainability spectrum-related positive effects are reviewed alongside academic and management outcomes, and directions for future research are presented in light of global learning game negotiation/conflict resolution and civics/sustainability-related teaching and learning.
Evaluation of the Predictive Ability and User Acceptance of Panoramix 2.0, an AI-Based E-Health Tool for the Detection of Cognitive Impairment
Authors: Valladares-Rodríguez Sonia , Fernández-Iglesias Manuel J. , Anido-Rifón Luis E. , Pacheco-Lorenzo Moisés
Published: October 2022

The high prevalence of Alzheimer-type dementia and the limitations of traditional neuropsychological tests motivate the introduction of new cognitive assessment methods. We discuss the validation of an all-digital, ecological and non-intrusive e-health application for the early detection of cognitive impairment, based on artificial intelligence for patient classification, and more specifically on machine learning algorithms. To evaluate the discrimination power of this application, a cross-sectional pilot study was carried out involving 30 subjects: 10 health control subjects (mean age: 75.62 years); 14 individuals with mild cognitive impairment (mean age: 81.24 years) and 6 early-stage Alzheimer’s patients (mean age: 80.44 years). The study was carried out in two separate sessions in November 2021 and January 2022. All participants completed the study, and no concerns were raised about the acceptability of the test. Analysis including socio-demographics and game data supports the prediction of participants’ cognitive status using machine learning algorithms. According to the performance metrics computed, best classification results are obtained a Multilayer Perceptron classifier, Support Vector Machines and Random Forest, respectively, with weighted recall values >= 0.9784 ± 0.0265 and F1-score = 0.9764 ± 0.0291. Furthermore, thanks to hyper-parameter optimization, false negative rates were dramatically reduced. Shapley’s additive planning (SHAP) applied according to the eXplicable AI (XAI) method, made it possible to visually and quantitatively evaluate the importance of the different features in the final classification. This is a relevant step ahead towards the use of machine learning and gamification to early detect cognitive impairment. In addition, this tool was designed to support self-administration, which could be a relevant aspect in confinement situations with limited access to health professionals. However, further research is required to identify patterns that may help to predict or estimate future cognitive damage and normative data.
A Robust Framework for Object Detection in a Traffic Surveillance System
Authors: Akhtar Malik Javed , Mahum Rabbia , Butt Faisal Shafique , Amin Rashid , El-Sherbeeny Ahmed M. , Lee Seongkwan Mark , Shaikh Sarang
Published: October 2022

Object recognition is the technique of specifying the location of various objects in images or videos. There exist numerous algorithms for the recognition of objects such as R-CNN, Fast R-CNN, Faster R-CNN, HOG, R-FCN, SSD, SSP-net, SVM, CNN, YOLO, etc., based on the techniques of machine learning and deep learning. Although these models have been employed for various types of object detection applications, however, tiny object detection faces the challenge of low precision. It is essential to develop a lightweight and robust model for object detection that can detect tiny objects with high precision. In this study, we suggest an enhanced YOLOv2 (You Only Look Once version 2) algorithm for object detection, i.e., vehicle detection and recognition in surveillance videos. We modified the base network of the YOLOv2 by reducing the number of parameters and replacing it with DenseNet. We employed the DenseNet-201 technique for feature extraction in our improved model that extracts the most representative features from the images. Moreover, our proposed model is more compact due to the dense architecture of the base network. We utilized DenseNet-201 as a base network due to the direct connection among all layers, which helps to extract a valuable information from the very first layer and pass it to the final layer. The dataset gathered from the Kaggle and KITTI was used for the training of the proposed model, and we cross-validated the performance using MS COCO and Pascal VOC datasets. To assess the efficacy of the proposed model, we utilized extensive experimentation, which demonstrates that our algorithm beats existing vehicle detection approaches, with an average precision of 97.51%.
Investigation of Barrier Layer Effect on Switching Uniformity and Synaptic Plasticity of AlN Based Conductive Bridge Random Access Memory
Authors: Mohanty Srikant Kumar , Reddy Kuppam Poshan Kumar , Wu Chien-Hung , Lee Po-Tsung , Chang Kow-Ming , Busa Prabhakar , Kuthati Yaswanth
Published: October 2022

In this work, we investigated the effect of the tungsten nitride (WNx) diffusion barrier layer on the resistive switching operation of the aluminum nitride (AlN) based conductive bridge random access memory. The WNx barrier layer limits the diffusion of Cu ions in the AlN switching layer, hence controlling the formation of metallic conductive filament in the host layer. The device operated at a very low operating voltage with a Vset of 0.6 V and a Vreset of 0.4 V. The spatial and temporal switching variability were reduced significantly by inserting a barrier layer. The worst-case coefficient of variations (σ/µ) for HRS and LRS are 33% and 18%, respectively, when barrier layer devices are deployed, compared to 167% and 33% when the barrier layer is not present. With a barrier layer, the device exhibits data retention behavior for more than 104 s at 120 °C, whereas without a barrier layer, the device fails after 103 s. The device demonstrated synaptic behavior with long-term potentiation/depression (LTP/LTD) for 30 epochs by stimulating with a train of identical optimized pulses of 1 µs duration.
A Deterministic Branch Prediction Technique for a Real-Time Embedded Processor Based on PicoBlaze Architecture
Authors: Ali Ehsan , Pora Wanchalerm
Published: October 2022

This paper proposes a new deterministic branch prediction unit to achieve a uniformly timed instruction set architecture (ISA). The deterministic ISA is achieved by utilizing two address buses in conjunction with dual-port block RAMs that are common in commercial FPGAs. The goal is to remove mandatory branch and load delays to achieve a uniform one clock cycle per every instruction. To demonstrate the concept, the proposed architecture is applied to the Xilinx PicoBlaze firm core. The result is a new soft core named DAP-Zipi8 that reduces the clock per instruction (CPI) metric of PicoBlaze from two to one at the expense of extra logic and a longer critical path. The increased critical path reduces maximum achievable clock speed from 357.509 MHz to 224.022 MHz. Merging the gain in CPI with the loss in maximum clock frequency still improves overall processor performance by 18.28–19.49%. The high-performance deterministic DAP-Zipi8 is a viable choice for hard RTES applications.
Multi-Area Microgrid Load-Frequency Control Using Combined Fractional and Integer Order Master–Slave Controller Considering Electric Vehicle Aggregator Effects
Authors: Shayeghi Hossein , Rahnama Alireza , Mohajery Reza , Bizon Nicu , Mazare Alin Gheorghita , Ionescu Laurentiu Mihai
Published: October 2022

Because of the lack of upstream grid support and low inertia, independent microgrids are very susceptible to load variations and uncertainty in the generation of renewable energy sources. Disruption of microgrid frequency stability causes severe damage to various system equipment and frequency-sensitive loads. By taking into account the effects of electric vehicles (EVs), this paper introduces an innovative control strategy with a master-slave configuration for frequency control of interconnected microgrids. In the proposed configuration, an integer-order controller serves as the master, while a merely fractional-order integrator acts as the slave controller. The master and slave controllers are concurrently optimized by the JAYA intelligent algorithm to achieve robust effectiveness. Additionally, nonlinearities in the system are implemented, such as diesel generator operating limits, signal controllers, and sending/receiving time delays. To assess the effectiveness of the proposed control strategy in a two-area microgrid, six basic scenarios are investigated: sudden load changes, perturbations at the inputs of renewable energy-based units, parametric uncertainties, time-delay effects as a nonlinear factor, complicated working conditions, and EVs impacts. Moreover, the controller’s performance on a simple closed-loop system has been carried out in order to confirm the viability of its practical implementation, and a comparison of experimental and simulation findings has also been provided. Studies demonstrate the proposed controller’s robustness as well as its fast-response capability. Besides, this controller features a simple structure that allows extra design flexibility.
Characteristics of Liquid-Hydrocarbon Yield and Biomarkers in Various Thermal-Evolution Stages: A Simulation Experiment with the Middle Jurassic Source Rocks in the Northern Margin of the Qaidam Basin
Authors: Chen Yongxin , Zhang Xilong , Li Xiang , Liu Tao , Sun Yaru , Zhu Guotao , Ju Pengfei
Published: October 2022

Although there are many studies on the Jurassic source rocks in the northern margin of the Qaidam Basin, the characteristics of biomarkers and products with the same source rock in different evolutionary stages are still not well understood. Such an understanding is essential for accurately estimating oil and gas resources. In order to explore the hydrocarbon-generation potential of high-quality source rocks of the Middle Jurassic and the evolution of liquid hydrocarbons and biomarkers, we carried out simulation research (under hydrous conditions) at various temperatures (250, 300, 350, 400 and 450 °C) with the mudstone of the Yu 33 well in the Yuka Sag. The results revealed that the “oil window” of the Middle Jurassic source rocks in the Yuka area was 300 °C (simulation temperature, Ro = 0.84%), but this was not the peak of hydrocarbon expulsion, which was gradually reached and stabilized above 350 °C. Overall, the concentration of alkanes and aromatics increased with temperature; although the concentration of alkanes was complex in the low evolutionary stages, temperature (simulated maturity) was still the main factor controlling the change in alkanes and aromatics. Among the maturity parameters of biomarkers, the ratio of ∑tricyclic terpanes/∑hopanes was the most effective parameter for indicating the maturity evolution of the Yuka area, but others were complicated by the increasing temperature. Therefore, when evaluating maturity, the applicability of other parameters needed to be fully considered. The results obtained offer new insights in the research on liquid-hydrocarbon and biomarker evolution of the Middle Jurassic source rocks in the Yuka Sag of the Qaidam Basin.
The Relationship between Electricity Prices and Household Welfare in South Africa
Authors: Qeqe Bekithemba , Kapingura Forget , Mgxekwa Bahle
Published: October 2022

The study examines the relationship between electricity prices and household welfare in South Africa. The study employs a demand system framework on annual time-series data from 2000 to 2018 and the analysis involves the calculation of price elasticities and measurement of welfare changes. The price elasticities in this study are drawn from the linear expenditure demand model. To analyse welfare change, we consider the impact of electricity pricing policies on cost of living (proxied by the consumer price index and households’ expenditure patterns). The study achieves this: (i) by comparing electricity price movements to changes in the rate of inflation between 2000 and 2018; (ii) by regressing total household energy expenditure against household expenditure on electricity, to examine how electricity costs affect a household’s overall energy bills; and (iii) thirdly, by regressing household food expenditure against households’ electricity expenditure to determine how the latter affects a household’s ability to spend on other basic goods and services. The results of the study show: (i) South African household electricity demand is inelastic to changes in price of electricity; (ii) electricity prices in the country increased at a higher rate than the rate of inflation for most of the time during the study period, suggesting that households incurred increased expenditures to achieve their desired utility or satisfy their energy needs during this period; (iii) household total electricity expenditure is positively related to household total energy expenditure, implying that high household expenditure on electricity exerts upward pressure on the overall household energy budgets; and (iv) household total food expenditure is negatively related to household total energy expenditure. This shows that while policy makers achieved significant success with providing physical access to electricity, affordable access to this basic service is still a concern and affects the overall welfare of households in the country. The study recommends a review of the country’s electricity tariff structure to make affordability a key objective. Moreover, the study calls for coordinated efforts in addressing Eskom challenges which have also played a contributing role to the current energy crisis, characterized by an unreliable electricity supply and constantly increasing electricity prices.
Influence of Reservoir Properties on the Velocity of Water Movement from Injection to Production Well
Authors: Poplygin Vladimir Valerievych , Poplygina Irina Sergeevna , Mordvinov Viktor Antonovich
Published: October 2022

To maintain reservoir pressure, water is injected into oil reservoirs. In carbonate rock, water quickly breaks through fractures and highly permeable formations to production wells. This study analyzes the effect of the permeability, oil viscosity, pressure drop, and distance on the water velocity from an injection well to a production well. In the Tempest MORE hydrodynamic simulator (Roxar), a three-layer model of an oil reservoir was created, and water flow from an injection well to a production well was simulated with various values of the permeability, oil viscosity, and bottom hole pressure. The water velocity in the reservoir was estimated based on the mobility factor (k/µo). The results showed that at a mobility factor of less than 2 μm2/Pa s at a distance of 100 m in the reservoirs, the time of water migration from the injection well to the production well increased sharply, and at a mobility factor of more than 2 μm2/Pa s, it became shorter. An analysis of the time of water migration in fields with high-viscosity oil was conducted. The watering time turned out to be shorter than that predicted by the simulation. The permeability of the reservoir and the viscosity of the oil had the greatest influence on the water velocity. To a lesser extent, the time of water migration was affected by the distance between the wells and the difference in the bottomhole pressures. The average migration time for water with a mobility factor of more than 2 µm2/(Pa s) was 6.3 years. Based on the regression analysis of the field data, a linear equation for the time of water migration was obtained. The resulting equation makes it possible to predict the water cuts of wells and optimize oil production.
Approaches to Disposal of Nuclear Waste
Authors: Ojovan Michael I. , Steinmetz Hans J.
Published: October 2022

We present a concise mini overview on the approaches to the disposal of nuclear waste currently used or deployed. The disposal of nuclear waste is the end point of nuclear waste management (NWM) activities and is the emplacement of waste in an appropriate facility without the intention to retrieve it. The IAEA has developed an internationally accepted classification scheme based on the end points of NWM, which is used as guidance. Retention times needed for safe isolation of waste radionuclides are estimated based on the radiotoxicity of nuclear waste. Disposal facilities usually rely on a multi-barrier defence system to isolate the waste from the biosphere, which comprises the natural geological barrier and the engineered barrier system. Disposal facilities could be of a trench type, vaults, tunnels, shafts, boreholes, or mined repositories. A graded approach relates the depth of the disposal facilities’ location with the level of hazard. Disposal practices demonstrate the reliability of nuclear waste disposal with minimal expected impacts on the environment and humans.
Numerical and Experimental Spray Analysis of Castor and Jatropha Biodiesel under Non-Evaporating Conditions
Authors: Haq Muteeb , Jafry Ali , Abbasi Muhammad , Jawad Muhammad , Ahmad Saad , Cheema Taqi , Abbas Naseem
Published: October 2022

Fuel spray characteristics influence combustion, which in turn has a direct impact on engine performance and emissions. Recently, there has been an increasing interest in novel castor oil biodiesel. However, few investigations have been performed that combine both numerical and experimental biodiesel spray analyses. Hence, in this paper, we aim to explore the spray behavior of castor and jatropha biodiesel by employing numerical and experimental methods under non-evaporating, varying injection, and ambient conditions. The experimental study was carried out in a control volume vessel (CVV) at high injection and ambient pressures. The fuel atomization was modelled in ANSYS Fluent using a Lagrangian/Eulerian multiphase formulation. The results revealed that the Kelvin–Helmholtz and Rayleigh–Taylor (KHRT) model coupled with the Taylor Analogy Breakup (TAB) model provide a better estimation of the penetration length (PL) and spray cone angle (SCA) compared to the KH and TAB models. On average, Jatropha biodiesel (JB-20) and castor biodiesel (CB-20) showed a 10% to 22% longer PL, 8% to 10.6% narrower spray cone angles, and 3% to 6% less spray area, respectively, compared to diesel. The numerical predictions showed that JB-20 and CB-20 had an around 24.7–48.3% larger Sauter mean diameter (SMD) and a 38.6–73.3% average mean diameter (AMD).
Hybrid Indirect Evaporative Cooling-Mechanical Vapor Compression System: A Mini-Review
Authors: Chen Qian , Burhan Muhammad , Ja M Kum , Shahzad Muhammad Wakil , Ybyraiymkul Doskhan , Zheng Hongfei , Cui Xin , Ng Kim Choon
Published: October 2022

The hybrid indirect evaporative cooling-mechanical vapor compression (IEC-MVC) process is deemed a promising cooling system for hot and humid areas. It possesses the merits of high energy efficiency and strong capability of temperature and humidity control. Herein, we provide an overview of the state-of-the-art investigations over different aspects of the hybrid IEC-MVC process. Firstly, we evaluate the potential of IEC as a pre-cooler and heat-recovery device. Then, we compare the energy efficiency of IEC-MVC with standalone MVC and summarize its long-term energy-saving potential under specific weather conditions. Subsequently, we discuss the economic viability and water consumption of the hybrid process. These studies form a solid foundation for the future installation of the IEC-MVC system.
Model Antiseptic Control Scheme to Torque Ripple Mitigation for DC-DC Converter-Based BLDC Motor Drives
Authors: Kumar Dileep , Choudhary Surya Deo , Tabrez Md , Ayob Afida , Hossain Lipu Molla Shahadat
Published: October 2022

Although brushless direct current motor (BLDCM) drives are becoming more popular in industrial and commercial applications, there are still significant difficulties and unresolved research issues that must be addressed. In BLDCM drives, commutation current ripple (CCR) and diode freewheeling during non-commutation zone (NCZ) are the major challenges. To overcome these limitations, this paper proposes a novel PWM-Model Antiseptic Control (PWM-MAC) technique to alleviate the freewheeling of the diode. The proposed PWM technique is used to alleviate the diode freewheeling in the NCZ, whereas the DCLV circuit is utilized to obtain variable DC-link voltage to address the CCR in the CZ. The MATLAB/Simulink results are included along with experimental results obtained from a laboratory prototype of 325 W. The proposed module reduces the current ripple by 31.7% and corresponding torque ripples are suppressed by approximately 32.5%. This evidences the performance of the proposed control technique.
On the Modeling of Energy-Multisource Networks by the Thermostatted Kinetic Theory Approach: A Review with Research Perspectives
Authors: Bianca Carlo
Published: October 2022

Recently, different mathematical frameworks of the thermostatted kinetic theory approach have been proposed for the modeling of complex systems. In particular, thermostatted kinetic frameworks have been employed for the modeling and time evolution of a hybrid energy-multisource network composed of renewable and nonrenewable energy sources, for the construction of the energy storage and for open networks. In the frameworks of the thermostatted kinetic theory approach, the evolution of an energy source and the interactions with other energy sources are modeled by introducing a distribution function and interaction rates. This paper is a survey of the recent proposed frameworks of the thermostatted kinetic theory for the modeling of a hybrid energy-multisource network and reviews the recent proposed models. The paper is not limited to review the existing frameworks, but it also generalizes the mathematical structures proposed in the pertinent literature and outlines future research perspectives and applications of this new approach proposed in 2012.
Assessment of Smart Grid Systems for Electricity Using Power Maclaurin Symmetric Mean Operators Based on T-Spherical Fuzzy Information
Authors: Naseem Areeba , Ullah Kifayat , Akram Maria , Božanić Darko , Ćirović Goran
Published: October 2022

Traditional electricity networks are replaced by smart grids to increase efficiency at a low cost. Several energy projects in Pakistan have been developed, while others are currently in the planning stages. To assess the performance of the smart grids in Pakistan, this article employs a multi-attribute group decision-making (MAGDM) strategy based on power Maclaurin symmetric mean (PMSM) operators. We proposed a T-spherical fuzzy (TSF) power MSM (TSFPMSM), and a weighted TSFPMSM (WTSFPMSM) operator. The proposed work aims to analyze the problem involving smart grids in an uncertain environment by covering four aspects of uncertain information. The idempotency, boundedness, and monotonicity features of the proposed TSFPMSM are investigated. In order to assess Pakistan’s smart grid networks based on the suggested TSFPMSM operators, a MAGDM algorithm has been developed. The sensitivity analysis of the proposed numerical example is analyzed based on observing the reaction of the variation of the sensitive parameters, followed by a comprehensive comparative study. The comparison results show the superiority of the proposed approach.
IoT-Based Decentralized Energy Systems
Authors: Biegańska Marta
Published: October 2022

In traditional energy production at large-scale, conventional methods are being used, including fossil fuels. This in turn leads to greenhouse gas emissions (e.g., carbon dioxide or CO2) that cause environmental concerns, but also those traditional methods rely on traditional distribution systems, which are burdened with high transmission losses. This paper focuses on a new concept in the energy sector that undergoes transformation from a traditional centralized system to a decentralized one. In reaching sustainability goals, such as net-zero emissions, the energy sector is incorporating renewable energy sources into the energy system. This requires transformation that combines big conventional energy producers with multiple small- and large-scale energy producers (rooftop photovoltaic panels, wind farms and solar plants) in one system. This enormous transformation is a difficult task, but with recent advancements in information and communication technologies, digitalization, the Industry 4.0 paradigm and Internet of Things technology, it is feasible to achieve. This paper provides a review based on keyword bibliometric analysis, and although it cannot be considered exhaustive or conclusive, it provides a picture of the current international research.
Highly Efficient Interleaved Solar Converter Controlled with Extended Kalman Filter MPPT
Authors: Kabalci Ersan , Boyar Aydin
Published: October 2022

DC-DC power converters play an important role in the performance and control methods of solar power systems. Solar power converters are prone to high power losses due to intermittent irradiation and shading effects on solar photovoltaic (PV) modules. The device topology and control algorithm of a solar power converter are key factors to increase the total amount of harvested energy. In this paper, a solar power converter is proposed with a two−phase interleaved boost converter (IBC) topology and a novel maximum power point tracking (MPPT) method. The proposed MPPT controller is based on extended Kalman filtering (EKF) and it improves the tracking efficiency in both steady irradiation and partial shading conditions. The algorithm is improved with the prediction and estimation capabilities of the EKF algorithm. The proposed EKF MPPT is validated with simulations and experimentally validated by using the implemented two−phase IBC that is comprised of SiC MOSFETs. The proposed converter provides over 99% power conversion efficiency at 3 kW and over 96% MPPT tracking efficiency under partial shading conditions. The experimental studies verify that the proposed MPPT controller and two−phase IBC increase the overall efficiency both in steady-state and partial shading operations of a solar power converter.
Energy Consumption under Circular Economy Conditions in the EU Countries
Authors: Khan Atif Maqbool , Osińska Magdalena
Published: October 2022

Due to industrialization, urbanization, and rapid population increases, the worldwide energy demand is increasing daily. The need for energy meets limitations, and searching for new energy sources is crucial, particularly for European countries. Energy crises occur temporarily due to different circumstances and cause oil price fluctuations. The present study aims to identify circular economy (CE) determinants that conditionally increase/decrease energy use to remain sustainable. It focuses on the linkage between energy consumption and circular economy in the European Union (EU) member states. In the econometric panel model specifications, two alternative endogenous variables are considered, i.e., total energy consumption and energy consumption from renewable sources. The results demonstrate that the selected CE indicators decreased the former and increased the latter. The data covered the period from 2010–2019. The significance of this study relies upon identifying the current level of CE implementation in the EU countries in the context of reducing total energy consumption and increasing the share of energy from renewable sources.
Optimal Multi-Objective Placement and Sizing of Distributed Generation in Distribution System: A Comprehensive Review
Authors: Kumar Mahesh , Soomro Amir , Uddin Waqar , Kumar Laveet
Published: October 2022

For over a decade, distributed generations (DGs) have sufficiently convinced the researchers that they are the economic and environment-friendly solution that can be integrated with the centralized generations. The optimal planning of distributed generations requires the appropriate location and sizing and their corresponding control with various power network types to obtain the best of the technical, economical, commercial, and regulatory objectives. Most of these objectives are conflicting in nature and require multi-objective solutions. Therefore, this paper brings a comprehensive literature review and a critical analysis of the state of the art of the optimal multi-objective planning of DG installation in the power network with different objective functions and their constraints. The paper considers the adoption of optimization techniques for distributed generation planning in radial distribution systems from different power system performance viewpoints; it considers the use of different DG types, distribution models, DG variables, and mathematical formulations; and it considers the participation of different countries in the stated DG placement and sizing problem. Moreover, the summary of the literature review and critical analysis of this article helps the researchers and engineers to explore the research gap and to find the future recommendations for the robust optimal planning of the DGs working with various objectives and algorithms. The paper considers the adoption of uncertainties on the load and generation side, the introduction of DGs with energy storage backups, and the testing of DG placement and sizing on large and complex distribution networks.
Performance of Two Variable Machine Learning Models to Forecast Monthly Mean Diffuse Solar Radiation across India under Various Climate Zones
Authors: Mustafa Jawed , Husain Shahid , Alqaed Saeed , Khan Uzair Ali , Jamil Basharat
Published: October 2022

For the various climatic zones of India, machine learning (ML) models are created in the current work to forecast monthly-average diffuse solar radiation (DSR). The long-term solar radiation data are taken from Indian Meteorological Department (IMD), Pune, provided for 21 cities that span all of India’s climatic zones. The diffusion coefficient and diffuse fraction are the two groups of ML models with dual input parameters (sunshine ratio and clearness index) that are built and compared (each category has seven models). To create ML models, two well-known ML techniques, random forest (RF) and k-nearest neighbours (KNN), are used. The proposed ML models are compared with well-known models that are found in the literature. The ML models are ranked according to their overall and within predictive power using the Global Performance Indicator (GPI). It is discovered that KNN models generally outperform RF models. The results reveal that in diffusion coefficient models perform well than diffuse fraction models. Moreover, functional form 2 is the best followed by form 6. The ML models created here can be effectively used to accurately forecast DSR in various climates.
Experimental Setup for Measurement of AC Loss in HTS under Rotating Magnetic Field
Authors: Soomro Wafa Ali , Guo Youguang , Lu Haiyan , Jin Jianxun , Shen Boyang , Zhu Jianguo
Published: October 2022

High-temperature superconducting materials have shown great potential for the design of large-scale industry applications. However, they are complicated under AC conditions, resulting in penalties such as power loss or AC loss. This loss has to be considered in order to design reliable and efficient superconducting devices. Furthermore, when superconductors are used in rotating machines, they may be exposed to rotating magnetic fields, which is critical for the design of such machines. Existing AC loss measuring techniques are limited to measuring under one-dimensional AC magnetic fields or transport currents. Therefore, it is essential to develop and investigate robust experimental techniques to investigate the loss mechanism in HTS machines. In this paper, a new and novel experimental technique has been presented to measure AC loss in rotating magnetic field conditions. The loss under rotating magnetic fields is measured and compared by numerical modeling methods, and the results show a strong correlation with the numerical modeling and show the effectiveness of the experimental setup.
Non-Destructive Electromagnetic Evaluation of Material Degradation Due to Steel Cutting in a Fully Stacked Electrical Machine
Authors: Selema Ahmed , Ibrahim Mohamed N. , Sergeant Peter
Published: October 2022

Although it is well known that the magnetic properties of electrical steel can be deeply affected by the cutting process, it is still not clear how to accurately evaluate these effects on a prototyped machine on its final shape, especially at a high frequency or a high power rating. This research provides a more practical method for accurate measurement of magnetic losses in electrical steel with consideration of material degradation effects due to the cutting process. Unlike other similar studies, these investigations are conducted not only on a few laminations but also on a complete electrical machine core. For a fair comparison between both cases, backlack bonding is used for lamination stacking since it is the most non-damaging joining technique. Two different test setups are used to measure the steel performance at a wide range of frequency and input power. Furthermore, a full axial length stator of a switched reluctance machine (SRM) is used as a case study to identify the magnetic properties of NO20 electrical steel. Additionally, by comparing the results obtained from the individual laminations and the assembled stator, the extra losses due to the cutting process and material degradation are extracted accurately.
Data-Free and Data-Efficient Physics-Informed Neural Network Approaches to Solve the Buckley–Leverett Problem
Authors: Diab Waleed , Chaabi Omar , Zhang Wenjuan , Arif Muhammad , Alkobaisi Shayma , Al Kobaisi Mohammed
Published: October 2022

Physics-informed neural networks (PINNs) are an emerging technology in the scientific computing domain. Contrary to data-driven methods, PINNs have been shown to be able to approximate and generalize well a wide range of partial differential equations (PDEs) by imbedding the underlying physical laws describing the PDE. PINNs, however, can struggle with the modeling of hyperbolic conservation laws that develop shocks, and a classic example of this is the Buckley–Leverett problem for fluid flow in porous media. In this work, we explore specialized neural network architectures for modeling the Buckley–Leverett shock front. We present extensions of the standard multilayer perceptron (MLP) that are inspired by the attention mechanism. The attention-based model was, compared to the multilayer perceptron model, and the results show that the attention-based architecture is more robust in solving the hyperbolic Buckley–Leverett problem, more data-efficient, and more accurate. Moreover, by utilizing distance functions, we can obtain truly data-free solutions to the Buckley–Leverett problem. In this approach, the initial and boundary conditions (I/BCs) are imposed in a hard manner as opposed to a soft manner, where labeled data are provided on the I/BCs. This allows us to use a substantially smaller NN to approximate the solution to the PDE.
Investigation of Heat Transfer Fluids Using a Solar Concentrator for Medium Temperature Storage Receiver Systems and Applications
Authors: Kuldeep Pawan Kumar , Kumar Sandeep , Khan Mohammed Saquib , Panchal Hitesh , Mawire Ashmore , Mahavar Sunita
Published: October 2022

Solar concentrator collectors have the potential of meeting the medium- and high-temperature thermal energy demands of the world. A heat transfer fluid (HTF) is a vital component of a concentrating system to transfer and store thermal energy. This paper presents the design development of a solar paraboloidal dish concentrator (SPDC) and a study of selected HTFs using the storage receiver system of the concentrator. The locally designed SPDC (diameter 1.21 m and height 0.20 m) has features like light weight, effortless tracking, convenient transportation along with high optical and thermal performance. Three HTFs, silicone oil (SO), engine oil (EO) and ethylene glycol (EG), are selected based on their favorable properties for medium temperature (150–300 °C) applications. The characteristic parameters of HTFs, heating rate (Rh), instant thermal efficiency (ηith) and the overall heat loss coefficient (UL), are illustrated and determined experimentally. A new characteristic parameter, the normalized maximum fluid temperature (Tnf), is also introduced in the paper. In the heating test, the maximum attained temperatures by fluids, SO, EO and EG are found to be 240 °C, 180 °C and 160 °C, respectively. The thermal efficiencies of SO, EO and EG are determined to be 45, 36 and 31%, respectively. The heating rate of 6.56 °C/s is found to be the maximum for SO. Through the cooling test, the overall heat loss coefficient (UL) is computed to be 14 W/mK, which is the least among the three fluids compared. The high thermal performance, environmental safety and chemical stability of silicone oil make it suitable for use in concentrators for medium-temperature heat transfer and storage applications.
Techno-Economic Optimization of an Off-Grid Hybrid Power Generation for SRM IST, Delhi-NCR Campus
Authors: Sambhi Shilpa , Sharma Himanshu , Kumar Pankaj , Fotis Georgios , Vita Vasiliki , Ekonomou Lambros
Published: October 2022

The limited availability of fossil fuels such as coal and increasing air pollution levels due to the burning of coal have pushed the trend of generating electricity from fossil fuels to generating it from locally available renewable resources. It is expected that the cost of electricity will decrease when locally available renewable resources are used. In this paper, it was proposed to commission a solar PV system in a part of an academic building of SRM IST University. The present study is an effort in-line with many initiatives taken up by the Indian Government. The performance index of solar PV system was analyzed. Supporting data were obtained from the NASA PDAV tool and then techno-economical analysis was carried out on HOMER. The average performance ratio and capacity factor of the solar PV system were obtained as 64.49% and 14.90%, respectively. For the optimal configuration, the net present cost and the levelized cost of electricity are $639,981 and $0.34 per kWh, respectively. As per the estimation, there will be no air pollution due to the proposed configuration, whereas if only a diesel generator is commissioned, then 200,417 kg of carbon dioxide will be emitted annually.