bluuebunny/crossref_metadata_2025 huggingface dataset:
Observation of Student and Teacher Behaviors during a Preliminary Active Playful Learning Intervention in Kindergarten Classrooms
Authors: Blinkoff Elias , Nesbitt Kimberly Turner , Golinkoff Roberta Michnick , Hirsh-Pasek Kathy
Published: June 2024

This study describes the implementation and effectiveness of an instructional coaching program for kindergarten teachers in the State of New Hampshire that was implemented in response to the State’s play-based kindergarten mandate. Coaching was provided to 20 teachers from across the State. It focused on guided play, principles of how children learn, and the breadth of skills needed to achieve in the classroom and beyond. A novel adaptation of a classroom observation protocol measured classroom-, teacher-, and student-level behaviors predicted to change with coaching. Classroom-level results revealed a significant decrease in teacher-led direct instruction with a significant shift towards playful instruction, a possible precursor to guided play. Teachers did not change how students were organized in the classroom to promote this instruction, nor did they individually provide more inferential instruction or change their affect with this pedagogical shift. Yet, changes in student behaviors aligned with the coaching program. Students became more engaged with their learning, more active in their use of learning tools, and more communicative. These results offer valuable insights on the initial impacts of an instructional coaching program focused on guided play, how children learn, and what children learn. This study presents a feasible and effective model for professional development on play-based learning that is rooted in the science of learning and measurable in the classroom.
Supporting the Teacher Identity of Pre-Service Science Teachers through Working at a Non-Formal STEM Learning Laboratory
Authors: Haatainen Outi , Pernaa Johannes , Pesonen Reija , Halonen Julia , Aksela Maija
Published: June 2024

This qualitative case study aims to examine the role of a non-formal STEM (science, technology, engineering, and mathematics) learning laboratory in supporting the development of teacher identity among pre-service science teachers. With teacher identity impacting the educational responsiveness and resilience of a teacher, it is important to support the professional identity of STEM educators if we are to enhance the quality of STEM education. Data collection occurred in three stages between 2017 and 2024. Qualitative content analysis through an inductive category formation was used for data analysis. The intercoder reliability was checked (Cohen’s kappa 0.802). Results suggest that non-formal STEM learning environments can enhance pre-service teachers’ professional learning and identity by allowing the autonomous practical application of theory in an authentic collaborative laboratory environment and by strengthening their self-efficacy through positive teaching experiences. Participants reported that such versatile experiences are generally not available during their formal university education. This study offers suggestions for STEM teacher education and insights into ongoing research dialogues about the role of non-formal learning in supporting the learning and identity of STEM teachers.
Preschool Class Children and Grade One Pupils’ Questions about Molecules from a Digital Interactive Session at a Culture Center in Sweden
Authors: Papantonis Stajcic Maria , Vidal Carulla Clara , Åkerblom Annika
Published: June 2024

This study focuses on preschool class children and grade one pupils’ questions about the natural sciences. The article presents the questions that preschool class children and grade one pupils asked via a chat function in connection with a digital interactive lesson about molecules arranged by a culture center in Sweden. The results of the thematic analysis are discussed in relation to their didactic implications for natural science teaching with young learners. The most relevant conclusions are that children drew from their own experiences when approaching molecules, they could generalize their experiences and apply them to other contexts, and they needed time to process the content and then ask questions. Therefore, the authors suggest the use of children’s questions as a useful pedagogical tool for helping young children understand abstract concepts such as molecules. Furthermore, follow-up interviews with children are suggested as a means of mapping the origin of such questions.
The Implementation and Evaluation of Virtualized Protection Intelligent Electronic Devices into a Virtual Substation
Authors: Rösch Dennis , Schäfer Kevin , Nicolai Steffen
Published: June 2024

This paper presents an investigation into the virtualization of substation protection IED functions using a sophisticated co-simulation environment that integrates virtual intelligent electronic devices (vIEDs) with a real-time power grid simulation. Anchored by the IEC 61850 protocol, this study constructs a virtualized IED framework, emphasizing the encapsulation of protection schemes using the example of different types of overcurrent protection within a containerized vIED. Using open-source software, this study aims to replicate the communication and functional aspects of physical IEDs. This study uses a co-simulation environment that couples virtualized network components with a real-time power grid simulation to validate the vIEDs against real substation hardware. Simulation results from induced short-circuit events confirm the operational congruence of the vIEDs with their physical counterparts, demonstrating their potential to serve as cost-effective and adaptable testbeds for substation automation. This paper concludes that virtualized IEDs represent a cost-effective, flexible alternative for substation automation testing, with future research directed towards increasing the functional complexity and real-world applicability of these virtual systems.
Underwater Fish Object Detection with Degraded Prior Knowledge
Authors: Zheng Shijian , Wang Rujing , Wang Liusan
Published: June 2024

Understanding fish distribution, behavior, and abundance is crucial for marine ecological research, fishery management, and environmental monitoring. However, the distinctive features of the underwater environment, including low visibility, light attenuation, water turbidity, and strong currents, significantly impact the quality of data gathered by underwater imaging systems, posing considerable challenges in accurately detecting fish objects. To address this challenge, our study proposes an innovative fish detection network based on prior knowledge of image degradation. In our research process, we first delved into the intrinsic relationship between visual image quality restoration and detection outcomes, elucidating the obstacles the underwater environment poses to object detection. Subsequently, we constructed a dataset optimized for object detection using image quality evaluation metrics. Building upon this foundation, we designed a fish object detection network that integrates a prompt-based degradation feature learning module and a two-stage training scheme, effectively incorporating prior knowledge of image degradation. To validate the efficacy of our approach, we develop a multi-scene Underwater Fish image Dataset (UFD2022). The experimental results demonstrate significant improvements of 2.4% and 2.5%, respectively, in the mAP index compared to the baseline methods ResNet50 and ResNetXT101. This outcome robustly confirms the effectiveness and superiority of our process in addressing the challenge of fish object detection in underwater environments.
A Visually Meaningful Color-Video Encryption Scheme That Combines Frame Channel Fusion and a Chaotic System
Authors: An Dezhi , Hao Dawei , Lu Jun , Zhang Shengcai , Zhang Jiaxin
Published: June 2024

Compared to text and images, video can show information more vividly and intuitively via a moving picture; therefore, video is widely used in all walks of life. However, videos uploaded or stored in various video applications have not been treated with any protection, and these videos contain a lot of sensitive information that is more likely to be compromised. To solve this problem, video encryption schemes have been proposed. However, the main concern with existing video encryption schemes is that the private information in the encrypted video should be effectively protected, and, thus, the pixel distribution of the original video can be greatly damaged in the process of encryption, resulting in no or poor visual usability of the encrypted video. To this end, a novel color-video encryption scheme is proposed, which can effectively protect video privacy information while retaining certain visual information, thus enhancing the usability of encrypted videos. Firstly, the R, G, and B channels of the original color video are viewed as a whole for splitting. The dimensions of the blocks are three-dimensional, and permutation encryption is performed in three-dimensional blocks, which eliminates the redundancy of information between the video frame channels. Secondly, after permutation encryption, the channels of the video frame are separated, and then each channel is divided into blocks. The shape of the blocks is a square, and substitution encryption and permutation encryption operations are performed in turn. The whole encryption process is combined with the 2D-LSM chaotic system to improve the security of the scheme, as well as to reduce the time. Extensive experiments have been carried out, and the results show that the proposed scheme allows the encrypted video to retain rough visual information and, at the same time, effectively protects privacy, achieving the goal of encrypted video security and usability.
Intelligent Type-2 Fuzzy Logic Controller for Hybrid Microgrid Energy Management with Different Modes of EVs Integration
Authors: Aljohani Tawfiq
Published: June 2024

The rapid integration of renewable energy sources (RES) and the electrification of transportation have significantly transformed modern energy infrastructures, emphasizing the need for efficient and flexible energy management systems. This study presents an intelligent, variable-fed, Type-2 Fuzzy Logic Controller (IT2FLC) designed for optimal management of Hybrid Microgrid (HMG) energy systems, specifically considering different modes of Electric Vehicles (EVs) integration. The necessity of this study arises from the challenges posed by fluctuating renewable energy outputs and the uncoordinated charging practices of EVs, which can lead to grid instability and increased operational costs. The proposed IT2FLC is based on comprehensive mathematical modeling that captures complex interactions among HMG components, including Doubly Fed Induction Generator (DFIG) units, photovoltaic (PV) systems, utility AC power, and EV batteries. Utilizing a yearly dataset for simulation, this work examines the HMG’s flexibility and adaptability under dynamic conditions managed by the proposed intelligent controller. A Simulink-based model is built for this study to replicate the dynamical operation of the HMG and test the precise and real-time decision-making capability of the proposed IT2FLC. The results demonstrate the IT2FLC’s superior performance, achieving a substantial cost avoidance of nearly $3,750,000 and efficient energy balance, affirming its potential to sustain optimal energy utilization under stochastic conditions. Additionally, the results attest that the proposed IT2FLC significantly enhances the resilience and economic feasibility of hybrid microgrids, achieving a balanced energy exchange with the utility grid and efficient utilization of EV batteries, proving to be a superior solution for optimal operation of hybrid grids.
A Comprehensive Analysis of the Best Practices in Applying Environmental, Social, and Governance Criteria within the Energy Sector
Authors: Zatonatska Tetiana , Soboliev Oleksandr , Zatonatskiy Dmytro , Dluhopolska Tetiana , Rutkowski Marek , Rak Natalia
Published: June 2024

This article embarks on a crucial exploration of the implementation and integration of environmental, social, and governance (ESG) criteria within the energy sector of European countries, with the ultimate objective of refining the energy legislation in Ukraine. The research delves into the evolving role of ESG standards as a cornerstone in corporate strategy and investment, transitioned from its roots in socially responsible investing to a comprehensive framework that intertwines ethical, environmental, and governance considerations with financial analysis. The main thrust of the study is the following: firstly, it provides a panoramic overview of ESG applications within European energy projects, underscoring pivotal policies, strategies, and instances of successful ESG standard incorporation. Secondly, it benchmarks and compares ESG practices across Europe’s energy sector to distill best practices and their consequential trends and impacts. Lastly, this study converges these European insights to forge pragmatic recommendations for Ukraine’s energy legislation, aiming for an elevated integration of ESG standards that are in step with European benchmarks. The anticipated outcomes offer recommendations for enhancing Ukraine’s energy sector with robust ESG standards, proposing steps that align with the country’s newly adopted Energy Strategy 2050 and international sustainability goals.
CFD Investigations on Heavy Liquid Metal Alternative Target Design for the SPS Beam Dump Facility
Authors: Calviani Marco , Carrelli Carlo , Cervone Antonio , Cioli Puviani Pietro , Di Piazza Ivan , Esposito Luigi Salvatore , Manservisi Sandro , Mazzola Giuseppe , Tricarico Luca , Franqueira Ximenes Rui
Published: June 2024

This study introduces numerical advancements in an alternative design for the Super Proton Synchrotron (SPS) Beam Dump Facility (BDF) at the European Laboratory for Particle Physics (CERN). The design envisions a high-power operation target made of flowing liquid lead. The proposed BDF is a versatile facility for both beam-dump-like and fixed-target experiments. The target behavior is studied, assuming a proton beam with a momentum of 400 GeV/c, a pulse frequency of 1/7.2 Hz, and an average beam power of 355 kW. Using various Computational Fluid Dynamics (CFD) codes, we evaluate the behavior of liquid lead and predict the thermal stress on the target vessel induced by the pulsed heat source generated by the charged particle beam. The comparison increases the reliability of the results, investigating the dependencies on the CFD modeling approach. The beam is a volumetric heat source with data from the beam-lead interaction simulations provided by the European Laboratory for Particle Physics and obtained with a Monte Carlo code. Velocity field and stress profiles can enhance the design of the lead loop and verify its viability and safety when operated with a liquid metal target.
Interoperability Testing for Explicit Demand Response in Buildings
Authors: Andreadou Nikoleta , Tsotakis Charalampos , Gkaidatzis Paschalis A. , Pitsiladis Giorgios , Kotsakis Evangelos , Ioannidis Dimosthenis , Papanikolaou Antonios , Tzovaras Dimitrios
Published: June 2024

The explicit demand response (DR) is a key program for reinforcing the participation of end customers and making the most out of the potential of the smart grid. The DR is a key topic in the field of buildings to make use of the flexibility that they can offer. However, in order to guarantee the correct functionality of a DR system, it is fundamental to perform interoperability tests among the various components/actors. In this paper, we take into consideration the technological solutions suggested in the framework of the DRIMPAC project to enable the DR in buildings. We consider all actors/devices involved in order to reach the objective of executing a flexibility order by an asset. Following a structured interoperability testing methodology created by the Joint Research Centre, we perform interoperability tests regarding all critical links of the full chain of interacting actors to obtain the DR in buildings. The results show that the system functions properly and the benefits from the DR can be exploited. On the other hand, we provide a concrete example of how to apply the interoperability methodology in the field of testing the DR in buildings.
Processing Orchard Grass into Carbon Bio Pellets via Hydrothermal Carbonisation—A Case Study Analysis
Authors: Kowalski Zygmunt , Makara Agnieszka
Published: June 2024

The presented case study evaluates the environmental and economic effects of carbon bio pellet production from orchard grass by Farmutil HS Inc. through the hydrothermal carbonisation method, using obtained biofuel as a substitute for natural gas for heat production. Hydrothermal carbonisation is a zero-waste technology that produces renewable bioenergy by substituting fossil fuels for non-renewable resources. Processing 60,000 t/y of orchard grass with this method resulted in a total amount of heat production of 456,780 GJ/y. This means that over 60% of the energy produced from natural gas could be substituted by renewable bioenergy. It is also very important that the estimated cost of heat produced from carbon bio pellets is 29% lower in comparison to the cost of heat produced from natural gas
Analysis of MW-Level Offshore Wind Turbine Generators with Dual Star–Delta Fractional-Slot Windings
Authors: Rudden Isaac , Li Guang-Jin , Zhu Zi-Qiang , Duke Alexander , Clark Richard
Published: June 2024

This paper investigates the use of fractional-slot concentrated windings (FSCWs) in large-scale (MW level) offshore wind generators. It focuses specifically on a power rating of 3 MW and uses an existing direct-drive synchronous PM machine (DD-SPM) with 480s/160p and dual three-phase integer-slot winding (ISW) as a baseline. A multiple of the common 12s/10p FSCW machine is used that matches the electrical frequency of the ISW machine, yielding a 192s/160p dual three-phase machine. The hybrid star–delta connection has grown increasingly popular owing to its unique harmonic cancellation properties, which can help reduce rotor and PM eddy current losses in FSCW machines. In this paper, two dual three-phase star–delta-wound machines are scaled to 3 MW and included in the investigation. Specifically, a 384s/160p dual three-phase and dual star–delta winding machine, which is a multiplication of the 24s/10p machine, and a 192s/176p dual three-phase and dual star–delta winding machine, which is a multiplication of the 24s/22p machine, are used. These machines are investigated using finite element analysis (FEA) and compared on the basis of their air-gap flux density harmonics, open-circuit electro-motive force (EMF), torque performance, and losses and power. It is found that the proposed 384s/160p dual star–delta winding machine has the best electromagnetic performance of all, with a stator power that is 1.2% greater than that of the baseline ISW machine. However, this machine has a coil pitch of 2 and so loses the manufacturing and fault-tolerant advantage of having concentrated windings. If concentrated windings are desired, then the proposed 192s/176p dual star–delta winding machine is the best choice, with the stator power only 2.6% less than that of the baseline ISW machine, but unfortunately still has significant rotor and PM eddy current losses.
Numerical Simulation Research on Combustion and Emission Characteristics of Diesel/Ammonia Dual-Fuel Low-Speed Marine Engine
Authors: Wu Qinran , Liang Xingyu , Zhu Zhijie , Cui Lei , Liu Teng
Published: June 2024

Amid increasingly stringent global environmental regulations, marine engines are undergoing an essential transition from conventional fossil fuels to alternative fuels to meet escalating regulatory requirements. This study evaluates the effects of injection pressure, the timing of ammonia injection, and the pre-injection of ammonia on combustion and emissions, aiming to identify optimal operational parameters for low-speed marine engines. A three-dimensional model of a large-bore, low-speed marine engine in a high-pressure diffusion mode was developed based on computational fluid dynamics (CFD). Simulations were conducted under 25%, 50%, 75% and 100% loads with a high ammonia energy substitution rate of 95%. The results indicate that, compared to traditional pure diesel operation, adjusting the injection pressure and the ammonia injection timing, along with employing appropriate pre-injection strategies, significantly enhances in-cylinder pressure and temperature, improves thermal efficiency, and reduces specific fuel consumption. Additionally, the dual-fuel strategy using diesel and ammonia effectively reduces nitrogen oxide emissions by up to 37.5% and carbon dioxide emissions by 93.7%.
Economics of Snow Accumulation on Photovoltaic Modules
Authors: Abou Yassine Abdel Hakim , Khoshbakhtnejad Ehsan , Sojoudi Hossein
Published: June 2024

The growth in photovoltaic (PV) module installations over the past decade has prompted a critical need to examine the economic implications of snow accumulation on solar energy production. The aim of this study is to quantify the economic impact of snow accumulation on PV modules in different regions and environmental conditions and to identify effective mitigation strategies for enhancing power generation efficiency and reliability of PV systems. It was found that snow accumulation on PV modules can lead to annual losses of 1% to 12% depending on the environmental conditions and geographic location. A financial analysis related to maintenance costs associated with snow accumulation on PV modules is also presented. A two-fold methodology of quantitative data analysis and interviews conducted with PV system operators is used for this purpose. In addition, the extent of snow accumulation financial losses in the U.S. is categorized based on the snowfall amount and solar market segment, suggesting an annual loss of at least USD 313M in utility and residential solar sectors. Furthermore, various currently employed active and passive snow mitigation strategies are presented in detail, describing their shortcomings and advantages. Finally, prospects on the need for developing reliable and cost-effective snow mitigation strategies for solar panels are discussed, paving the path for future studies.
Laser-Induced Breakdown Spectroscopy Analysis of Sheet Molding Compound Materials
Authors: Shen Hua , Jian Honglin , Zhen Haohan , Yu Lei , Chen Haibin , Tong Tao , Cui Xuhui , Wang Xilin
Published: June 2024

Sheet Molding Compound (SMC) materials are extensively utilized as high-voltage insulation materials in electrical equipment. SMC materials are prone to aging after long-term operation. Conducting non-destructive testing to assess their electrical and physicochemical properties is crucial for the safe operation of electrical equipment. This study identifies the optimal equipment parameters for testing SMC materials using Laser-Induced Breakdown Spectroscopy (LIBS) technology through experimental investigation and also explores the ablation characteristics of SMC under various laser parameters. The results indicate a significant positive correlation between the ablation depth and laser pulse number, while there is no correlation with single laser pulse energy. However, the ablation area demonstrates a strong positive correlation with both single laser pulse energy and laser pulse number. Additionally, LIBS spectral analysis provides elemental results comparable to Energy Dispersive Spectroscopy (EDS), facilitating the examination of variations in Na, Ti, Fe, Mg, Ca, and C elemental contents with depth. Moreover, an enhanced iterative Boltzmann plot method is suggested for calculating the plasma temperature using 21 Fe I spectral lines and the electron density using the Fe II 422.608 nm line. The variations of these plasma parameters with laser pulse number are documented, and the results show consistent trends, confirming that the laser-induced SMC plasma adheres to local thermodynamic equilibrium.
Optimal Network Reconfiguration and Power Curtailment of Renewable Energy Sources to Eliminate Overloads of Power Lines
Authors: Pijarski Paweł , Saigustia Candra , Kacejko Piotr , Belowski Adrian , Miller Piotr
Published: June 2024

The increasing number of renewable energy sources in power systems contributes to overloads of power lines in emergency situations. Lines made with relatively small cross-section cables, which in the past were designed for an operating temperature of 40 °C, are particularly exposed to overloads. Currently, they constitute the so-called “bottlenecks” in network capacity. This is manifested in the fact that when carrying out expert opinions aimed at examining the impact of a source on the network, computational analyses show overloads of its elements. This article proposes a methodology for eliminating these overloads. It involves the use of two methods at the same time, namely optimal network reconfiguration combined with minimisation of the total power curtailment in RE sources. The search for the optimal network configuration will also allow for minimising power curtailment in renewable energy sources, and thus reduce the costs of this type of operation. With such a tool, network operators will be able to achieve the effect of relieving the line load with the lowest possible cost of redistribution. Based on the IEEE 118 bus test network, calculations were performed that confirmed the effectiveness of the proposed approach. The operation of the proposed methodology is presented with the example of two selected network failure states. The novelty of the proposed solution lies in the simultaneous use of two methods of eliminating line overloads. This streamlines the entire process and improves its effectiveness.
Sag and Tension Calculations for High-Voltage Overhead Line Conductors
Authors: Kampik Marian , Kubek Paweł , Krupanek Beata , Bogacz Ryszard
Published: June 2024

Overhead lines are used to transmit electricity from where it is generated to the receiving stations. The correct design of an overhead line affects public safety, because it should ensure the required clearances between conductors and the ground and objects located in the space under the overhead line. The temperature of conductors in overhead lines depends on the load current and weather conditions, and affects the sag and tension of the conductors. Calculations of sags and tensions of overhead conductors can be performed using simplified calculation methods that do not consider insulator sets. In some situations, this approach may cause calculation errors. This article discusses algorithms for calculating overhead conductor tensions and sags in the tensioning sections of high-voltage overhead lines, accounting for and excluding insulator sets. The analysis is carried out for different lengths of tensioning sections and various thermal and mechanical states of the conductors.
Photovoltaic Power Prediction Based on Irradiation Interval Distribution and Transformer-LSTM
Authors: Liao Zhiwei , Min Wenlong , Li Chengjin , Wang Bowen
Published: June 2024

Accurate photovoltaic power prediction is of great significance to the stable operation of the electric power system with renewable energy as the main body. In view of the different influence mechanisms of meteorological factors on photovoltaic power generation in different irradiation intervals and that the data-driven algorithm has the problem of regression to the mean, in this article, a prediction method based on irradiation interval distribution and Transformer-long short-term memory (IID-Transformer-LSTM) is proposed. Firstly, the irradiation interval distribution is calculated based on the boxplot. Secondly, the distributed data of each irradiation interval is input into the Transformer-LSTM model for training. The self-attention mechanism of the Transformer is applied in the coding layer to focus more important information, and LSTM is applied in the decoding layer to further capture the potential change relationship of photovoltaic power generation data. Finally, sunny data, cloudy data, and rainy data are selected as test sets for case analysis. Through experimental verification, the method proposed in this article has a certain improvement in prediction accuracy compared with the traditional methods under different weather conditions. In the case of local extrema and large local fluctuations, the prediction accuracy is clearly improved.
Exploring Hydrogen Embrittlement: Mechanisms, Consequences, and Advances in Metal Science
Authors: Sobola Dinara , Dallaev Rashid
Published: June 2024

Hydrogen embrittlement (HE) remains a pressing issue in materials science and engineering, given its significant impact on the structural integrity of metals and alloys. This exhaustive review aims to thoroughly examine HE, covering a range of aspects that collectively enhance our understanding of this intricate phenomenon. It proceeds to investigate the varied effects of hydrogen on metals, illustrating its ability to profoundly alter mechanical properties, thereby increasing vulnerability to fractures and failures. A crucial section of the review delves into how different metals and their alloys exhibit unique responses to hydrogen exposure, shedding light on their distinct behaviors. This knowledge is essential for customizing materials to specific applications and ensuring structural dependability. Additionally, the paper explores a diverse array of models and classifications of HE, offering a structured framework for comprehending its complexities. These models play a crucial role in forecasting, preventing, and mitigating HE across various domains, ranging from industrial settings to critical infrastructure.
Evaluation of the Significance of Agriculture in Renewable Energy Production in the Member States of the EU
Authors: Krukowski Artur , Nowak Anna , Jarosz-Angowska Aneta , Różańska-Boczula Monika
Published: June 2024

The need to contain climate change and improve energy security has increased the interest in agricultural biomass as a renewable energy source (RES). Given the complexity of the issue of energy production and its environmental impact, the main objective of this study was to assess the significance and potential of the agriculture of the European Union Member States in terms of the capability of producing renewable energy. Using the multi-criteria TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method, we designed a synthetic measure based on several diagnostic characteristics for 2010–2021, obtaining a ranking for EU countries reflecting their agriculture’s RES potential. The research showed that the agricultural sectors with the highest potential for renewable energy production were in the Netherlands, Lithuania, Latvia, and Hungary during the study period. Bulgaria, Denmark, and Spain joined this group in 2021. A comprehensive assessment was conducted using the TOPSIS method to identify the leaders and areas in need of support in leveraging the potential of agriculture for energy in the EU.
Sequential Data-Based Fault Location for Single-Line-to-Ground Fault in a T-Connection Power Line
Authors: Li Lisheng , Yu Haidong , Wang Bin , Liu Yang , Lu Yuanyuan , Liu Wenbin
Published: June 2024

Due to the demand for temporary rapid grid connection in renewable energy power plants, the topology structure of T-connected power lines has been widely used in the power grid. In this three-terminal system, fault localization is difficult because of traditional impedance-based or traveling wave-based fault localization methods; the three-terminal data should be synchronized and communicated. Since different terminal assets belong to different enterprises, it is actually difficult to maintain good synchronization between them. Therefore, in practical applications, the fault location of T-connected power lines often fails. This article proposes a single terminal fault location method for a T-connection power line to address this issue. It is based on the fact that the local topology of the T-connected power line in the healthy phase remains unchanged during the fault-clearing process. It utilizes the sequential current and voltage data changes generated by the sequential tripping ping emitted by the circuit breaker from different terminals to describe the constant topology of the healthy phase as an equation and calculates the accurate fault location after solving the equation. The Levenberg–Marquardt algorithm was used to calculate fault distance and transition resistance, and the effectiveness of this method was verified through simulation.
A High-Speed Multichannel Electrochemical Impedance Spectroscopy System Using Broadband Multi-Sine Binary Perturbation for Retired Li-Ion Batteries of Electric Vehicles
Authors: Sheraz Muhammad , Choi Woojin
Published: June 2024

Retired electric vehicle (EV) batteries are reused in second-life energy storage applications. However, the overall performance of repurposed energy storage systems (ESSs) is limited by the variability in the individual batteries used. Therefore, battery grading is required for the optimal performance of ESSs. Electrochemical impedance spectroscopy (EIS)-based evaluation of battery aging is a promising way to grade lithium-ion batteries. However, it is not practical to measure the impedance of mass-retired batteries due to their high complexity and slowness. In this paper, a broadband multi-sine binary signal (MSBS) perturbation integrated with a multichannel EIS system is presented to measure the impedance spectra for the high-speed aging evaluation of lithium-ion batteries or modules. The measurement speed is multiple times higher than that of the conventional EIS. The broadband MSBS is validated with a reference sinusoidal sweep perturbation, and the corresponding root-mean-square error (RMSE) analysis is performed. Moreover, the accuracy of the presented multichannel EIS system is validated by impedance spectra measurements of Samsung INR18650-29E batteries and compared with those measured using a commercial EIS instrument. A chi-squared error under 0.641% is obtained for all channels. The non-linearity of batteries has a significant impact on the quality of impedance spectra. Therefore, Kronig–Kramer (KK) transform validation is also performed.
PEMFC Electrochemical Degradation Analysis of a Fuel Cell Range-Extender (FCREx) Heavy Goods Vehicle after a Break-In Period
Authors: Yang Jia-Di , Suter Theo , Millichamp Jason , Owen Rhodri E. , Du Wenjia , Shearing Paul R. , Brett Dan J. L. , Robinson James B.
Published: June 2024

With the increasing focus on decarbonisation of the transport sector, it is imperative to consider routes to electrify vehicles beyond those achievable using lithium-ion battery technology. These include heavy goods vehicles and aerospace applications that require propulsion systems that can provide gravimetric energy densities, which are more likely to be delivered by fuel cell systems. While the discussion of light-duty vehicles is abundant in the literature, heavy goods vehicles are under-represented. This paper presents an overview of the electrochemical degradation of a proton exchange membrane fuel cell integrated into a simulated Class 8 heavy goods range-extender fuel cell hybrid electric vehicle operating in urban driving conditions. Electrochemical degradation data such as polarisation curves, cyclic voltammetry values, linear sweep voltammetry values, and electrochemical impedance spectroscopy values were collected and analysed to understand the expected degradation modes in this application. In this application, the proton exchange membrane fuel cell stack power was designed to remain constant to fulfil the mission requirements, with dynamic and peak power demands managed by lithium-ion batteries, which were incorporated into the hybridised powertrain. A single fuel cell or battery cell can either be operated at maximum or nominal power demand, allowing four operational scenarios: maximum fuel cell maximum battery, maximum fuel cell nominal battery, nominal fuel cell maximum battery, and nominal fuel cell nominal battery. Operating scenarios with maximum fuel cell operating power experienced more severe degradation after endurance testing than nominal operating power. A comparison of electrochemical degradation between these operating scenarios was analysed and discussed. By exploring the degradation effects in proton exchange membrane fuel cells, this paper offers insights that will be useful in improving the long-term performance and durability of proton exchange membrane fuel cells in heavy-duty vehicle applications and the design of hybridised powertrains.
Selecting Cycle and Design Parameters of a Super Critical CO2 Cycle for a 180 kW Biogas Engine
Authors: Milewski Jarosław , Szczęśniak Arkadiusz , Lis Piotr , Szabłowski Łukasz , Dybiński Olaf , Futyma Kamil , Sieńko Arkadiusz , Olszewski Artur , Sęk Tomasz , Kryłłowicz Władysław
Published: June 2024

The objective of this paper was to study the sCO2 cycle as a waste heat recovery system for a 180 kW biogas engine. The research methodology adopted was numerical simulations through two models built in different programs: Aspen HYSYS and GT Suite. The models were used to optimize the design and thermodynamic parameters of a CO2 cycle in terms of system power, system efficiency, expander, and compressor efficiency. Depending on the objective function, the sCO2 cycle could provide additional power ranging from 27.9 to 11.3 kW. Based on the calculation performed, “Recuperated cycle at maximum power” was selected for further investigation. The off-design analysis of the system revealed the optimum operating point. The authors designed the preliminary dimensions of the turbomachinery, i.e., the rotor dimension is 16 mm, which will rotate at 100,000 rpm.
Insights and Guidance for China’s Offshore CO2 Storage Development: Evidence from Global Experience
Authors: Zhang Tao , Wu Linqiang , Yan Wei , Zhu Zuofei , Su Pibo , Jiang Chengzhu , Fu Yutong , Cheng Huai
Published: June 2024

Through extensive data research and analysis, this paper comprehensively summarizes the status and key insights of global carbon dioxide capture and storage (CCS) development. It aims to gain a comprehensive understanding of the relevant policies, technologies, and security measures adopted by major countries in their CCS development processes. Furthermore, it explores the existing status and limitations of China’s offshore development efforts, while providing valuable recommendations for enhancing China’s offshore CCS initiatives, as well as serving as a reference for other nations worldwide. Offshore CCS plays a crucial role for China to achieve the development target of carbon peak and carbon neutrality, due to its energy structure and industrial distribution. While China possesses significant offshore CCS potential, achieving commercialization still requires substantial efforts. To facilitate the process and draw insights from successful experiences in other countries, this paper illustrates the characteristics and generalizes the experience of offshore CCS industry practices in America, Europe and Japan, respectively. Furthermore, it is recommended that a new round of investigation into offshore CCS potential be conducted, while promoting integrated collaboration between geological surveying and marine scientific research. Additionally, further research on industrial policies and green financial strategies should be undertaken.
Research on Photovoltaic Maximum Power Point Tracking Control Based on Improved Tuna Swarm Algorithm and Adaptive Perturbation Observation Method
Authors: Li Xianqi , He Ye , Li Maojun
Published: June 2024

In situations where photovoltaic (PV) systems are exposed to varying light intensities, the conventional maximum power point tracking (MPPT) control algorithm may become trapped in a local optimal state. In order to address this issue, a two-step MPPT control strategy is suggested utilizing an improved tuna swarm optimization (ITSO) algorithm along with an adaptive perturbation and observation (AP&O) technique. For the sake of enhancing population diversity, the ITSO algorithm is initialized by the SPM chaos mapping population. In addition, it also uses the parameters of the spiral feeding strategy of nonlinear processing and the Levy flight strategy adjustment of the weight coefficient to enhance global search ability. In the two-stage MPPT algorithm, the ITSO is applied first to track the vicinity of the global maximum power point (MPP), and then it switches to the AP&O method. The AP&O method’s exceptional local search capability enables the global MPP to be tracked with remarkable speed and precision. To confirm the effectiveness of the suggested algorithm, it is evaluated against fuzzy logic control (FLC), standard tuna swarm optimization (TSO), grey wolf optimization (GWO), particle swarm optimization (PSO), and AP&O. Finally, the proposed MPPT strategy is verified by the MATLAB R2022b and RT-LAB experimental platform. The findings indicate that the suggested method exhibits improved precision and velocity in tracking, efficiently following the global MPP under different shading conditions.
Authentication and Key Agreement Protocol in Hybrid Edge–Fog–Cloud Computing Enhanced by 5G Networks
Authors: Zhang Jiayi , Ouda Abdelkader , Abu-Rukba Raafat
Published: June 2024

The Internet of Things (IoT) has revolutionized connected devices, with applications in healthcare, data analytics, and smart cities. For time-sensitive applications, 5G wireless networks provide ultra-reliable low-latency communication (URLLC) and fog computing offloads IoT processing. Integrating 5G and fog computing can address cloud computing’s deficiencies, but security challenges remain, especially in Authentication and Key Agreement aspects due to the distributed and dynamic nature of fog computing. This study presents an innovative mutual Authentication and Key Agreement protocol that is specifically tailored to meet the security needs of fog computing in the context of the edge–fog–cloud three-tier architecture, enhanced by the incorporation of the 5G network. This study improves security in the edge–fog–cloud context by introducing a stateless authentication mechanism and conducting a comparative analysis of the proposed protocol with well-known alternatives, such as TLS 1.3, 5G-AKA, and various handover protocols. The suggested approach has a total transmission cost of only 1280 bits in the authentication phase, which is approximately 30% lower than other protocols. In addition, the suggested handover protocol only involves two signaling expenses. The computational cost for handover authentication for the edge user is significantly low, measuring 0.243 ms, which is under 10% of the computing costs of other authentication protocols.
An Examination of the Effects of Dorsal Fin-Mounted SPOT on Carcharodon carcharias, the Great White Shark
Authors: Hicks Grace L. , Lobel Phillip S.
Published: June 2024

This opinion piece presents empirical evidence to examine possible negative consequences of the use of penetrative tagging as used on the great white shark (GWS). Tagging programs currently using this method attach SPOT (Spatial Positioning Only Tags) using corrodible bolts inserted through the dorsal fin while the shark is taken out of water. Such methods can cause harm to the tagged individual. Possible adverse effects include impacts on growth, tag biofouling, wounds, heightened stress, and hemorrhaging. This method may adversely impact dorsal fin structure and the shark’s hydrodynamics. As a result, data collected may not be reflective of natural behavior. Bolted SPOT are semi-permanently affixed to the shark but can have a battery life of approximately 3.5 years. Most of these tags (69%) ceased transmitting in less than 2 years. Alternative tagging technologies exist as more humane options.
(−)-Gallocatechin Gallate: A Novel Chemical Marker to Distinguish Triadica cochinchinensis Honey
Authors: Jiang Huizhi , Li Zhen , Zhong Shiqing , Zeng Zhijiang
Published: June 2024

Triadica cochinchinensis honey (TCH) is collected from the nectar of the medicinal plant T. cochinchinensis and is considered the most important honey variety in southern China. TCH has significant potential medicinal properties and commercial value. However, reliable markers for application in the authentication of TCH have not yet been established. Herein, a comprehensive characterization of the botanical origin and composition of TCH was conducted by determining the palynological characteristics and basic physicochemical parameters. Liquid chromatography tandem-mass spectrometry (LC-MS/MS) was used to investigate the flavonoid profile composition of TCH, T. cochinchinensis nectar (TCN) and 11 other common varieties of Chinese commercial honey. (−)-Gallocatechin gallate (GCG) was identified as a reliable flavonoid marker for TCH, which was uniquely shared with TCN but absent in the other 11 honey types. Furthermore, the authentication method was validated, and an accurate quantification of GCG in TCH and TCN was conducted. Overall, GCG can be applied as a characteristic marker to identify the botanical origin of TCH.
Modeling the Thermal Inactivation of Monascus ruber Ascospores Isolated from Green Olive (Arauco Cultivar) Storage Brine: An Alternative Strategy to Reduce Antifungal Chemical Agents
Authors: Cappato Leandro Pereira , Dias-Martins Amanda Mattos , Meireles Izadora Martina de Freitas , Ferreira Elisa Helena da Rocha , Lemos Junior Wilson José Fernandes , Rosenthal Amauri
Published: June 2024

Monascus ruber is an important fungus that causes spoilage in table olives, resulting in the darkening of the brine, the softening of the fruit, increased pH, and apparent mycelial growth. This study aimed to evaluate this resistance, providing a model to determine the optimal processing conditions for mitigating fungal contamination and prolonging shelf life without antifungal agents while optimizing pasteurization to reduce energy consumption. The resistance in brine (3.5% NaCl; pH 3.5) from Arauco cultivar green olives imported from Argentina was assessed. Four predictive models (log linear, log linear + shoulder, log linear + tail, log linear + shoulder + tail) estimated kinetic parameters for each survival curve. Log linear + shoulder + tail provided the best fit for 70 °C and 75 °C, with low RMSE (0.171 and 0.112) and high R2 values (0.98 and 0.99), respectively, while the log linear model was used for 80 °C. Decimal reduction times at 70, 75, and 80 °C were 24.8, 5.4, and 1.6 min, respectively, with a z-value of 8.2 °C. The current regulatory processes are insufficient to eliminate M. ruber at requisite levels, considering reduced antifungal agents.