bluuebunny/crossref_metadata_2025 huggingface dataset:
Tsallis q-Statistics Fingerprints in Precipitation Data across Sicily
Authors: Pecorino Vera , Pluchino Alessandro , Rapisarda Andrea
Published: July 2024

Precipitation patterns are critical for understanding the hydrological and climatological dynamics of any region. Sicily, the largest island in the Mediterranean sea, with its diverse topography and climatic conditions, serves as an ideal case study for analyzing precipitation data, to gain insights into regional water resources, agricultural productivity, and climate change impacts. This paper employs advanced statistical physics methods, particularly Tsallis q-statistics, to analyze sub-hourly precipitation data from 2002 to 2023, provided by the Sicilian Agrometeorological Informative System (SIAS). We investigate several critical variables related to rainfall events, including duration, depth, maximum record, and inter-event time. The study spans two decades (2002–2012 and 2013–2023), analyzing the distributions of relevant variables. Additionally, we examine the simple returns of these variables to identify significant temporal changes, fitting these returns with q-Gaussian distributions. Our findings reveal the scale-invariant nature of precipitation events, the presence of long-range interactions, and memory effects, characteristic of complex environmental processes.
An Attacker–Defender Game Model with Constrained Strategies
Authors: Ren Jiaqi , Liu Jin , Dong Yibo , Li Zhe , Li Weili
Published: July 2024

Recently, research interest in the field of infrastructure attack and defense scenarios has increased. Numerous methods have been proposed for studying strategy interactions that combine complex network theory and game theory. However, the unavoidable effect of constrained strategies in complex situations has not been considered in previous studies. This study introduces a novel approach to analyzing these interactions by including the effects of constrained strategies, a factor often neglected in traditional analyses. First, we introduce the rule of constraints on strategies, which depends on the average distance between selected nodes. As the average distance increases, the probability of choosing the corresponding strategy decreases. Second, we establish an attacker–defender game model with constrained strategies based on the above rule and using information theory to evaluate the uncertainty of these strategies. Finally, we present a method for solving this problem and conduct experiments based on a target network. The results highlight the unique characteristics of the Nash equilibrium when setting constraints, as these constraints influence decision makers’ Nash equilibria. When considering the constrained strategies, both the attacker and the defender tend to select strategies with lower average distances. The effect of the constraints on their strategies becomes less apparent as the number of attackable or defendable nodes increases. This research advances the field by introducing a novel framework for examining strategic interactions in infrastructure defense and attack scenarios. By incorporating strategy constraints, our work offers a new perspective on the critical area of infrastructure security.
Specific Effect of Innovation Factors on Socioeconomic Development of Countries in View of the Global Crisis
Authors: Vasin Sergey Mikhailovich , Timokhina Daria Mikhailovna
Published: July 2024

Although the coronavirus pandemic has now faded into the background, the global crisis caused by COVID-19 has had the most devastating impacts worldwide. Given the potential relapse of such unexpected and uncertain events, it is vital to specify the patterns thereof and develop proactive measures for the countries to acquire an advanced readiness to deal with the related incidents. The most infected countries faced an increase in business bankruptcies, unemployment and inflation rates, low production volumes, and a decline in Gross Domestic Product (GDP). To withstand such socioeconomic consequences, the countries had to employ a number of measures, with innovation development acceleration being one. This paper aims to assess the dependency of an increase in GDP and a decrease in inflation and unemployment rates on the country-level growth of innovation development according to such Global Innovation Index (GII) pillars as institutions, human capital and research, infrastructure, market sophistication, business sophistication, knowledge and technology outputs, and creative outputs. The conducted research analysis covered the period from 2019 to 2022 based on the data for the GII pillar development level and economic performance indicators for 20 countries from five socioeconomic models. Descriptive and comparative statistics as well as correlation and regression analysis were used to prove the innovation development to be a key driver in increasing GDP and reducing inflation. To increase the GDP value, special attention should be paid to such GII pillars as institutions and human capital and research, while infrastructure and human capital and research are the pillars to reduce the inflation rates.
Financial Development, Monetary Policy, and the Monetary Transmission Mechanism—An Asymmetric ARDL Analysis
Authors: Oyadeyi Olajide O.
Published: July 2024

This paper’s objective is to examine the asymmetric cointegration and asymmetric effects of financial development and monetary policy on monetary transmission mechanisms in the Nigerian context using annual data spanning the period from 1986 to 2023. This study pushes the frontiers of knowledge by providing information on the nonlinear impacts of monetary policy and financial sector innovations on monetary transmission mechanisms in Nigeria to help policymakers tailor their strategies to local conditions, enhancing the effectiveness of monetary interventions in the economy. To achieve this, this paper adopted nonlinear ARDL models to understand how changes in the direction of monetary policy and developments in the financial system induce changes in the transmission of monetary policy. The findings document the existence of asymmetries in both the short and long run, revealing that the impacts of financial development and monetary policy on the different monetary policy channels are not uniform. These asymmetries indicate that the responses of various economic variables to monetary policy actions differ depending on the level of financial development. These findings underscore the complexity of the monetary transmission mechanism and the necessity for a nuanced understanding of how financial development and monetary policy interact in different contexts. Consequently, this finding is symptomatic of some characteristics of those financial markets on their way toward advanced developments. As the financial system matures, monetary policy may have a greater impact on the cost of short-term funding for banks without having any discernible effect on the rates at which businesses and households access funding. Therefore, this paper recommends focusing on the policies that will foster the financial system across the banking sector, capital market, bond market, and overall financial sector to improve the efficiency of the monetary transmission process.
Does Mainstreamed Aid Advance Gender Parity? Insights from Empirical Evidence
Authors: Tadesse Bedassa , Shukralla Elias K. , Fayissa Bichaka
Published: July 2024

This study investigates the effectiveness of gender-mainstreamed aid in mitigating gender inequality. We develop a robust theoretical model that accounts for the potential positive and perceived negative effects of shifts toward gender parity, capturing diverse societal perspectives. Utilizing a comprehensive dataset on aid activities focused on gender (in)equality and women’s empowerment across 118 countries from 2009 to 2022, primarily low-income nations, we employ panel fixed-effects and mixed-effects random coefficient models to examine the impact of gender-related aid on gender inequality. Our findings reveal that significant gender-related aid (SGRA), which integrates gender considerations into broader development projects, reduces gender inequality in 115 out of 118 countries. In contrast, principal gender-related aid (PGRA), which explicitly targets gender equality, shows significant effects in only 85 countries. When analyzing the effects of both components of gender-related aid, we find that SGRA consistently impacts gender inequality. However, the effectiveness of PGRA becomes less clear-cut. This observation, coupled with the variation in the effectiveness of the components across countries, underscores the importance of developing strategies tailored to country-specific needs and conditions in promoting gender parity effectively.
The Impact of COVID-19 on ‘Spanish-Speaking’ Children’s Phonological Development
Authors: Acero-Ferrero Marían , Lozano-Blasco Raquel , Moreno María Jesus Cardoso , Benaque Giner Sandra
Published: July 2024

Communication and social interaction have been limited during the COVID-19 pandemic. The aim of this study was to check if 3-, 4-, and 5-year-old children manifest alterations in oral language according to their stage of language development. To carry it out, the Induced Phonological Register developed by Monfort and Juárez was applied to analyze 150 participants (77 boys and 73 girls) with an average age of 4 years and 6 months. Children who experienced the COVID-19 pandemic for an extended period show a delay in the acquisition of some phonemes compared to children who undergo typical phonological development as specified by Laura Bosch (2003) regarding language development for Spanish children. Likewise, they present a higher number of erroneous words and phonemes than expected for their age.
Design of a Real-Time Monitoring System for Electroencephalogram and Electromyography Signals in Cerebral Palsy Rehabilitation via Wearable Devices
Authors: Xiong Anshi , Wu Tao , Jia Jingtao
Published: July 2024

Cerebral palsy is a disorder of central motor and postural development, resulting in limited mobility. Cerebral palsy is often accompanied by cognitive impairment and abnormal behavior, significantly impacting individuals and society. Time, energy, and economic investment in the rehabilitation process is substantial, yet the rehabilitation outcomes often remain unsatisfactory. Additionally, some patients have limited sensory perception during rehabilitation training, making it challenging to effectively regulate exercise intensity. Traditional evaluation methods are mostly based on recovery performance, lack guidance at the neurophysiological level, and have an unequal distribution of medical rehabilitation resources, which pose great challenges to the rehabilitation of patients. Based on the issues mentioned above, this paper proposes a real-time cerebral signal monitoring system based on wearable devices. This system can monitor and store blood oxygen, heart rate, myoelectric, and EEG signals during cerebral palsy rehabilitation, and it can track and monitor signals during the rehabilitation treatment process. The system includes two parts: hardware design and software design. The hardware design includes a data signal acquisition module, a main control chip (ESP32), a muscle electrical sensor module, a brain electrical sensor module, a blood/heart rate acquisition module, etc. It is primarily for real-time signal data acquisition, processing, and uploading to the cloud server. The software design includes functions such as data receiving, data processing, data storage, network configuration, and remote communication and enables the visual monitoring of data signals. The system can achieve real-time monitoring of electromyography, electroencephalography, and blood oxygen levels, as well as the heart rate of patients with cerebral palsy, and adjust rehabilitation training in real-time during the rehabilitation process. At the same time, based on the real-time storage of the original electromyography and electroencephalography data, it can provide auxiliary guidance for later rehabilitation evaluation and effective data support for the entire rehabilitation treatment process.
Smartphone-Based Task Scheduling in UAV Networks for Disaster Relief
Authors: Li Lin , Wang Zhenchuan , Zhu Jinqi , Ma Shizhao
Published: July 2024

Earthquake disasters are usually very destructive and pose a great threat to human life and property. Based on the relatively mature technology of unmanned aerial vehicles (UAVs) and their high flexibility, these devices are widely used for information collection and processing in post-disaster relief operations. However, UAVs are limited by their battery capacity, which makes it hard for them to perform both large-scale information gathering and data processing at the same time. Nowadays, smartphones (SPs), which have become portable devices for people, have the characteristics of strong computing power, rich communication means and wide distribution. Therefore, in this study, we developed SPs to assist UAVs in computation incentive-based task execution. To balance the cost of UAVs and the execution utility of SPs during the task execution process, a multi-objective optimization problem was established, and the Multi-Objective Mutation-Immune Bat (MOMIB) algorithm was developed to optimize the proposed problem. Additionally, considering the diversity of tasks in real-world scenarios, Quality of Service (QoS) coefficients were introduced to ensure the performance requirements of different types of tasks. A large number of simulation experiments show that the task-offloading scheme that we propose is effective.
Two-Area Automatic Generation Control for Power Systems with Highly Penetrating Renewable Energy Sources
Authors: Lam Le Hong , Nam Le Khoa , Dung Nguyen Khac Tien , Hieu Nguyen Huu
Published: July 2024

Currently, renewable energy sources (RESs) are gradually replacing traditional power sources that use fossil fuels. In some countries, such as Vietnam, RESs are developed on a massive scale and are concentrated in some key areas. This causes negative impacts on a power system when its transmission system is not deployed synchronously to release their capacity from these new renewable energy plants. An important challenge today is to ensure frequency stability in power systems with high uncertainty in RES output power. Additionally, the system requires solutions to prevent transmission line overloads during periods when RESs make a substantial contribution to the electricity generation capacity. Therefore, this paper builds an automatic generation control (AGC) system for a two-area power system with high penetration of RESs. This AGC system model aims to maintain system frequency stability amid unpredictable changes in RESs while also ensuring that tie-lines transmit the predetermined power levels to mitigate frequent congestion. By continuously monitoring and adjusting the system’s frequency, the challenges posed by the inherent variability of RESs can be effectively mitigated. The AGC model is simulated on DIgSILENT PowerFactory software and tested with a 106-bus system. The simulation results of this study show that the AGC system operates effectively, ensuring that the frequency returns to the rated value and maintaining the exchange capacity on the tie-lines after occurrences of RES power decrease events.
Compressive Sensing-Based Channel Estimation for Uplink and Downlink Reconfigurable Intelligent Surface-Aided Millimeter Wave Massive MIMO Systems
Authors: Oyerinde Olutayo Oyeyemi , Flizikowski Adam , Marciniak Tomasz , Zelenchuk Dmitry , Ngatched Telex Magloire Nkouatchah
Published: July 2024

This paper investigates single-user uplink and two-user downlink channel estimation in reconfigurable intelligent surface (RIS)-aided millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) wireless communication systems. Because of the difficulty associated with the estimation of channels in RIS-aided wireless communication systems, channel state information (CSI) is assumed to be known at the receiver in some previous works in the literature. By assuming that prior knowledge of the line-of-sight (LoS) channel between the RIS and the base station (BS) is known, two compressive sensing-based channel estimation schemes that are based on simultaneous orthogonal matching pursuit and structured matching pursuit (StrMP) algorithms are proposed for estimation of uplink channel between RIS and user equipment (UE), and joint estimations of downlink channels between BS and a UE, and between RIS and another UE, respectively. The proposed channel estimation schemes exploit the inherent common sparsity shared by the angular domain mmWave channels at different subcarriers. The superiority of one of the proposed channel estimation techniques, the StrMP-based channel estimation technique, with negligibly higher computational complexity cost compared with other channel estimators, is documented through extensive computer simulation. Specifically, with a reduced pilot overhead, the proposed StrMP-based channel estimation scheme exhibits better performance than other channel estimation schemes considered in this paper for signal-to-noise ratio (SNR) between 0 dB and 5 dB upward at different instances for both uplink and downlink scenarios, respectively. However, below these values of SNR the proposed StrMP-based channel estimation scheme will require higher pilot overhead to perform optimally.
Affective Computing in Augmented Reality, Virtual Reality, and Immersive Learning Environments
Authors: Lampropoulos Georgios , Fernández-Arias Pablo , Antón-Sancho Álvaro , Vergara Diego
Published: July 2024

As students’ affective states can differ between learning that occurs in traditional classrooms when compared with learning that takes place in extended reality and immersive learning environments, it is important to examine the role of affective computing. Therefore, this study aims to provide an overview regarding the use of affective computing in the context of augmented reality, virtual reality, and immersive learning environments and the metaverse. Hence, it examines and presents the state of the art through a review and bibliometric analysis of 188 documents of the existing literature from Scopus and Web of Science (WoS) from 2005 to 2023. The study follows the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement to identify and select relevant to the topic documents. In addition to the analysis of the existing literature, emerging topics and themes are identified and future research directions are presented. The significant role of affective computing within augmented reality and virtual reality environments arose. Their ability to offer engaging and interactive learning experiences while also being able to recognize, monitor, and respond to students’ affective states and to consider their emotions, personalities, characteristics, knowledge, and preferences to provide adaptive and personalized learning was evident. Additionally, their potential to enrich educational activities, increase learning outcomes, and support special education emerged. When augmented reality, virtual reality, and immersive learning environments capitalize on affective computing, meaningful learning can occur and self-regulated learning can be promoted.
Research on the Inhibition and Transmission Properties of Photonic Spiking Dynamics in Semiconductor Ring Lasers
Authors: Zhang Xueting , Mu Penghua , Liu Guopeng , Wang Yiqiao , Li Xueyuan
Published: July 2024

Significant progress has been made in the research of all-optical neural networks in recent years. In this paper, we theoretically explore the properties of a neural system composed of semiconductor ring lasers (SRLs). Our study demonstrates that external optical signals generated by a tunable laser (TL) are injected into the first semiconductor ring laser photonic neuron (SRL1). Subsequently, the responses of SRL1 in the clockwise (CW) and counterclockwise (CCW) directions are unidirectionally injected into the CW and CCW directions of the second semiconductor ring laser photonic neuron (SRL2), respectively, which then exhibits similar spiking inhibition behaviors. Numerical simulations reveal that the spiking inhibition behavior of the SRL response can be precisely controlled by adjusting the perturbation time and intensity of the external injection signal, and this behavior is highly repeatable. Most importantly, we successfully achieve the stable transmission of these responses between the two SRL photonic neurons. These inhibition behaviors are analogous to those of biological neurons, but with a response speed reaching the sub-nanosecond level. Additionally, we indicate that SRL photonic neurons undergo a refractory-period-like phenomenon when subjected to two consecutive perturbations. These findings highlight the immense potential for the design and implementation of future all-optical neural networks, providing critical theoretical foundations and support for them.
3D Human Pose Estimation Based on Wearable IMUs and Multiple Camera Views
Authors: Chen Mingliang , Tan Guangxing
Published: July 2024

The problem of 3D human pose estimation (HPE) has been the focus of research in recent years, yet precise estimation remains an under-explored challenge. In this paper, the merits of both multiview images and wearable IMUs are combined to enhance the process of 3D HPE. We build upon a state-of-the-art baseline while introducing three novelties. Initially, we enhance the precision of keypoint localization by substituting Gaussian kernels with Laplacian kernels in the generation of target heatmaps. Secondly, we incorporate orientation regularized network (ORN), which enhances cross-modal heatmap fusion by taking a weighted average of the top-scored values instead of solely relying on the maximum value. This not only improves robustness to outliers but also leads to higher accuracy in pose estimation. Lastly, we modify the limb length constraint in the conventional orientation regularized pictorial structure model (ORPSM) to improve the estimation of joint positions. Specifically, we devise a soft-coded binary term for limb length constraint, hence imposing a flexible and smoothed penalization and reducing sensitivity to hyperparameters. The experimental results using the TotalCapture dataset reveal a significant improvement, with a 10.3% increase in PCKh accuracy at the one-twelfth threshold and a 3.9 mm reduction in MPJPE error compared to the baseline.
Few-Shot Learning Based on Dimensionally Enhanced Attention and Logit Standardization Self-Distillation
Authors: Tang Yuhong , Li Guang , Zhang Ming , Li Jianjun
Published: July 2024

Few-shot learning (FSL) is a challenging problem. Transfer learning methods offer a straightforward and effective solution to FSL by leveraging pre-trained models and generalizing them to new tasks. However, pre-trained models often lack the ability to highlight and emphasize salient features, a gap that attention mechanisms can fill. Unfortunately, existing attention mechanisms encounter issues such as high complexity and incomplete attention information. To address these issues, we propose a dimensionally enhanced attention (DEA) module for FSL. This DEA module introduces minimal additional computational overhead while fully attending to both channel and spatial information. Specifically, the feature map is first decomposed into 1D tensors of varying dimensions using strip pooling. Next, a multi-dimensional collaborative learning strategy is introduced, enabling cross-dimensional information interactions through 1D convolutions with adaptive kernel sizes. Finally, the feature representation is enhanced by calculating attention weights for each dimension using a sigmoid function and weighting the original input accordingly. This approach ensures comprehensive attention to different dimensions of information, effectively characterizing data in various directions. Additionally, we have found that knowledge distillation significantly improves FSL performance. To this end, we implement a logit standardization self-distillation method tailored for FSL. This method addresses the issue of exact logit matching, which arises from the shared temperature in the self-distillation process, by employing logit standardization. We present experimental results on several benchmark datasets where the proposed method yields significant performance improvements.
Study on Leakage and Diffusion Behavior of Liquid CO2 Vessel in CCES
Authors: Gao Lin , Wang Jinlong , Wu Song , Liu Xuan , Zhu Binfei , Fan Yuguang
Published: July 2024

Numerical simulations of the leakage and diffusion behavior of liquid CO2 vessels and security analyses were conducted in this paper, based on a CO2 compression energy storage system. With isentropic choking model, the leakage of vessels under specific conditions was numerically simulated. The influence of different wind speeds on leakage in near-zone field was studied. Meanwhile, the diffusion characteristics of CO2 under three different influencing factors were investigated with the UDM (Unified Dispersion Model) diffusion model, and the diffusion ranges of certain concentrations were detected in the far-zone field. The results show that the low-temperature zone of the 50 mm leak aperture can reach 0.74 m downwind, and basically does not change with wind speed. In the leakage direction, the maximum damage zone of high-speed flow can reach 7.70 m. For the far-zone field, the diffusion area and downwind distance of a dangerous concentration decrease with the increasing of wind speed, and the hazardous area of the low concentration is greatly affected. Based on specific conditions, the maximum diffusion area is 78.46 m2 at 1 m/s wind speed, and the dangerous range reaches 36.32 m downwind. The larger the leakage aperture, the faster the growth trend of the low concentration area under the same conditions. As the equivalent radius of the leakage aperture is less than 50 mm, the maximum diffusion area is proportional to the cubic of the leakage aperture radius. The higher the height of the leakage source, the smaller the concentration range at 1.5 m, which is the average human breathing height. The overall cloud moves upward, meaning that the ground risk decreases. When the leakage aperture is 50 mm and the wind speed is 1 m/s, the maximum cloud diffusion range is 857.35 m2 at the leakage height of 2 m, and the dangerous range reaches 109.53 m downwind, where the maximum concentration is 14.65%.
Correction: Lu et al. Dimensioning Air Reactor and Fuel Reactor of a Pressurized CLC Plant to Be Coupled to a Gas Turbine: Part 2, the Fuel Reactor. Energies 2023, 16, 3850
Authors: Lu Wang , Bartocci Pietro , Abad Alberto , Bischi Aldo , Yang Haiping , Cabello Arturo , de Las Obras Loscertales Margarita , Zampilli Mauro , Fantozzi Francesco
Published: July 2024

In the original publication [...]
A Survey of Multi-Agent Systems for Smartgrids
Authors: Izmirlioglu Yusuf , Pham Loc , Son Tran Cao , Pontelli Enrico
Published: July 2024

This paper provides a survey of the literature on the application of Multi-agent Systems (MAS) technology for Smartgrids. Smartgrids represent the next generation electric network, as communities are developing self-sufficient and environmentally friendly energy production. As a cyber-physical system, the development of the vision of Smartgrids requires the resolution of major technical problems; this has fed over a decade of research. Due to the stochastic, intermittent nature of renewable energy resources and the heterogeneity of the agents involved in a Smartgrid, demand and supply management, energy trade and control of grid elements constitute great challenges for stable operation. In addition, in order to offer resilience against faults and attacks, Smartgrids should also have restoration, self-recovery and security capabilities. Multi-agent systems (MAS) technology has been a popular approach to deal with these challenges in Smartgrids, due to their ability to support reasoning in a distributed context. This survey reviews the literature concerning the use of MAS models in each of the relevant research areas related to Smartgrids. The survey explores how researchers have utilized agent-based tools and methods to solve the main problems of Smartgrids. The survey also discusses the challenges in the advancement of Smartgrid technology and identifies the open problems for research from the view of multi-agent systems.
Analysis of Non-Road Mobile Machinery Homologation Standards in Relation to Actual Exhaust Emissions
Authors: Szymlet Natalia , Kamińska Michalina , Ziółkowski Andrzej , Sobczak Jakub
Published: July 2024

This article presents issues related to the current approval procedures in the group of off-road vehicles. Our research aimed to demonstrate significant differences between actual railway vehicle operation and stationary homologation tests regarding exhaust emissions. The research cycle consisted of analyzing emissions of toxic compounds from exhaust systems under real operating conditions, supplemented by a temporal share analysis based on the denormalized NRTC test upon which the tested object was homologated. Based on the conducted analyses, a significant difference was found between the actual operation of the tested railway vehicle and the stationary homologation test. By interpreting emission intensities within the parameter ranges of the propulsion unit’s operation, key areas with a significant impact on the vehicle’s overall emissions were identified. Based on the obtained results, a critical opinion is expressed regarding current homologation standards for the off-road vehicle group and the necessity for further empirical research in the area of actual operation of the tested vehicle group.
Mechanical Damage to Coal and Increased Coal Permeability Caused by Water-Based Ultrasonic Cavitation
Authors: Guo Xiaoyang , Liu Yijia , Li Yanfeng , Deng Cunbao , Zhang Lemei , Zhang Yu
Published: July 2024

Coalbed methane (CBM), recognized as a sustainable and environmentally friendly energy source, plays a crucial role in mitigating global climate change and advancing low-carbon energy solutions. However, the prevalence of low-permeability coal seams poses a significant challenge to effective CBM extraction. Improving coal permeability has emerged as a viable strategy to address the issue of low-permeability coal. Conventional CBM stimulation methods fall short in overcoming this obstacle. In contrast, the enhanced technique of CBM extraction by water-based ultrasonic cavitation holds great promise due to its use of high energy intensity, safety, and efficiency. Nevertheless, the inadequate theoretical framework for managing this technology impedes its widespread adoption for large-scale applications. This study investigated the impact of water-based ultrasonic cavitation treatment on coal’s properties and permeability through mechanical testing and permeability measurements conducted before and after treatment. This study also explored the process by which this technology, known as WUC-ECBM, improves coal’s mechanical properties and permeability. The findings suggest a potential stimulation technique (WUC-ECBM) for use in CBM extraction, and its physical mechanism.
Advanced Multi-Sampling PWM Technique for Single-Inductor MIMO DC-DC Converter in Electric Vehicles
Authors: Solangi Hanan , Hafeez Kamran , Mekhilef Saad , Seyedmahmoudian Mehdi , Stojcevski Alex , Khan Laiq
Published: July 2024

Amongst the various topologies of multi-input multi-output (MIMO) DC-DC converters, single-inductor MIMO (SI-MIMO) converters have the advantages of a reduced component count, a simpler structure, and low cost. These converters are suitable in electric vehicle (EV) applications involving variable ports, essential for performing different functions. Digital control in SI-MIMO converters is promising for enhancing transient performance due to its numerous benefits. However, delays in digital control, particularly computational and pulse width modulation (PWM) delays, can negatively impact the performance of DC-DC converters. Multi-sampling and double PWM update methods can mitigate these control delays, but they often necessitate complex control schemes, adding computational burden. In this work, an advanced multi-sampling PWM technique, integrating sample shift and multi-sampling, is proposed while employing a simple digital PID control scheme. The proposed method was tested for a shared-switch SI-MIMO converter with battery discharging and charging modes in the MATLAB/Simulink environment and compared with the conventional single- and multi-sampling PWM methods. The results demonstrated that the proposed method significantly improved the converter performance, surpassing the conventional single- and multi-sampling PWM methods. In the battery discharging mode, utilizing the proposed method, the output voltage achieved a settling time of 0.075 s in response to a step change in its reference, significantly outperforming multi-sampling, which yielded a settling time of 0.124 s, and single sampling, which exhibited an even longer settling time of 0.898 s. It also demonstrated a minimal overshoot of 0.06 volts compared to 1.5 volts with multi-sampling during the step change in the input voltage. Similarly, in the battery charging mode, upon a step change in the reference output voltage, the proposed method effectively minimized the overshoot of the output voltage to 0.845 volts compared to 1.175 volts with multi-sampling, and it decreased the inductor current settling time to 0.296 s from 0.330 s recorded under multi-sampling. These findings underscore the potential of the proposed method in enhancing the digital control performance of SI-MIMO DC-DC converters in electric vehicles.
Investigation of a Modified Wells Turbine for Wave Energy Extraction
Authors: Uddin Mohammad Nasim , Opoku Frimpong , Atkinson Michael
Published: July 2024

The Oscillating Water Column (OWC) is the most promising self-rectifying device for power generation from ocean waves; over the past decade, its importance has been rekindled. The bidirectional airflow inside the OWC drives the Wells turbine connected to a generator to harness energy. This study evaluated the aerodynamic performance of two hybrid airfoil (NACA0015 and NACA0025) blade designs with variable chord distribution along the span of a Wells turbine. The present work examines the aerodynamic impact of the variable chord turbine and compares it with one with a constant chord. Ideally, Wells rotor blades with variable chords perform better since they have an even axial velocity distribution on their leading edge. The variable chord rotor blade configurations differ from hub to tip with taper ratios (Chord at Tip/Chord at Hub) of 1.58 and 0.63. The computation is performed in ANSYS™ CFX 2023 R2 by solving three-dimensional, steady-state, incompressible Reynolds Averaged Navier–Stokes (RANS) equations coupled with a k-ω Shear Stress Transport (SST) turbulence model in a non-inertial reference frame rotating with the turbine. The accuracy of the numerical results was achieved by performing a grid independence study. A refined mesh showed good agreement with the available experimental and numerical data in terms of efficiency, torque, and pressure drop at different flow coefficients. A variable chord Wells turbine with a taper ratio of 1.58 had a peak efficiency of 59.6%, as opposed to the one with a taper ratio of 0.63, which had a peak efficiency of 58.2%; the constant chord Wells turbine only had a peak efficiency of 58.5%. Furthermore, the variable chord rotor with the higher taper ratio had a larger operating range than others. There are significant improvements in the aerodynamic performance of the modified Wells turbine, compared to the conventional Wells turbine, which makes it suitable for wave energy harvesting. The flow field investigation around the turbine blades was conducted and analyzed.
Research on the Control and Modulation Scheme for a Novel Five-Switch Current Source Inverter
Authors: Fu Tao , Gao Jihao , Liu Haiyan , Xia Bo
Published: July 2024

Different from the voltage source inverter (VSI), the current source inverter (CSI) can boost the voltage and eliminate the additional passive filter and dead time. However, the DC-side inductor current is not a real current source and is generated by a DC voltage supply and an inductor. Under different switching states, the DC-side inductor will be charged or discharged, which leads to the DC-side inductor current being discontinuous or increasing. To solve the control problem of the DC-side inductor current of the CSI, a novel single-phase CSI topology with five switching tubes for grid-connected applications is proposed. Firstly, the reference calculation method and the hysteresis loop control scheme for the DC-side inductor current are proposed, and the adjustable and constant DC-side inductor current are obtained. Since the PWM signals cannot be directly implemented to the switching tubes, the modulation strategy for the single-phase CSI is proposed in this paper. Then, an active damping method based on the feedback capacitor voltage is presented to suppress the resonance peak caused by the LC filter on the grid side. Finally, the math model of the AC-side structure is established, and the optimal proportional-resonant controller parameters’ design method is explored by the amplitude–frequency characteristic curves. The simulation and experiment are implemented for the proposed CSI topology. The results show that a high-quality power with a good control performance can be obtained with the proposed CSI topology.
Grid-Forming Control for Solar Generation System with Battery Energy Storage
Authors: Cai Yupeng , Yu Lujie , Wu Meng , Lv Shengyang , Fu Ziyu , Tong Wenhao , Li Wei , Shi Songjie
Published: July 2024

Solar generation systems with battery energy storage have become a research hotspot in recent years. This paper proposes a grid-forming control for such a system. The inverter control consists of the inner dq-axis current control, the dq-axis voltage control, the phase-locked loop (PLL) based frequency control, and the DC voltage control. The proposed control embeds the PLL into the grid-forming inverter control, offering the advantages of better synchronization and fault current-limiting capability. With the proposed control, the battery energy storage is able to provide inertial and primary frequency support during the grid frequency disturbance. Simulation models are established in PSCAD/EMTDC, and the results during the active power variation and AC voltage variation, the grid frequency disturbance, grid fault, and mode switch validate the effectiveness of the proposed control.
Computational Fluid Dynamic Investigation of Local Flow-Field Conditions in Lab Polymer Electrolyte Membrane Fuel Cells to Identify Degradation Stressors and Performance Enhancers
Authors: Bulgarini Margherita , Della Torre Augusto , Baricci Andrea , Grimaldi Amedeo , Marocco Luca , Mereu Riccardo , Montenegro Gianluca , Onorati Angelo
Published: July 2024

The use of polymer electrolyte membrane (PEM) fuel cells as an alternative to internal combustion engines can significantly contribute to the decarbonization of the transport sector, especially for heavy-duty applications. However, degradation is still an issue for this type of component, affecting their durability and performance. In this scenario, a detailed analysis of the anodic and cathodic distributors’ flow-field geometry may help to identify some local stressors that trigger the degradation mechanism, such as local hot spots and reactants not having a uniform distribution. A computational fluid dynamic (CFD) methodology is able to provide a volumetric description of a PEM fuel cell so it can be a useful tool to better understand the physical phenomena that govern the component operations. In this work, the open-source simulation library openFuelCell2 is adopted for a detailed analysis of two different PEM fuel cells characterized by standard distributor geometries, namely a parallel channel geometry and a serpentine configuration. The library, based on the OpenFOAM code, has been extended with a novel implementation accounting for the catalytic activity reduction due to the platinum oxide (PtOx) formation occurring under certain particular conditions. The adopted methodology is firstly validated resorting to experimental data acquired for the two different fuel cell configurations. The analysis highlights that the PtOx formation leads to a reduction in the fuel cell performance reaching up to 60–80% when operating at high voltages. Then, the effect of the distributor geometries on the component performance is investigated by resorting to in-plane and through-plane physical quantity distribution, such as reactant concentration, pressure or velocity fields. While the parallel flow channel configuration shows some diffusion losses under the rib, the serpentine channel geometry configuration can achieve some local performance peaks thanks to the convective flow in the gas diffusion layer (GDL) driven by local pressure gradients. Furthermore, the local enhancement in terms of higher current density under the rib is associated with an effective heat removal due to the high thermal capacity of the bipolar plate, avoiding the generation of local hot spots.
A Comprehensive Review of Syngas Production, Fuel Properties, and Operational Parameters for Biomass Conversion
Authors: Khlifi Saaida , Pozzobon Victor , Lajili Marzouk
Published: July 2024

This study aims to provide an overview of the growing need for renewable energy conversion and aligns with the broader context of environmentally friendly energy, specifically through producing syngas from biomass. Unlike natural gas, which is mainly composed of methane, syngas contains a mixture of combustible CO, H2, and CnHm. Therefore, optimizing its production requires a thorough examination of various operational parameters such as the gasifying agent, the equivalence ratio, the biofuel type, and the state, particularly in densified forms like pellets or briquettes. As new biomass sources are continually discovered and tested, operational parameters are also constantly evaluated, and new techniques are continuously developed. Indeed, these techniques include different gasifier types and the use or non-use of catalysts during biofuel conversion. The present study focuses on these critical aspects to examine their effect on the efficiency of syngas production. It is worth mentioning that syngas is the primary gaseous product from gasification. Moreover, it is essential to note that the pyrolysis process (prior to gasification) can produce, in addition to tar and char, a mixture of gases. The common feature among these gases is their versatility in energy generation, heat production, and chemical synthesis. The analysis encompasses the resulting gas features, including the yield and composition, mainly through the hydrogen-to-carbon monoxide ratio and the carbon monoxide-to-carbon dioxide ratio, as well as the lower heating value and considerations of the tar yield.
Comprehensive Experimental Study of Biomass Conversion Behavior: From Particle Phenomena to Reactor Scale
Authors: Silva João , Fraga Lelis , Teixeira Senhorinha , Teixeira José
Published: July 2024

During biomass combustion in a grate-fired boiler, each particle undergoes a sequence of different reactions, and the phenomena differ from the conversion of a single, thermally thin, particle. Hence, this paper aims to deepen the understanding of biomass conversion processes and provides valuable insights for advancing biomass-based energy systems. Firstly, the weight loss characteristics of the larger particles of eucalyptus, pine, acacia, and olive samples were investigated at different isothermal temperatures in a purpose-built reactor that simulates the devolatilization process in a controllable manner. As opposed to the thermogravimetric analysis using thermally thin particles, it was concluded that all fuels show that the combustion of large particles does not exhibit separate consecutive conversion stages, due to internal diffusion resistance. Furthermore, it was verified that the devolatilization rate depends mainly on the reactor temperature, and, consequently, the mass-loss profile is independent of the biomass type. In addition to these experiments, the composition of the gases over the devolatilization period was analyzed for the main fuel used in power plants, eucalyptus. Once again, a strong correlation to the reactor temperature was observed, with CO2 and CO always being the main devolatilization products. The temperature dependence of both compounds presented an increase from 8 to 13% between 600 and 800 °C for CO, while the CO2 yield only slightly increased from 11 to 12%. These observations were essential to identify the transport phenomena effect and the gaseous products released during the biomass combustion.
Soil pH and Nutrient Content Sustain Variability of Soil Bacterial Community Structure and Activity after Forest Clear-Cutting
Authors: Bereczki Katalin , Benke Attila , Tóth Endre György , Megyes Melinda , Korponai Kristóf , Szili-Kovács Tibor , Illés Gábor , Lados Botond Boldizsár , Márialigeti Károly
Published: July 2024

Clear-cutting is the most robust intervention in a forest ecosystem, causing marked changes in ecosystem processes. Although the effects of forest harvesting have been widely investigated, comparative studies can provide vital supplementary information concerning specific fields, including changes in soil microbiota structure and functioning. Our study examined the soil bacterial community composition, diversity, and activity of a mixed pedunculate oak stand over three years after clear-cutting based on 16S rRNA sequencing and substrate-induced respiration data. In addition, we conducted a yearly comparison with a control oak stand already in the regeneration phase. According to our results, the forest harvest caused only limited changes in the diversity, structure, and activity of the soil bacterial community of the oak stand, suggesting that soil parameters influence the soil bacterial community structure and functioning more significantly than the cessation of forest cover.
Experimental and Statistical Determination of Convective Heat and Mass Transfer Coefficients for Eucalyptus nitens Sawn Wood Drying
Authors: Rozas Carlos , Erazo Oswaldo , Ortiz-Araya Virna , Linfati Rodrigo , Montero Claudio
Published: July 2024

This study aimed to develop a model using experimentally obtained convective heat and mass transfer coefficients to predict the effect of temperature, humidity, and drying rate on wood drying. Tangential wood samples of Eucalyptus nitens (H. Deane & Maiden) were used in the investigation. The experimental design consisted of two temperature levels (40 °C and 55 °C), two relative humidity levels (55% and 75%), and two air velocity settings (2 m·s−1 and 3 m·s−1). The experiments were conducted under a constant evaporation rate, spanning the maximum and critical moisture content in the wood. A statistical model using multivariate regression was created to predict the convective heat and mass transfer coefficients. The results indicated that the experimental data and empirical correlations exhibited an error margin of 37.77% and 37.86%, respectively. A significant positive correlation was found between the convective heat transfer coefficient and air velocity, temperature, and relative humidity, while the convective mass transfer coefficient showed a significant positive correlation only with air velocity and temperature. The model predicted the convective heat and mass transfer coefficients with high accuracy and statistical significance. Using the proposed method, we successfully obtained both convective coefficients, which enable accurate description of heat and mass flow during the convective drying of Eucalyptus nitens wood.