bluuebunny/crossref_metadata_2025 huggingface dataset:
Biocompatibility and Corrosion of Microplasma-Sprayed Titanium and Tantalum Coatings versus Titanium Alloy
Authors: Alontseva Darya , Safarova (Yantsen) Yuliya , Voinarovych Sergii , Obrosov Aleksei , Yamanoglu Ridvan , Khoshnaw Fuad , Yavuz Hasan Ismail , Nessipbekova Assem , Syzdykova Aizhan , Azamatov Bagdat , Khozhanov Alexandr , Weiß Sabine
Published: February 2024

This study investigates the in vitro biocompatibility, corrosion resistance, and adhesion strength of a gas abrasive-treated Ti6Al4V alloy, alongside microplasma-sprayed titanium and tantalum coatings. Employing a novel approach in selecting microplasma spray parameters, this study successfully engineers coatings with tailored porosity, roughness, and over 20% porosity with pore sizes up to 200 μm, aiming to enhance bone in-growth and implant integration. This study introduces an innovative methodology for quantifying surface roughness using laser electron microscopy and scanning electron microscopy, facilitating detailed morphological analysis of both the substrate and coatings. Extensive evaluations, including tests for in vitro biocompatibility, corrosion resistance, and adhesive strength, revealed that all three materials are biocompatible, with tantalum coatings exhibiting superior cell proliferation and osteogenic differentiation, as well as the highest corrosion resistance. Titanium coatings followed closely, demonstrating favorable osteogenic properties and enhanced roughness, which is crucial for cell behavior and attachment. These coatings also displayed superior tensile adhesive strengths (27.6 ± 0.9 MPa for Ti and 28.0 ± 4.9 MPa for Ta), surpassing the ISO 13179-1 standard and indicating a robust bond with the substrate. Our findings offer significant advancements in biomaterials for medical implants, introducing microplasma spraying as a versatile tool for customizing implant coatings, particularly emphasizing the superior performance of tantalum coatings in terms of biocompatibility, osteogenic potential, and corrosion resistance. This suggests that tantalum coatings are a promising alternative for enhancing the performance of metal implants, especially in applications demanding high biocompatibility and corrosion resistance.
Linear Actuators in a Haptic Feedback Joystick System for Electric Vehicles
Authors: Daniel Kamil Andrzej , Kowol Paweł , Lo Sciuto Grazia
Published: February 2024

Several strategies for navigation in unfamiliar environments have been explored, notably leveraging advanced sensors and control algorithms for obstacle recognition in autonomous vehicles. This study introduces a novel approach featuring a redesigned joystick equipped with stepper motors and linear drives, facilitating WiFi communication with a four-wheel omnidirectional electric vehicle. The system’s drive units integrated into the joystick and the encompassing control algorithms are thoroughly examined, including analysis of stick deflection measurement and inter-component communication within the joystick assembly. Unlike conventional setups in which the joystick is tilted by the operator, two independent linear drives are employed to generate ample tensile force, effectively “overpowering” the operator’s input. Running on a Raspberry Pi, the software utilizes Python programming to enable joystick tilt control and to transmit orientation and axis deflection data to an Arduino unit. A fundamental haptic effect is achieved by elevating the minimum pressure required to deflect the joystick rod. Test measurements encompass detection of obstacles along the primary directions perpendicular to the electric vehicle’s trajectory, determination of the maximum achievable speed, and evaluation of the joystick’s maximum operational range within an illuminated environment.
Atomistic Study on Defect–Grain Boundary Interactions in TiVTa Concentrated Solid–Solution Alloys
Authors: Wang Linfeng , Zhao Yongpeng , Dou Yankun , He Xinfu , Zhang Zhongao , Chen Mengyao , Deng Huiqiu , Yang Wen
Published: February 2024

The elemental segregation behaviors and interactions between point defects and symmetrical tilt grain boundaries (GBs) in TiVTa concentrated solid–solution alloys (CSAs) have been studied through hybrid Monte Carlo/molecular dynamics (MC/MD) simulations. A pure V model, a random TiVTa CSA with randomly distributed elements, and an equilibrated TiVTa CSA with Ti segregation were constructed to investigate the influence of chemical disorder and local elemental segregation on defect–GB interactions. For defect–GB interactions, GBs interact more strongly with interstitials than with vacancies. Compared with the pure V, the vacancy absorption length scale of GBs is greater, whereas the interstitial absorption length scale of GBs is shorter in TiVTa CSAs due to the chemical fluctuation and local lattice distortion. This means a higher recombination efficiency of point defects in TiVTa CSAs. The elemental (Ti) segregation in TiVTa CSAs can further enhance the sink strength of GBs towards interstitials, while simultaneously reducing their sink strength towards vacancies. Consequently, the preference effects of GBs towards interstitials and vacancies are amplified in the equilibrated CSA due to local ordering, thereby reducing efficient defect annihilation around GBs. These results provide fundamental insights into the irradiation defect dynamics of CSAs with body-centered cubic (bcc) structure.
HELLP Syndrome and Differential Diagnosis with Other Thrombotic Microangiopathies in Pregnancy
Authors: Giannubilo Stefano Raffaele , Marzioni Daniela , Tossetta Giovanni , Ciavattini Andrea
Published: February 2024

Thrombotic microangiopathies (TMAs) comprise a distinct group of diseases with different manifestations that can occur in both pediatric and adult patients. They can be hereditary or acquired, with subtle onset or a rapidly progressive course, and they are particularly known for their morbidity and mortality. Pregnancy is a high-risk time for the development of several types of thrombotic microangiopathies. The three major syndromes are hemolysis, elevated liver function tests, and low platelets (HELLP); hemolytic uremic syndrome (HUS); and thrombotic thrombocytopenic purpura (TTP). Because of their rarity, clinical information and therapeutic results related to these conditions are often obtained from case reports, small series, registries, and reviews. The collection of individual observations, the evolution of diagnostic laboratories that have identified autoimmune and/or genetic abnormalities using von Willebrand factor post-secretion processing or genetic–functional alterations in the regulation of alternative complement pathways in some of these TMAs, and, most importantly, the introduction of advanced treatments, have enabled the preservation of affected organs and improved survival rates. Although TMAs may show different etiopathogenesis routes, they all show the presence of pathological lesions, which are characterized by endothelial damage and the formation of thrombi rich in platelets at the microvascular level, as a common denominator, and thrombotic damage to microcirculation pathways induces “mechanical” (microangiopathic) hemolytic anemia, the consumption of platelets, and ischemic organ damage. In this review, we highlight the current knowledge about the diagnosis and management of these complications during pregnancy.
A Rare Cause of Deep Vein Thrombosis in a Young Orchestra Conductor
Authors: Lungu Anca Mihaela , Andrei Irina Mariella , Uscoiu Gabriela , Grigore Mihai , Iliesiu Adriana Mihaela
Published: February 2024

Upper extremity deep vein thrombosis (DVT) of the axillary/subclavian veins is rare (5–10% of DVT). After clinical suspicion and duplex ultrasound, anticoagulation, surgical decompression and sometimes thrombolysis are mandatory due to complications. We discuss the case of a young healthy orchestra conductor with primary DVT of the left upper extremity and concomitant left shoulder musculo-tendinous traumatic injury. Symptoms of both conditions and subtle signs of upper extremity DVT delayed the diagnosis until full-blown DVT occurred. After successful anticoagulation and surgical TOS (thoracic outlet syndrome) decompression, evolution was favorable, without recurrent thrombosis.
Thermal Image Tracking for Search and Rescue Missions with a Drone
Authors: Yeom Seokwon
Published: February 2024

Infrared thermal imaging is useful for human body recognition for search and rescue (SAR) missions. This paper discusses thermal object tracking for SAR missions with a drone. The entire process consists of object detection and multiple-target tracking. The You-Only-Look-Once (YOLO) detection model is utilized to detect people in thermal videos. Multiple-target tracking is performed via track initialization, maintenance, and termination. Position measurements in two consecutive frames initialize the track. Tracks are maintained using a Kalman filter. A bounding box gating rule is proposed for the measurement-to-track association. This proposed rule is combined with the statistically nearest neighbor association rule to assign measurements to tracks. The track-to-track association selects the fittest track for a track and fuses them. In the experiments, three videos of three hikers simulating being lost in the mountains were captured using a thermal imaging camera on a drone. Capturing was assumed under difficult conditions; the objects are close or occluded, and the drone flies arbitrarily in horizontal and vertical directions. Robust tracking results were obtained in terms of average total track life and average track purity, whereas the average mean track life was shortened in harsh searching environments.
Detection Probability and Bias in Machine-Learning-Based Unoccupied Aerial System Non-Breeding Waterfowl Surveys
Authors: Viegut Reid , Webb Elisabeth , Raedeke Andrew , Tang Zhicheng , Zhang Yang , Zhai Zhenduo , Liu Zhiguang , Wang Shiqi , Zheng Jiuyi , Shang Yi
Published: February 2024

Unoccupied aerial systems (UASs) may provide cheaper, safer, and more accurate and precise alternatives to traditional waterfowl survey techniques while also reducing disturbance to waterfowl. We evaluated availability and perception bias based on machine-learning-based non-breeding waterfowl count estimates derived from aerial imagery collected using a DJI Mavic Pro 2 on Missouri Department of Conservation intensively managed wetland Conservation Areas. UASs imagery was collected using a proprietary software for automated flight path planning in a back-and-forth transect flight pattern at ground sampling distances (GSDs) of 0.38–2.29 cm/pixel (15–90 m in altitude). The waterfowl in the images were labeled by trained labelers and simultaneously analyzed using a modified YOLONAS image object detection algorithm developed to detect waterfowl in aerial images. We used three generalized linear mixed models with Bernoulli distributions to model availability and perception (correct detection and false-positive) detection probabilities. The variation in waterfowl availability was best explained by the interaction of vegetation cover type, sky condition, and GSD, with more complex and taller vegetation cover types reducing availability at lower GSDs. The probability of the algorithm correctly detecting available birds showed no pattern in terms of vegetation cover type, GSD, or sky condition; however, the probability of the algorithm generating incorrect false-positive detections was best explained by vegetation cover types with features similar in size and shape to the birds. We used a modified Horvitz–Thompson estimator to account for availability and perception biases (including false positives), resulting in a corrected count error of 5.59 percent. Our results indicate that vegetation cover type, sky condition, and GSD influence the availability and detection of waterfowl in UAS surveys; however, using well-trained algorithms may produce accurate counts per image under a variety of conditions.
Target Tracking Algorithm Based on Adaptive Strong Tracking Extended Kalman Filter
Authors: Tian Feng , Guo Xinzhao , Fu Weibo
Published: February 2024

Kalman filtering is a common filtering method for millimeter-wave traffic radars. The proposal is for an Adaptive Strong Tracking Extended Kalman Filter (EKF) algorithm that aims to address the issues of classic EKF’s low accuracy and lengthy convergence time. This method, which incorporates time-varying fading effects into the covariance matrix of the traditional EKF, is based on the ST algorithm. It allows the recalibration of the covariance matrix and precise filtering and state estimation of the target vehicle. By altering the fading and attenuating factors of the ST algorithm and using orthogonality principles, many fine-tuned fading factors produced from least-squares optimization are introduced together with regionally optimum attenuation factors. The results of Monte Carlo experiments indicate that the average velocity inaccuracy is reduced by at least 38% in comparison to existing counterparts. The results validate the efficacy of this methodology in observing vehicular movements in metropolitan regions, satisfying the prerequisites of millimeter-wave radar technology for traffic monitoring.
Asymmetric GaN High Electron Mobility Transistors Design with InAlN Barrier at Source Side and AlGaN Barrier at Drain Side
Authors: Lv Beibei , Zhang Lixing , Mo Jiongjiong
Published: February 2024

The InAlN/GaN HEMT has been identified as a promising alternative to conventional AlGaN/GaN HEMT due to its enhanced polarization effect contributing to higher 2DEG in the GaN channel. However, the InAlN barrier usually suffers from high leakage and therefore low breakdown voltage. In this paper, we propose an asymmetrical GaN HEMT structure which is composed of an InAlN barrier at the source side and an AlGaN barrier at the drain side. This novel device combines the advantages of high 2DEG density at the source side and low electrical-field crowding at the drain side. According to the TCAD simulation, the proposed asymmetric device exhibits better drain current and transconductance compared to AlGaN/GaN HEMT, and enhanced breakdown voltage compared to InAlN/GaN HEMT. The current collapse effects have also been evaluated from the process-related point of view. Possible higher interface traps related to the two-step epitaxial growth for the asymmetric structure fabrication will not exacerbate the current collapse and reliability.
Data-Driven Distributionally Robust Optimization-Based Coordinated Dispatching for Cascaded Hydro-PV-PSH Combined System
Authors: Zhang Shuai , Qiu Gao , Liu Youbo , Ding Lijie , Shui Yue
Published: February 2024

The increasing penetration of photovoltaic (PV) and hydroelectric power generation and their coupling uncertainties have brought great challenges to multi-energy’s coordinated dispatch. Traditional methods such as stochastic optimization (SO) and robust optimization (RO) are not feasible due to the unavailability of accurate probability density function (PDF) and over-conservative decisions. This limits the operational efficiency of the clean energies in cascaded hydropower and PV-enriched areas. Based on data-driven distributionally robust optimization (DRO) theory, this paper tailors a joint optimization dispatching method for a cascaded hydro-PV-pumped storage combined system. Firstly, a two-step model for a Distributed Renewable Optimization (DRO) dispatch is developed to create the daily dispatch plan, taking into account the system’s complementary economic dispatch cost. Furthermore, the inclusion of a complementary norm constraint is implemented to restrict the confidence set of the probability distribution. This aims to identify the optimal adjustment scheme for the day-ahead dispatch schedule, considering the adjustment cost associated with real-time operations under the most unfavorable distribution conditions. Utilizing the MPSP framework, the Column and Constraint Generation (CCG) algorithm is employed to resolve the two-stage dispatch model. The optimal dispatch schedule is then produced by integrating the daily dispatch plan with the adjustive dispatch scheme. Finally, the numerical dispatch results obtained from an actual demonstration area substantiate the effectiveness and efficiency of the proposed methodology.
Secure Healthcare Model Using Multi-Step Deep Q Learning Network in Internet of Things
Authors: Roy Patibandla Pavithra , Teju Ventrapragada , Kandula Srinivasa Rao , Sowmya Kambhampati Venkata , Stan Anca Ioana , Stan Ovidiu Petru
Published: February 2024

Internet of Things (IoT) is an emerging networking technology that connects both living and non-living objects globally. In an era where IoT is increasingly integrated into various industries, including healthcare, it plays a pivotal role in simplifying the process of monitoring and identifying diseases for patients and healthcare professionals. In IoT-based systems, safeguarding healthcare data is of the utmost importance, to prevent unauthorized access and intermediary assaults. The motivation for this research lies in addressing the growing security concerns within healthcare IoT. In this proposed paper, we combine the Multi-Step Deep Q Learning Network (MSDQN) with the Deep Learning Network (DLN) to enhance the privacy and security of healthcare data. The DLN is employed in the authentication process to identify authenticated IoT devices and prevent intermediate attacks between them. The MSDQN, on the other hand, is harnessed to detect and counteract malware attacks and Distributed Denial of Service (DDoS) attacks during data transmission between various locations. Our proposed method’s performance is assessed based on such parameters as energy consumption, throughput, lifetime, accuracy, and Mean Square Error (MSE). Further, we have compared the effectiveness of our approach with an existing method, specifically, Learning-based Deep Q Network (LDQN).
Nonlinear Magnetic Model of IPMSM Based on the Frozen Permeability Technique Utilized in Improved MTPA Control
Authors: Vučković Mladen , Popović Vladimir , Jerkan Dejan , Jarić Milica , Banović Milica , Vasić Veran , Marčetić Darko
Published: February 2024

In this paper, the enhanced nonlinear magnetic model of the low voltage interior permanent magnet synchronous machine (IPMSM) is developed using the frozen permeability (FP) technique in finite element analysis (FEA) FEMM 4.2 software. The magnetic model is derived by obtaining flux saturation maps for a wide range of dq stator currents. Furthermore, the FEA FP technique accounts for the corresponding offset in the flux maps due to the excitation of the permanent magnets, and well as for fitting the coefficients for the curve-fitting procedure. In order to demonstrate the usefulness of the proposed magnetic model, a nonlinear control strategy based on the maximum torque per ampere (MTPA) optimal algorithm for IPMSM is employed. The magnetic model and the MTPA control strategy are validated through a variety of computer simulations based on FEMM 4.2 and MATLAB R2023a software, as well as on a real IPMSM electric vehicle (EV) traction drive experimental setup.
Popularity-Debiased Graph Self-Supervised for Recommendation
Authors: Li Shanshan , Hu Xinzhuan , Guo Jingfeng , Liu Bin , Qi Mingyue , Jia Yutong
Published: February 2024

The rise of graph neural networks has greatly contributed to the development of recommendation systems, and self-supervised learning has emerged as one of the most important approaches to address sparse interaction data. However, existing methods mostly focus on the recommendation’s accuracy while neglecting the role of recommended item diversity in enhancing user interest and merchant benefits. The reason for this phenomenon is mainly due to the bias of popular items, which makes the long-tail items (account for a large proportion) be neglected. How to mitigate the bias caused by item popularity has become one of the hot topics in current research. To address the above problems, we propose a Popularity-Debiased Graph Self-Supervised for Recommendation (PDGS). Specifically, we apply a penalty constraint on item popularity during the data enhancement process on the user–item interaction graph to eliminate the inherent popularity bias. We generate item similarity graphs with the popularity bias removed to construct a self-supervised learning task under multiple views, and we design model optimization strategies from the perspectives of popular items and long-tail items to generate recommendation lists. We conduct a large number of comparison experiments, as well as ablation experiments, on three public datasets to verify the effectiveness and the superiority of the model in balancing recommendation accuracy and diversity.
Effect of the Degree of Hybridization and Energy Management Strategy on the Performance of a Fuel Cell/Battery Vehicle in Real-World Driving Cycles
Authors: Agati Giuliano , Borello Domenico , Migliarese Caputi Michele Vincenzo , Cedola Luca , Gagliardi Gabriele Guglielmo , Pozzessere Adriano , Venturini Paolo
Published: February 2024

The study utilizes open-access data to generate power demand curves for a hybrid automotive system, testing twelve configurations with three different energy management strategies and four values for the degree of hybridization (DOH), the latter representing the share of the total power of the vehicle powertrain supplied by the battery. The first control logic (Battery Main—BTM) uses mainly batteries to satisfy the power demand and fuel cells as backup, while in the other two controllers, fuel cells operate continuously (Fuel Cell Main—FCM) or within a fixed range (Fuel Cell Fixed—FCF) using batteries as backup. The results are assessed in terms of H2 consumption, overall system efficiency, and fuel cell predicted lifespan. The battery is heavily stressed in the BTM and FCF logics, while the FCM logic uses the battery only occasionally to cover load peaks. This is reflected in the battery’s State of Charge (SOC), indicating different battery stress levels between the BTM and FCF modes. The FCF logic has higher stress levels due to load demand, reducing battery lifetime. In the BTM and FCM modes, the fuel cell operates with variable power, while in the FCF mode, the fuel cell operates in a range between 90 and 105% of its rated power to ensure its lifetime. In the BTM and FCM modes, hydrogen consumption decreases at almost the same rate as the DOH increases, due to a decrease in battery capacity and a smaller amount of hydrogen being used to recharge it. In contrast, the FCF control logic results in a larger fuel consumption when the DOH decreases. In terms of FC durability, the FCF control logic performs better, with a predicted lifetime ranging from 1815 h for DOH = 0.5 to 2428 h for DOH = 0.1. The FCM logic has the worst performance, with a predicted lifetime of 800 to 808 h, being almost insensitive to the DOH variation. Simulations were performed on two different driving cycles, and similar trends were observed. Simulations taking into account fuel cell (FC) performance degradation showed an increase in hydrogen consumption of approximately 38% after 12 years. Overall, this study highlights the importance of optimizing control systems to improve the performance of fuel cell hybrid vehicles, also taking into account the component of performance degradation.
High-Performance Wireless Power and Data Transmission System for Medical Implant Devices Using ASK Modulation
Authors: Zhu Haoqi , Tahir Mustafa , Wu Xu , Hu Sideng
Published: February 2024

Wireless power and data transmission (WPDT) solutions for medical implants are highly desired. However, achieving a high-power transmission efficiency and data rate simultaneously over an inductive link remains a significant challenge. This paper presents an innovative WPDT circuit that incorporates additional MOSFETs with an inductor in a Class-E power amplifier (PA), achieving amplitude-shift keying (ASK) modulation to address this issue. Firstly, the efficiency of the inductive power transmission link and Class-E PA was analyzed, providing design insights. Then, leveraging the insights, the proposed circuit was designed in such a way that it could effectively switch between two load networks to maintain high transfer efficiency for ASK modulation. Based on the load networks, the relationship between introducing the inductor’s value and the data modulation index (MI) was derived to help achieve the desired high-power transmission efficiency. Additionally, the design and calculation of the proposed circuit are also presented. Finally, the proposed circuit was validated through simulations and experiments, demonstrating a power delivery to a load of 84.1 mW with a power transmission efficiency of 70.8% at a data rate and carrier frequency of 3 Mbps and 16 MHz, respectively. Furthermore, the bit error rate (BER) is less than 10−6 with an MI of 10%.
Investigation of the Combination Mechanism of Spontaneous Imbibition and Water Flooding in Tight Oil Reservoirs Based on Nuclear Magnetic Resonance
Authors: Tao Lei , Wang Longlong , Bai Jiajia , Zhang Na , Shi Wenyang , Zhu Qingjie , Xu Zhengxiao , Wang Guoqing
Published: February 2024

As conventional oil reservoirs are gradually being depleted, researchers worldwide are progressively shifting their focus towards the development and comprehensive study of tight oil reservoirs. Considering that hydraulic fracturing is one of the main approaches for developing tight sandstone reservoirs, it is of great significance to explore the mechanism of spontaneous imbibition and waterflooding behavior after hydraulic fracturing in tight oil reservoirs. This research delves into the analysis of tight sandstone core samples obtained from the Shahejie Formation in the Bohai Bay Basin. All core samples are used for a series of experiments, including spontaneous imbibition and water flooding experiments. An additional well-shut period experiment is designed to understand the impact and operational dynamics of well shut-in procedures in tight reservoir development. Utilizing nuclear magnetic resonance (NMR) technology, the pore sizes of a sample are divided into three types, namely, macropores (>100 ms), mesopores (10–100 ms), and micropores (<10 ms), to thoroughly assess the fluid distribution and changes in fluid signals during the spontaneous imbibition and water flooding stages. Experimental outcomes reveal that during the spontaneous imbibition stage, oil recovery ranges from 12.23% to 18.70%, predominantly depending on capillary forces. The final oil recovery initially rises and then falls as permeability decreases, while the contribution of micropores progressively grows as the share of mesopores and macropores deceases. With water flooding processes carried out after spontaneous imbibition, enhanced oil recovery is observed between 28.26% and 33.50% and is directly proportional to permeability. The well shut-in procedures can elevate the oil recovery to as high as 47.66% by optimizing energy balance.
Locational Role Analysis of Energy Storage Systems Based on Optimal Capacity Needs and Operations under High Penetration of Renewable Energy
Authors: Park Heejung
Published: February 2024

As the need for energy storage systems (ESSs) capacity is increasing due to high accommodation of renewable resources, it is crucial to analyze in which location and for what purpose the ESSs are required to achieve the highest efficiency. Investors and system operators can place and operate the ESSs as expected based on this analysis. Therefore, this study assesses the specific roles of ESSs in a grid system based on their optimal capacity needs, locations, and operations. A long-term simulation model using mixed-integer programming is proposed to obtain these optimal solutions, such as ESS capacity and operational schedules for energy and reserves. Four-week operational simulations are performed for each month using data from the California Independent System Operator. ESSs are placed at sites with solar photovoltaic (PV) systems or wind farms, at baseload generator buses, and at load buses to verify the role of ESSs, depending on the locational differences. The detailed roles are analyzed from the aspects of flexible capacity supply, reserve deployments, time-shifting renewable and thermal energy generation, and costs. The results show that the ESSs on the baseload generation side provide flexibility by time-shifting baseload generation and turn on baseload generators, even when the net load is small. For instance, the required capacity of the flexible thermal generators, such as natural gas turbine generators, is about 3004 MW without the ESS operations in May. When 450 MW ESSs colocated with solar PVs are operated, the required flexible capacity of the thermal generators is lowered to 2404 MW. Moreover, ESSs are highly utilized as a downward reserve provider, although their costs for reserves are higher than thermal generators.
Study on the near Wake Aerodynamic Characteristics of Floating Offshore Wind Turbine under Combined Surge and Pitch Motion
Authors: Leng Shudong , Cai Yefeng , Zhao Haisheng , Li Xin , Zhao Jiafei
Published: February 2024

Floating offshore wind turbines (FOWTs) may experience six degree of freedom (DoF) movements under the influence of environmental conditions. Different combinations of platform movements with the same amplitude and frequency may have distinct influences on the aerodynamic characteristics of the wind turbine. In this study, a detailed, full-scale CFD model of NREL 5 MW wind turbine is developed to investigate the specific aerodynamic and near wake characteristics under the influence of surge, pitch, and coupled surge–pitch platform motion based on the OpenFOAM tool box. It is clearly noted that different platform movements led to varying relative velocities of the blade, which affected the aerodynamic performance of wind turbines such as thrust, torque, and angle of attack (AOA). On the other hand, when the wind turbine was subjected to combined surge–pitch motion with the same phase, the wake velocity field fluctuated greatly, and the velocity at the center of the wake even exceeded the free flow velocity. Moreover, the platform movement affected the gap between the shed vortices. When the wind turbine moved forward, the gap between the vortices increased, while when the wind turbine moved backward, the gap between the vortices decreased or even converged, resulting in vortex–vortex interaction.
Effect of Machine Learning Algorithms on Prediction of In-Cylinder Combustion Pressure of Ammonia–Oxygen in a Constant-Volume Combustion Chamber
Authors: Fang Lijia , Singh Hardeep , Ohashi Takuma , Sanno Masato , Lin Guansen , Yilmaz Emir , Ichiyanagi Mitsuhisa , Suzuki Takashi
Published: February 2024

Road vehicles, particularly cars, are one of the primary sources of CO2 emissions in the transport sector. Shifting to unconventional energy sources such as solar and wind power may reduce their carbon footprints considerably. Consequently, using ammonia as a fuel due to its potential benefits, such as its high energy density, being a carbon-free fuel, and its versatility during storage and transportation, has now grabbed the attention of researchers. However, its slow combustion speed, larger combustion chamber requirements, ignition difficulties, and limited combustion stability are still major challenges. Therefore, authors tried to analyze the combustion pressure of ammonia in a constant-volume combustion chamber across different equivalence ratios by adopting a machine learning approach. While conducting the analysis, the experimental values were assessed and subsequently utilized to predict the induced combustion pressure in a constant-volume combustion chamber across various equivalence ratios. In this research, a two-step prediction process was employed. In the initial step, the Random Forest algorithm was applied to assess the combustion pressure. Subsequently, in the second step, artificial neural network machine learning algorithms were employed to pinpoint the most effective algorithm with a lower root-mean-square error and R2. Finally, Linear Regression illustrated the lowest error in both steps with a value of 1.0, followed by Random Forest.
How Does Renewable Energy Respond to Financial Globalization and Information and Communications Technology Trade?
Authors: Fan Chaoqun , Usman Ahmed
Published: February 2024

Policymakers are looking at renewable energy as a substitute for traditional fossil fuels due to the growing concern about climate change and sustainable development. However, in the case of Asian countries, nothing is known about how ICT trade and financial globalization affect renewable energy consumption. To fill this gap, we have gathered data across 24 Asian economies, and a dynamic panel data approach known as GMM panel VAR is applied. The key outcomes of the GMM panel VAR underscore that ICT trade, financial globalization, and GDP favorably impact the current renewable energy consumption. Furthermore, the panel causality results indicate bidirectional causality between ICT trade, financial globalization, and renewable energy consumption. These findings have policy-relevant implications, highlighting the significance of financial liberalization and ICT-enabled trade in promoting renewable energy usage in Asian nations.
Reuse and Valorization of Solid Digestate Ashes from Biogas Production
Authors: Mammarella Daniel , Di Giuliano Andrea , Gallucci Katia
Published: February 2024

Digestate is produced in large quantities by the anaerobic digestion process, which is recognized to be a promising technology for producing bioenergy from biological waste. Digestate is a highly humid by-product containing organic and inorganic substances, including nutrients that make it suitable for soil applications. However, it can be considered a high-risk environmental contaminant if it is not correctly treated. For these reasons, thermochemical treatment is one of the alternatives for valorizing the digestate, leading to a high ash quantity. This review aims to investigate the formation of ash derived from thermochemical valorization treatments of digestate. Furthermore, considering the compositions of the elements present in these ashes, an additional objective is to identify possible prospects for the reuse of these ashes following a circular economy approach.
A Layered Parallel Equaliser Based on Flyback Transformer Multiplexed for Lithium-Ion Battery System
Authors: Liu Hongrui , Wei Xiangyang , Ai Junjie , Yang Xudong
Published: February 2024

An effective equaliser is crucial for eliminating inconsistencies in the connected serial batteries and extending the life of the battery system. The current equalisers generally have the problems of low equalisation efficiency, slow equalisation speed, and complex switching control. A layered parallel equaliser based on a flyback transformer multiplexed for a lithium-ion battery system is proposed. The equaliser employs both hierarchical and parallel equalisation techniques, allowing for simultaneous processing of multiple objectives. This enhances both the efficiency and speed of the equalisation process. The efficiency of equalisation can be further improved by implementing PWM control with deadband complement. Additionally, the flyback transformer serves as an energy storage component for both layers of the equalisation module, resulting in a significant reduction in the size and cost of the equaliser. The circuit topology of the equaliser is presented, and its operational principle, switching control, and equalisation control strategy are analysed in detail. Finally, an experimental platform consisting of six lithium-ion batteries is constructed, and equalisation experiments are conducted to verify the advantages of the proposed equaliser in terms of equalisation speed, efficiency, and cost.
Interval State Estimation of Electricity-Gas Systems Considering Measurement Correlations
Authors: Huang Yan , Feng Lin
Published: February 2024

The popularization of electricity-gas systems leads to increasing demand for state management of systems. However, the existence of neglected measurement correlations brings uncertainties to the electricity-gas systems state estimation. In this paper, an interval state estimation method that considers measurement correlations existing in the electricity-gas systems is presented. We derive the linear measurement model for the electricity-gas systems through Taylor series expansion and estimate the measurement variance-covariance matrix with measurement correlations. The system parameter matrix and the measurement variance-covariance matrix containing measurement correlations are combined into an interval, and the interval state matrix considering measurement correlations is constructed. Then, the linear equations for the state estimation interval considering measurement correlations are established based on the measurement containing correlations and interval state matrix; as a result, the electricity-gas system state estimation model containing measurement correlations is established. In addition, a method for determining the range of state estimation intervals is proposed. Numerical tests on an integrated electricity-gas system comprising a 10-node natural gas network and IEEE 30-bus system indicate that the proposed approach has more advantages over the UT+KO approach in computation accuracy and computation efficiency.
An Autonomous Distributed Coordination Strategy for Sustainable Consumption in a Microgrid Based on a Bio-Inspired Approach
Authors: García Marcel , Aguilar Jose , R-Moreno María D.
Published: February 2024

Distributed energy resources have demonstrated their potential to mitigate the limitations of large, centralized generation systems. This is achieved through the geographical distribution of generation sources that capitalize on the potential of their respective environments to satisfy local demand. In a microgrid, the control problem is inherently distributed, rendering traditional control techniques inefficient due to the impracticality of central governance. Instead, coordination among its components is essential. The challenge involves enabling these components to operate under optimal conditions, such as charging batteries with surplus solar energy or deactivating controllable loads when market prices rise. Consequently, there is a pressing need for innovative distributed strategies like emergent control. Inspired by phenomena such as the environmentally responsive behavior of ants, emergent control involves decentralized coordination schemes. This paper introduces an emergent control strategy for microgrids, grounded in the response threshold model, to establish an autonomous distributed control approach. The results, utilizing our methodology, demonstrate seamless coordination among the diverse components of a microgrid. For instance, system resilience is evident in scenarios where, upon the failure of certain components, others commence operation. Moreover, in dynamic conditions, such as varying weather and economic factors, the microgrid adeptly adapts to meet demand fluctuations. Our emergent control scheme enhances response times, performance, and on/off delay times. In various test scenarios, Integrated Absolute Error (IAE) metrics of approximately 0.01% were achieved, indicating a negligible difference between supplied and demanded energy. Furthermore, our approach prioritizes the utilization of renewable sources, increasing their usage from 59.7% to 86.1%. This shift not only reduces reliance on the public grid but also leads to significant energy cost savings.
Molecular and Carbon Isotopic Compositions of Crude Oils from the Kekeya Area of the Southwest Depression, Tarim Basin: Implications for Oil Groups and Effective Sources
Authors: Gao Xiaojie , Xiao Qilin , Ge Zhushi , Cai Suyang , Zhang Haizhu , Wang Xiang , Xu Zhenping , Wang Zhanghu , Xie Xiaomin , Meng Qiang
Published: February 2024

Molecular and stable carbon isotopic compositions of 32 crude oils from the Kekeya area of the Southwest Depression, Tarim Basin, were analyzed comprehensively to clarify oil groups and trace oil sources. The results indicate that lacustrine shale sequences within the Upper-Middle Permian Pusige Formation (P3–2p) are the major effective oil sources; the thermal maturation effects exert the crucial impact on geochemical compositions of crude oils. In the Kekeya structural belt, crude oils produced from the Lower-Neogene, Middle-Paleogene and Middle-Cretaceous sandstone reservoirs were generated mainly from deeply buried P3–2p at the late-to-high maturity stage. These condensates are depleted in terpanes, steranes and triaromatic steranes and enriched in adamantanes and diamantanes. The evaluated thermal maturity levels of crude oils by terpanoids and steranes are generally lower than that of diamondoids, implying at least two phases of oil charging. In the Fusha structural belt, oils produced from the Lower-Jurassic reservoirs (J1s) of Well FS8 were generated from the local P3–2p at the middle to late mature stage. On the contrary, these oils are relatively rich in molecular biomarkers such as terpanes and steranes and depleted in diamondoids with only adamantanes detectable. The P3–2p-associated oils can migrate laterally from the Kekeya to Fusha structural belt, but not to the location of Well FS8. The Middle-Lower Jurassic (J1–2) lacustrine shales as the major oil sources are limited to the area around Well KS101 in the Kekeya structural belt. Crude oils originated from J1–2 and P3–2p can mix together within the Cretaceous reservoirs of Well KS101 by presenting the concurrence of high concentrations of terpane and sterane biomarkers and diamondoids as well as 2–4% 13C-enriched n-alkanes than those of P3–2p derived oils. This study provides a better understanding of hydrocarbon sources and accumulation mechanisms and hence petroleum exploration in this region.
A Study of a Two-Phase Heat Transfer Mechanism in a Vertical Sintering Cooling Furnace
Authors: Xu Weihui , Wang Qinbao , Zhen Juan , Wang Weishu , Peng Yan , Tian Boyan , Ruan Yushuai , Li Renjie
Published: February 2024

In order to explore the law of gas–solid countercurrent cooling heat transfer in a vertical sinter cooling furnace at a high temperature, based on the Euler model and the local non-thermodynamic equilibrium theory, an exergy efficiency model was built to evaluate the heat transfer process in the vertical sinter cooling furnace with different parameter changes. It was found that the inlet temperature of cooling air and sinter inlet temperature are the main factors affecting the temperature field and gas–solid heat transfer characteristics in the furnace. Under the conditions of each parameter, the cooling air temperature presents a radial “M” shape distribution. The axial cooling section is the most intense area of gas–solid heat transfer, and this part has the best heat transfer effect. When the inlet temperature of cooling air and the inlet temperature of sinter increase, the outlet temperature of sinter and the outlet temperature of cooling air increase. When the sinter equivalent diameter increases, the cooling air outlet temperature decreases gradually, while the sinter outlet temperature increases gradually. When the diameter and height of the cooling section increase, respectively, the outlet temperature of the sinter decreases and the outlet temperature of the cooling air increases. Based on dimensional analysis, the heat transfer correlation formula suitable for certain test conditions is obtained.
Assessing the Effectiveness of an Innovative Thermal Energy Storage System Installed in a Building in a Moderate Continental Climatic Zone
Authors: Coelho Luis , Koukou Maria K. , Konstantaras John , Vrachopoulos Michail Gr. , Rebola Amandio , Benou Anastasia , Karytsas Constantine , Tourou Pavlos , Sourkounis Constantinos , Gaich Heiko , Goldbrunner Johan
Published: February 2024

In the present work, the operating results from an innovative, renewable, energy-based space-heating and domestic hot water (DHW) system are shown. The system used solar thermal energy as its primary source and was assisted by a shallow geothermal application in order to accommodate the space-heating and DHW needs of a domestic building in Austria. The system incorporated phase-change materials (PCMs) in specially designed containers to function as heat-storage modules and provide an energy storage capability for both the space-heating and DHW subsystems. This system was designed, implemented, and tested under real operating conditions in a building for a period of one year. The operating and energy results for the system are demonstrated in this work. The system was compared with a conventional one, and a reduction in the primary energy consumption equal to 84.3% was achieved. The maintenance and operating costs of the system were reduced by 79.7% compared to the conventional system, thus significantly contributing to the NZEB target of the building. The newly proposed system, although presenting an increased operating complexity, utilizes an innovative self-learning control system that manages all of its operations. The combination of a solar thermal energy source with thermal energy storage increases the use of renewable energy by extending the capacity of the system beyond the solar hours and using excess solar energy for space-heating needs. The thermal energy storage unit also increases the energy and economic efficiency of the geothermal heat pump by operating it during the hours of a reduced electricity tariff and using the stored energy during hours of a high electricity demand. The cost for the installation of such a system is higher than a conventional one, but due to the significantly decreased operating costs, the pay-back period was calculated to be 8.7 years.
Petrophysical and Geochemical Investigation-Based Methodology for Analysis of the Multilithology of the Permian Longtan Formation in Southeastern Sichuan Basin, SW China
Authors: Zhang Shengqi , Liu Jun , Li Li , Kassabi Nadhem , Hamdi Essaieb
Published: February 2024

Against the backdrop of the national strategic goals of carbon peaking and carbon neutrality, the imperative for China’s low-carbon new energy transformation is evident. Emerging as an efficient and clean new energy source, the coal-based “three gases” (coalbed methane, tight sandstone gas, and shale gas) have gained prominence. Nevertheless, the current exploration of the coal-based “three gases” is limited to individual reservoirs, posing challenges to achieving overall extraction efficiency. The primary obstacle lies in the conspicuous disparities in gas content among different reservoirs, with the causes of such disparities remaining elusive. To address this issue, this study focused on the Permian Longtan Formation (coal, shale, and tight sandstone) in the southeastern Sichuan Basin. Through a comparative analysis of the mineral composition, organic geochemical features, and pore structure characteristics, this study aimed to delineate reservoir variations and establish a foundation for the simultaneous exploration and exploitation of the coal-based “three gases”. The research findings revealed that the differences in reservoir characteristics account for the variations in gas content among coal, shale, and tight sandstone. The mineral composition of the rock formations in the study area primarily consists of quartz, feldspar, clay minerals, pyrite, calcite, and dolomite. By comparison, the coal samples from the four major coal seams in the study area exhibited relatively large pore sizes, which are favorable for gas accumulation.