Energy Science & Engineering最新文献

{"title":"Exploring Review of Advancements in Fast-Charging Techniques and Infrastructure for Electric Vehicles Revolution","authors":"Ahmed Zentani,&nbsp;A. M. Almaktoof,&nbsp;M. T. E. Kahn","doi":"10.1002/ese3.70051","DOIUrl":"https://doi.org/10.1002/ese3.70051","url":null,"abstract":"<p>The rapid growth of the electric vehicle (EV) industry has increased the demand for efficient and reliable fast-charging infrastructure. This paper comprehensively reviews advancements in fast-charging techniques, focusing on DC fast charging, evolving standards, and charging modes. A detailed analysis of on-board and off-board EV chargers is presented, including DC–DC conversion stages with a comparison of isolated and non-isolated topologies. Key control strategies, such as voltage and current regulation and AI-driven approaches, are examined to optimize performance and reliability. Thermal management strategies using advanced sensors to enhance safety and battery longevity are also discussed. This paper highlights recent research contributions and emerging challenges, with insights into infrastructure development, energy storage integration, and policy implications. Notably, projections indicate that global EV sales could rise to 35% by 2030, with fast-charging infrastructure supporting charging times as low as 15 min for 80% battery capacity. Advancements in bidirectional charging and AI-driven optimization are shaping the next generation of smart EV charging stations. This review serves as a valuable resource for researchers, engineers, and policymakers engaged in EV technology and infrastructure development.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"13 6","pages":"3437-3447"},"PeriodicalIF":3.5,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70051","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144244999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Experimental Study on Instability Mechanism of Red Shale Roadway Under Dynamic Disturbance","authors":"Xuewu Wu,&nbsp;Zhenqian Ma,&nbsp;Jinlian Zhou,&nbsp;Chunhng Mao,&nbsp;Jimin Zhang","doi":"10.1002/ese3.70043","DOIUrl":"https://doi.org/10.1002/ese3.70043","url":null,"abstract":"<p>To delve into the instability mechanism of the surrounding rock in red shale roadways, a bespoke device was chosen to fabricate a physical model, and a similar experiment was conducted with a blasting-induced disturbance. A meticulous examination was performed on the evolution of surface fractures and the macroscopic failure patterns of the surrounding rock in conjunction with the temperature data gathered via infrared thermal imaging. In accordance with the similarity principle, five perturbation sources were strategically positioned on either side of the roadway, at the haunches, and at a location three times the roadway diameter away from the roof, aiming to comprehensively investigate the root causes of instability under dynamic loading conditions. Simultaneously, a 30° inclined rock layer model was developed using numerical simulation techniques to contrast the alterations in stress, displacement, and other relevant aspects of the surrounding rock under both static and dynamic loads. External dynamic disturbances were then applied to probe the deformation behavior. The experimental results revealed that, subsequent to applying a dynamic load at the midpoint of the left rib of the model, the horizontal and vertical displacements of the surrounding rock augmented, whereas the displacement distribution pattern exhibited minimal alteration. Under static load conditions, the displacement of the left rib surged by 22.5%, that of the right rib climbed by 20.6%, the roof displacement expanded by 33%, and the floor displacement grew by 12.2%, with the peak acceleration at the left rib being the most prominent.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"13 5","pages":"2440-2454"},"PeriodicalIF":3.5,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70043","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143919945","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Blended Ensemble Learning for Robust Normal Behavior Modeling of Wind Turbines","authors":"Jianghao Zhu,&nbsp;Tingting Pei,&nbsp;Le Su,&nbsp;Bin Lan,&nbsp;Wei Chen","doi":"10.1002/ese3.70055","DOIUrl":"https://doi.org/10.1002/ese3.70055","url":null,"abstract":"<p>The increasing scale of wind farms demands more efficient approaches to turbine monitoring and maintenance. Here, we present an innovative framework that combines enhanced kernel principal component analysis (KPCA) with ensemble learning to revolutionize normal behavior modeling (NBM) of wind turbines. By integrating random kitchen sinks (RKS) algorithm with KPCA, we achieved a 25.21% reduction in computational time while maintaining model accuracy. Our mixed ensemble approach, synthesizing LightGBM, random forest, and decision tree algorithms, demonstrated exceptional performance across diverse operational conditions, achieving <i>R</i>² values of 0.9995 in primary testing. The framework reduced mean absolute error by 25.1% and mean absolute percentage error by 33.4% compared to conventional methods. Notably, when tested across three distinct operational environments, the model maintained robust performance (<i>R</i>² &gt; 0.97), demonstrating strong generalization capability. The system automatically detects anomalies using a 0.1% threshold, enabling real-time monitoring of 78 variables across 136,000+ operational records. This scalable approach integrates seamlessly with existing SCADA infrastructure, offering a practical solution for large-scale wind farm management. Our findings establish a new paradigm for wind turbine monitoring, combining computational efficiency with unprecedented accuracy in normal behavior prediction.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"13 5","pages":"2565-2584"},"PeriodicalIF":3.5,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70055","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143919943","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Estimation of Daily Photovoltaic Power One Day Ahead With Hybrid Deep Learning and Machine Learning Models","authors":"Tuba T. Ağır","doi":"10.1002/ese3.1994","DOIUrl":"https://doi.org/10.1002/ese3.1994","url":null,"abstract":"<p>In this study, hybrid LSTM-SVM and hybrid LSTM-KNN models were developed to predict hourly PV power one day ahead. The performances of these hybrid models were compared with K-nearest neighbors (KNN), long short-term memory (LSTM), and support vector machine (SVM) models. The input data of these models were pressure, cloudiness, humidity, temperature, and solar intensity, while the output data was the daily photovoltaic (PV) power one day ahead. The performances of the models were evaluated using mean square error (MSE), root mean square error (RMSE), normalized root mean square error (NRMSE), and peak signal-to-noise ratio (PSNR). The prediction accuracies of hybrid LSTM-KNN, LSTM, KNN, hybrid LSTM-SVM, and SVM were 98.72%, 95.8%, 90.25%, 76.3%, and 48.87%, respectively. Hybrid LSTM-KNN predicted the daily PV power of the day ahead with higher accuracy than LSTM, KNN, SVM, and hybrid LSTM-SVM. The effect of input variables on output variables was examined with sensitivity analysis. Sensitivity analyses showed that the most important meteorological data affecting the daily PV power one day ahead was solar intensity with a rate of 95%.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"13 4","pages":"1478-1491"},"PeriodicalIF":3.5,"publicationDate":"2025-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.1994","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143852830","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mechanical Mechanism of Surrounding Rock Failure and Stability Control for Gob-Side Entry Driving Near an Advancing Working Face","authors":"Delong Cui,&nbsp;Yujiang Zhang,&nbsp;Shuai Zhang,&nbsp;Xiangye Wu,&nbsp;Qian Wang,&nbsp;Bingyuan Cui,&nbsp;Defu Zhu","doi":"10.1002/ese3.70057","DOIUrl":"https://doi.org/10.1002/ese3.70057","url":null,"abstract":"<p>Addressing the challenges of surrounding rock control in gob-side entry driving near an advancing working face affected by adjacent working faces and gobs, taking 5104 return airway of No.1 well in Checun Coal Mine as the background, using theoretical analysis, numerical simulation, and field measurement methods, the reasonable size of coal pillar for roadway protection is judged, the spatial stage evolution law of surrounding rock plastic zone in recovery mining roadway excavation is obtained, the mechanical mechanism of distribution characteristics change of surrounding rock plastic zone in recovery mining roadway excavation is revealed and the method of graded reinforcement and support for roadway surrounding rock is put forward and applied. The results showed that: (1) By establishing the mechanical model of gob-side entry-pillar surrounding rock structure and comparing the distribution characteristics of plastic zone in roadway excavation with different coal pillar widths, it is judged that the reasonable size of coal pillar is 12 m. The top angle of coal wall and the bottom angle of coal pillar are the key control parts of surrounding rock stability in roadway driving engineering. (2) The plastic zone of surrounding rock in roadway excavation shows five stages in axial direction, and the whole shows that the smaller the width of coal pillar, the larger the peak value of deviator stress in surrounding rock of roadway, the larger the gap, and the angle of maximum principal stress gradually deflects from horizontal to vertical direction, which leads to the increase of plastic zone range and the change of shape from symmetry to asymmetry. (3) The method of reinforcing support by stages is put forward, and the industrial verification of the proposed scheme is carried out. The deformation of surrounding rock of roadway tends to be stable and the control effect of surrounding rock is good.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"13 6","pages":"2631-2646"},"PeriodicalIF":3.5,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70057","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144244946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Method for Predicting Different Types of Natural Fractures in Tight Sandstone Based on the Secondary Rescaled Range Analysis of Logging Curves: A Case Study From the Chang 7 Member in Huaqing Oilfield, Ordos Basin, China","authors":"Zikang Xiao,&nbsp;Wenlong Ding,&nbsp;Arash Dahi Taleghani,&nbsp;Liu Jingshou,&nbsp;Chong Xu,&nbsp;Huiran Gao,&nbsp;Wenwen Qi,&nbsp;Xiangli He","doi":"10.1002/ese3.70034","DOIUrl":"https://doi.org/10.1002/ese3.70034","url":null,"abstract":"<p>Currently, there are various methods for predicting natural fractures using logging data, however these methods are primarily for predicting the number and location of fractures. This is making it difficult to determine fracture types. This paper introduces the R/S-FD method, and combined with the natural fracture development pattern in the study area, secondary R/S analysis was introduced to construct the Secondary R/S-FD method. This method overcomes the limitations of traditional R/S-FD methods that can only predict the location of fractures and cannot predict the type of fractures. After eliminating systematic errors, the prediction accuracy of the Secondary R/S-FD method for bedding fractures and high-angle fractures reaches 73% and 74%, respectively. By analyzing the fracture development characteristics of 23 wells in the study area, the research provided insights into the development characteristics of bedding fractures and high-angle fractures in oil layers within the region. The secondary R/S-FD method is a precise, fast, and cost-effective approach for predicting the development characteristics of different types of natural fractures. The next step involves leveraging a large number of fracture prediction cases as the data foundation, based on big data analysis and machine learning techniques, to establish a correlation between the F value and fracture type and number to enabling more accurate predictions of the types and quantities of natural fractures.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"13 4","pages":"2045-2062"},"PeriodicalIF":3.5,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70034","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143852627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analysis of Geological Characteristics and Reservoir Potential Formation Damage Factors of Shallow Low-Temperature Low-Pressure Low-Permeability Sandstone Reservoir","authors":"Yanfei Li,&nbsp;Lizhi Yuan,&nbsp;Tao Wang,&nbsp;Wei Liu,&nbsp;Xingbin Zhao,&nbsp;Lanling Shi,&nbsp;Wei Huang,&nbsp;Yu Wang","doi":"10.1002/ese3.2027","DOIUrl":"https://doi.org/10.1002/ese3.2027","url":null,"abstract":"<p>The C-S reservoir in the YQ district of Ordos basin, China, is located at a relatively shallow depth (240–720 m), with an original pressure coefficient of approximately 0.85 for the oil layer. Calculations indicate that the initial pressure of the oil layer ranges from 4.1 to 6.0 MPa, averaging 4.75 MPa, with an average temperature of 30°C. The reservoir is classified as shallow, low-pressure, low-temperature sandstone. This research examines the C-S tight sandstone oil reservoir located in the Ordos Basin, providing an in-depth analysis of its mineral and rock composition along with its porosity and permeability characteristics. Through the analysis of the microscopic geological features of the reservoir, significant geological factors that may contribute to reservoir degradation are identified. Research shows that the C-S reservoir has an average porosity of 8.39%, average permeability of 0.54 × 10⁻³ μm², a micro-thin-necked pore type, and a median pore radius of 1.9060 μm. The reservoir exhibits strong heterogeneity, characterized by low porosity and permeability. Laboratory experiments revealed sensitivity characteristics including weak sensitivity to velocity and water, as well as moderate sensitivity to acid and salt. Water-phase seal test results show that the self-absorption rate decreases to less than 0.1 g/h within about 12 h, leading to significant water-phase seal formation damage due to high water saturation (above 45%) within a short time. The research suggests that limited fluid passageways in the reservoir result in insufficient in situ energy for fluid migration and increased viscosity, which complicates the process of returning fractured reservoirs to their original state after digitalization.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"13 4","pages":"1544-1554"},"PeriodicalIF":3.5,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.2027","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143852998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Energy and Exergy Efficiency Analysis of an Ejector-Expansion Refrigeration Cycle Using the Working Fluid R134a and Its Potential Substitutes","authors":"Xiaoqin Liu,&nbsp;Weibin Wang,&nbsp;Jianyong Wang","doi":"10.1002/ese3.70039","DOIUrl":"https://doi.org/10.1002/ese3.70039","url":null,"abstract":"<p>This paper proposes an ejector-expansion refrigeration cycle (EERC) with two evaporating temperatures to recover partial expansion work and greatly reduces the throttling loss of the other expansion valve connected to the evaporator compared with the conventional bievaporator refrigeration cycle (CBEC). Furthermore, R134a will be phased out due to its high global warming potential, while the mixture refrigerants of R1234yf, R1234ze, and R152a were considered as potential alternatives. The energy and exergy analysis methods are used to evaluate and compare the performance of two cycles and seven kinds of different refrigerants. Results show that the coefficient of performance (COP) and exergy efficiency of EERC are 17.1% and 16.4% higher than those of CBEC, and the total exergy loss can be reduced by 26.1% under given operating conditions. The drop-in analysis is carried out for equal operating conditions, and the EERC performances of mixtures are analyzed. The mixture refrigerants of R1234yf R152a/R1234yf/R1234ze (mass fraction of 0.4/0.3/0.3) and R134a/R1234yf (mass fraction of 0.9/0.1) appear to be a good candidate for drop-in replacement of R134a due to similar COP, volumetric cooling capacity, and exergy efficiency.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"13 5","pages":"2389-2400"},"PeriodicalIF":3.5,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70039","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143919788","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reasonable Intake and Exhaust Processes Scheduling of Two-Stroke Free Piston Linear Generator for Intelligent New Energy Vehicles","authors":"Dequan Zeng,&nbsp;Jun Lu,&nbsp;Yiming Hu,&nbsp;Peizhi Zhang,&nbsp;Jinwen Yang,&nbsp;Qin Yu,&nbsp;Xiaoliang Wang","doi":"10.1002/ese3.70042","DOIUrl":"https://doi.org/10.1002/ese3.70042","url":null,"abstract":"<p>Considered a promising power plant offering 25% higher efficiency than conventional reciprocating engines, the free piston linear generator (FPLG) has garnered significant attention due to its breakthrough design that eliminates the crank-connecting rod, thereby achieving enhanced efficiency. However, this structural innovation is a double-edged sword, while having the advantages such as compact structure and short transfer path to reduce energy loss, it inevitably makes the stability of the system sensitive to the operating parameters of the intake and exhaust process, which is extremely easy to lead to instability shutdown or knock. Aiming at scheduling the intake and exhaust processes rationally for system stabilization, a fast numerical method is proposed, which is different from the existing research methods. It does not need to rely on extremely time-consuming and complex CFD models, while taking into account the intake and exhaust processes as a whole rather than treating each as a separate part. The fast numerical method mainly consists of four steps. First, the gas mass variations in-cylinder and in-port due to fuel injection quality are defined. Second, gas flow is established in the valve geometry and operation pressure. Employed gas mass and gas flow, the intake pressure, the exhaust pressure, the allowable duration, and the time consumption would be settled. Third, the total power subsection is used to compute certain fuel quality. Finally, the piston dynamics are applied to calculate piston displacement for objecting valve operation and piston velocity for simulating FPLG output power. The results show that the cyclic fuel injection quality is 42–53 mg for the output power about 12.5 kW, and total efficiency about 35.5%; the intake pressure would be not less than 1.83 atm when the compression ratio is from 8 to 10 and the exhaust pressure ranges from 3.78 to 6 atm.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"13 5","pages":"2428-2439"},"PeriodicalIF":3.5,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70042","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143919755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Systematic Literature Review of Low-Carbon Technology Innovation: 2013–2022","authors":"Yifan Li,&nbsp;Mingmei Sun,&nbsp;Yongxin Huang,&nbsp;Yu Wang,&nbsp;Lihua Ma,&nbsp;Huizhe Yan,&nbsp;Yufei Chen","doi":"10.1002/ese3.70041","DOIUrl":"https://doi.org/10.1002/ese3.70041","url":null,"abstract":"<p>In the process of low-carbon globalization, low-carbon technological innovation has received increasing attention as a key driver of economic decarbonization and low-carbon transition. Despite the self-evident importance of this field, systematic research has yet to be conducted in depth. In this study, bibliometric tools such as CiteSpace and VOSviewer were used to search the relevant literature between 2013 and 2022, covering databases such as Elsevier, Springer, Emerald, Wiley, Nature, and Science, and 27,775 articles with top 30% citation rates were collected. The results of the study show that China has maintained its position as a global leader in the field of research. The results of the study show that while China maintains its position as the world's largest carbon emitter, it also has one of the highest numbers of academic papers in the world, revealing the link between carbon emissions and low-carbon technological innovation. The Beijing Institute of Technology, the Chinese Academy of Sciences, and the International University of Cyprus are the most active institutions in the field, while Renewable and Sustainable Energy Review and Energy Policy are the most cited journals. An analysis of the literature and keywords reveals that the research hotspots in the field include “economic growth”, “financial development” and “economic complexity”, while emerging themes include “Carbon dioxide emissions”, “renewable energy,” and “economic growth.” These trends indicate a growing interest in low-carbon technologies and renewable energy in developing countries. This study not only deepens the understanding of the field, but also provides important guidance for future research.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"13 5","pages":"2415-2427"},"PeriodicalIF":3.5,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70041","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143919841","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}