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SSRN 2024年

作者： Xie, Wenlong Gao, Xinlei Zhang, Zhengjie Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology China Department of Mechanical Engineering Imperial College London LondonSW7 2AZ United Kingdom School of Transportation Science and engineering Beihang University Beijing100191 China

The thermal characteristics of lithium-ion batteries during the charging process significantly impact their electrochemical performance and safety, particularly under high-rate or extreme temperature conditions. In this study, an electrochemical-thermal coupling model for a 2.5 Ah LiNi0.8Co0.1Mn0.1O2 18650 lithium-ion battery is proposed and experimentally validated. The heat generation and variation patterns of the electrodes at different charging rates and temperatures are evaluated, and the influence mechanisms of various electrode design parameters on charging energy efficiency are elucidated. The results reveal that high-rate charging increases the proportion of irreversible heat in the total heat generation, primarily due to the increase in ohmic heating at the positive electrode. Ambient temperature is less sensitive to heat generation than the C-rate, but low temperatures can also increase irreversible heat and are associated with an increase in positive polarization heat. Analyzing thermal characteristics at the electrode level can contribute to the optimization of battery design and the improvement of thermal safety. Electrode architectures, including electrode thickness, active material porosity, particle radius and negative/positive electrode capacity (N/P) ratio, are determined to analyze their effects on the heat generation of various components within the battery. Thick electrodes or active materials with high porosity induce significant ohmic heating and increase irreversible heat, with a slight effect on reversible heat, which is detrimental to energy efficiency. Large particle radii primarily increase reaction heat and polarization heat, and a high N/P ratio reduces the battery heat generation and is related to the reduction of negative reaction heat. Notably, variations in both two parameters have limited impact on to energy efficiency. Therefore, implementing appropriate thermal management across various charging scenarios is crucial for achievin

关键词： Lithium-ion batteries

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A Service-Environment-Oriented Shape Reconstruction Method of Vehicle-borne Active Phased Array Antenna

A Service-Environment-Oriented Shape Reconstruction Method o...

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2021 CIE International Conference on Radar, Radar 2021

作者： Xu, Pengying Xu, Xiaoxian Wang, Yan Teng, Yucheng Wang, Congsi Ge, Dongming Kang, Mingkui Yuan, Shuai Wang, Xuezi Xidian University Key Laboratory of Electronic Equipment Structure Design Ministry of Education Xi'an China School of Information and Control Engineering Xi'an University of Architecture and Technology Xi'an China Beijing Institute of Spacecraft System Engineering Beijing China No.771 Institute of China Aerospace Science and Technology Corporation Xi'an China China Electronics Technology Group Corporation No.38 Research Institute Hefei China

ISBN: (纸本)9781665498142

Modern electronic equipment has been moving towards large scale and increased complexity. Affected by such factors as complex working environments, the performance of a large number of structures in engineering is degraded or even destroyed. Therefore, structure shape estimation is of great significance. The complexity of the structure, however, makes it impossible for a single deformation evaluation algorithm to evaluate the structure comprehensively and accurately. In this paper, a modal-approximate curve (M-AC) method, using a small amount of strain data, is proposed for block shape estimation of structures. Three typical wind load experiments are carried out on the finite element model (FEM) of the vehicle-borne active phased array antenna, and the effectiveness of the algorithm is verified. Under the wind speed of 28 (m/s), the deformation of antenna front is 104.70 mm and the estimation accuracy of the M-AC method is 87.43%, which is 16.47% higher than that of the modal approach. The results indicate that the estimated displacement is consistent well with the simulation results of the finite element method. © 2021 IEEE.

关键词： active phased array antenna Fiber Bragg grating mode shapes sensor shape estimation

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Understanding the Limitations of Thick Electrodes on the Rate Capability of High-Energy Density Lithium-Ion Batteries

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SSRN 2024年

作者： Xie, Wenlong Zhang, Zhengjie Gao, Xinlei Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology China School of Transportation Science and engineering Beihang University Beijing100191 China Department of Mechanical Engineering Imperial College London LondonSW7 2AZ United Kingdom

As a core component of transportation electrification, lithium-ion batteries need to address two critical challenges: achieving high energy density and enabling fast charging. However, changes in electrode thickness could result in a trade-off between these two characteristics. Herein, the impact of electrode thickness on the electrochemical performance, thermal behavior, as well as energy and power density of LiNi0.8Co0.1Mn0.1O2(NCM)/graphite batteries are investigated through mathematical modeling. Underutilization of active materials of the thick electrode is identified as the primary limitation on rate capability, which can be attributed to the slow solid-state diffusion and poor electrolyte transport within the electrode, especially the enlarged concentration gradients in the solid phase and the lithium depletion in the electrolyte phase during high-rate charging. Evolutions of local current density and heat generation rate along the electrode thickness are compared, identifying the underlying mechanism of inducing uneven reaction kinetics inside the battery. The trade-off between the energy and power density as a function of electrode thickness is investigated based on the limitations of charge transfer and mass transport. Furthermore, the rate-limiting factors under various application requirements are elucidated. This study will provide guidance for the electrode design of high-energy-density batteries with fast-charging capabilities. © 2024, The Authors. All rights reserved.

关键词： Lithium-ion batteries

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An Efficient Digital Twin Based on Machine Learning Svd Autoencoder and Generalised Latent Assimilation for Nuclear reactor Physics

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SSRN 2022年

作者： Gong, Helin Cheng, Sibo Chen, Zhang Li, Qing Quilodrán-Casas, César Xiao, Dunhui Arcucci, Rossella SJTU-ParisTech Elite Institute of Technology Shanghai 200240 China Data Science Institute Imperial College London LondonSW7 2AZ United Kingdom Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China Chengdu610041 China Faculty of Sciences and Engineering Swansea University SwanseaSA1 8EN United Kingdom Department of Earth Science & Engineering Imperial College London LondonSW7 2AZ United Kingdom

This paper proposes an approach that combines reduced-order models with machine learning in order to create an digital twin to predict the power distribution over the core during the operation stage. The operational digital twin is designed to solve forward problems given input operation parameters, as well as to solve inverse problems given some observations of the power field. The forward model is realised using SVD autoencoder reduced order model and machine learning methods. The inverse model is based on a generalised latent assimilation method. The effectiveness in the sense of accuracy and real-time solver of the digital twin is illustrated through a real engineering problem in nuclear reactor physics - reactor core simulation in the life cycle of HPR1000 affected by control rod inserting step, burnup, power level and inlet temperature of the coolant, which shows potential applications for on-line monitoring purpose. © 2022, The Authors. All rights reserved.

关键词： Inverse problems

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Investigation of Heat Transfer and Flow Boiling Characteristics of a New Symmetric Cosine Mini-Channel Heat Exchanger with High Heat Flow Density

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SSRN 2023年

作者： Xu, Zhanying Liu, Huan-Ling Xie, Gongnan Shaanxi Key Laboratory of Space Solar Power Station System School of Electromechanical Engineering Xidian University Xi’an710071 China Key Laboratory of Electronic Equipment Structure Design Ministry of Education School of Electromechanical Engineering Xidian University Xi’an710071 China School of Marine Science and Technology Northwestern Polytechnical University Xi’an710072 China

A novel symmetric cosωx mini-channel heat exchanger (SCMC) with a combined bionic leaf vein diverter with ethanol as coolant is designed to meet the heat dissipation requirements for high heat flux chips. The mini-channel is firstly passed through a bionic leaf vein diverter to ensure the uniformity of the liquid distribution in the different mini-channels. Firstly, the homogeneity of the liquid distribution in different mini-channels is ensured by a bionic leaf vein divertor. Then, in order to obtain the flow characteristics and bubble features in the channel under conjugate conditions, a systematic three-dimensional numerical study is carried out by coupling the phase transition model with the volume of fluid (VOF) model. It is found that the symmetric distribution structure of the SCMC flow channel not only provides nucleation points for bubble generation, but also provides rupture points for large bubbles that can block the flow channel due to bubble aggregation, which reduces the instability of phase transition heat. Compared with the smooth flow channel structure of ω=1 and ω=1.5, the steep structure of ω=2 not only helps the mixing of coolant, but also increases the probability of bubbles hitting the sharp structure, which is more helpful for the rupture of large bubbles. In addition, the effects of waviness (ω ~ 0-2) and inlet velocity (Re ~ 234.07-1170.37) on the heat transfer performance under non-constant flow boiling conditions are investigated. The results show that the heat transfer capacity of SCMC increases firstly and then decreases with the increase of ω and subsequently increases again with the constant Re. The performance factor shows a decrease and then increases, which gets the maximum value at ω=2 and still shows an increasing trend. In the case of constant ω, the heat transfer capacity of SCMC is enhanced with the increase of Re, but the enhancement trend gradually slows down, and the performance factor shows a trend of increasing at first an

关键词： Heat exchangers

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Two points are enough

arXiv

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arXiv 2024年

作者： Liu, Hao Zhao, Yanbin Zheng, Huarong Fan, Xiulin Deng, Zhihua Chen, Mengchi Wang, Xingkai Liu, Zhiyang Lu, Jianguo Chen, Jian State Key Laboratory of Fluid Power Components and Mechatronic Systems School of Mechanical Engineering Zhejiang University Hangzhou China Ocean College Zhejiang University Hangzhou China State Key Laboratory of Silicon and Advanced Semiconductor Materials School of Materials Science and Engineering Zhejiang University Hangzhou China Nanyang Technological University Singapore School of Control Science and Engineering Zhejiang University Hangzhou China School of Materials Science and Engineering Tianjin University Tianjin China School of System Design and Intelligent Manufacturing Southern University of Science and Technology Shenzhen China

Prognosis and diagnosis play an important role in accelerating the development of lithium-ion batteries, as well as reliable and long-life operation. In this work, we answer an important question: What is the minimum amount of data required to extract features for accurate battery prognosis and diagnosis? Based on the first principle, we successfully extracted the best two-point feature (BTPF) for accurate battery prognosis and diagnosis using the fewest data points (only two) and the simplest feature selection method (Pearson correlation coefficient). The BTPF extraction method is tested on 820 cells from 6 open-source datasets (covering five different chemistry types, seven manufacturers, and three data types). It achieves comparable accuracy to state-of-the-art features in both prognosis and diagnosis tasks. This work challenges the cognition of existing studies on the difficulty of battery prognosis and diagnosis tasks, subverts the fixed pattern of establishing prognosis and diagnosis methods for complex dynamic systems through deliberate feature engineering, highlights the promise of data-driven methods for field battery prognosis and diagnosis applications, and provides a new benchmark for future studies. Copyright © 2024, The Authors. All rights reserved.

关键词： Lithium-ion batteries

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Distilling Autoregressive Models to Obtain High-Performance Non-Autoregressive Solvers for Vehicle Routing Problems with Faster Inference Speed

arXiv

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arXiv 2023年

作者： Xiao, Yubin Wang, Di Li, Boyang Wang, Mingzhao Wu, Xuan Zhou, Changliang Zhou, You Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education College of Computer Science and Technology Jilin University China Joint NTU-UBC Research Centre of Excellence in Active Living for the Elderly Nanyang Technological University Singapore WeBank-NTU Joint Research Institute on Fintech Nanyang Technological University Singapore School of Computer Science and Engineering Nanyang Technological University Singapore School of System Design and Intelligent Manufacturing Southern University of Science and Technology China

Neural construction models have shown promising performance for Vehicle Routing Problems (VRPs) by adopting either the Autoregressive (AR) or Non-Autoregressive (NAR) learning approach. While AR models produce high-quality solutions, they generally have a high inference latency due to their sequential generation nature. Conversely, NAR models generate solutions in parallel with a low inference latency but generally exhibit inferior performance. In this paper, we propose a generic Guided Non-Autoregressive Knowledge Distillation (GNARKD) method to obtain high-performance NAR models having a low inference latency. GNARKD removes the constraint of sequential generation in AR models while preserving the learned pivotal components in the network architecture to obtain the corresponding NAR models through knowledge distillation. We evaluate GNARKD by applying it to three widely adopted AR models to obtain NAR VRP solvers for both synthesized and real-world instances. The experimental results demonstrate that GNARKD significantly reduces the inference time (4∼5× faster) with acceptable performance drop (2∼3%). To the best of our knowledge, this study is first-of-its-kind to obtain NAR VRP solvers from AR ones through knowledge distillation. Copyright © 2023, The Authors. All rights reserved.

关键词： Distillation

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Generative API usage code recommendation with parameter concretization

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science China(Information sciences) 2019年第9期62卷 51-72页

作者： Chi CHEN Xin PENG Jun SUN Zhenchang XING Xin WANG Yifan ZHAO Hairui ZHANG Wenyun ZHAO School of Computer Science Fudan University Shanghai Key Laboratory of Data Science Fudan University Shanghai Institute of Intelligent Electronics & Systems Pillar of Information System Technology and Design Singapore University of Technology and Design Research School of Computer Science Australian National University

Many programming languages and development frameworks have extensive libraries(e.g., JDK and Android libraries) that ease the task of software engineering if used effectively. With numerous library classes and sometimes intricate API(application programming interface) usage constraints, programmers often have difficulty remembering the library APIs and/or using them correctly. This study addresses this problem by developing an engine called DeepAPIRec, which automatically recommends the API usage *** to the existing proposals, our approach distinguishes itself in two ways. First, it is based on a tree-based long short-term memory(LSTM) neural network inspired by recent developments in the machinelearning community. A tree-based LSTM neural network allows us to model and reason about variable-length,preceding and succeeding code contexts, and to make precise predictions. Second, we apply data-flow analysis to generate concrete parameters for the API usage code, which not only allows us to generate complete code recommendations but also improves the accuracy of the learning results according to the tree-based LSTM neural network. Our approach has been implemented for supporting Java programs. Our experimental studies on the JDK library show that at statement-level recommendations, DeepAPIRec can achieve a top-1 accuracy of about 37% and a top-5 accuracy of about 64%, which are significantly better than the existing approaches. Our user study further confirms that DeepAPIRec can help developers to complete a segment of code faster and more accurately as compared to IntelliJ IDEA.

关键词： code recommendation API deep learning data dependency parameter concretization

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Fluoride-Salt-Cooled High-Temperature reactor: An Integrated Nuclear-Based Energy Production and Conversion system

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SSRN 2023年

作者： Zhang, Dalin Li, Xinyu Jiang, Dianqiang Zhou, Xingguang Lv, Xindi Yun, Shichang Wu, Wenqiang He, Xuanang Li, Haoyang Min, Xin Chen, Kailong Tian, Wenxi Qiu, Suizheng Su, Guanghui Zhao, Quanbin Fu, Yao Tang, Chuntao Zhuo, Wenbin Li, Jinggang Zuo, Jiaxu State Key Laboratory of Multiphase Flow in Power Engineering Shaanxi Key Laboratory of Advanced Nuclear Energy and Technology School of Nuclear Science and Technology Xi’an Jiaotong University Xi’an710049 China Shanghai Institute of Applied Physics Chinese Academy of Sciences Shanghai201800 China Shanghai Nuclear Engineering Research & Design Institute Co. Ltd. Shanghai200233 China CNNC Key Laboratory on Nuclear Reactor Thermal Hydraulics Technology Nuclear Power Institute of China Chengdu610213 China China Nuclear Power Technology Research Institute Guangdong Shenzhen518000 China Nuclear and Radiation Safety Center Ministry of Ecology and Environment Beijing100082 China

Based on the analysis of energy structure and the development trends of advanced nuclear energy technology, combining the complementary advantages of nuclear energy and other energy sources in China, the Fluoride-salt-cooled High-temperature reactor(FuSTAR) system has been proposed. FuSTAR system is designed to address production capacity issues in areas with energy shortages or resource concentration and can be combined with high-temperature process heat to achieve high-value-added processes such as hydrogen production. In this paper, the design and optimization processes of FuSTAR are described from three aspects: the neutronic and thermal-hydraulic system, the thermal transport system, and the power cycle system. Tri-structural isotropic fuel combined with helical cruciform elements has been studied in detail on the neutron physics and thermal-hydraulic properties, and the flow and heat transfer experiment is carried out for the first time. The multilayer nonlinear programming method has been applied to the design of thermal transport systems and the passive residual heat removal system and proved to be fast and efficient. Then the optimal parameters and configuration of the thermoelectric conversion system are obtained directly by using the superstructure optimization method, which saves computing resources greatly. Based on the above design and parameters, the inherent safety of FuSTAR is demonstrated through deterministic safety analysis. In addition, the iodine-sulfur cycle technology is also designed and analyzed, and the characteristics of tritium production in FuSTAR are calculated. The research provides important guidance for the detailed design and operation of FuSTAR. Moreover, this study highlights the significant potential of integrating nuclear energy with other energy sources in an optimized energy-production system. Based on the current research findings, prospects for future research directions are also suggested. © 2023, The Authors. All rights r

关键词： High temperature reactors

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Study on the mechanism of microcrack propagation in bentonite under confining pressure conditions

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Quarterly Journal of Engineering Geology and Hydrogeology 2025年

作者： Guo, Jingna Liu, Jiangfeng Liu, Daoping Zhao, Yu Lei, Min Shi, Hao School of Applied Mathematics Chengdu University of Information Technology Sichuan Chengdu610225 China State Key Laboratory of Intelligent Construction and Healthy Operation and Maintenance of Deep Underground Engineering China University of Mining and Technology Jiangsu Xuzhou221116 China Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China Chendu610213 China School of Civil Engineering and Architecture Anhui University of Science and Technology Huainan232001 China

For underground nuclear disposal repositories, sealing performance is crucial to ensuring long-term operational safety. Bentonite, widely employed as a sealing material, effectively reduces leakage risks owing to its self-healing capacity. However, a comprehensive investigation of gas migration mechanisms in bentonite is imperative to elucidate the underlying leakage dynamics. This study not only offers theoretical insights for the safety assessment and design optimization of disposal repositories but also holds substantial practical significance in ensuring their secure performance. To accurately model gas migration in saturated bentonite, this study systematically investigates the effects of pore pressure on soil deformation and experimentally evaluates the impact of damage evolution on permeability and elastic modulus. Building on these experimental insights, we propose a coupled fluid-solid constitutive model. This model elucidates the progressive development of microcracks within bentonite under increasing gas pressure, providing a mechanistic understanding of fracture propagation in sealing systems. By integrating experimental data from bentonite hydration and gas breakthrough tests, the study verifies that gas migration under flexible boundary conditions is primarily governed by the dilatancy effect of bentonite. Furthermore, the model's validity and applicability are demonstrated. Subsequently, the model is employed to systematically investigate the influence of confining pressure on (1) the evolution of microcracks in bentonite, (2) permeability variations, and (3) gas breakthrough pressure thresholds. Based on these analyses, theoretical mitigation strategies to prevent gas breakthrough are established for specific confining pressure ranges. © 2025 The Author(s). Published by The Geological Society of London. All rights, including for text and data mining (TDM), artificial intelligence (AI) training, and similar technologies, are reserved. For permissions:

关键词： Microcracks

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