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学者姓名：刘海滨
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Abstract ：
Schedule maintenance activities for hydrogen fuel cell vehicles are aimed to keep them in better condition in long-term operation. In this paper, we develop a reinforcement learning based schedule maintenance strategy, which is used to comprehensively consider the balance between safety and maintenance cost, so as to find the optimal maintenance strategy. A multi-level framework is established with remaining useful life of key components, fault tree analysis, and logistics cost model to generate an exploration environment that can express the operational stability, the failure rate of components, and the cost of repair and storage. The trained agent combines a deep neural network to explore the optimal strategy under the dynamic reliability of key components. Finite steps are the constraints. Safety rates, maintenance cost, and episode of operation are incorporated into a multi-objective reward function. The hydrogen supply circuit of fuel cell vehicle is simulated via Python. The trained agent is compared with traditional time-based schedule maintenance strategy and corrective maintenance strategy. The results show that the reinforcement learning based schedule maintenance agent has optimized the total reward, cost control and accident rate by 77%, 59% and 5%, respectively, compared with the traditional time-based schedule maintenance strategy. In the safe operation management of fuel cell vehicles, efficient and stable decision-making ability has been achieved.
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| GB/T 7714 | Miao, Yang , Li, Yantang , Zhang, Xiangyin et al. An intelligent schedule maintenance method for hydrogen fuel cell vehicles based on deep reinforcement learning considering dynamic reliability [J]. | INTERNATIONAL JOURNAL OF HYDROGEN ENERGY , 2024 , 64 : 455-467 . |
| MLA | Miao, Yang et al. "An intelligent schedule maintenance method for hydrogen fuel cell vehicles based on deep reinforcement learning considering dynamic reliability" . | INTERNATIONAL JOURNAL OF HYDROGEN ENERGY 64 (2024) : 455-467 . |
| APA | Miao, Yang , Li, Yantang , Zhang, Xiangyin , Xu, Jingxiang , Wu, Di , Sun, Lejia et al. An intelligent schedule maintenance method for hydrogen fuel cell vehicles based on deep reinforcement learning considering dynamic reliability . | INTERNATIONAL JOURNAL OF HYDROGEN ENERGY , 2024 , 64 , 455-467 . |
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Abstract ：
Hydrogen leakage diagnosis has attracted more and more attention, especially in the high -pressure hydrogen system of fuel cell vehicles, where the chance of deflagration is quite high. Traditional methods for detecting gas leaks rely on stationary sensor measurements and manual inspections. Manual inspections are time and resourceconsuming, and it is challenging to achieve real -time, comprehensive inspections in large spaces. In this study, a new Adaptive Stream Stripe-Background Oriented Schlieren (ASS-BOS) method for hydrogen jet visualization is proposed. Three different background patterns, namely random scatter background, checkerboard background, and stripe background, are designed for multiple experiments. The results show that when observing hydrogen jets in the far -field region (low-density gradient), ASS-BOS has higher accuracy and resolution, detects larger background displacements, and shows more turbulence details. In addition, the concentration distribution of the hydrogen jet is reconstructed using ASS-BOS. We compare the concentration of the hydrogen jet obtained from the inversion of the ASS-BOS method with the experimental results measured by the sensor. We find that the average error is 3.45%, indicating that ASS-BOS can accurately reconstruct the concentration distribution of the hydrogen jet.
Keyword ：
Safety monitoring Safety monitoring Synthetic schlieren Synthetic schlieren Background oriented schlieren Background oriented schlieren Hydrogen leak Hydrogen leak
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| GB/T 7714 | Miao, Yang , Jia, Chenghao , Hua, Yang et al. Measurement of the concentration distribution of hydrogen jets using adaptive stream stripe- background oriented schlieren (ASS-BOS) [J]. | INTERNATIONAL JOURNAL OF HYDROGEN ENERGY , 2024 , 77 : 281-290 . |
| MLA | Miao, Yang et al. "Measurement of the concentration distribution of hydrogen jets using adaptive stream stripe- background oriented schlieren (ASS-BOS)" . | INTERNATIONAL JOURNAL OF HYDROGEN ENERGY 77 (2024) : 281-290 . |
| APA | Miao, Yang , Jia, Chenghao , Hua, Yang , Sun, Lejia , Xu, Jingxiang , Wu, Di et al. Measurement of the concentration distribution of hydrogen jets using adaptive stream stripe- background oriented schlieren (ASS-BOS) . | INTERNATIONAL JOURNAL OF HYDROGEN ENERGY , 2024 , 77 , 281-290 . |
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Hands-on detection (HOD) is critical to making the transition decision on the driving authority between the human driver and the automated system in conditional autonomous vehicles. However, existing HOD solutions using individual sensing elements are limited in area sensing capabilities over the entire steering wheel. To implement both position and intensity sensing, a compliant large-area sensor that is able to cover the entire rim of a steering wheel is developed based on the technique of electrical impedance tomography (EIT) in this work. The sensor is made by spray coating low-cost exfoliated graphite polymer composites over an insulating hyper-elastic fabric, forming a continuous piezoresistive sensing area ( 100 x 10 cm) using only boundary electrodes for measurements. The spatial performance is investigated in both simulation and experiments, showing nonuniform wavy patterns in terms of the reconstructed peak, the reconstructed size, and the position error. To obtain correct information on the tactile intensity, the relation between the reconstructed peak and the size is modeled by an inverse equation, the fit coefficient of which is found an effective indicator to the intensity. Indentation experiments validates the proposed method to estimate the intensity, and the position error is measured 1.1 +/- 0.7 cm. The performance for HOD is also evaluated by wrapping the compliant sensor over a true-size steering wheel in laboratory environment, validating the potential of applying the cost-competitive large-area sensing solution for conditional autonomous driving.
Keyword ：
polymer composites polymer composites Area sensing Area sensing hands-on detection (HOD) hands-on detection (HOD) tactile sensors tactile sensors electrical impedance tomography (EIT) electrical impedance tomography (EIT)
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| GB/T 7714 | Chen, Ying , Jin, Leizhi , Qin, Yujiao et al. Position and Intensity Sensing of a Large-Area Tactile Sensor for Hands-on Detection in Conditional Autonomous Driving [J]. | IEEE SENSORS JOURNAL , 2024 , 24 (8) : 12504-12513 . |
| MLA | Chen, Ying et al. "Position and Intensity Sensing of a Large-Area Tactile Sensor for Hands-on Detection in Conditional Autonomous Driving" . | IEEE SENSORS JOURNAL 24 . 8 (2024) : 12504-12513 . |
| APA | Chen, Ying , Jin, Leizhi , Qin, Yujiao , Xie, Ruishan , Liu, Haibin . Position and Intensity Sensing of a Large-Area Tactile Sensor for Hands-on Detection in Conditional Autonomous Driving . | IEEE SENSORS JOURNAL , 2024 , 24 (8) , 12504-12513 . |
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Abstract ：
This study aims to figure out some safety issues by investigating the roof shape of infrastructures such as zerocarbon huts that people are already using to prevent dangerous hydrogen clouds from building up in places with little airflow when there is a leak. We designed three different obstacles. The horizontal and vertical concentration distributions of the free-jet hydrogen cloud when encountering different obstacles were determined by concentration measurements. In addition, the diffusion characteristics of the hydrogen jet in the presence of obstacles were investigated by using the Background Oriented Schlieren (BOS). The results show that there is a linear relationship between the measured axial concentration of the hydrogen jet and the leakage parameters at lower flow rates. The measured radial concentration of the hydrogen jet shows a "Gaussian-like" distribution when encountering a flat plate obstacle, a "W" distribution when encountering a flat plate obstacle with sidewalls, and a "W-like" distribution when encountering a dome-type obstacle. A method of inverting the radial concentration distribution of the hydrogen jet using the BOS is also proposed, and the error between the theoretical and experimental values is calculated to be 3.81 %. This study stresses the significance of geometric and dimensional parameters on hydrogen leakage characteristics and, as a result, provides insights into developing performance standards for the availability and reliability of safety-critical systems.
Keyword ：
Accidental leak Accidental leak BOS BOS Obstacle shape Obstacle shape Concentration measurement Concentration measurement Hydrogen-electric coupling Hydrogen-electric coupling
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| GB/T 7714 | Miao, Yang , Jia, Chenghao , Hua, Yang et al. Quantification of concentration characteristics of hydrogen leakage in electro-hydrogen coupled system with different obstacles via Background Oriented Schlieren [J]. | JOURNAL OF ENERGY STORAGE , 2024 , 83 . |
| MLA | Miao, Yang et al. "Quantification of concentration characteristics of hydrogen leakage in electro-hydrogen coupled system with different obstacles via Background Oriented Schlieren" . | JOURNAL OF ENERGY STORAGE 83 (2024) . |
| APA | Miao, Yang , Jia, Chenghao , Hua, Yang , Zhang, Xiaolu , Sun, Lejia , Huang, Gang et al. Quantification of concentration characteristics of hydrogen leakage in electro-hydrogen coupled system with different obstacles via Background Oriented Schlieren . | JOURNAL OF ENERGY STORAGE , 2024 , 83 . |
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Abstract ：
Friction rolling additive manufacturing (FRAM) is a solid-state additive manufacturing method capable of accommodating a wide range of material forms. However, there is a lack of comprehensive research on the optimal feedstock form. Thus, this study investigated the influence of feedstock shape on material formation, microstructure, and mechanical properties. The results revealed that irrespective of whether a strip or wire was used, the plasticized material flowed through a thin plastic flow channel (approximately 112 mu m) between the tool head and the feedstock. Wire feedstock resulted in greater deformation and more significant grain refinement than strip feedstock, with grain refinements of 95 % and 81 %, respectively. Additionally, gaps between multiple wires were filled with plasticized material, forming a dense and defect-free mixing zone. Moreover, the tensile performances of the deposited samples obtained from wire and strip feedstocks exhibited no significant differences, measuring 143.9 MPa and 144.5 MPa, respectively. Numerical simulations were employed to elucidate the underlying mechanism of the temperature field and material flow behavior when strips and wires were used as feed materials. The findings of this study are anticipated to serve as a reference for selecting feedstock forms for FRAM.
Keyword ：
Solid-state additive manufacturing Solid-state additive manufacturing Mechanical property Mechanical property Microstructure Microstructure Material shape Material shape Friction stir processing Friction stir processing
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| GB/T 7714 | Xie, Ruishan , Chen, Pingping , Shi, Yanchao et al. Effect of feeding material shape on microstructures and mechanical properties in friction rolling additive manufacturing [J]. | MATERIALS & DESIGN , 2024 , 241 . |
| MLA | Xie, Ruishan et al. "Effect of feeding material shape on microstructures and mechanical properties in friction rolling additive manufacturing" . | MATERIALS & DESIGN 241 (2024) . |
| APA | Xie, Ruishan , Chen, Pingping , Shi, Yanchao , Chen, Ying , Liu, Haibin , Chen, Shujun . Effect of feeding material shape on microstructures and mechanical properties in friction rolling additive manufacturing . | MATERIALS & DESIGN , 2024 , 241 . |
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Abstract ：
The study on forecasting demand for online car-hailing holds substantial implications for both online car-hailing platforms and government agencies responsible for traffic management. This research proposes an enhanced Empirical Mode Decomposition Long-short Term Memory Neural Network (EMD-LSTM) model. EMD technique reduces noise and extracts stable intrinsic mode functions (IMF) from the original time series. Genetic algorithm is deployed to improve the K-Means clustering for determining optimal clusters. These sub time series serve as input for the prediction model, with combined results giving final predictions. Experimental data from Didi includes Haikou's car-hailing orders from May to October 2017 and Beijing's from January to May 2020. Results show improved EMD-LSTM reduces instability and captures characteristics better. Compared to unmodified EMD-LSTM, RMSE decreases by 3.50%, 6.81%, and 6.81% for the three datasets, and by 30.97%, 20%, and 9.24% respectively compared to single LSTM model.
Keyword ：
EMD EMD online car-hailing demand forecasting online car-hailing demand forecasting LSTM LSTM improved K-Means improved K-Means
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| GB/T 7714 | Liu, Jiaming , Tang, Xiaoya , Liu, Haibin . Enhanced forecasting of online car-hailing demand using an improved empirical mode decomposition with long short-term memory neural network [J]. | TRANSPORTATION LETTERS-THE INTERNATIONAL JOURNAL OF TRANSPORTATION RESEARCH , 2024 . |
| MLA | Liu, Jiaming et al. "Enhanced forecasting of online car-hailing demand using an improved empirical mode decomposition with long short-term memory neural network" . | TRANSPORTATION LETTERS-THE INTERNATIONAL JOURNAL OF TRANSPORTATION RESEARCH (2024) . |
| APA | Liu, Jiaming , Tang, Xiaoya , Liu, Haibin . Enhanced forecasting of online car-hailing demand using an improved empirical mode decomposition with long short-term memory neural network . | TRANSPORTATION LETTERS-THE INTERNATIONAL JOURNAL OF TRANSPORTATION RESEARCH , 2024 . |
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Abstract ：
本发明公开了一种基于Conv‑Dueling与泛化表征的动态车间调度方法，首先采用多维矩阵来表示设备状态和工件状态；设计了复合奖励函数，以引导算法的收敛。提出Conv‑Dueling网络模型，以多维状态矩阵作为输入，以调度规则价值作为输出，在不同的重调度决策点上选择最优的调度规则。该网络模型由特征提取网络、状态网络和优势网络三部分组成，实现全局最优调度。经过静态和动态情况下的验证，该网络模型均能得到良好的优化效果。本发明提出的动态车间调度方法可以减少最大完工时间、提高准时完成率和降低总延迟时间，同时保证了鲁棒性和稳定性，其综合调度性能优于现有的调度方法。
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| GB/T 7714 | 刘海滨 , 夏铭浩 , 李明飞 et al. 一种基于Conv-Dueling与泛化表征的动态车间调度方法 : CN202310600842.X[P]. | 2023-05-25 . |
| MLA | 刘海滨 et al. "一种基于Conv-Dueling与泛化表征的动态车间调度方法" : CN202310600842.X. | 2023-05-25 . |
| APA | 刘海滨 , 夏铭浩 , 李明飞 , 王龙 , 董浩 . 一种基于Conv-Dueling与泛化表征的动态车间调度方法 : CN202310600842.X. | 2023-05-25 . |
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Abstract ：
Friction-rolling additive manufacturing (FRAM) is an innovative solid-state additive manufacturing method for "non-weldable" alloys. The basic physics of this method relies on a rotating toolhead to generate severe plastic deformation and thereby deposit the material. However, the specific processes of heat generation and material flow behaviors induced by the rotating toolhead are not fully understood. In this study, a novel three-dimensional thermomechanically coupled Eulerian-Lagrangian model with a particle tracing technique was developed to analyze the transient temperature evolution and material flow behaviors during FRAM. The nu-merical simulation was validated based on experimental temperature measurements and the geometry of the deposit. The heat-generation process and gradual stabilization of the temperature field during the three stages of FRAM--namely, toolhead insertion, material feeding, and toolhead advancement--were successfully charac-terized. The results show that the toolhead simultaneously generates heat in the material strip and substrate, and more heat is generated in the shoulder and the transition zone where the toolhead shape changes from concave to convex. The presence of a single shoulder leads to an asymmetrical temperature distribution along the axial direction (Y direction) of the toolhead. The material near the toolhead flows tangentially around the toolhead, and the flow of the strip is better than that of the substrate. The particle tracing results show that the strip and substrate surfaces are well-mixed in the Z direction under the rotating action of the toolhead. The findings from this study can be applied in further fundamental investigations of the FRAM process and toolhead morphology design.
Keyword ：
Severe plastic deformation Severe plastic deformation Temperature evolution Temperature evolution Thermomechanical modeling Thermomechanical modeling Material flow Material flow Solid-state additive manufacturing Solid-state additive manufacturing
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| GB/T 7714 | Xie, Ruishan , Liang, Tongshuai , Chen, Shujun et al. In-depth understanding of rotating toolhead-induced heat generation and material flow behavior in friction-rolling additive manufacturing [J]. | ADDITIVE MANUFACTURING , 2023 , 67 . |
| MLA | Xie, Ruishan et al. "In-depth understanding of rotating toolhead-induced heat generation and material flow behavior in friction-rolling additive manufacturing" . | ADDITIVE MANUFACTURING 67 (2023) . |
| APA | Xie, Ruishan , Liang, Tongshuai , Chen, Shujun , Liu, Haibin . In-depth understanding of rotating toolhead-induced heat generation and material flow behavior in friction-rolling additive manufacturing . | ADDITIVE MANUFACTURING , 2023 , 67 . |
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Abstract ：
Despite extensive use of ER2319 welding wires for additive manufacturing of aluminum alloys in the aerospace and automotive field, the internal denseness, grain coarseness, and non-uniformity of additive-manufactured aluminum alloy parts are yet to be appropriately addressed. Thus, this study attempted to overcome this gap by using an ER2319 aluminum alloy welding wire to produce a uniform and fine-grained aluminum alloy using deformation-based friction rolling additive manufacturing (FRAM). The findings demonstrated that the FRAMprepared materials were free of voids and cracks, with approximately equiaxed grains of only 4-6 & mu;m. Further, the ultimate tensile strength (UTS) and yield strength (YS) of the deposited material in all directions differed only slightly, with the strengths in the longitudinal direction being 9.5 and 9.6% higher than that in the vertical direction, respectively. Furthermore, the combined UTS and elongation of the FRAM-prepared material are, to the best of the authors' knowledge, the best results reported for printed aluminum alloys using ER2319 welding wire. The interesting research results presented in this study are expected to have significant practical application implications and usher in further research in this field.
Keyword ：
Grain refinement Grain refinement Aluminum alloy Aluminum alloy Equiaxed grain Equiaxed grain Solid-state additive manufacturing Solid-state additive manufacturing
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| GB/T 7714 | Xie, Ruishan , Chen, Xiaoguang , Shi, Yanchao et al. Printing high-strength high-elongation aluminum alloy using commercial ER2319 welding wires through deformation-based additive manufacturing [J]. | MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING , 2023 , 868 . |
| MLA | Xie, Ruishan et al. "Printing high-strength high-elongation aluminum alloy using commercial ER2319 welding wires through deformation-based additive manufacturing" . | MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING 868 (2023) . |
| APA | Xie, Ruishan , Chen, Xiaoguang , Shi, Yanchao , Yang, Chunyang , Chen, Shujun , Liu, Haibin . Printing high-strength high-elongation aluminum alloy using commercial ER2319 welding wires through deformation-based additive manufacturing . | MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING , 2023 , 868 . |
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Abstract ：
The main objective of this work is to propose a new hydrogen leakage visualization method to evaluate hydrogen jet pressure. A mathematical model is proposed to reveal the intensity distribution of the laser beam through the hydrogen jet at different outlet pressures. Our findings show that the hydrogen jet can be regarded as a gas lens with adjustable laser beam energy, and a change in jet pressure causes a change in the halfheight width of the spectrum, which affects the intensity distribution of the laser beam after it passes through the hydrogen jet. The error between the light intensity distribution of the theory and the light intensity distribution obtained from the experimental results is 2.59%. The error is within the allowable range. Our technique shows that the variation of the hydrogen jet pressure can be estimated by analyzing the intensity data after the laser passes through the hydrogen jet.(c) 2023 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.
Keyword ：
Visualization Visualization Intensity Intensity Hydrogen jet Hydrogen jet Optical measurement Optical measurement
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| GB/T 7714 | Miao, Yang , Jia, Chenghao , Zhang, Xiaolu et al. Visualization of hydrogen jet using intensity projection of the laser beam [J]. | INTERNATIONAL JOURNAL OF HYDROGEN ENERGY , 2023 , 48 (87) : 34094-34104 . |
| MLA | Miao, Yang et al. "Visualization of hydrogen jet using intensity projection of the laser beam" . | INTERNATIONAL JOURNAL OF HYDROGEN ENERGY 48 . 87 (2023) : 34094-34104 . |
| APA | Miao, Yang , Jia, Chenghao , Zhang, Xiaolu , Li, Yuejuan , Sun, Lejia , Yiao, Luqiao et al. Visualization of hydrogen jet using intensity projection of the laser beam . | INTERNATIONAL JOURNAL OF HYDROGEN ENERGY , 2023 , 48 (87) , 34094-34104 . |
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