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    Fault Detection in Power Distribution Systems Based on Gated Recurrent Attention Network
    CHEN Haolan, JIN Bingying, LIU Yadong, QIAN Qinglin, WANG Peng, CHEN Yanxia, YU Xijuan, YAN Yingjie
    Journal of Shanghai Jiao Tong University    2024, 58 (3): 295-303.   DOI: 10.16183/j.cnki.jsjtu.2022.091
    Abstract171)   HTML10)    PDF(pc) (2938KB)(2188)       Save

    To improve fault identification accuracy in power distribution systems, a model named gated recurrent attention network is proposed. First, a higher weight is put on the key cycles of fault phase based on the attention mechanism, making the model focus more on these key messages by weight assignment. Then, the gated recurrent network is adopted, which controls the memory transmission with gate signal and constructs the relationship between input waveform and probability of events at different stages to process the waveform sequence, thereby improving recognition accuracy. Experiments based on both simulation and field data show that the proposed method, under the small-sample-learning condition, is much better than other commonly-used classification models, such as support vector machine, gradient boosting decision tree, and convolutional neural network, providing new insights into fault identification technology in power distribution systems.

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    An Admittance Reshaping Strategy of Three-Phase LCL Grid-Connected Inverter Based on Modified Passive Control
    WANG Han, ZHANG Jianwen, SHI Gang, ZHU Miao, CAI Xu
    Journal of Shanghai Jiao Tong University    2023, 57 (9): 1105-1113.   DOI: 10.16183/j.cnki.jsjtu.2022.120
    Abstract316)   HTML34)    PDF(pc) (3313KB)(864)       Save

    The passivity-based control (PBC) based on energy function has been studied for grid-connected converters to achieve a better performance. However, traditional PBC method relies on the accurate mathematical model of grid-connected inverter. In previous studies on PBC, the effect of digital control delay is rarely considered and the stability under grid impedance uncertainties is not discussed, especially in the capacitive grid or complex weak grid. To address these issues, this paper proposes an improved PBC method to reshape the output admittance for LCL-filtered grid-connected inverters. The system passive region is expanded up to the Nyquist frequency by adding a capacitor current feedback loop which can achieve active damping control of LCL resonant frequency under the wide range of grid impedance changes. The parameter design method is also presented for the proposed PBC control. To verify the correctness of the theoretical analysis, both simulation and experiments are conducted on a 3 kW grid-connected inverter prototype.

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    Optimal Planning of Power Systems with Flexible Resources for High Penetrated Renewable Energy Accommodation
    GUO Yongtao, XIANG Yue, LIU Junyong
    Journal of Shanghai Jiao Tong University    2023, 57 (9): 1146-1155.   DOI: 10.16183/j.cnki.jsjtu.2022.269
    Abstract201)   HTML11)    PDF(pc) (2433KB)(812)       Save

    High penetrated renewable energy has brought great challenges to the flexibility of the power system due to its volatility and intermittency. To improve the capacity of renewable energy accommodation, the flexibility reformation of thermal power units, the construction of gas-fired units, and the electrical energy storage installation are considered as effective solutions. Thus, an optimization model for power system planning scheme considering multi-type flexible resources with their different output characteristics is established. The simulation results on a modified IEEE 24-bus power system and 12-node natural gas system demonstrate the effectiveness of the proposed model. In addition, the applicability of different flexible resource planning schemes is comprehensively evaluated from the perspectives of economy, accommodation capacity, and carbon reduction, so as to meet the different planning goals.

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    Unmanned Aerial Vehicle Path Planning Algorithm Based on Improved Informed RRT* in Complex Environment
    LIU Wenqian, SHAN Liang, ZHANG Weilong, LIU Chenglin, MA Qiang
    Journal of Shanghai Jiao Tong University    2024, 58 (4): 511-524.   DOI: 10.16183/j.cnki.jsjtu.2022.442
    Abstract732)   HTML18)    PDF(pc) (11075KB)(589)       Save

    To address the problems of long planning time, redundant planning path, and even planning failure caused by local constraints in narrow spaces in the rapid exploring random trees (RRT) algorithm when unmanned aerial vehicle is planning a path in a complex environment, an improved Informed RRT* algorithm is proposed. First, the artificial potential field (APF) method is used to make the sampling points move to the target point in the way of potential field descending, which improves the purpose and directionality of RRT tree expansion. Considering the complexity of the global environment during tree expansion, an adaptive step size is introduced to accelerate the expansion speed of the RRT tree in an unobstructed environment. Then, relevant constraints are added in the process of random tree expansion to ensure the feasibility of the generated paths. After the first reachable path is found, variable elliptic or ellipsoidal sampling domain is used to limit the selection of sampling points and the expansion range of adaptive step size, so as to accelerate the convergence of the algorithm to the asymptotic optimization. Finally, the original algorithm and the improved algorithm are compared in two-dimensional and three-dimensional complex environment. The simulation results show that the improved algorithm can find a better reachable path with a small number of iterations, lock the elliptic or ellipsoidal sampling domain faster and leave more time for path optimization. The improved algorithm performs better in path planning.

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    Interval Estimation of State of Health for Lithium Batteries Considering Different Charging Strategies
    ZHANG Xiaoyuan, ZHANG Jinhao, YANG Lixin
    Journal of Shanghai Jiao Tong University    2024, 58 (3): 273-284.   DOI: 10.16183/j.cnki.jsjtu.2022.347
    Abstract220)   HTML11)    PDF(pc) (3204KB)(481)       Save

    State of health (SOH) estimation of lithium-ion (Li-ion) batteries is of great importance for battery use, maintenance, management, and economic evaluation. However, the current SOH estimation methods for Li-ion batteries are mainly targeted at specific charging strategies by using deterministic estimation models, which cannot reflect uncertain information such as randomness and fuzziness in the battery degradation process. To this end, a method for estimating the SOH interval of Li-ion batteries applicable to different charging strategies is proposed, which extracts multiple feature parameters from the cyclic charging and discharging data of batteries with different charging strategies, and automatically selects the optimal combination of feature parameters for a specific charging strategy by using the cross-validation method. In addition, considering the limited number of cycles in the whole life cycle of Li-ion batteries as a small sample, support vector quantile regression (SVQR), which integrates the advantages of support vector regression and quantile regression, is proposed for the estimation of SOH interval of lithium-ion batteries. Li-ion battery charge/discharge cycle data with deep discharge degree is selected as the training set for offline training of the SVQR model, and the trained model is used for online estimation of the SOH of Li-ion batteries of different charging strategies. The proposed method is validated using three datasets with different charging strategies. The experimental results show that the proposed method is applicable to different charging strategies and the estimation results are better than those of quantile regression, quantile regression neural network and Gaussian process regression.

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    A Structured Pruning Method Integrating Characteristics of MobileNetV3
    LIU Yu, LEI Xuemei
    Journal of Shanghai Jiao Tong University    2023, 57 (9): 1203-1213.   DOI: 10.16183/j.cnki.jsjtu.2022.077
    Abstract458)   HTML24)    PDF(pc) (11611KB)(463)       Save

    Due to its huge amount of calculation and memory occupation, the traditional deep neural network is difficult to be deployed to embedded platform. Therefore, lightweight models have been developing rapidly. Among them, the lightweight architecture MobileNet proposed by Google has been widely used. To improve the performance, the model of MobileNet has developed from MobileNetV1 to MobileNetV3. However, the model has become more complex and its scale continues to expand, which is difficult to give full play to the advantages of lightweight model. To reduce the difficulty of deploying MobileNetV3 on embedded platform while maintaining its performance, a structured pruning method integrating the characteristics of MobileNetV3 is proposed to prune the lightweight model MobileNetV3-Large to obtain a more compact lightweight model. First, the model is trained by sparse regularization to obtain a sparse network model. Then, the product of the sparse value of convolution layer and scale factor of batch normalization layer is used to identify the redundant filter, which is structurally pruned, and experiment is conducted on CIFAR-10 and CIFAR-100 datasets. The results show that the proposed compression method can effectively compress the model parameters, and the compressed model can still ensure a good performance. While the accuracy remains unchanged, the number of parameters on CIFAR-10 in the model is reduced by 44.5% and calculation amount is reduced by 40%.

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    Interval Prediction Technology of Photovoltaic Power Based on Parameter Optimization of Extreme Learning Machine
    HE Zhizhuo, ZHANG Ying, ZHENG Gang, ZHENG Fang, HUANG Wandi, ZHANG Shenxi, CHENG Haozhong
    Journal of Shanghai Jiao Tong University    2024, 58 (3): 285-294.   DOI: 10.16183/j.cnki.jsjtu.2022.338
    Abstract288)   HTML9)    PDF(pc) (1907KB)(443)       Save

    This paper proposes an interval prediction technology of photovoltaic (PV) power based on parameter optimization of extreme learning machine (ELM) model. First, the weighted Euclidean distance is proposed as the evaluation index of PV power prediction interval. The historical sample units are screened and the ELM training set is optimized. Then, a hybrid optimization algorithm for ELM parameters is proposed. The hidden layer input and output weights and biases parameters of the ELM model are optimized by using the elitist strategy genetic algorithm and quantile regression, and the trained model is used to predict the PV power range. Finally, an actual calculation example is constructed based on the historical data of PV power plants and weather stations. The PV power interval is predicted, and the results are compared with those obtained by other methods. The results of the calculation example show that the method proposed can greatly improve the accuracy of interval prediction while increasing the reliability of interval prediction.

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    Application of Machine Learning in Chemical Synthesis and Characterization
    SUN Jie, LI Zihao, ZHANG Shuyu
    Journal of Shanghai Jiao Tong University    2023, 57 (10): 1231-1244.   DOI: 10.16183/j.cnki.jsjtu.2023.078
    Abstract514)   HTML52)    PDF(pc) (4421KB)(439)       Save

    Automated chemical synthesis is one of the long-term goals pursued in the field of chemistry. In recent years, the advent of machine learning (ML) has made it possible to achieve this goal. Data-driven ML uses computers to learn relative information in massive chemical data, find objective connections between information, train models by using objective connections, and analyze the actual problems which can be solved according to these models. With its excellent computational prediction capabilities, ML helps chemists solve chemical synthesis problems quickly and efficiently and accelerate the research process. The emergence and development of ML has shown a strong research assistance in the field of chemical synthesis and characterization. However, there is no highly versatile ML model at present, and chemists still need to choose different models for training and learning according to actual situations. This paper aims to show chemists the best cases of common learning methods in chemical synthesis and characterization from the perspective of ML, such as supervised learning, unsupervised learning, semi-supervised learning, reinforcement learning, etc., and help them use ML knowledge to further broaden their research ideas.

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    Attitude Planning Method of Satellite Staring Imaging to Aerial Dynamic Target
    DU Ning, WU Shufan, CHEN Zhansheng, CHEN Wenhui, WANG Shiyao, XU Jiaguo, QIN Dongdong
    Journal of Shanghai Jiao Tong University    2024, 58 (4): 411-418.   DOI: 10.16183/j.cnki.jsjtu.2022.425
    Abstract344)   HTML60)    PDF(pc) (1661KB)(422)       Save

    Aimed at the staring imaging requirements of the low earth orbit (LEO) satellite array camera for aerial dynamic targets, a method for target position estimation and staring attitude planning based on image miss-distance of the satellite platform is proposed. Based on the prior knowledge of the flying altitude of the aerial dynamic target, taking the latitude and longitude change rate of the target geography as the state quantity and the central pixel value of the target as the observation, an extended Kalman filter (EKF) is designed to realize the accurate smooth estimation and prediction of the geographical latitude and longitude of the target. On this basis, the attitude and angular velocity of the satellite are planned, the influence of target pixel noise and delay on attitude stability is avoided, and the position estimation of a single satellite to target is realized. The effectiveness of the proposed method is illustrated by a numerical simulation.

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    Refined Simulation of Near-Surface Wind Field of Atmospheric Boundary Layer Based on WRF-LES Model
    LIU Dalin, TAO Tao, CAO Yong, ZHOU Dai, HAN Zhaolong
    Journal of Shanghai Jiao Tong University    2024, 58 (2): 220-231.   DOI: 10.16183/j.cnki.jsjtu.2022.415
    Abstract1722)   HTML25)    PDF(pc) (9950KB)(414)       Save

    Extreme meteorological disasters such as typhoons pose a serious threat to the safety of engineering structures. Therefore, the refined simulation on the near-surface atmospheric boundary layer (ABL) is valuable for civil engineering. Large-eddy simulation (LES) implemented in the weather research and forecating (WRF) model has the advantages of multiple options of numerical schemes and high accuracy. It is generally suitable for the refined simulation of the near-surface wind field, although the performance of simulation results is closely related to the numerical methods. This paper assesses the impacts of vital parameters regarding subfilter-scale (SFS) stress models, mesh size, and spatial difference schemes within WRF-LES to simulate the ideal ABL in order to figure out appropriate numerical schemes for the refined simulation of the near-surface wind field. The wind field characteristics are addressed and analyzed such as mean wind speed profile, turbulence intensity profile, and power of spectrum. Comparisons of simulation results among different SFS stress models indicate that the nonlinear backscatter and anisotropy one (NBA1) SFS stress model can effectively improve the accuracy of simulation in the near-surface wind profiles. Investigations of mesh resolution effects indicate that the nonuniformly refined vertical grid near the surface agrees much better with the expected profiles and reduces the expenditure of computational resources. Furthermore, the results show that the even-order spatial difference schemes produce more small-scale turbulent structures than the odd-order difference schemes. The numerical methods of WRF-LES proposed can provide a technical reference for refined simulation of the near-surface wind field and typhoon boundary layer.

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    A CNN-LSTM Ship Motion Extreme Value Prediction Model
    ZHAN Ke, ZHU Renchuan
    Journal of Shanghai Jiao Tong University    2023, 57 (8): 963-971.   DOI: 10.16183/j.cnki.jsjtu.2022.089
    Abstract291)   HTML16)    PDF(pc) (2516KB)(392)       Save

    Aimed at the short-term extreme value prediction of ship motion, a sliding window method based on motion spectrum information is proposed to extract feature data, based on which, a series prediction model of convolutional neural networks (CNN) and long short-term memory (LSTM) is built. The CNN module aims at the local correlation characteristics of the input data, and the LSTM module aims at the time dimension characteristics of the data. The simulation test results of S175 ship show that the model has a good prediction effect on the motion extremum information in the next 1 and 2 cycles, and the evaluation indexes are significantly better than those of LSTM and gate recurrent unit (GRU) models, which has an important application value.

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    RUL Prediction Method for Quay Crane Hoisting Gearbox Bearing Based on LSTM-CAPF Framework
    SUN Zhiwei, HU Xiong, DONG Kai, SUN Dejian, LIU Yang
    Journal of Shanghai Jiao Tong University    2024, 58 (3): 352-360.   DOI: 10.16183/j.cnki.jsjtu.2022.440
    Abstract145)   HTML5)    PDF(pc) (5678KB)(376)       Save

    The health condition of hoisting gearbox bearings of quay cranes is of great importance for the safety of port production. A remaining useful life (RUL) predicting framework for lifting gearbox bearings of quay crane under time-varying operating conditions is proposed. First, the working load is discretized and the condition boundaries are determined. Then, the long short-term memory (LSTM) network model is adopted to predict the load and the corresponding operating conditions. Afterwards, considering the degradation rates and jump coefficients under different operating conditions, the state degradation function is established based on the Wiener process. Finally, the condition-activated particle filter (CAPF) is used to predict the degradation state and RUL of bearings. The proposed prediction framework is verified by the full-life data of the hoisting gearbox bearings in a port in Shanghai collected by the NetCMAS system. A comparison with the other three prediction methods shows that the proposed framework is able to obtain more accurate degradation states and RUL predictions under time-varying operating conditions.

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    Optimization Design of New Bionic Propeller
    WU Chunxiao, LU Yu, LIU Shewen, GU Zhuhao, SHAO Siyu, SHAO Wu, LI Chuang
    Journal of Shanghai Jiao Tong University    2023, 57 (11): 1421-1431.   DOI: 10.16183/j.cnki.jsjtu.2022.174
    Abstract1770)   HTML27)    PDF(pc) (10709KB)(374)       Save

    A novel method for optimal design of hydrodynamic performance of bionic propeller with a deformable leading edge is proposed. Based on the bionics principle and method of parameterized modeling, the fore-fin concave-convex structure of humpback whales is applied to the propeller leading edge, the leading edge in the propeller to meet flow region according to the exponential decay curve and the standard sine curve smooth leading edge for similar humpback fins protuberant structure of concave and convex deformation, and the leading edge of concave and convex bionic propeller. The hydrodynamic performance, the cavitation performance, and the noise performance of the exponential decay bionic propeller and the sinusoidal function bionic propeller were simulated respectively. The propeller with a better performance is selected, and the simulation based design (SBD) technology is introduced into the optimization design of the new bionic propeller. The parameters controlling the shape of the exponential attenuation curve of the guide edge deformation are taken as optimization design variables, the torque of the parent propeller is taken as the constraint condition, the open water efficiency is selected as the objective function, and the optimization algorithm of Sobol and T-Search is adopted. A bionic propeller optimization system based on the exponential decay curve is constructed. The results show that the application of the concave and convex structure of the humpback whale fore-fin to the guide edge of the propeller improves the cavitation performance and noise performance of the propeller, but the improvement of the open water performance of the propeller is not particularly significant. It is verified that the hydrodynamic performance optimization design method of the bionic propeller established in this paper is effective and reliable, which provides a certain theoretical basis and technical guidance for the performance numerical calculation and configuration optimization design of the bionic propeller.

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    Key Technologies and Applications of Shared Energy Storage
    SONG Meng, LIN Gujing, MENG Jing, GAO Ciwei, CHEN Tao, XIA Shiwei, BAN Mingfei
    Journal of Shanghai Jiao Tong University    2024, 58 (5): 585-599.   DOI: 10.16183/j.cnki.jsjtu.2022.360
    Abstract1295)   HTML23)    PDF(pc) (4173KB)(361)       Save

    Under the goal of “carbon peaking and carbon neutrality”, the penetration rate of renewable energy continues to rise, whose volatility, intermittency, and uncertainty pose significant challenges to the safe and stable operation of the power system. As a typical application of the sharing economy in the field of energy storage, shared energy storage (SES) can maximize the utilization of resources by separating the “ownership” and “usage” of energy storage resources, which provides a new solution to the problem of imbalance between supply and demand caused by the large-scale integration of renewable energy into the grid, and has broad development prospects. The business model of SES is explored based on value positioning, cost modeling, and profitability strategies, and a detailed summary of SES trading varieties, operational structure, and engineering applications is discussed. Finally, the future trend of shared energy storage is discussed and envisioned.

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    Theoretical Modeling, Simulation Analysis, and Experimental Investigation of a Pneumatic Toothed Soft Actuator
    SU Yiyi, XU Qiping, LIU Jinyang
    Journal of Shanghai Jiao Tong University    2023, 57 (8): 1016-1027.   DOI: 10.16183/j.cnki.jsjtu.2022.039
    Abstract255)   HTML10)    PDF(pc) (17776KB)(356)       Save

    Based on the nonlinear geometric relationship of the bulging angle and the bending angle, and the principle of virtual work and nonlinear constitutive relationship of Neo-Hookean incompressible hyperelastic material, a quasi-static mechanical model for pneumatic toothed soft actuator was established, considering the strain energy of the bottom, side walls, and front and rear walls. Considering the geometric nonlinearity and material nonlinearity, the proposed model could solve the configuration of the soft actuator at different driving pressures and terminal loads precisely and efficiently. The finite element simulation of the cantilevered-free soft actuator was conducted by Abaqus, and the corresponding experimental device was established. The simulation analysis and experimental investigation were performed at different driving pressures. A comparison of the results show that there is a positive linear correlation between the driving pressure and the bending angle of the soft actuator, and the prediction of the theoretical model agrees well with the simulation and experimental results. In addition, the distribution of the strain energy was analyzed. Based on the equal-curvature model, the configuration results of the soft actuator at terminal loads are basically consistent with those obtained by Abaqus. The proposed quasi-static mechanical modeling method provides a theoretical basis for the structural optimization design, performance improvement, and motion control of similar soft actuators.

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    Matching Characteristics of Expansion Valve Opening and Flow Rate of High Temperature Heat Pump with Green Refrigerant HP-1
    WANG Yuehan, NAN Xiaohong, OUYANG Hongsheng, GUO Zhikai, HU Bin, WANG Ruzhu
    Journal of Shanghai Jiao Tong University    2023, 57 (10): 1367-1377.   DOI: 10.16183/j.cnki.jsjtu.2022.155
    Abstract238)   HTML8)    PDF(pc) (1421KB)(339)       Save

    The throttling process, as an important part of the heat pump system, plays a crucial role in the efficient and reliable operation of the whole system. This paper, taking the quasi two-stage compression high-temperature heat pump with green refrigerant HP-1 as the research subject, established the mathematical models of the circulatory system and electronic expansion valve by using MATLAB and considering the influence of the opening of electronic expansion valve and thermodynamic properties of the new green refrigerant. It simulated the matching characteristics of electronic expansion valve opening and flow rate under variable operating conditions, and fitted the HP-1 dimensionless flow coefficient correlation by power-law distribution using experimental data. The research results show that the electronic expansion valve with an elliptical conical body structure adapts to the throttling characteristics of the HP-1 high-temperature heat pump system under variable operating conditions. When the evaporating temperature varies from 50 ℃ to 90 ℃ and the condensing temperature varies from 60 ℃ to 120 ℃, the opening adjustment range of this type of valve body is from 49.8% to 69.8% for the main throttle valve, and from 41.5% to 56.0% for the injection throttle valve. The relative deviation of the fitted correlation results and the actual test data is between -7.8% and +7.5%, and the flow coefficient correlation can accurately predict the flow characteristics of the electronic expansion valve with a similar body structure. The selection of favorable electronic expansion valve matching refrigerant properties and the optimization of the electronic expansion valve control system are essential for the actual operating performance. This study provides a good research foundation for the selection of electronic expansion valves and the optimization of the control system for the HP-1 high temperature heat pump.

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    Low-Carbon Operation Strategy of Integrated Energy System Based on User Classification
    ZHANG Chunyan, DOU Zhenlan, BAI Bingqing, WANG Lingling, JIANG Chuanwen, XIONG Zhan
    Journal of Shanghai Jiao Tong University    2024, 58 (1): 1-10.   DOI: 10.16183/j.cnki.jsjtu.2022.321
    Abstract2246)   HTML32)    PDF(pc) (1783KB)(334)       Save

    Integrated energy system (IES) is an important means to achieve the goal of “carbon peaking and carbon neutrality”. However, different types of users in the system have different energy consumption behaviors, which makes the coordinated optimization and low-carbon operation of the integrated energy system more difficult. In order to give full play to the subjective initiative of users, the user behavior of the integrated energy system is modelled based on user behavior analysis, and users are classified into aggressive and conservative types by convolutional neural network (CNN). Then, the decision model of integrated energy system operator is constructed to determine the supply mode of electric heating energy, and the corresponding energy package is designed for different types of users. Finally, the effectiveness of the above models and methods is analyzed based on actual data, and the value of user classification in low-carbon operation of integrated energy systems is verified.

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    Experimental Study of Influence of Different Parameters on Flow Field Structures Around an Airfoil Covered with Rough Ice
    ZHENG Chengyi, DU Xuzhi, DONG Qiaotian, YANG Zhigang, XIONG Bing, XU Yi, WU Linghao, JIN Zheyan
    Journal of Shanghai Jiao Tong University    2023, 57 (9): 1221-1230.   DOI: 10.16183/j.cnki.jsjtu.2022.149
    Abstract134)   HTML13)    PDF(pc) (8438KB)(322)       Save

    Rough ice can change the leading edge of airfoil and affect the aerodynamic characteristics. Studying the influence of rough ice caused by supercooled water droplets can provide reference for anti-icing design of aircrafts. A detailed experimental study was conducted to measure the flow field structure of an airfoil model with rough ice in a low-speed wind tunnel by using particle image velocimetry. The parameters include Reynolds number, roughness of rough ice, and angle of attack. The results show that with the increase of Reynolds number, the range and value of spanwise vorticity at the wake of the airfoil with ice increased, while the normalized Reynolds stress decreased slightly. The presence of rough ice reduced the airflow velocity near the airfoil, increased the vorticity of wake, and seriously affected the shear stress distribution. Compared with the clean airfoil, the rough ice caused the air flow to separate earlier and the velocity in the separation bubble fluctuated more violently.

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    Support Structure Optimization of High-Pile Cap Supported Horizontal Axis Wind Turbine System Based on BESO Algorithm
    ZHAN Lingyu, HE Wenjun, ZHOU Dai, HAN Zhaolong, ZHU Hongbo, ZHANG Kai, TU Jiahuang
    Journal of Shanghai Jiao Tong University    2023, 57 (8): 939-947.   DOI: 10.16183/j.cnki.jsjtu.2022.182
    Abstract257)   HTML33)    PDF(pc) (9027KB)(309)       Save

    The study of reliable support structure is of great significance to the safety of large-scaled horizontal axis wind turbine (HAWT) system. In this paper, for cap-supported HAWT with high pile, the bidirectional evolutional structure optimization (BESO) algorithm based on inversely proportional deletion rate was used to optimize its support structure. Using computational fluid dynamics (CFD) and the principle of pile-soil interaction, the finite element model of HAWT was established, where the wind load and pile-soil interaction were taken into consideration. The reliability of the structural optimization method was verified through the comparison of the dynamic response characteristics between the initial and the optimized model. The results show that the current BESO algorithm can effectively generate a novel support structure form for high-pile HAWT, whose dynamic response is significantly reduced. The results can provide useful references for HAWTs designs.

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    Operation Parameters of Air-Cooled Fuel Cell Based on In-Situ Testing of Reaction State
    CHEN Minxue, QIU Diankai, PENG Linfa
    Journal of Shanghai Jiao Tong University    2024, 58 (3): 253-262.   DOI: 10.16183/j.cnki.jsjtu.2022.318
    Abstract329)   HTML36)    PDF(pc) (25048KB)(304)       Save

    The internal reaction state of air-cooled proton exchange membrane fuel cell (PEMFC) is the key factor affecting the output performance and stability of the cell. By developing an in-situ testing device for the reaction state of air-cooled fuel cell, the real-time measurement of cell temperature and current density is realized, and the influence mechanism of hydrogen outlet pulse interval, hydrogen inlet pressure and cathode wind speed on the performance of the cell is revealed. The results show that the distribution of temperature and current density in air-cooled cells is uneven. The temperature difference can reach 20 °C, and the current density difference reaches 400 mA/cm2 when the average current density is 500 mA/cm2. As the interval between pulses decreases and the inlet pressure increases, the performance of the hydrogen outlet area and the uniformity of the distribution increase, which can reduce the fluctuation of current density in the cells and improve output stability. If the cathode wind speed is too low, the temperature in central areas is high, and the temperature distribution uniformity is reduced. However, excessive wind speed causes the generating water to be blown away. The water content of the proton exchange membrane thus decreases, and the uniformity of the current density distribution deteriorates.

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    Growth Rates of HFCVD Diamond Films on Silicon Carbide Substrates for Heat Dissipation Applications
    LI Weihan, QIAO Yu, SHU Da, WANG Xinchang
    Journal of Shanghai Jiao Tong University    2023, 57 (8): 1078-1085.   DOI: 10.16183/j.cnki.jsjtu.2022.043
    Abstract227)   HTML4)    PDF(pc) (18057KB)(293)       Save

    Diamond has an extremely high thermal conductivity, making it to have a great potential as a heat dissipation material. Based on the hot filament chemical vapor deposition (HFCVD) technique, diamond thick films were deposited on silicon carbide substrates by using the multi-step method in this paper. The scanning electron microscopy (SEM) and Raman spectroscopy were adopted for characterizing the samples. The influences of filament power, carbon concentration, and reactive pressure on the growth rate and quality of the diamond films were systematically studied. It is found that the diamond film with the best quality is synthesized by adopting a filament power of 1 600 W, a methane/hydrogen flux ratio of 18/300 (nucleation stage) and 14/300 (growth stage), and a reactive pressure of 4 kPa. The corresponding growth rate is 1.4 μm/h.

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    Resilience Evaluation and Enhancement Strategy of Distribution Network Considering Impact of Seismic Attack on Transportation Networks
    YAN Wenting, YANG Long, LI Changcheng, LUO Wei
    Journal of Shanghai Jiao Tong University    2023, 57 (9): 1165-1175.   DOI: 10.16183/j.cnki.jsjtu.2022.152
    Abstract826)   HTML19)    PDF(pc) (2248KB)(292)       Save

    Serious earthquake disasters not only cause power outages in distribution network, but also destroy transportation networks, which hinders the transportation of resources for restoration of distribution network and slows down the restoration. This paper proposes an improved resilience evaluation method and a resilience enhancement strategy of distribution network considering the effects of seismic attack on transportation networks. First, a seismic attack model is established to describe the relation between earthquake disasters and failure probability of transportation-distribution networks based on peak ground acceleration. The impact of earthquake disasters on transportation-distribution networks is quantified, and the failure scenarios are generated. Then, a resilience evaluation index is proposed by introducing the waiting time for road repair of emergency repair teams. Afterwards, a bi-level optimization model for distribution network restoration considering the fault line repair, the road repair, and the emergency resource scheduling is established and solved. The upper layer aims at the minimum power loss load, while the lower layer takes the minimum waiting time of the repair team as the goal. Finally, case studies on a coupling example of a 12-node transportation network and an IEEE 33-node distribution network verify the feasibility of the improved resilience index and the effectiveness of the proposed method. The results show that the resilience index considering seismic attack on transportation networks is accurate, and the restoration strategy can effectively enhance the resilience of distribution network in earthquake disasters.

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    Numerical Study of Deformation and Breakup Processes of Water Droplets in Air Flow
    SANG Xu, JIN Zheyan, YANG Zhigang, YU Fang
    Journal of Shanghai Jiao Tong University    2024, 58 (4): 419-427.   DOI: 10.16183/j.cnki.jsjtu.2022.414
    Abstract288)   HTML19)    PDF(pc) (2771KB)(287)       Save

    Aimed at the problem that water droplets are easy to break up during the acceleration process in icing wind tunnel experiment, which makes it difficult for the particle size distribution of water droplets in the test section to conform to the icing weather conditions, the deformation and breakup regime of water droplets with a diameter of 100, 200, 400, 600, 800, 1 000 and 1 200 μm under the action of different air velocities(20, 50, and 80 m/s) are simulated by using the volume of fluid (VOF) method. The results show that under the action of 20 m/s air flow, the water droplet with a diameter of 600 μm does not break. Under the action of 50 m/s air flow, the water droplet with a diameter of 100 μm does not break. With the increase of Weber number, the wavelength of the most destructive wave also increases, and the breakup regime of water droplets changes from bag breakup to bag-plume breakup, to plume-shear breakup, and to shear breakup successively. The droplet breakup regime, including the bag breakup, bag/plume breakup, the plume/sheet-thinning breakup, and the shear breakup, has a significant effect on the ratio of the area of the largest droplet to the initial droplet. Under the condition that the initial drop diameter is the same, as the inlet velocity increases, the area ratio after breakup increases.

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    Review of High Voltage Ride-Through Control Method of Large-Scale Wind Farm
    WEI Juan, LI Canbing, HUANG Sheng, CHEN Sijie, GE Rui, SHEN Feifan, WEI Lai
    Journal of Shanghai Jiao Tong University    2024, 58 (6): 783-797.   DOI: 10.16183/j.cnki.jsjtu.2022.416
    Abstract330)   HTML9)    PDF(pc) (1884KB)(281)       Save

    As the major demand for the development and utilization of new energy, the large-scale development of wind power is a key support in achieving the strategic goal of “cabron peaking and carbon neutrality” for China. The problem of safe and stable operation of wind farms caused by external grid faults has become one of the key bottlenecks restricting the large-scale, clustered, and intelligent development of wind power. This paper mainly focuses on the voltage surge condition of the power grid. First, it analyzes the transient characteristics of high voltage ride-through (HVRT) of the doubly-fed induction generator-wind turbine, permanent magnet synchronous generator-wind turbine, and wind farms. Then, it summarizes the corresponding HVRT and post-fault voltage recovery coordinated optimal control strategies based on the different control areas, and it classifies and compares the working principles and advantages and disadvantages of various control strategies. Afterwards, it recapitulates the principle, advantages and disadvantages, and effects of the existing HVRT control method for large-scale wind farms, and analyzes the differences between the single wind turbine and the large-scale wind farms from the perspective of control structure. Finally, it discusses the development trend and potential research hotspots of wind farm voltage intelligent safety control in the future, aiming to provide reference for improving the large-scale application of wind power and the safe operation of power grids in China.

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    Coordinated Active Power-Frequency Control Based on Safe Deep Reinforcement Learning
    ZHOU Yi, ZHOU Liangcai, SHI Di, ZHAO Xiaoying, SHAN Xin
    Journal of Shanghai Jiao Tong University    2024, 58 (5): 682-692.   DOI: 10.16183/j.cnki.jsjtu.2022.358
    Abstract1196)   HTML2)    PDF(pc) (2823KB)(278)       Save

    The continuous increase in renewables penetration poses a severe challenge to the frequency control of interconnected power grid. Since the conventional automatic generation control (AGC) strategy does not consider the power flow constraints of the network, the traditional approach is to make tentative generator power adjustments based on expert knowledge and experience, which is time consuming. The optimal power flow-based AGC optimization model has a long solution time and convergence issues due to its non-convexity and large size. Deep reinforcement learning has the advantage of “offline training and online end-to-end strategy formation”, which yet cannot ensure the security of artificial intelligence (AI) in power grid applications. A coordinated optimal control method is proposed for active power and frequency control based on safe deep reinforcement learning. First, the method models the frequency control problem as a constrained Markov decision process, and an agent is designed by considering various safety constraints. Then, the agent is trained using the example of East China Power Grid through continuous interactions with the grid. Finally, the effect of the agent and the conventional AGC strategy is compared. The results show that the proposed approach can quickly generate control strategies under various operating conditions, and can assist dispatchers to make decisions online.

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    Low Carbon Economic Operation of Hydrogen-Enriched Compressed Natural Gas Integrated Energy System Considering Step Carbon Trading Mechanism
    FAN Hong, YANG Zhongquan, XIA Shiwei
    Journal of Shanghai Jiao Tong University    2024, 58 (5): 624-635.   DOI: 10.16183/j.cnki.jsjtu.2022.377
    Abstract1144)   HTML8)    PDF(pc) (3488KB)(278)       Save

    Hydrogen energy plays a crucial role in meeting the “carbon peaking and carbon neutrality” goals, and the carbon capture technology is a vital technique for emission reduction in the energy industry. Blending hydrogen with natural gas to produce hydrogen-enriched compressed natural gas (HCNG) facilitates the transportation and utilization of hydrogen energy. At the same time, applying the carbon capture technology to retrofit thermal power units can effectively promote the large-scale consumption of renewable energy and reduce carbon emissions. For this purpose, a detailed model of hydrogen production equipment and fuel cells is established. Then, aimed at the problem of system carbon emissions, a carbon emission and output model of carbon capture thermal power units and a mathematical model of hydrogen doped cogeneration are established, and a stepped carbon trading mechanism is introduced to control carbon emissions. Based on this, an optimal scheduling model for hydrogen-enriched compressed natural gas integrated energy system is established with the goal of minimizing the sum of energy purchase cost, carbon emission cost, wind abandonment cost, and carbon sequestration cost, and taking into account the constraints such as hydrogen blending ratio and carbon capture in the pipeline network, which is solved by using the particle swarm optimization algorithm in conjunction with CPLEX. The analysis of the models built in different scenarios verifies the advantages of the proposed scheduling model in low-carbon economy.

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    Nonlinear Degradation Modeling and Residual Life Prediction for Rollers Based on Kernel-based Wiener Process
    WANG Hanyu, CHEN Zhen, ZHOU Di, CHEN Zhaoxiang, PAN Ershun
    Journal of Shanghai Jiao Tong University    2023, 57 (8): 1037-1045.   DOI: 10.16183/j.cnki.jsjtu.2022.004
    Abstract236)   HTML6)    PDF(pc) (1553KB)(277)       Save

    In the process of steel rolling, due to wear and other reasons, the working performance of the roll under long and complex working conditions has a gradual decline. Considering the characteristics of complex working conditions and strong random interference of the roll working environment, this paper proposed a kernel-based Wiener process (KWP) degradation model to characterize the strong randomness of the roll degradation trend by using the Wiener process, and to capture the nonlinear degradation path of the roll by using the kerna function. This paper derives the analytical expression of parameter estimation in the Bayesian framework, and constructs the health index of the roll working rotation, then predicts the remaining useful life (RUL) of the roll. In combination with the field data of 1580 hot rolling production line of an iron and steel company, the goodness of fit of the model built is 0.989, and the residual life prediction error is less than 4.7%. Compared with the common machine learning algorithm, it has achieved better results, which is helpful to improve the operating efficiency and safety of equipment and achieve maintenance as needed.

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    A Method for Carbon Emission Measurement and a Carbon Reduction Path of Urban Power Sector
    HU Zhuangli, LUO Yichu, CAI Hang
    Journal of Shanghai Jiao Tong University    2024, 58 (1): 82-90.   DOI: 10.16183/j.cnki.jsjtu.2022.222
    Abstract1979)   HTML8)    PDF(pc) (1670KB)(277)       Save

    To measure and reduce carbon emissions in the urban power sector, a method for measuring carbon emissions in the urban power sector and a carbon reduction path are proposed. First, a carbon emission measurement model for the urban power sector is established based on the data of local power generation and net inward power. Then, carbon reduction measures for the urban power sector are proposed from the generation side, grid side, load side and energy storage side. After that, an evaluation model for the effect of the carbon reduction measures is established. Finally, taking a typical city F in the Pearl River Delta as an example, the proposed carbon emission calculation model is used to calculate the carbon emissions of power sector of the city, and the effectiveness of carbon reduction in 2030 carbon peak scenario of the city is evaluated based on the carbon reduction measures. The results show that the proposed model can accurately measure the carbon emissions of the urban power sector, and by utilizing carbon reduction measures, carbon emissions of the city can be reduced by at least 10.6 million tons in 2030.

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    Numerical Simulation of Stamping-Spinning Hybrid Process for Aluminum Alloy Hemispherical Shells
    YU Xiaopeng, WANG Zimin, YU Zhongqi, LUO Yimin, YU Li
    Journal of Shanghai Jiao Tong University    2023, 57 (10): 1329-1336.   DOI: 10.16183/j.cnki.jsjtu.2022.165
    Abstract156)   HTML6)    PDF(pc) (4480KB)(276)       Save

    Aimed at the poor accuracy in traditional deep drawing of aerospace aluminum alloy hemispherical shells, and by introducing metal spinning, a stamping-spinning hybrid process strategy for aluminum alloy hemispherical shells is proposed, which can achieve the forming processing of the formed component with a high thickness uniformity and high shape accuracy. The finite element simulation model of the hybrid process of the aluminum alloy hemispherical shell is developed, which realizes the simulation. In addition, the variation law of the wall thickness and shape fitting of the hemispherical shells formed by the hybrid process are analyzed. The simulation results show that the uniformity of wall thickness of the hemispherical shells formed by 50% stamping + 50% spinning is significantly improved. The shape accuracy of the component can be obviously improved by changing the stress state of the forming component by power spinning. Meanwhile, the hybrid process is verified by using an aluminum alloy hemispherical shell with a diameter of 1 m in processing test, which improves the thickness uniformity and the shape accuracy of the hemispherical shell.

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    A Resolved CFD-DEM Approach Based on Immersed Boundary Method
    MAO Jia, XIAO Jingwen, ZHAO Lanhao, DI Yingtang
    Journal of Shanghai Jiao Tong University    2023, 57 (8): 988-995.   DOI: 10.16183/j.cnki.jsjtu.2022.095
    Abstract328)   HTML8)    PDF(pc) (11088KB)(274)       Save

    Based on the immersed boundary method, a resolved CFD-DEM algorithm is proposed to tackle fluid-solid interaction problems which widely exist. In the proposed method, the fluid filed is described by the computational fluid dynamics in the Eulerian framework, while the movement and collision of the solids are simulated by the discrete element method in the Lagrangian framework. In order to deal with the moving interfaces between the fluid and the solids, several immersed boundary points are allocated on the boundaries of the solids. Two classic test cases are calculated to verify the accuracy of the proposed method, including the vortex-induced vibration of a cylinder and the rotational galloping of a rectangular rigid body. Good agreements are achieved between the current results and those in previous references and the reliability of the present method in modelling the fluid-solid interaction problems are proved. Finally, the sedimentation of multiple solids is simulated and the ability of the proposed CFD-DEM method in solving the complex fluid field and the collision among the solids with arbitrary shapes are verified.

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    Energy Management Strategy of Integrated Electricity-Heat Energy System Based on Federated Reinforcement Learning
    WANG Jinfeng, WANG Qi, REN Zhengmou, SUN Xiaochen, SUN Yi, ZHAO Yiyi
    Journal of Shanghai Jiao Tong University    2024, 58 (6): 904-915.   DOI: 10.16183/j.cnki.jsjtu.2022.418
    Abstract243)   HTML3)    PDF(pc) (4615KB)(271)       Save

    The energy management of the electricity-heating integrated energy system (IES) is related to the economic benefits and multi-energy complementary capabilities of a park, but it faces the challenges of the randomness of renewable energy and the uncertainty of load. First, in this paper, a mathematical model of the energy management problem for the electricity-heating IES is conducted, and each energy supply subsystem is empowered as an agent. Based on the deep deterministic policy gradient (DDPG) algorithm, a system energy management model is established that comprehensively considers the real-time energy load of the subsystem, the time-of-use pricing, and the output of each equipment. Then, the federated learning technology is used to interact with the gradient parameters of the energy management model of the three subsystems during the training process to synergistically optimize the training effect of the model, which can protect the data privacy of each subsystem while breaking the data barriers. Finally, an example analysis verifies that the proposed federated-DDPG energy management model can effectively improve the economic benefits of the park-level IES.

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    Evaluation of Thermal Insulation Performance of EB-PVD YSZ Thermal Barrier Coatings by Phosphorescence Lifetime Online Measurement
    LIU Zhenghong, YU Yali, CHENG Weilun, LI Muzhi, YANG Lixia, ZHAO Xiaofeng, PENG Di, MOU Rende, LIU Delin
    Journal of Shanghai Jiao Tong University    2023, 57 (9): 1186-1195.   DOI: 10.16183/j.cnki.jsjtu.2022.252
    Abstract162)   HTML11)    PDF(pc) (10690KB)(270)       Save

    Precise measurement of the thermal insulation performance of thermal barrier coatings (TBCs) under the thermal gradient environment is important for the design and development of TBCs. A phosphorescent sensor TBC which contains an Eu doped yttria-stabilized zirconia (YSZ:Eu) surface layer, a YSZ intermediate layer, and a YSZ:Dy bottom layer, is designed and prepared by electron beam physical vapor deposition (EB-PVD). Based on the thermal quenching characteristics of phosphorescence signal, the surface temperature of the YSZ coating and the interface temperature of the bond-coat/YSZ layer are measured online in a temperature gradient environment, and the real thermal insulation effect of the EB-PVD YSZ thermal barrier coating is evaluated. The results show that the EB-PVD YSZ coating with a thickness of 113 μm can achieve an average temperature decrease of 66.5 ℃. The average thermal conductivity of the coating is (0.87±0.15) W/(m·K) in the temperature range between 400 and 700 ℃, which is slightly lower than the value (0.95±0.02) W/(m·K) obtained by using the traditional laser flash method. The above results validate the reliability of online phosphorescence temperature measurement technique, and provide an effective method to monitor the thermal insulation effect of TBCs in real time.

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    Forced Oscillation Characteristics of Natural Gas Mixed with Hydrogen Combustion in Gas Turbine Central Staged Burner
    SHI Ting, JIN Ming, GE Bing, ZANG Shusheng
    Journal of Shanghai Jiao Tong University    2024, 58 (3): 304-311.   DOI: 10.16183/j.cnki.jsjtu.2022.454
    Abstract206)   HTML4)    PDF(pc) (12811KB)(260)       Save

    Natural gas mixed with hydrogen combustion is one of the important measures to reduce carbon emissions of gas turbine. However, the composition change of fuel will lead to changes in the flame structure and combustion stability of the combustor. In order to analyze the combustion instability of natural gas mixed with hydrogen combustion in the central staged burner, the effects of different hydrogen doping ratios on the transient flame structure, pressure and heat release response of the central staged combustion are experimentally studied. The proper orthogonal decomposition (POD) method is used to extract the characteristic modes of flame pulsation. It is found that the flame pulsation mainly includes two modes: a strong pulsation in the interference zone of flame and an axial disturbance. The experimental results show that as the volume ratio of hydrogen doped increases from 0% to 30%, the flame front moves upstream, the spacing between two staged flames is shortened, the energy proportion of pulsation mode corresponding to the flame interference increases, and the coupling of pressure and heat release is strengthened, which ultimately results in a 9% increase in pressure response and a 37% increase in heat release response in the combustor.

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    Remaining Useful Life Prediction of IGBT Modules Across Working Conditions Based on ProbSparse Self-Attention
    ZHONG Zhiwei, WANG Yuxiang, HUANG Yixiang, XIAO Dengyu, XIA Pengcheng, LIU Chengliang
    Journal of Shanghai Jiao Tong University    2023, 57 (8): 1005-1015.   DOI: 10.16183/j.cnki.jsjtu.2021.538
    Abstract373)   HTML12)    PDF(pc) (5921KB)(251)       Save

    In order to improve the accuracy of remaining useful life (RUL) prediction of insulated gate bipolar transistor(IGBT) modules across working conditions to enhance their reliability, an RUL prediction method based on the ProbSparse self-attention mechanism and transfer learning was proposed based on the transient thermal resistance features of IGBT modules under different working conditions. An accelerated aging test bench of the IGBT module was designed ang built to perform power cycling experiments in different temperature ranges, and state data of full life-time under different working conditions were collected. Transient thermal resistance change data during the IGBT module degradation were calculated, and the transient thermal features that can accurately reflect the aging state of the IGBT module were extracted and selected. These features were used to predict the RUL of IGBT modules across different working conditions based on the proposed method. The experimental result shows that the accuracy of the proposed RUL prediction method of IGBT modules across working conditions outperforms other compared methods. Particularly, the RUL prediction accuracy during the early degradation stage has been significantly improved.

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    Defect Classification of Weld Metallographic Structure Based on Data Augmentation of Poisson Fusion
    BAI Xiongfei, GONG Shuicheng, LI Xuesong, XU Bo, YANG Xiaoli, WANG Mingyan
    Journal of Shanghai Jiao Tong University    2023, 57 (10): 1316-1328.   DOI: 10.16183/j.cnki.jsjtu.2022.202
    Abstract294)   HTML11)    PDF(pc) (10332KB)(250)       Save

    The classification of the defects in welding applications based on the metallographic structure images plays an important part in industrial welding quality inspections. In order to improve the classification performance of defects in the weld metallographic structure images with a small sample dataset available (the amount of samples being less than 30), a Poisson fusion method is used for data augmentation of the defect images and the ResNet18_PRO network is proposed. Both of the methods notably improve the defects classification performance. During data augmentation, the defect area is extracted from original defect samples via digital image processing, and the defect area is fused with normal samples by the Poisson fusion method to generate new defect samples, thus increasing the number of defect samples. The model in this paper is improved based on the ResNet18 network. The downsampling structure is improved to reduce the information loss in the original downsampling structure, and an improved space pyramid pooling structure is added at the end of the network to integrate multi-scale feature information. The classification performance before and after data augmentation is compared by different classification models, which verifies the significant effect of the data augmentation on the classification performance. Meanwhile, the ablation experiment of the ResNet18_PRO is conducted to verify the effectiveness of the improved network structure and the training strategy. It is found that the average classification accuracy of ResNet18_PRO reaches 98.83% and the average F1-score reaches 98.76%, which greatly improves the classification accuracy of metallographic structure defects. Finally, the network is trained and tested with another industrial defect dataset and obtains good classification results. These results show that the proposed network has a good robustness and practical application value.

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    Numerical Analysis of Hydrodynamic Performance of Propeller in Waves
    ZHANG Geng, YAO Jianxi
    Journal of Shanghai Jiao Tong University    2024, 58 (2): 175-187.   DOI: 10.16183/j.cnki.jsjtu.2022.247
    Abstract1103)   HTML11)    PDF(pc) (14901KB)(246)       Save

    The hydrodynamic performance of propeller is mostly studied in calm water, but the propeller working behind ship is often affected by waves. According to the literature, there is relatively little research on hydrodynamic performance of propeller in waves at present. In view of this, RANS solver based on OpenFOAM is used to calculate and analyze the influence of waves on the thrust and torque of propeller. The results show that time history curves of thrust and torque oscillate under the influence of waves. The disturbance of free surface and the oscillation amplitude of time history curves increase with the decrease of immersion depth and advance coefficient. Compared with the calm water condition, the average thrust and torque of propeller in waves are reduced when the immersion depth and advance coefficient are the same. The computational results are in good agreement with the experimental data.

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    Optimization of Lithium Battery Lifetime Based on Dual-Stage Active Topology
    ZHANG Cheng, JU Changjiang, XIONG Can, YANG Genke
    Journal of Shanghai Jiao Tong University    2024, 58 (5): 719-729.   DOI: 10.16183/j.cnki.jsjtu.2022.285
    Abstract1089)   HTML3)    PDF(pc) (1687KB)(245)       Save

    With the increasing demand for energy storage charging stations, many energy storage systems utilize lithium batteries as the major carriers. However, due to frequent charging and discharging at high power levels, the cycle life of lithium batteries is greatly reduced, which increases the energy storage costs. Given the longevity of supercapacitors, a supercapacitor-lithium hybrid energy storage system has been developed to effectively extend the lifespan of lithium batteries and reduce both investment and operational costs of energy storage charging stations. Based on the dual-stage active topology, a hybrid energy storage system combining supercapacitor-lithium is proposed. Under mild load conditions, two supercapacitor modules are alternatively charged by the lithium battery. Then, the supercapacitor modules are discharges when high power demands are encountered. Accordingly, based on working conditions of the charging pile, a multi-stage strategy, integrating state-of-power estimation and programming, is proposed to optimize the power distribution, smooth the power fluctuation of the lithium battery, and protect the lithium battery. The simulation results show that compared with the lithium batteries only energy storage and the traditional full active topology energy storage, the dual-stage active topology energy storage significantly improves the cycle life of lithium batteries.

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    Experimental Investigation of Dynamic Response of Pile-Supported Wharf in Liquefiable Ground Under Wave Action
    BI Jianwei, SU Lei, XIE Libo, ZHANG Yu, LING Xianzhang
    Journal of Shanghai Jiao Tong University    2023, 57 (11): 1442-1454.   DOI: 10.16183/j.cnki.jsjtu.2022.163
    Abstract1606)   HTML9)    PDF(pc) (8259KB)(245)       Save

    Pile-supported wharf (PSW) is widely used in the deep-water port engineering construction, most of which are located in liquefiable ground. The effect of wave action on the working performance of PSW in liquefiable ground cannot be ignored, but few studies have been reported. This study performs the wave flume test of PSW in liquefiable ground considering the soil-structure-wave interaction. This test really reproduces the operating condition of PSW, and explores the internal response difference of wharf structure under wave. The influence of wave height on dynamic response of the PSW system is discussed systematically. The result shows that the acceleration and displacement of the PSW deck gradually increase first and finally remain relatively stable with the increase of wave action. The hydrodynamic pressure and deformation of each pile in pile group are obviously different, and the response variation is related to the pile position. The pore pressure of the soil layer in the free field and around the pile decreases with the increase of depth, and the existence of the pile group can reduce the pore pressure in the soil layer around the pile, and increase the acceleration of the soil layer. The effect of wave height on the soil layer decreases with the increase of depth. The above results can provide reference for the similar PSW test under wave and the support for the design and wave protection of PSW.

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    Two Dimensional Nonlinear Consolidation Analysis of Saturated Soft Soil Around Tunnel
    HU Anfeng, GONG Zhaoqi, XIAO Zhirong, CHEN Yuan
    Journal of Shanghai Jiao Tong University    2023, 57 (12): 1631-1638.   DOI: 10.16183/j.cnki.jsjtu.2022.228
    Abstract107)   HTML8)    PDF(pc) (2636KB)(239)       Save

    Considering the nonlinear changes of compressibility and permeability of soft soil around the tunnel, a two-dimensional nonlinear seepage consolidation control equation is established, which is solved by an alternating implicit difference method, and the development law of the average degree of consolidation with time under the three conditions of complete permeability, complete impermeability, and semi permeability of the tunnel is obtained. By comparing the degenerate solution with the existing analytical solution, the correctness of the difference solution is verified. In addition, the effects of compression index Cc and permeability index Ck on the consolidation degree of soft soil around the tunnel are analyzed. The results show that the permeability of tunnel is an important factor affecting the development and change of consolidation degree. The influence of compression index Cc on the development of degree of consolidation is less than that of permeability index Ck. Seepage consolidation will change the effective stress field of the soil around the tunnel, and the average degree of consolidation decreases with the increase of permeability index Ck. If the nonlinearity of soil is not considered, there will be a large error in the calculation of degree of consolidation.

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    Arc Attachment Characteristics of Carbon Fiber Reinforced Thermoplastic Materials
    XIE Minqi, XIAO Cien, BIAN Jiapeng, LIU Yakun, FAN Yin, CHEN Xiuhua, LIU Libo
    Journal of Shanghai Jiao Tong University    2023, 57 (9): 1214-1220.   DOI: 10.16183/j.cnki.jsjtu.2022.146
    Abstract165)   HTML13)    PDF(pc) (14040KB)(231)       Save

    As a promising structural material, carbon fiber reinforced thermoplastic (CFRTP) has been gradually applied on aircrafts. The lightning arc adhesion characteristics of CFRTP, however, are still unclear. Therefore, the arc adhesion characteristics of CFRTP were studied by simulating the lightning test method. Based on the finite element method, the effect of CFRTP on spatial electric field was analyzed and compared with that of metal materials. It is found that for the structure containing both CFRTP and metal materials, CFRTP is possible to be attached by the lightning discharging channel, but the probability is lower than that of the metal material by 22.5%. In the process of lightning arc adhesion, single upward leader and multiple upward leaders appear on the surface of CFRTP, resulting in the corresponding single or multiple arc attachment points. Simultaneous adhesion of lightning arc on both CFRTP and metal material also occurs. The spatial electric distribution obtained by simulation is consistent with the experimental results. This paper can provide the basis for the lightning characteristics and damage response of CFRTP.

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