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    Transknowletology: Its Naming and Concept Construction,
    MENG Xiangchun
    Contemporary Foreign Languages Studies    2022, 22 (3): 55-64.   DOI: 10.3969/j.issn.1674-8921.2022.03.007
    Abstract1241)   HTML31)    PDF (1268KB)(228)      

    With cross-cultural interaction between local knowledge and global knowledge as its fundamental rationale, and with knowledge and culture synthesized in this conception, Transknowletology, proposed by Yang Feng, integrates “knowledge” in the ontological sense into Translatology, thereby constructing a fundamentally and ultimately knowledge-centered translation theory whose major inquiry focuses on “knowledge translation” and “translated knowledge” essentially in the framework of translation studies. If it should develop following the path of “studies of knowledge translation”, the term “knowledge translation studies”, therefore, may serve as its proper name. If it develops as knowledge-rooted-and-centered translation studies, as it is intended, Transknowletology may be its possible, if not the best, name. By virtue of the naming of “Transknowletology” per se, a series of new concepts or discourses can be reversely constructed, such as “knowledge glocalization”, the “scissors differential of knowledge”, “knowledge impact”, “knowledge-culture entanglement”, the “ripple effect of knowledge”, and the “knowledge translation paradox”, thus enriching and empowering the theory in question. A complete, mature Transknowletology necessitates a proper definition of “knowledge”, the establishment of translation criteria, the organic synthesis of newly constructed concepts and discourses, self-introspection with “others” as frames of reference, and engagement in global scholarship through discourse featuring “comparative glocalism”. These endeavors may enrich and even reshape global translation studies.

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    An Identification Method for DC-Link Capacitor Capacitance of Grid Connected Inverter
    ZHU Chenghao, WANG Han, SUN Guoqi, WEI Xiaobin, WANG Fuwen, CAI Xu
    Journal of Shanghai Jiao Tong University    2022, 56 (6): 693-700.   DOI: 10.16183/j.cnki.jsjtu.2021.515
    Abstract683)   HTML1271)    PDF (5050KB)(866)      

    DC-link for the capacitor is one of the most vulnerable components of the grid connected converter, whose capacitance identification will help to improve the system reliability by finding and replacing the aging capacitor in time. An identification method for the DC-link capacitor capacitance of the grid connected inverter based on pre-charging circuit is proposed. By analyzing the relationship between the capacitance and the charging current, charging voltage during pre-charging process, and combining the historical operating data, the set of capacitance state feature vector is built. The support vector regression (SVR) model is trained and the regression prediction relationship between the state value and the capacitance is set. The model is optimized by using the particle swarm optimization (PSO) algorithm, which can be used for capacitance identification of the DC-link capacitor. Simulation and experiments results show that the proposed method can implement the accurate capacitance identification of the DC-link capacitor of the grid connected inverter, with an identification error of less than 0.95%. This method does not need to add hardware circuit and change the control algorithm, and has a certain practical value.

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    A Novel Prediction Model for Fatigue Strength
    DUAN Hongyan, TANG Guoxin, SHENG Jie, CAO Mengjie, PEI Lei, TIAN Hongwei
    Journal of Shanghai Jiao Tong University    2022, 56 (6): 801-808.   DOI: 10.16183/j.cnki.jsjtu.2021.051
    Accepted: 08 June 2021

    Abstract659)   HTML119)    PDF (1208KB)(394)      

    Fatigue failure is one of the most important reasons for the failure of engineering application components. However, due to the high cost of fatigue experiments, it is necessary to use mechanical properties to predict fatigue strength. Based on the true stress-strain curves, a novel model for fatigue strength prediction is established and is used to calculate the fatigue strength. The strength predicted is compared with that calculated by the staircase method and the Basquin equation. The results show that the model could obtain the fatigue strength of the materials only by using tensile strength and work-hardening strength, and it is suitable for other steels, which greatly saves costs and increases accuracy.

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    Differentiated Allocation Model of Renewable Energy Green Certificates for New-Type Power System
    ZHANG Shuo, LI Wei, LI Yingzi, LIU Qiang, ZENG Ming
    Journal of Shanghai Jiao Tong University    2022, 56 (12): 1561-1571.   DOI: 10.16183/j.cnki.jsjtu.2022.150
    Accepted: 24 October 2022

    Abstract634)   HTML757)    PDF (1436KB)(333)      

    In order to achieve China’s “30·60” decarbonization goal, the green and low-carbon transformation of the energy system is the fundamental support; the construction of new-type power system is the key step, and the green certificate is the important voucher to reflect the green value of renewable energy. Currently, the distribution mechanism of green certificates in China is oversimplified, which neither effectively measures the variability of green values generated by different types of renewable energy, nor balances the coordinated development of renewable energy. Therefore, to differentiate the exchange mechanism of green certificates by different types of renewable energy power in this paper, an evaluation index system is established, which describes the difference between green certificates, considering the comprehensive value of renewable energy, and an evaluation model is built with the criteria importance by using the intercriteria correlation (CRITIC) method, the entropy weight method, and the technique for order preference by similarity to an ideal solution (TOPSIS) method. Under the development scenario of peaking carbon emissions before 2030, the impact of the differentiated distribution model on the green incomes of centralized photovoltaic distributed photovoltaic power, onshore wind power, and offshore wind power is analyzed. Moreover, the development plan of renewable energy is modified in consideration of the effect of the differentiated distribution model, and policy suggestions on green certificates are proposed accordingly. The results show that the differentiated distribution model of green certificates is practical to provide corresponding decision-making support to the construction and improvement of green certificates trading mechanism in China.

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    Real-Time Calculation of Carbon Emissions in County-Level Administrative Regions Based on ‘Energy Brain’
    CHEN Yun, SHEN Hao, WANG Jiayu, ZHAO Wenkai, PAN Zhijun, WANG Xiaohui, XIAO Yinjing
    Journal of Shanghai Jiao Tong University    2022, 56 (9): 1111-1117.   DOI: 10.16183/j.cnki.jsjtu.2021.364
    Abstract622)   HTML771)    PDF (851KB)(441)      

    Existing calculation methods of carbon emission cannot well meet the needs of gradual refinement and real-time of carbon emission regions. In order to ensure the real-time and accuracy of carbon emissions responsibility allocation, a real-time calculation method of carbon emissions in urban regions is proposed. The improved K-means clustering algorithm is used to cluster and combine the operating periods and operating scenarios of the urban area energy load,so as to obtain the typical carbon emission characteristics. The regional unit electricity carbon emission is proposed as a carbon emission indicator, the operating period and scenario are classified, and the unit electricity carbon emission and the total carbon emission of urban regions for each cluster are calculated. The proposed algorithm is verified based on part of the historical data of energy consumption in the energy brain of a certain region in eastern China. The results show that the clustering method and carbon emission indicators can effectively calculate the total carbon emission of urban regions in real-time.

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    Challenges of Distributed Green Energy Carbon Trading Mechanism and Carbon Data Management
    LI Xingzhi, HAN Bei, LI Guojie, WANG Keyou, XU Jin
    Journal of Shanghai Jiao Tong University    2022, 56 (8): 977-993.   DOI: 10.16183/j.cnki.jsjtu.2021.450
    Abstract609)   HTML873)    PDF (2604KB)(762)      

    To achieve the double carbon goal of “carbon peaking and carbon neutrality”, the construction of the power system which is based on the green energy needs to be accelerated. With the growth of the system scale, the distributed green energy carbon trading mechanism and the carbon data management technology based on the blockchain technology can effectively encourage the development of green energy and become effective means for the implementation of low-carbon electricity. The accurate and real-time carbon emission calculation will further provide data support for the accuracy and security of carbon trading information. First, the current research status of green certificate trading and carbon asset management is introduced. Next, the adaptability analysis of the key technologies of the blockchain technology in the four directions of green electricity traceability, green certificate trading, carbon trading, and joint market of green certificate and carbon assets is performed. Afterwords, the specific mathematical models of carbon emission calculation is studied, and the data availability of carbon source traceability methods applicable to the blockchain architecture are discussed. Finally, some suggestions for the future development of carbon emission flow analysis are proposed.

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    Application of Plane Elements and Shell Elements in Imitating Ribs of Members in Compound Strip Method
    HOU Yanguo, LI Zhanjie, GONG Jinghai
    Journal of Shanghai Jiao Tong University    2022, 56 (6): 710-721.   DOI: 10.16183/j.cnki.jsjtu.2021.071
    Abstract579)   HTML445)    PDF (10465KB)(449)      

    Finite strip method (FSM) is a classical method to analyze the buckling of thin-walled members. The traditional FSM adopting trigonometric functions longitudinally can hardly analyze the members with spaced ribs along the longitudinal direction, while the compound strip method (CSM) can compensate for this shortcoming. Based on the CSM, the influence of utilizing plane elements and shell elements to respectively imitate stiffeners on buckling is investigated. Compared with the shell-element ribs, the plane-element ribs are prone to assembling the stiffener matrices with fewer degrees of freedom. But the shell-element ribs are more comprehensive as the out-plane displacement of ribs are taken into consideration. It is found that plane element ribs and shell element ribs have little difference on the buckling capacity of members. The buckling capacity has a small difference of mean absolute error (MAE) underneath 0.75% between the two types of CSMs, and the buckling capacity and modes are in good agreement with the finite element results. The buckling loads of the two types of CSMs are close to the FEM with a MEA less than 5%. The accuracy of the plane elements satisfies the predicted requirements, which helps to reduce the program computation and simplify the analysis complexity. The efficiency of analysis can be dramatically improved for fine meshing elements.

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    Linear Parameter-Varying Integrated Control Law Design for a Hypersonic Vehicle
    YANG Shu, QIAN Yunxiao, YANG Ting
    Journal of Shanghai Jiao Tong University    2022, 56 (11): 1427-1437.   DOI: 10.16183/j.cnki.jsjtu.2022.190
    Accepted: 05 September 2022

    Abstract549)   HTML341)    PDF (2903KB)(276)      

    A linear parameter-varying (LPV) integrated control law is designed for a hypersonic vehicle to achieve trajectory control based on an altitude-horizontal trajectory control concept. The LPV output-feedback control theory and pole placement techniques are employed to design parameters of the control law within a Mach number envelope. Such a control law performs integrated control for longitudinal and lateral-directional dynamics of the vehicle, free from the scheme of inner and outer control loops of classical flight controls and ensuring robust and optimal control performance in the sense of L2-induced norm. A mathematical model of the hypersonic vehicle is developed in the Earth-centered-Earth-fixed reference frame. Earth rotation, Earth oblateness, and the second order harmonic perturbations of Earth are considered in the model. Numerical simulations are conducted to examine the performance of the LPV controller. The simulation results indicate that the closed-loop system of the hypersonic vehicle achieves D-stability. The LPV control law achieves a good performance in vehicle trajectory control and has sufficient robustness with respect to perturbations and sensor noise.

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    Inertial Control Strategy for Wind Farm with Distributed Energy Storage System Based on Model Predictive Control
    SHEN Yangwu, SONG Xingrong, LUO Ziren, SHEN Feifan, HUANG Sheng
    Journal of Shanghai Jiao Tong University    2022, 56 (10): 1285-1293.   DOI: 10.16183/j.cnki.jsjtu.2022.134
    Accepted: 19 May 2022

    Abstract533)   HTML1086)    PDF (1641KB)(362)      

    Distributed energy storage (DES) wind turbine is an effective means to solve the problem of system frequency stability caused by large-scale wind power connection. In this paper, an inertial control method for DES wind farms based on model predictive control (MPC) is proposed.First, the linearized prediction model of the DES wind farm is established. Then, on this basis, in combination with the control framework of MPC, an optimization model and strategy of MPC inertial control are proposed considering the cost of energy storage loss and the balanced change of wind turbine rotor speed,in order to achieve the balanced change of wind turbine rotor speed during inertia control. The simulation results show that the proposed control strategy can effectively coordinate the active power output of the wind power generation unit and the energy storage system unit in the DES wind turbine, reduce the cost of charging and discharging loss of the energy storage system, and ensure that the rotational speed of all wind turbines in the wind farm tends to be average during the inertial control period, avoiding the problem of wind turbines exiting frequency regulation due to excessive reduction of the rotational speed of wind turbines. The inertial control strategy of the DES wind farm is beneficial to improve the frequency stability of the power grid, which is of great significance to ensure the safe operation of the power grid.

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    Ultra-Short-Term Load Forecasting of Electric Vehicle Charging Stations Based on Ensemble Learning
    LI Hengjie, ZHU Jianghao, FU Xiaofei, FANG Chen, LIANG Daming, ZHOU Yun
    Journal of Shanghai Jiao Tong University    2022, 56 (8): 1004-1013.   DOI: 10.16183/j.cnki.jsjtu.2021.486
    Abstract519)   HTML374)    PDF (3182KB)(415)      

    Accurate electric vehicle load forecasting is the basis for maintaining the safe and economical operation of charging stations, and for supporting the planning and decision-making of new and expanded charging infrastructure. In order to improve the accuracy of the ultra-short-term load forecasting of charging stations, an ultra-short-term load forecasting method based on ensemble learning is proposed. First, aimed at the prediction accuracy and the response speed, the light gradient boosting machine (LightGBM) framework is utilized to build several basic regressors. Next, the basic regressors are integrated by using the adaptive boosting (Adaboost) method. Finally, by using hyperparameter adjustment and optimization, a dual-system for ultra-short-term load forecasting of charging stations named energy ensemble boosting-light gradient boosting machine (EEB-LGBM) is generated. The analysis of the numerical examples shows that the proposed model has a higher accuracy than the back propagation neural network (BPNN), convolutional neural networks-long short term memory (CNN-LSTM), autoregressive integrated moving average (ARIMA), and other load forecasting methods, which can greatly reduce the training time and the computing power requirements of the training platform.

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    Energy Consumption Prediction of Office Buildings Based on CNN-RNN Combined Model
    ZENG Guozhi, WEI Ziqing, YUE Bao, DING Yunxiao, ZHENG Chunyuan, ZHAI Xiaoqiang
    Journal of Shanghai Jiao Tong University    2022, 56 (9): 1256-1261.   DOI: 10.16183/j.cnki.jsjtu.2021.192
    Abstract511)   HTML71)    PDF (2358KB)(215)      

    In order to accurately reflect the operation characteristics of office buildings, a convolutional neural network(CNN)-recurrent neural network(RNN)combined model for energy consumption prediction of office buildings is proposed by using the good feature extraction ability of CNN and the good time series learning ability of RNN. Besides, a two-dimensional matrix data input structure suitable for the deep learning model is designed. The case study results show that compared with the simple recurrent neural network and long short term memory network, both the prediction accuracy and computational efficiency of CNN-RNN combined model are significantly improved, and the generalization of the model is also good.

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    A Shared Energy Storage Optimal Operation Method Considering the Risk of Probabilistic Voltage Unbalance Factor Limit Violation
    FANG Xiaotao, YAN Zheng, WANG Han, XU Xiaoyuan, CHEN Yue
    Journal of Shanghai Jiao Tong University    2022, 56 (7): 827-839.   DOI: 10.16183/j.cnki.jsjtu.2021.455
    Abstract508)   HTML595)    PDF (1838KB)(357)      

    The distributed access with single-phase and uncertain generation of the renewable energy increase the risk of voltage unbalance limit violation in the distribution network. With the increasing penetration rate of the renewable energy generation, it is important to study the mitigation of the impacts of intermittent renewable energy generation on the risk of voltage unbalance limit violation in the distribution network. A shared energy storage allocation strategy and optimal operation method based on global sensitivity analysis (GSA) is proposed. First, a back propagation neural network (BPNN) based probabilistic voltage unbalance factor calculation model for the distribution network is constructed, and the risk index of the distribution network probabilistic voltage unbalance factor limit violation is defined, which can quickly and accurately quantify the impact of uncertain renewable energy generation on the risk of voltage unbalance limit violation in the distribution network. Then, a GSA method based on Wasserstein distance is proposed to identify the critical renewable energy sources affecting the distribution network voltage unbalance. Finally, the GSA-based shared energy storage allocation strategy and the rolling prediction optimization-based operation method of the shared energy storage are proposed. The effectiveness of the proposed method is verified through the simulation analysis of IEEE 123-bus distribution network.

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    Intelligent Global Sensitivity Analysis Based on Deep Learning
    WU Shuchen, QI Zongfeng, LI Jianxun
    Journal of Shanghai Jiao Tong University    2022, 56 (7): 840-849.   DOI: 10.16183/j.cnki.jsjtu.2021.191
    Abstract504)   HTML33)    PDF (1418KB)(366)      

    This paper proposes an end-to-end method that combines deep learning and sensitivity analysis, which can perform gradient back propagation calculation sensitivity on the saved weight information while training the model. The structure and activation function of the depth model are specially designed to adapt to the subsequent sensitivity calculation. The experimental results conducted on a Boston house prices dataset, a track information fusion dataset, and the G function show that the proposed method is more accurate than classical methods such as Sobol’ method when the parameter distribution is uneven, and has a stronger robustness. Compared with the traditional neural network method, the accuracy of the proposed method is higher. The experiment proves that the sample parameter sensitivity obtained by the deep learning model can be used to optimize the model output.

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    An LC Inverter Based on Novel Dual-Loop Control
    LI Shuang, SHI Jianqiang
    Journal of Shanghai Jiao Tong University    2022, 56 (9): 1139-1147.   DOI: 10.16183/j.cnki.jsjtu.2021.275
    Abstract488)   HTML118)    PDF (1553KB)(417)      

    To improve the voltage tracking and anti-disturbance performance of the LC inverter, a novel voltage-current dual-loop control strategy is proposed. First, the voltage loop is tuned to first-order inertia link by zero-pole cancellation based on virtual resistance, which restrains the overshoot during voltage tracking. Next, the hypo-time-optimal current-loop is adopted to enhance the response speed of the current loop, which suppresses the sudden change of transient voltage. Finally, the cause of overshoot during the voltage recovery period is analyzed and the overshoot is eliminated by the adaptive integrator initial value, which modifies the voltage waveform distortion under loading disturbance. Based on the traditional double-loop control, the voltage loop and the current loop are improved respectively by the proposed novel control strategy, which overcomes the shortcomings of step response and anti-load disturbance performance. The feasibility and effectiveness of this method are validated through simulations on MATLAB/Simulink.

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    Radar Signal Recognition Based on Dual Channel Convolutional Neural Network
    QUAN Daying, CHEN Yun, TANG Zeyu, LI Shitong, WANG Xiaofeng, JIN Xiaoping
    Journal of Shanghai Jiao Tong University    2022, 56 (7): 877-885.   DOI: 10.16183/j.cnki.jsjtu.2021.209
    Abstract485)   HTML21)    PDF (4098KB)(352)      

    In order to solve the problems of difficult feature extraction and low recognition rate of radar signal at low signal-to-noise ratios, a dual channel convolutional neural network model based on Choi-Williams distribution (CWD) and multisynchrosqueezing transform (MSST) is proposed, which obtains two-dimensional time-frequency images by CWD and MSST time-frequency analyses on radar signals. Respectively, the time-frequency images are preprocessed and sequencely fed to a dual channel convolutional neural network for deep feature extraction. Finally, the features acquired by the two channels are fused, and the radar signal is classified and recognized through the convolutional neural network classifier. The simulation results show that when the signal-to-noise ratio is -10 dB, the overall recognition accuracy can reach above 96%, which is excellent at low signal-to-noise ratios.

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    Cryogenic Minimal Quantity Lubrication Assisted Cutting Process for Polyimide Materials
    CAO Zheng, LEI Xuelin, ZHANG Hang, CAI Xiaojiang
    Journal of Shanghai Jiao Tong University    2022, 56 (6): 784-793.   DOI: 10.16183/j.cnki.jsjtu.2021.173
    Accepted: 22 September 2021

    Abstract473)   HTML21)    PDF (21845KB)(459)      

    The cutting performance of the porous polyimide material assisted by cold air trace lubrication was investigated, and the influence law of cutting process parameters on the cutting effect (cutting force, surface finish quality, and oil content) of the porous material was explored. The results show that compared with dry cutting and low-temperature cold air cutting, the cutting temperature and the machined surface roughness of cold air micro-lubrication cutting are the lowest, and the damage to the porous runner is the smallest. The depth of cut and the feed volume are the factors that have the greatest influence on milling force and surface roughness, respectively. Defects such as chip burrs and tears are the main factors that lead to the increase in surface roughness. The existence of drawing, micro-crack, stacking, and tiny debris on the workpiece surface are the main causes for the decrease in the oil content and oil delivery rate of the material. The optimal machining parameters of the porous polyimide material in the orthogonal experiment with the aid of cold air trace lubrication are vc=(100±2) mm/min, fz=(0.3±0.01) mm/r, ap=(0.8±0.1) mm (vc is the cutting speed, fz is the feeding rate, and ap is the cutting depth). With the assist of the cryogenic minimal quantity lubrication technology, the low damage processing, high oil content, and high oil delivery rate of cage products can be obtained.

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    Clustering Separation Method Based on Multi-Source Partial Discharge Signal Data Stream
    CHEN Changchuan, LIU Kai, LIU Renguang, FENG Xiaozong, QIN Yanjia, DAI Shaosheng, ZHANG Tianqi
    Journal of Shanghai Jiao Tong University    2022, 56 (8): 1014-1023.   DOI: 10.16183/j.cnki.jsjtu.2021.195
    Abstract467)   HTML132)    PDF (7466KB)(231)      

    In partial discharge(PD) detection, due to the simultaneous and constantly changing phenomenon of multiple discharge sources and on-site interference sources, it is difficult to effectively separate and identify multiple PD sources. An efficient adaptive efficient adaptive online data stream clustering algorithm (EAOStream) is proposed. The algorithm uses natural neighborhoods to create K-dimensional (KD) trees to improve the efficiency of querying neighbors. That is, the adaptive neighborhood radius and the area density are obtained through the characteristics of the flow data, which can search locally and form clusters, and realize the real-time online separation of multiple local discharge sources. The superiority of EAOStream is verified in the artificial data set and the real data set. After comparing EAOStream with the traditional DenStream and SE-Stream algorithms, it is applied to the pattern recognition of gas-insulated substation faults. Experimental test results show that the clustering accuracy of EAOStream in the real network intrusion detection, the forest cover type, and the multi-source PD signal data sets reaches 95.28%, 98.47%, and 97.23%, verifying the practicability and effectiveness of the algorithm in fault diagnosis of gas-insulated substations.

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    Calculation Method of Bearing Capacity of Screw Pile Based on Unified Strength Theory
    MA Jiakuan, LUO Lijuan, REN Xiang, SHI Hang, YIN Yimo
    Journal of Shanghai Jiao Tong University    2022, 56 (6): 754-763.   DOI: 10.16183/j.cnki.jsjtu.2021.077
    Abstract459)   HTML23)    PDF (1180KB)(236)      

    Based on the unified strength theory and the Terzaghi limit equilibrium theory, the ultimate bearing capacity of screw pile has been deduced. The method to determine the critical pitch and calculate the ultimate bearing capacity of the screw pile in two failure modes including the independent bearing failure mode and the cylinder shear failure mode has been proposed. The influence of the unified strength theoretical parameter b and the key parameters of concrete screw pile on the ultimate bearing capacity has been analyzed. The results show that the ultimate bearing capacity of the screw pile is 1.5—2 times that of the round pile with the same outer diameter. The ultimate bearing capacity of the screw teeth is mainly determined by the cohesion, the internal friction angle, and the buried depth of the soil. As b increases from 0 to 1, the theoretical value of the ultimate bearing capacity of the screw pile increases by nearly 48%. As the influence of the medium principal stress on the soil strength is considered, the theoretical calculation results of the bearing capacity of the concrete screw pile will be more accurate. Of the parameters of the concrete screw pile, the screw height bh has the greatest influence on the ultimate bearing capacity, while the screw thickness t has little influence on the bearing capacity. When designing threaded pile, the height of screw can be increased to some extent to improve the ultimate bearing capacity of the screw pile.

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    Cooperative Navigation of UAV Formation Based on Relative Velocity and Position Assistance
    GUO Pengjun, ZHANG Rui, GAO Guangen, XU Bin
    Journal of Shanghai Jiao Tong University    2022, 56 (11): 1438-1446.   DOI: 10.16183/j.cnki.jsjtu.2022.232
    Accepted: 05 September 2022

    Abstract450)   HTML24)    PDF (1260KB)(216)      

    Because the navigation errors of inertial navigation system accumulate with time, the unmanned aerial vehicle (UAV) formation that only relies on inertial navigation system for positioning cannot obtain precision navigation information in long time flight. To solve this problem, this paper proposes a cooperative navigation scheme for master-slave UAV formation. First, the UAV is equipped with relative navigation sensors to measure the relative velocity and position information between the members of the master-slave UAV formation. Then, considering the relative pose of formation members, the spatial unified transformation scheme is studied. The absolute navigation information measured by each member of UAV formation by inertial navigation system and the relative navigation information measured by relative sensors is unified into the same navigation coordinate system. Finally, a cooperative navigation scheme based on relative velocity and relative position assistance is given. The 30 min simulation results show that the speed and position errors of each cluster converge to 0.1 m/s and 5 m respectively under this scheme, which is more suitable than the inertial navigation system.

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    An Image Self-Calibration Method Based on Parallel Laser Ranging
    CHENG Bin, HUANG Bin, LI Derui
    Journal of Shanghai Jiao Tong University    2022, 56 (7): 850-857.   DOI: 10.16183/j.cnki.jsjtu.2021.447
    Abstract435)   HTML19)    PDF (3660KB)(343)      

    Regarding the disadvantages of existing camera calibration methods, such as external information relative, special camera poses,the need for calibration targets, and complex operations, this paper proposes a real-time self-calibration method based on parallel laser ranging by employing high-precision laser rangefinders to synchronously measure the position of the measured object plane when taking pictures, so that the object plane equation can be solved. The 2D coordinates of at least four sets of corresponding points on object plane and image planes are selected to obtain the homography matrix, which represents the mapping relationship between object and image planes, so as to complete the calibration simply and quickly. A calibration device is developed to validate the accuracy of the proposed self-calibration method in different testing scenarios. The results show that the measurement error of line segments length in the image are between -0.49% and 0.15%, and the average errors are merely -0.14%, which indicates that the parallel laser ranging self-calibration method proposed in this paper is accurate and robust. The causes of measurement error are further investigated by analyzing the influences of laser ranging, laser inclination, and device offset. The error eliminating suggestions are provided to give references for the application of the proposed self-calibration method in the field of image measurement.

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    Design and Realization of Continuum Manipulator Based on Coupling of Double Parallel Mechanism
    WU Guanlun, SHI Guanglin
    Journal of Shanghai Jiao Tong University    2022, 56 (6): 809-817.   DOI: 10.16183/j.cnki.jsjtu.2021.060
    Abstract434)   HTML27)    PDF (14846KB)(360)      

    A 5-degree-of-freedom continuum manipulator is designed and implemented to improve the flexible positioning ability of the continuum mechanism in applications such as interactivity operations, light object grabbing, and human-machine collaboration. In the design process, by introducing a two-segment constant curvature model, the distribution of degrees of freedom on the mechanism is explained geometrically by the method of twist. Coupling two stretchable parallel modules in series, a two-segment structure is formed for curving and each segment has two degrees of freedom in bending and one degree of freedom in stretching, thereby giving 5 degrees of freedom to the end-effector. Concentrating on the dynamic performance of the manipulator, an electromechanical system platform is built as a prototype. The experiments show that the structure realizes the control of the end-effector during large deformation of the manipulator, and is able to achieve extreme pose in 2 s with an approximation positioning error of 2% of the nominal arm length.

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    A Dual-System Reinforcement Learning Method for Flexible Job Shop Dynamic Scheduling
    LIU Yahui, SHEN Xingwang, GU Xinghai, PENG Tao, BAO Jinsong, ZHANG Dan
    Journal of Shanghai Jiao Tong University    2022, 56 (9): 1262-1275.   DOI: 10.16183/j.cnki.jsjtu.2021.215
    Abstract431)   HTML62)    PDF (4009KB)(442)      

    In the production process of aerospace structural parts, there coexist batch production tasks and research and development (R&D) tasks. Personalized small-batch R&D and production tasks lead to frequent emergency insertion orders. In order to ensure that the task is completed on schedule and to solve the flexible job shop dynamic scheduling problem, this paper takes minimization of equipment average load and total completion time as optimization goals, and proposes a dual-loop deep Q network (DL-DQN) method driven by a perception-cognition dual system. Based on the knowledge graph, the perception system realizes the representation of workshop knowledge and the generation of multi-dimensional information matrix. The cognitive system abstracts the scheduling process into two stages: resource allocation agent and process sequencing agent, corresponding to two optimization goals respectively. The workshop status matrix is designed to describe the problems and constraints. In scheduling decision, action instructions are introduced step by step. Finally, the reward function is designed to realize the evaluation of resource allocation decision and process sequence decision. Application of the proposed method in the aerospace shell processing of an aerospace institute and comparative analysis of different algorithms verify the superiority of the proposed method.

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    Mechanism and Influencing Factors of Frictional Energy Dissipation in Multilayer Ultrasonic Welding
    MA Zunnong, ZHANG Yansong, ZHAO Yixi
    Journal of Shanghai Jiao Tong University    2022, 56 (6): 772-783.   DOI: 10.16183/j.cnki.jsjtu.2020.423
    Abstract426)   HTML21)    PDF (6855KB)(225)      

    In multilayer ultrasonic welding, the sonotrode presses on metal sheets and drives the sheets to produce ultrasonic vibration. Then, each contact interface generates heat, produces plastic deformation, and forms solid-state bonding. However, the load distributes unevenly in each sheet, which results in the uneven friction state and inconsistent welding quality. Hence, it is necessary to reveal the mechanism of frictional state and energy dissipation based on the load distribution in each sheet. A finite element model of 5-layer copper sheets is established using Abaqus and considering the Cattaneo-Mindlin contact theory. The clamping force and ultrasonic vibration in each interface is simulated. The slip-stick state of each interface is obtained and the effect of the clamping force are analyzed. The frictional energy dissipation and proportion of each interface are calculated, the influencing factors of frictional energy dissipation are summarized, and the optimization of input clamping force is discovered, which can provide theoretical guidance for the improvement of multilayer ultrasonic welding.

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    Peafowl Optimization Algorithm Based Bi-Level Multi-Objective Optimal Allocation of Energy Storage Systems in Distribution Network
    YANG Bo, WANG Junting, YU Lei, CAO Pulin, SHU Hongchun, YU Tao
    Journal of Shanghai Jiao Tong University    2022, 56 (10): 1294-1307.   DOI: 10.16183/j.cnki.jsjtu.2021.371
    Abstract425)   HTML193)    PDF (2519KB)(200)      

    Based on the relation between battery energy storage systems (BESSs) planning and operation, a multi-objective optimal allocation model that takes into account both economic and technical requirements is established, and a bi-level optimization structure is constructed to ensure effective planning and high-efficient operation of BESSs. In the inner layer, a peafowl optimization algorithm (POA) is employed to solve the BESSs charge-discharge operation strategy with the purpose of BESSs operation benefit maximization. In the outer layer, a multi-objective peafowl optimization algorithm (MOPOA) is devised to solve the Pareto solution set of BESSs siting and sizing scheme, which aims at minimizing BESSs cost, as well as voltage fluctuation and load fluctuation in distribution network. Furthermore, a typical scenario set is obtained via the clustering algorithm considering uncertain operating conditions. The simulation is performed based on the extended IEEE-33 bus system. The results show that the proposed algorithm achieves a trade-off between local search and global search, thus obtains a high-quality solution. It can obtain a more widely distributed and uniform Pareto front, which not only achieves the best investment benefit, but also improves voltage quality and power stability.

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    Multi-Objective Optimization Strategy of Trajectory Planning for Unmanned Aerial Vehicles Considering Constraints of Safe Flight Corridors
    HUANG Yuhao, HAN Chao, ZHAO Minghui, DU Qiankun, WANG Shigang
    Journal of Shanghai Jiao Tong University    2022, 56 (8): 1024-1033.   DOI: 10.16183/j.cnki.jsjtu.2021.154
    Abstract423)   HTML38)    PDF (5684KB)(703)      

    Aimed at the problem of generating a smooth, safe, and dynamically feasible continuous-time trajectory for unmanned aerial vehicles (UAV) in complex environments, a trajectory planning algorithm is proposed to minimize a multi-objective function based on safe flight corridors. The safe flight corridor represented by a collection of convex polyhedra is built based on the initial discrete waypoints generated by the improved rapidly-exploring random tree(RRT), namely the RRT* algorithm. The safety objective function is established according to the constraints of limiting the trajectory inside safe flight corridors. In combination with the flight smoothness, dynamic characteristics, and time performance, a multi-objective function is built. The gradient-based convex optimization algorithm is used to derive the continuous-time trajectory expressed as a piece-wise polynomial by optimizing the position, velocity, acceleration of waypoints, and time allocation. The effectiveness and performance of the proposed algorithm is tested and compared under complex environments such as the coal mine. The test results demonstrate that the proposed algorithm has a better comprehensive performance in comparison with existing algorithms.

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    Numerical Study of Stern Vibration of a Self-Propulsion Ship in Propeller Induced Pressure Fluctuation
    QIN Guangfei, YAO Huilan, ZHANG Huaixin
    Journal of Shanghai Jiao Tong University    2022, 56 (9): 1148-1158.   DOI: 10.16183/j.cnki.jsjtu.2021.175
    Abstract414)   HTML20)    PDF (15563KB)(288)      

    To study the stern vibration characteristics of the ship sailing in still water under the action of propeller induced pressure fluctuation, the propeller self-propulsion numerical simulation was conducted based on the Reynolds-averaged Navier-Stokes (RANS) method, in combination with the shear-stress transport (SST) k-ω model. Taking the obtained fluctuating pressure on the hull surface as the external excitation, the acoustic-structure coupling calculation was performed through the structural finite element model coupled with the flow field boundary element model, and a numerical prediction method for the stern vibration of the self-propulsion ship excited by the propeller surface force was established. By analyzing the fluctuating pressure characteristics in the time domain and frequency domain, it is found that the amplitude of the blade frequency component is much larger than that of other frequency components. For the right-handed propeller, the starboard side pressure amplitude above the propeller is higher than that on the port side. The analysis of the corresponding relationship between the propeller fluctuating pressure, the structural inherent characteristics, and the vibration response shows that the coupled mode natural frequency should be far away from the propeller excitation force frequency to reduce the vibration response. The exploration of the effect of modifying stern structure on the vibration response at the same excitation indicates that increasing the plate thickness or installing stiffeners can change the inherent characteristics of the structure, thus avoiding resonance and achieving the vibration reduction effect.

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    Numerical Simulation and Flow Pattern Evolution of Gas-Liquid Two-Phase Flow Passing Through a 90° Pipe Bend Based on CFD
    WANG Zhiwei, HE Yanping, LI Mingzhi, QIU Ming, HUANG Chao, LIU Yadong
    Journal of Shanghai Jiao Tong University    2022, 56 (9): 1159-1167.   DOI: 10.16183/j.cnki.jsjtu.2021.185
    Abstract414)   HTML17)    PDF (11131KB)(237)      

    In order to investigate the evolution characteristics of gas-liquid two-phase flow passing through a 90° pipe bend, the volume of fluid (VOF) multiphase flow model and the Realizable k-ε turbulence model are used to conduct numerical simulations. The evolution of velocity, pressure distribution, gas void fraction, and flow pattern passing through a 90° pipe bend is studied in detail. The results show that different gas-liquid two-phase flow patterns will produce different degrees of secondary flow phenomenon after passing through the 90° pipe bend, and the tangential velocity presents a bimodal distribution, which eventually dissipates into a unimodal distribution in the horizontal pipe. The pressure on the outer wall of the pipe bend increases as the inlet velocity increases. The change of gas void fraction is related to the transformation of the flow pattern, the bubbly flow evolves into a slender slug flow in the horizontal pipe after passing through the 90° pipe bend, and the gas void fraction will decrease. The slug flow, the churn flow, and the annular flow evolve into the stratified-wave flow in the horizontal pipe after passing through the pipe bend, and the variation of the gas void fraction is relatively low. The research results can provide certain theoretical support for the design and development of gas-liquid two-phase flow conveying elbows and the prediction of induced stress.

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    Multiscale Calculation of Elastic Modulus of Cement Paste Based on Grid Nanoindentation Technology
    CHEN Xiaowen, HAN Yudong, DING Xiaoping, HOU Dongwei
    Journal of Shanghai Jiao Tong University    2022, 56 (9): 1199-1207.   DOI: 10.16183/j.cnki.jsjtu.2021.089
    Abstract414)   HTML13)    PDF (1695KB)(228)      

    The calculation of multiscale elastic parameters of cementitious materials based on micromechanical tests and the composite material theory is one of the key theoretical bases for precise design of cementitious materials performance. In this paper, grid nanoindentation tests of microscopic elastic modulus and the mercury intrusion test were conducted on hardened cement paste specimens at different water-cement ratios, to establish a multiscale homogenization calculation method for the elastic modulus of cement paste considering the influence of pores. Besides, the applicability of the dilute method, the self-consistent method, the Mori-Tanaka method, the interaction direct derivation (IDD) method, and the multilevel homogenization method was compared. The results show that the multi-phase and multi-scale calculations considering the effect of pores is in good agreement with experimental values. Except the multi-level homogenization method, the calculation results of several commonly used composite homogenization methods are similar.

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    Control of Unmanned Aerial Vehicle Based on Gain Adaptive Super-Twisting Sliding Mode Theory
    ZHOU Qixian, WANG Yin, SUN Xuean
    Journal of Shanghai Jiao Tong University    2022, 56 (11): 1453-1460.   DOI: 10.16183/j.cnki.jsjtu.2022.238
    Accepted: 08 September 2022

    Abstract413)   HTML10)    PDF (1184KB)(175)      

    In this paper, a nonlinear control method is proposed based on the framework of gain adaptive sliding mode control to deal with the attitude control problem of an unmanned aerial vehicle (UAV), which shows a strong robustness with respect to dynamical uncertainties and external disturbance. In the proposed method, an adaptive gain schedule scheme is proposed to deal with dynamical uncertainties while suppressing the chattering in the sliding mode control. First, the UAV model is introduced and its mathematical model is given. Then, the error is used as the state variable to design a stably converging sliding mode surface, and the gain adaptive super-twisting sliding mode (ASTSM) algorithm is used to design a UAV attitude controller that can converge in finite time, and the stability of the closed-loop UAV system is demonstrated by the Lyapunov’s second method. Finally, the efficiency of the proposed method is demonstrated through comparative simulations.

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    Robust Seabed Terrain Following Control of Underactuated AUV with Prescribed Performance Guidance Law Under Time Delay of Actuator
    LI Jinjiang, XIANG Xianbo, LIU Chuan, YANG Shaolong
    Journal of Shanghai Jiao Tong University    2022, 56 (7): 944-952.   DOI: 10.16183/j.cnki.jsjtu.2021.375
    Abstract409)   HTML15)    PDF (1420KB)(172)      

    To address the uneven seabed following control problem under the time delay constraint of the actuator for the autonomous underwater vehicle (AUV), a robust time-delay controller with prescribed performance guidance law is proposed in this paper, which can improve the safety of the AUV during navigation. First, the seabed following error conversion is firstly performed based on a navigational safety barrier function. Then, by integrating the time-varying line-of-sight guidance angle, the prescribed performance guidance law is designed at the kinematics level to provide reference state input for the AUV. After that, to tackle the time delay problem of actuators and reduce demand for accurate modeling, a robust time-delay dynamic controller is designed using the radial basis function (RBF) neural network. Finally, based on the Lyapunov theory, the stability of the closed-loop system is proved. The simulation results illustrate that the designed controller can achieve uneven seabed following control. Moreover, the following errors are always confined to the preset limits, which can also enhance the safety performance of the AUV when following the uneven terrain of the seabed.

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    Prediction of Modulus of Composite Materials by BP Neural Network Optimized by Genetic Algorithm
    WANG Zhuoxin, ZHAO Haitao, XIE Yuehan, REN Hantao, YUAN Mingqing, ZHANG Boming, CHEN Ji’an
    Journal of Shanghai Jiao Tong University    2022, 56 (10): 1341-1348.   DOI: 10.16183/j.cnki.jsjtu.2021.126
    Accepted: 28 June 2022

    Abstract408)   HTML123)    PDF (2532KB)(252)      

    In order to reduce the cost of testing and shorten the design cycle, this paper studies the prediction method of the modulus of resin matrix composites based on the machine learning method. Using a new prediction method — the neural network in combination with the genetic algorithm (GA-ANN), the strength, the Poisson’s ratio, and the failure strain of the T800/epoxy composite material are used as three input variables of the back propagation (BP) neural network. Then, the optimal threshold and weight are obtained in the genetic algorithm (GA), which are assigned to the corresponding network parameters, and the BP neural network is updated for higher accuracy to predict the modulus of resin matrix composites. Under the same conditions, the Adam algorithm is used to predict. A comparison of these two methods fully proves the feasibility of the GA-ANN algorithm.

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    Calculation Method of Uplift Capacity of Pile-Anchor Composite Foundation and Influence of Parameters
    SUN Yizhou, SUN Honglei, CAI Yuanqiang
    Journal of Shanghai Jiao Tong University    2022, 56 (6): 701-709.   DOI: 10.16183/j.cnki.jsjtu.2021.366
    Abstract407)   HTML496)    PDF (3967KB)(212)      

    In view of the extensive geology of overlying soil and underlying rock in mountainous areas, a pile-anchor composite foundation has been used in transmission line tower engineering. To reveal the uplift bearing mechanism and supplement the calculation method of the uplift capacity and the bearing exertion coefficient k, the verification model of field test case was established by using the PLAXIS 3D finite element software to study this problem. Parameter studies were conducted on this foundation. The influence of elastic modulus and cohesion of rock and soil and foundation condition on coefficient k was studied. The results show that there is asynchronism of ultimate uplift limit state of upper and lower parts of the pile-anchor foundation. The bearing ratio and coefficient k of the upper and lower parts of the foundation are related to geology and foundation structure. In combination with the parameter study and the relevant analytical solution of the relationship between the uplift load and the displacement, a theoretical calculation method of the coefficient k considering the foundation weight was proposed. Three test cases were used to perform confirmatory calculations for this method. By comparing with field tests and numerical calculation results, the correctness of this method has been verified. This method provides a theoretical reference for the design and application of this type of new foundation.

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    Quasi-Steady State Time Model of Fire Smoke Transmission in Long-Narrow Spaces
    WANG Jinhui, HUANG Yijun, CUI Xin, ZHANG Shaogang, ZHANG Ruiqing
    Journal of Shanghai Jiao Tong University    2022, 56 (6): 746-753.   DOI: 10.16183/j.cnki.jsjtu.2021.062
    Abstract406)   HTML20)    PDF (1102KB)(231)      

    Transport time lag is a crucial characteristic of fire spreading in fire early stage, which determines the activation time of the fire detector. To clarify the quantitative relationship between the delay behavior and the quasi-steady state of smoke transmission in a long-narrow space, a time-varying spreadsheet is theoretically proposed to calculate the delay time of fire smoke transmission based on the theory of weak plume and the existing achievements concerned. Moreover, a theoretical model concerning the critical time for quasi-steady state assumption applicability is developed, where the method of calculating the critical time is also presented. The results of the case study show that due to the difference of smoke spreading velocity in long-narrow spaces and unconfined spaces for a case with the same conditions, the critical time for the smoke transmission to reach the quasi-steady state at a given radial distance on the ceiling in a long-narrow space is larger than that in the open space. For the open case, the thin ceiling plume, the small volume of entrained air, and the relatively high velocity of smoke lead to the longer delay time of smoke transmission in a long-narrow space than that in the open space under the same situations.

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    College English as General Education or Discipline-specific Education:Tthe Orientation of College English Teaching to ESP Revisited
    CAI Jigang
    Contemporary Foreign Languages Studies    2022, 22 (3): 84-91.   DOI: 10.3969/j.issn.1674-8921.2022.03.010
    Abstract406)   HTML8)    PDF (1210KB)(112)      

    College English Teaching Guidelines defines college English as general education and assigns English for specific purposes (ESP) a minor role. We believe that college English is discipline-specific education and should be orientated towards ESP. Its instrumental and humanistic harmony could be found in its pedagogy. It could not only help students engage in their disciplinary studies in English, but also improve their cross-cultural competence in the domain of their disciplines. With the credit decrease of college English, we suggest that general English and culture courses should be removed from the required courses of college English.

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    Real-Time Detection of Insulator Drop String Based on UAV Aerial Photography
    LI Dengpan, REN Xiaoming, YAN Nannan
    Journal of Shanghai Jiao Tong University    2022, 56 (8): 994-1003.   DOI: 10.16183/j.cnki.jsjtu.2021.416
    Abstract403)   HTML385)    PDF (28565KB)(343)      

    It is of great significance for unmanned aerial vehicle(UAV) to replace manual inspection of power insulators. Aimed at the problem of limited computing power and storage resources of the UAV, an improved real-time target detection algorithm suitable for insulator drop string failure detection is proposed. Based on the YOLOv5s detection network, first, the PANet networks in neck are replaced with bi-directional feature pyramid network(BiFPN) to improve the feature fusion ability. Next, DIoU is used to optimize the loss function to optimize the model. The channel pruning and fine tuning of the γ coefficient generally improve the accuracy, speed, and deployment ability of the detection network. Finally, the image is enhanced at the network output to improve the availability of the algorithm. The proposed algorithm is tested under a specially expanded insulator fault data set. The results show that compared with the original YOLOv5s algorithm, the average accuracy of the proposed algorithm is improved by 3.91%, the detection speed is improved by 25.6%, and the model volume is reduced by 59.1%.

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    Sealing Performance of Pressure-Adaptive Seal
    LI Yuanfeng (李元丰), WANG Yiling (王怡灵), ZHANG Wanxin∗ (张万欣), LIU Jinian (刘冀念), MA Jialu (马加炉)
    J Shanghai Jiaotong Univ Sci    2022, 27 (6): 747-756.   DOI: 10.1007/s12204-022-2510-x
    Abstract396)      PDF (2268KB)(161)      
    A pressure-adaptive seal is developed to meet the demands of quick assembling and disassembling for an individual protection equipment in aerospace. The analysis model, which reflects the main characteristics of the seal structure, is built based on the finite element method and the Roth’s theory of rubber seal, and verified by the prototype test. The influences of precompression ratio, hardness of the sealing ring rubber, and friction coefficient on the sealing performance are investigated by variable parameter method. Results show that the model can describe the essential characteristics of the pressure-adaptive seal structure, which has good follow-up to the cavity pressure to achieve the purpose of pressure self-adaptive. The leakage rate correlates negatively with the precompression ratio of the sealing ring and the hardness of the sealing ring material, while is positively related to the friction coefficient between the sealing ring and the sealing edge. The maximum contact stress on sealing surface has negative correlation with the precompression ratio of the sealing ring, and positive correlation with the hardness of the seal ring material. The damage risk of the sealing ring increases with the increases of the precompression ratio of sealing ring, hardness of sealing ring material, and friction coefficient.
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    Slope Stability Considering the Effects of Air Pressure and Seepage Under Heavy Rainfall Conditions
    YAO Maohong, CHEN Tielin, FAN Rong, YANG Zili, SHI Ye
    Journal of Shanghai Jiao Tong University    2022, 56 (6): 739-745.   DOI: 10.16183/j.cnki.jsjtu.2021.302
    Abstract393)   HTML20)    PDF (1020KB)(228)      

    Rainfall infiltration analysis is one of the important methods for predicting engineering disasters. In order to effectively analyze the infiltration process of slope under heavy rainfall, based on the classical Green-Ampt model, a slope rainfall infiltration model considering the effect of saturated zone seepage and air pressure under the condition of non-uniform distribution of initial water content was established, and the corresponding expression of landslide stability coefficient was derived. The results show that the influence of slope size on rainfall infiltration is obvious. On the one hand, the expansion rate of wetting front increases with the increase of slope length, on the other hand, when considering the effect of air pressure, the smaller the slope length, the longer it takes to reach the same wet front. When the slope length increases to a certain extent, the difference is not obvious. In addition, the influence of seepage force on slope stability is greater than that of air pressure. Because the former gradually increases during the rainfall process while the latter is basically unchanged, the influence of seepage force increases, and the influence of air pressure decreases.

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    Dynamic Responses Law of Subgrade of a Special Railway Line in Loess Region
    WANG Rui, HU Zhiping, YIN Ke, MA Jiakuan, REN Xiang
    Journal of Shanghai Jiao Tong University    2022, 56 (7): 908-918.   DOI: 10.16183/j.cnki.jsjtu.2021.130
    Abstract392)   HTML17)    PDF (4239KB)(204)      

    In order to investigate the dynamic response law of subgrade of a special railway line in loess region under moving train loading, the field test data and 2.5D finite element results were adopted to assess the dynamic stress distribution and its influence depth, and the environmental vibration law in the office area along the line was also analyzed. The results show that the excessive abstraction of the track system might enlarge the amplitude and influence the range of dynamic stress. The entity modeling of the ‘ballast-sleeper-fastener’ system makes the distribution of the dynamic stress in the subgrade more reasonable. The influence of energy consumption caused by the dynamic creep of soil have a negligible influence when the subgrade is in a quasi-static state. The speed has a negligible effect on the distribution of the dynamic stress of the subgrade when a freight train is running at a low speed, and the influence depth of the dynamic stress is about 4.2 m. As the speed decreases, the influence of track irregularity on the environmental vibration increases. The environmental vibration can be effectively controlled by improving the short wave length irregularity.

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    Loop Closure Detection Method of Laser SLAM Based on Global Feature Descriptor
    HAN Chao, CHEN Min, HUANG Yuhao, ZHAO Minghui, DU Qiankun, LIANG Qinhua
    Journal of Shanghai Jiao Tong University    2022, 56 (10): 1379-1387.   DOI: 10.16183/j.cnki.jsjtu.2021.202
    Abstract392)   HTML70)    PDF (5130KB)(201)      

    To solve the problem that localization error of the underground inspection system continues to accumulate over time, a loop closure detection algorithm based on point cloud global feature descriptor is proposed, which is suitable for laser simultaneous localization and mapping (SLAM). The feature vector of each point in point cloud is calculated by curvature, then the global feature descriptor of point cloud is constructed based on the angle distribution and scale distribution relationship between the feature vector and center point coordinate system. In addition, the pose transformation of two similar frames is calculated by feature point registration to improve computing efficiency. The proposed algorithm is verified by simulation experiments and open-source data experiments. The experimental results show that the proposed algorithm has a significant improvement in localization accuracy and real-time performance, which can effectively solve the problems of increased cumulative error and poor global consistency of the localization algorithm during long-term inspections.

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    A Numerical Study of Hydrodynamic Interactions Between a Large Cruise Ship and a Container Ship
    SONG Shenke, XIA Li, ZOU Zaojian, ZOU Lu
    Journal of Shanghai Jiao Tong University    2022, 56 (7): 919-928.   DOI: 10.16183/j.cnki.jsjtu.2021.257
    Abstract390)   HTML16)    PDF (3495KB)(183)      

    The large cruise ship is a type of ship with large size and high added value, which has been increasingly studied and developed during the recent years. Since a large cruise ship often sails in the crowded waters such as harbor and coastal area, the study of the hydrodynamic interaction between the cruise ship and other ships is crucial to ensure the navigation safety. Taking a large cruise ship and a KCS container ship as the study object, the hydrodynamic characteristics of the two ships at different longitudinal positions, transverse positions, and ship speeds in both deep and shallow water are predicted in model scale by solving the unsteady Reynolds-averaged Navier-Stokes (RANS) equations, and the variations of the hydrodynamic interactions between the two ships are identified. It is shown that different relative positions and ship speeds have significant effects on the lateral force and yaw moment acting on the two ships. The hydrodynamic interaction between the two ships in shallow water is more remarkable, and the relatively smaller ship is more affected by the ship-to-ship interaction.

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