Xuedong Luo

China University of Geosciences

Author Statistics

Papers

Citation

H-Index

i-10 index

Research Trends

Author Order

Document Type

Co-Authors

Nan Jiang

Jianghan University

Chuanbo Zhou

China University of Geosciences

Tingyao Wu

Chongqing University

Shengtao Zhou

Hohai University

Shuaishuai Niu

China University of Geosciences

Yingkang Yao

Jianghan University

Yu Lei

China University of Geosciences

Yuqing Xia

Jianghan University

Bin Zhu

China University of Geosciences

Bingzhen Yu

China University of Geosciences

Cooperative Institutions

China University of Geosciences

Jianghan University

China University of Mining and Technology

Chongqing University

China University of Geosciences (Beijing)

Sichuan University

Huazhong University of Science and Technology

Chinese Academy of Sciences

Tianjin University

Harbin Institute of Technology

Author Statistics

Papers

Citation

H-Index

i-10 index

Research Field

Blasting vibration characteristics of high-density polyethylene pipes in operation water-filled state

Journal of ZheJiang University (Engineering Science) (2020)

Yuqi Zhang Nan Jiang Yongsheng Jia Chuan-bo Zhou Xuedong Luo

High-density polyethylene

10.3785/j.issn.1008-973x.2020.11.007

Cite

Citations (0)

Prediction of Ground Vibration Induced by Rock Blasting Based on Optimized Support Vector Regression Models

Computer Modeling in Engineering & Sciences (2024)

Yifan Huang Zikang Zhou Mingyu Li Xuedong Luo

Accurately estimating blasting vibration during rock blasting is the foundation of blasting vibration management.In this study, Tuna Swarm Optimization (TSO), Whale Optimization Algorithm (WOA), and Cuckoo Search (CS) were used to optimize two hyperparameters in support vector regression (SVR).Based on these methods, three hybrid models to predict peak particle velocity (PPV) for bench blasting were developed.Eighty-eight samples were collected to establish the PPV database, eight initial blasting parameters were chosen as input parameters for the prediction model, and the PPV was the output parameter.As predictive performance evaluation indicators, the coefficient of determination (R 2 ), root mean square error (RMSE), mean absolute error (MAE), and a10-index were selected.The normalized mutual information value is then used to evaluate the impact of various input parameters on the PPV prediction outcomes.According to the research findings, TSO, WOA, and CS can all enhance the predictive performance of the SVR model.The TSO-SVR model provides the most accurate predictions.The performances of the optimized hybrid SVR models are superior to the unoptimized traditional prediction model.The maximum charge per delay impacts the PPV prediction value the most.

10.32604/cmes.2024.045947

Cite

Citations (5)

Dynamic response and safety assessment of buried gas pipe subjected to ground surface explosion

International Journal of Pressure Vessels and Piping (2021)

Tingyao Wu Nan Jiang Chuanbo Zhou Xuedong Luo Haibo Li

Gas explosion

Response analysis

10.1016/j.ijpvp.2021.104527

Cite

Citations (7)

Frost-heaving characteristics and formation mechanism of saturated sandstone under unidirectional freezing conditions

Cold Regions Science and Technology (2023)

Shuaishuai Niu Xuedong Luo Nan Jiang

Frost heaving

Frost (temperature)

Capillary pressure

10.1016/j.coldregions.2023.104049

Cite

Citations (4)

Dynamic behaviors of buried reinforced concrete pipelines with gasketed bell-and-spigot joints subjected to tunnel blasting vibration

Tunnelling and Underground Space Technology (2021)

Yuqing Xia Nan Jiang Chuanbo Zhou Jinshan Sun Xuedong Luo

10.1016/j.tust.2021.104172

Cite

Citations (14)

Experimental study on dynamic response of high-density polyethylene bellows under blasting seismic load

爆炸与冲击 (2020)

Yuqi Zhang Jiang Nan Jia Yongsheng Zhou Chuanbo Xuedong Luo

The dynamic response of buried high density polyethylene (HDPE) bellows under blasting seismic load was studied. First, the blasting test of buried pipeline was carried out by combining the blasting seismic test and dynamic strain test. Secondly, the dynamic response characteristics of buried pipeline under blasting seismic load were analyzed. Then, the characteristics of vibration velocity and dynamic strain distribution were studied. Finally, the pipe safety was evaluated based on the von Mises yield criterion, and the blasting vibration velocity control standard was proposed. The experimental results show that the vibration velocity of pipeline and ground and the dynamic strain of pipeline increase with the decrease of core distance and the increase of explosive quantity. The dominant frequency of blasting seismic wave is higher. The dominant frequency of pipeline is higher than the surface. Under the same blasting condition, the ground vibration velocity above the pipeline is generally higher than that of the pipeline. The peak axial strain on the back explosion side of the pipeline section is mainly tensile strain, and the peak circumferential strain on the front explosion side is mainly compressive strain. The vibration velocity of the pipeline can be safely controlled by 20 cm·s−1, and the pipeline is in a safe state.

Bellows

Dynamic load testing

10.11883/bzycj-2019-0399

Cite

Citations (1)

Evaluate of anti-explosion for high-pressure gas steel pipeline subjected to ground explosion

Journal of Constructional Steel Research (2020)

Tingyao Wu Nan Jiang Chuanbo Zhou Xuedong Luo Jinshan Sun

Internal pressure

10.1016/j.jcsr.2020.106429

Cite

Citations (25)

Effect of Freeze–Thaw Temperature and Number of Cycles on the Physical and Mechanical Properties of Marble

Geotechnical and Geological Engineering (2020)

Xuedong Luo Shengtao Zhou Bin Huang Nan Jiang Mengxin Xiong

10.1007/s10706-020-01513-0

Cite

Citations (18)

A practical sieve algorithm finding prime numbers

Communications of the ACM (1989)

Xuedong Luo

Based on the sieve of Eratosthenes, a faster and more compact algorithm is presented for finding all primes between 2 and N.

Sieve (category theory)

10.1145/62065.62072

Cite

Citations (10)

Slope with Predetermined Shear Plane Stability Predictions under Cyclic Loading with Innovative Time Series Analysis by Mechanical Learning Approach

Sensors (2022)

Tingyao Wu Hongan Yu Nan Jiang Chuanbo Zhou Xuedong Luo

We propose a mechanical learning method that can be used to predict stability coefficients for slopes where slopes with predetermined shear planes are subjected to cyclic seismic loads under undrained conditions. Firstly, shear tests with cyclic loading of different parameters were simulated on designated slip zone soil specimens, in which the strain softening process leading to landslide occurrence was closely observed. At the same time, based on the limit equilibrium analysis of the Sarma method, the variation of slope stability coefficients under different cyclic loads was investigated. Finally, a Box-Jenkins' modeling approach is used to predict the data from the time series of slope stability coefficients using a mechanical learning approach. The simulation results show that (1) reduction in coordination number can be an accurate indicator of the level of strain softening and evolutionary processes; (2) the gradual reduction of shear stress facilitates the soil strain softening process, while different cyclic loading stress amplitudes will result in rapid penetration or non-penetration of the fracture zone by means of particulate flow. Although the confining pressure of the slip zone soil can inhibit the increase of fractures, it has a limited inhibitory effect on strain softening; (3) based on field observations of the slope stability factor and stress field, two possible landslide triggering mechanisms are described. (4) Mechanical learning of time series can accurately predict the changing pattern of stability coefficients of slopes without loading. This study establishes a potential bridge between the geological investigation of landslides and the theoretical background of landslide stability coefficient prediction.

10.3390/s22072647

Cite

Citations (0)