To address the problems of low accuracy by the CONWEP model and poor efficiency by the Coupled Eulerian-Lagrangian(CEL)method in predicting close-range air blast loads of cylindrical charges,a neural network-based sim...To address the problems of low accuracy by the CONWEP model and poor efficiency by the Coupled Eulerian-Lagrangian(CEL)method in predicting close-range air blast loads of cylindrical charges,a neural network-based simulation(NNS)method with higher accuracy and better efficiency was proposed.The NNS method consisted of three main steps.First,the parameters of blast loads,including the peak pressures and impulses of cylindrical charges with different aspect ratios(L/D)at different stand-off distances and incident angles were obtained by two-dimensional numerical simulations.Subsequently,incident shape factors of cylindrical charges with arbitrary aspect ratios were predicted by a neural network.Finally,reflected shape factors were derived and implemented into the subroutine of the ABAQUS code to modify the CONWEP model,including modifications of impulse and overpressure.The reliability of the proposed NNS method was verified by related experimental results.Remarkable accuracy improvement was acquired by the proposed NNS method compared with the unmodified CONWEP model.Moreover,huge efficiency superiority was obtained by the proposed NNS method compared with the CEL method.The proposed NNS method showed good accuracy when the scaled distance was greater than 0.2 m/kg^(1/3).It should be noted that there is no need to generate a new dataset again since the blast loads satisfy the similarity law,and the proposed NNS method can be directly used to simulate the blast loads generated by different cylindrical charges.The proposed NNS method with high efficiency and accuracy can be used as an effective method to analyze the dynamic response of structures under blast loads,and it has significant application prospects in designing protective structures.展开更多
Small tunnels such as engineering geological exploratory tunnels and mine roadways are generally narrow, which make the existing photographic geological logging technique inapplicable. Therefore, geological logging of...Small tunnels such as engineering geological exploratory tunnels and mine roadways are generally narrow, which make the existing photographic geological logging technique inapplicable. Therefore, geological logging of exploratory tunnels has always been taking the method of manual sketch work which has low efficiency and poor informatization degree of products, and it is a technical issue requiring urgent settlement for geological logging of small tunnels. This paper proposes and studies novel methods of photographic geological logging suitable for small tunnels, including image acquisition, image orientation control, image geometric correction, unfolded image map generation and geological attitude measurement, etc. Experiments show that the method can meet the precision requirement of geological logging. The novel method helps to realize the fast acquisition and processing of image-based geological logging data for small tunnels, and the forms of logging result are more abundant and more applicable to informatized management and application of geological logging data.展开更多
基金financially supported by the National Natural Science Foundation of China(Grant Nos.52271317 and 52071149)the Fundamental Research Funds for the Central Universities(HUST:2019kfy XJJS007)。
文摘To address the problems of low accuracy by the CONWEP model and poor efficiency by the Coupled Eulerian-Lagrangian(CEL)method in predicting close-range air blast loads of cylindrical charges,a neural network-based simulation(NNS)method with higher accuracy and better efficiency was proposed.The NNS method consisted of three main steps.First,the parameters of blast loads,including the peak pressures and impulses of cylindrical charges with different aspect ratios(L/D)at different stand-off distances and incident angles were obtained by two-dimensional numerical simulations.Subsequently,incident shape factors of cylindrical charges with arbitrary aspect ratios were predicted by a neural network.Finally,reflected shape factors were derived and implemented into the subroutine of the ABAQUS code to modify the CONWEP model,including modifications of impulse and overpressure.The reliability of the proposed NNS method was verified by related experimental results.Remarkable accuracy improvement was acquired by the proposed NNS method compared with the unmodified CONWEP model.Moreover,huge efficiency superiority was obtained by the proposed NNS method compared with the CEL method.The proposed NNS method showed good accuracy when the scaled distance was greater than 0.2 m/kg^(1/3).It should be noted that there is no need to generate a new dataset again since the blast loads satisfy the similarity law,and the proposed NNS method can be directly used to simulate the blast loads generated by different cylindrical charges.The proposed NNS method with high efficiency and accuracy can be used as an effective method to analyze the dynamic response of structures under blast loads,and it has significant application prospects in designing protective structures.
基金Project(201508)supported by the Open Research Foundation of Engineering Research Center for Rock-Soil Drilling & Excavation and Protection(Ministry of Education),ChinaProject(BK2012812)supported by the Natural Science Foundation of Jiangsu Province,China+1 种基金Project(KYLX_0492)supported by the University Postgraduate Scientific Research and Innovation Project of Jiangsu Province,ChinaProject(2014B38714)supported by the Fundamental Research Funds for the Central Universities,China
文摘Small tunnels such as engineering geological exploratory tunnels and mine roadways are generally narrow, which make the existing photographic geological logging technique inapplicable. Therefore, geological logging of exploratory tunnels has always been taking the method of manual sketch work which has low efficiency and poor informatization degree of products, and it is a technical issue requiring urgent settlement for geological logging of small tunnels. This paper proposes and studies novel methods of photographic geological logging suitable for small tunnels, including image acquisition, image orientation control, image geometric correction, unfolded image map generation and geological attitude measurement, etc. Experiments show that the method can meet the precision requirement of geological logging. The novel method helps to realize the fast acquisition and processing of image-based geological logging data for small tunnels, and the forms of logging result are more abundant and more applicable to informatized management and application of geological logging data.
