Compared with RGB videos and images,human bone data is less vulnerable to external factors and has stronger robustness.Therefore,behavior recognition methods based on skeletons are widely studied.Because graph convolu...Compared with RGB videos and images,human bone data is less vulnerable to external factors and has stronger robustness.Therefore,behavior recognition methods based on skeletons are widely studied.Because graph convolution network(GCN)can deal with the irregular topology data of hu-man skeletons very well,more and more researchers apply GCN to human behavior recognition.Tra-ditional graph convolution methods only consider the joints with physical connectivity or the same type when building the behavior recognition model based on human skeletons structure,which cannot capture higher-order information better.To solve this problem,Motif-GCN is used in this paper to ex-tract spatial features.The relationship between the joints with natural connection in the human body is encoded by the first Motif-GCN,and the possible relationship between the unconnected joints in the human skeleton is encoded by the second Motif-GCN.In this way,the relationship between non-physical joints can be strengthened.Then a two stream framework combining joint and bone informa-tion is used to capture more action information.Finally,experiments are conducted on two subdata-sets X-Sub and X-View of NTU-RGB+D,and the accuracy shown in Top-1 classification results is 89.5%and 95.4%respectively.The experimental results are 1.0%and 0.3%higher than those of the 2S-AGCN model respectively.The superiority of this method is also proved by the experimental results.展开更多
边坡的宏观力学特性是由组成土体颗粒的细观参数及其运动决定的,基于连续介质模型的有限元方法虽然能够在宏观层面上基本等效地得到边坡土体的应力变形特性,但难以反映边坡体在微细观尺度上的变形失稳机理,存在明显的局限性。将离散元方...边坡的宏观力学特性是由组成土体颗粒的细观参数及其运动决定的,基于连续介质模型的有限元方法虽然能够在宏观层面上基本等效地得到边坡土体的应力变形特性,但难以反映边坡体在微细观尺度上的变形失稳机理,存在明显的局限性。将离散元方法(discrete element method,DEM)与计算流体动力学方法(computational fluid dynamic,CFD)进行耦合,建立了煤系土边坡3维DEM-CFD流固耦合细观作用计算模型,对降雨作用下煤系土边坡失稳破坏的细观机理进行分析。结果表明,采用DEM-CFD流固耦合方法模拟的煤系土边坡破坏形式主要是雨水冲刷,边坡滑动面预测为近似的直线段,这与室外模型试验边坡雨水冲刷的范围非常接近,验证了该数值方法的适应性。边坡土体颗粒的力链、配位数以及孔隙率等细观参数,在降雨过程中都会随之发生变化,如坡顶颗粒的孔隙率由初始状态的0.35变化至失稳状态的0.80,这些细观参数的变化与边坡土体的宏观力学表现直接关联。文中通过对颗粒细观参数变化分析,从细观角度解释了雨水作用下煤系土边坡的破坏演变规律。研究成果为该区域煤系土边坡的防护设计与施工提供理论依据,并从微细观角度更好地分析离散介质岩土工程的宏观力学规律提供了一种思路。展开更多
本文建立了燃油驱动装置(柴油发电机)排放的尾气与颗粒物在大气风场中的扩散、迁移以及浓度分布的理论模型,采用计算流体力学结合颗粒动力学及直接模拟蒙特卡洛(direct simulation Monte Carlo,DSMC)方法模拟尾气与颗粒物在南极地区大...本文建立了燃油驱动装置(柴油发电机)排放的尾气与颗粒物在大气风场中的扩散、迁移以及浓度分布的理论模型,采用计算流体力学结合颗粒动力学及直接模拟蒙特卡洛(direct simulation Monte Carlo,DSMC)方法模拟尾气与颗粒物在南极地区大气风场中的扩散、迁移与浓度分布特性。结果表明:在发电机排气管出口附近,尾气被大气迅速稀释,NO_2的质量浓度以及尾气温度快速下降;在远离排气管出口的区域,尾气的扩散逐渐变缓。颗粒物在大气风场中的碰撞、凝聚降低了其质量浓度,使得颗粒物扩散对大气环境的影响范围缩小。颗粒物质量流量的增加、颗粒物初始粒径的增大、大气风场流速的降低,均导致颗粒物在大气风场中各位置点的质量浓度升高。颗粒物质量流量、初始粒径及大气风场流速对颗粒物扩散的影响半径略有不同,在距离颗粒物发散源40m左右,颗粒物的质量浓度均达到国家标准。展开更多
基金the National Natural Science Foundation of China(No.61834005,61772417,61802304)the Shaanxi Province Key Research and Development Project(2021GY280).
文摘Compared with RGB videos and images,human bone data is less vulnerable to external factors and has stronger robustness.Therefore,behavior recognition methods based on skeletons are widely studied.Because graph convolution network(GCN)can deal with the irregular topology data of hu-man skeletons very well,more and more researchers apply GCN to human behavior recognition.Tra-ditional graph convolution methods only consider the joints with physical connectivity or the same type when building the behavior recognition model based on human skeletons structure,which cannot capture higher-order information better.To solve this problem,Motif-GCN is used in this paper to ex-tract spatial features.The relationship between the joints with natural connection in the human body is encoded by the first Motif-GCN,and the possible relationship between the unconnected joints in the human skeleton is encoded by the second Motif-GCN.In this way,the relationship between non-physical joints can be strengthened.Then a two stream framework combining joint and bone informa-tion is used to capture more action information.Finally,experiments are conducted on two subdata-sets X-Sub and X-View of NTU-RGB+D,and the accuracy shown in Top-1 classification results is 89.5%and 95.4%respectively.The experimental results are 1.0%and 0.3%higher than those of the 2S-AGCN model respectively.The superiority of this method is also proved by the experimental results.
文摘边坡的宏观力学特性是由组成土体颗粒的细观参数及其运动决定的,基于连续介质模型的有限元方法虽然能够在宏观层面上基本等效地得到边坡土体的应力变形特性,但难以反映边坡体在微细观尺度上的变形失稳机理,存在明显的局限性。将离散元方法(discrete element method,DEM)与计算流体动力学方法(computational fluid dynamic,CFD)进行耦合,建立了煤系土边坡3维DEM-CFD流固耦合细观作用计算模型,对降雨作用下煤系土边坡失稳破坏的细观机理进行分析。结果表明,采用DEM-CFD流固耦合方法模拟的煤系土边坡破坏形式主要是雨水冲刷,边坡滑动面预测为近似的直线段,这与室外模型试验边坡雨水冲刷的范围非常接近,验证了该数值方法的适应性。边坡土体颗粒的力链、配位数以及孔隙率等细观参数,在降雨过程中都会随之发生变化,如坡顶颗粒的孔隙率由初始状态的0.35变化至失稳状态的0.80,这些细观参数的变化与边坡土体的宏观力学表现直接关联。文中通过对颗粒细观参数变化分析,从细观角度解释了雨水作用下煤系土边坡的破坏演变规律。研究成果为该区域煤系土边坡的防护设计与施工提供理论依据,并从微细观角度更好地分析离散介质岩土工程的宏观力学规律提供了一种思路。
文摘本文建立了燃油驱动装置(柴油发电机)排放的尾气与颗粒物在大气风场中的扩散、迁移以及浓度分布的理论模型,采用计算流体力学结合颗粒动力学及直接模拟蒙特卡洛(direct simulation Monte Carlo,DSMC)方法模拟尾气与颗粒物在南极地区大气风场中的扩散、迁移与浓度分布特性。结果表明:在发电机排气管出口附近,尾气被大气迅速稀释,NO_2的质量浓度以及尾气温度快速下降;在远离排气管出口的区域,尾气的扩散逐渐变缓。颗粒物在大气风场中的碰撞、凝聚降低了其质量浓度,使得颗粒物扩散对大气环境的影响范围缩小。颗粒物质量流量的增加、颗粒物初始粒径的增大、大气风场流速的降低,均导致颗粒物在大气风场中各位置点的质量浓度升高。颗粒物质量流量、初始粒径及大气风场流速对颗粒物扩散的影响半径略有不同,在距离颗粒物发散源40m左右,颗粒物的质量浓度均达到国家标准。
