A mechanical model of visco-elastic material is established in order to investigate viscous effect in dynamic growing crack-tip field of mode Ⅱ. It is shown that in stable creep growing phase, elastic deformation and...A mechanical model of visco-elastic material is established in order to investigate viscous effect in dynamic growing crack-tip field of mode Ⅱ. It is shown that in stable creep growing phase, elastic deformation and viscous deformation are equally dominant in the near-tip field, the stress and strain have the same singularity, namely, (oε) ∝ r- 1/( n-1). The asymptotic solutions of separatied variables of stress, stain and displacement in crack-tip field are obtained by asymptotic analysis, and the results of numerical value of stress and strain in crack-tip field are obtained by shooting method. Through numerical calculation, it is shown that the near-tip fields are mainly governed by the creep exponent n and Mach number M. By the asymptotic analysis to the crack-tip field, the fracture criterion of mode Ⅱ dynamic growing crack of visco-elastic materials is put forward from the point of view of strain.展开更多
Video synopsis is an effective and innovative way to produce short video abstraction for huge video archives,while keeping the dynamic characteristic of activities in the original video.Abnormal activity,as the critic...Video synopsis is an effective and innovative way to produce short video abstraction for huge video archives,while keeping the dynamic characteristic of activities in the original video.Abnormal activity,as the critical event,is always the main concern in video surveillance context.However,in traditional video synopsis,all the normal and abnormal activities are condensed together equally,which can make the synopsis video confused and worthless.In addition,the traditional video synopsis methods always neglect redundancy in the content domain.To solve the above-mentioned issues,a novel video synopsis method is proposed based on abnormal activity detection and key observation selection.In the proposed algorithm,activities are classified into normal and abnormal ones based on the sparse reconstruction cost from an atomically learned activity dictionary.And key observation selection using the minimum description length principle is conducted for eliminating content redundancy in normal activity.Experiments conducted in publicly available datasets demonstrate that the proposed approach can effectively generate satisfying synopsis videos.展开更多
文摘A mechanical model of visco-elastic material is established in order to investigate viscous effect in dynamic growing crack-tip field of mode Ⅱ. It is shown that in stable creep growing phase, elastic deformation and viscous deformation are equally dominant in the near-tip field, the stress and strain have the same singularity, namely, (oε) ∝ r- 1/( n-1). The asymptotic solutions of separatied variables of stress, stain and displacement in crack-tip field are obtained by asymptotic analysis, and the results of numerical value of stress and strain in crack-tip field are obtained by shooting method. Through numerical calculation, it is shown that the near-tip fields are mainly governed by the creep exponent n and Mach number M. By the asymptotic analysis to the crack-tip field, the fracture criterion of mode Ⅱ dynamic growing crack of visco-elastic materials is put forward from the point of view of strain.
基金Supported by the National Natural Science Foundation of China(No.61402023)Beijing Technology and Business' University Youth Fund(No.QNJJ2014-23)Beijing Natural Science Foundation(No.4162019)
文摘Video synopsis is an effective and innovative way to produce short video abstraction for huge video archives,while keeping the dynamic characteristic of activities in the original video.Abnormal activity,as the critical event,is always the main concern in video surveillance context.However,in traditional video synopsis,all the normal and abnormal activities are condensed together equally,which can make the synopsis video confused and worthless.In addition,the traditional video synopsis methods always neglect redundancy in the content domain.To solve the above-mentioned issues,a novel video synopsis method is proposed based on abnormal activity detection and key observation selection.In the proposed algorithm,activities are classified into normal and abnormal ones based on the sparse reconstruction cost from an atomically learned activity dictionary.And key observation selection using the minimum description length principle is conducted for eliminating content redundancy in normal activity.Experiments conducted in publicly available datasets demonstrate that the proposed approach can effectively generate satisfying synopsis videos.
