Automatic extraction method of force chain information and its application in the flow photoelastic experiment of granular matter

The force chain is the core of the multi-scale analysis of granular matter.Accurately extracting the force chain information among particles is of great significance to the study of particle mechanics and geological hazards caused by particle flow.However,in the photoelastic experiment,the precise identification of the branching points of force chains has not been effectively realized.Therefore,this study proposes an automatic extraction method of force chain key information.First,based on the Hough transform and the Euclidean distance,a particle geometric information identification model is established and geometric information such as particle circle center coordinates,radius,contact point location,and contact angle is extracted.Then,a particle contact force information identification model is established following the color gradient mean square method.The model realizes the rapid calibration and extraction of a large number of particle media contact force information.Next,combined with the force chain composition criterion and its quasilinear feature,an automatic extraction method of force chain information is established,which solves the problem of the accurate identification of the force chain branch points.Finally,in the photoelastic experiment of ore drawing from a single drawpoint,the automatic extraction method of force chain information is verified.The results show that the macroscopic distribution of force chains during ore drawing from a single drawpoint is left–right symmetrical.Strong force chains are mostly located on the two sides of the model but in small numbers and they mainly develop vertically.Additionally,the ends are mostly in a combination of Y and inverted Y shapes,while the middle is mostly quasilinear.Weak force chains are abundant and mostly distributed in the middle of the model,and develop in different directions.The proposed extraction method accurately extracts the force chain network from the photoelastic experiment images and dynamically characterizes the force chains of granular matter,which has significant advantages in particle geometry information extraction,force chain branch point discrimination,force chain retrieval,and force chain distribution and its azimuthal characterization.The results provide a scientific basis for studying the macroscopic and microscopic mechanical parameters of granular matter.

动态视角下欣喜和满意驱动什么忠诚?交易阶段和转换成本的调节作用

顾客欣喜和顾客满意到底谁更能驱动顾客忠诚早已经成为学者和实践者关注的热点问题之一。本研究构建了一个动态的欣喜、满意、忠诚之间的作用关系模型,考察了交易阶段和转换成本的交互调节作用。研究发现,顾客欣喜显著影响顾客满意,顾客欣喜和顾客满意一起很好地解释了行为忠诚和态度忠诚,且态度忠诚显著影响行为忠诚。随着从首次网购阶段到重购阶段,顾客欣喜对行为忠诚的解释作用增加,而顾客满意只对态度忠诚的解释作用增加,且转换成本直接显著影响态度忠诚,交易阶段(T/T+1)与转换成本的交互作用在顾客欣喜和行为忠诚与顾客满意和行为忠诚之间表现出不同的特征。本研究结论为网上商家合理配置有限资源及如何维持高忠诚方面提供有意义的启示。