Granular size segregation is an inevitable phenomenon in both natural and industrial processes.To understand the underlying mechanisms and develop effective optimization strategies,it is essential to employ robust met...Granular size segregation is an inevitable phenomenon in both natural and industrial processes.To understand the underlying mechanisms and develop effective optimization strategies,it is essential to employ robust methodologies that can quantitatively characterize and evaluate size segregation behaviors in granular systems.This review critically examines a wide variety of state-of-the-art methodologies from recent studies to quantify granular size segregation.The features of these methodologies are extracted and organized into a comprehensive framework.Four key questions are thoroughly discussed:evaluation criteria for identical segregation states,sensitivity to sample size,the influence of sampling division pattern,and the capability of handling multiple-component system.Finally,we provide an outlook on the future development of advanced and effective methodologies for granular size segregation characterization.展开更多
基金support from the Natural Science Foundation of Chongqing,China (grant Nos.Cstc2021ycjhbgzxm0165,CSTB2023NSCQ-MSX0514)the Fundamental Research Funds for the Central Universities (grant No.2020CDJQY-A005).
文摘Granular size segregation is an inevitable phenomenon in both natural and industrial processes.To understand the underlying mechanisms and develop effective optimization strategies,it is essential to employ robust methodologies that can quantitatively characterize and evaluate size segregation behaviors in granular systems.This review critically examines a wide variety of state-of-the-art methodologies from recent studies to quantify granular size segregation.The features of these methodologies are extracted and organized into a comprehensive framework.Four key questions are thoroughly discussed:evaluation criteria for identical segregation states,sensitivity to sample size,the influence of sampling division pattern,and the capability of handling multiple-component system.Finally,we provide an outlook on the future development of advanced and effective methodologies for granular size segregation characterization.
