Year: 2024
Type: conference-paper
Abstract: This paper presents a nested tracking framework for analyzing cycles in 2D force networks within granular materials. These materials are composed of interacting particles, whose interactions are described by a force network. Understanding the cycles within these networks at various scales and their evolution under external loads is crucial, as they significantly contribute to the mechanical and kinematic properties of the system. Our approach involves computing a cycle hierarchy by partitioning the 2D domain into segments bounded by cycles in the force network. We can adapt concepts from nested tracking graphs originally developed for merge trees by leveraging the duality between this partitioning and the cycles. We demonstrate the effectiveness of our method on two force networks derived from experiments with photoelastic disks.
Authors: Farhan Rasheed, Abrar Naseer, Emma Nilsson, Talha Bin Masood, Ingrid Hotz
Institutions: Linköping University, Indian Institute of Science Bangalore
Language: English
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Awards: Robust topological methods for analysis of dynamic large scale data for modern material design, G712881263, Topological descriptors for tracking, comparison and visual exploration of complex scientific data, Scientific data analysis and visualization via topology guided feature extraction and comparison
OpenAlex ID: W4404238875