USER EXPERIENCE ORIENTED PARALLEL RANDOM TREE MINIMIZATION OF FLUX TARGETS FOR WEARABLE FABRIC COLLISION DETECTION

摘要

Based on multi-scale structural characteristics and destruction process of fabric matrix material, a kind of UE (user experience)-oriented parallel random tree clothing material collision detection method for minimizing flux targets is designed to study the mechanical properties of based wood such as compressive strength, bending strength, bend ductility, multiple cracking morphology and fracture process. The results show that the strength and toughness of the matrix material have been significantly improved. MSFRCC exhibits hardening behavior and multiple cracking modes under bending load. Scanning electron microscopy and fracture test results confirm that multi-scale fibers play a role of multi-scale crack resistance in the destruction process of fabric matrix composites. The study shows that implementing multi-scale composite design of fiber can significantly improve the toughness of fabric matrix composites.