Impact-absorbing helmet design inspired by walnut texture reaction-diffusion mechanisms.

Abstract

This study investigates the complex textures on walnut shells, which play a vital role in enhancing crashworthiness performance. Despite the challenges in deciphering their functionality and formation, we discovered that these textures can be described by reaction-diffusion equations. These equations capture the shell hardening mechanism and simulate texture formation based on observed lignin diffusion patterns. The texture sample sets, derived from diverse local sampling positions and scopes, were analyzed using a Convolutional Neural Network classification model to determine the most representative texture classes. The parameter combinations from the control equations, integrated with impact risk assessments and personalized needs, informed the design of a protective helmet. Physical and numerical tests confirmed the helmet's impact-absorption capabilities. These insights pave the way for the development of impact-resistant devices, such as bio-armor and shell for automotive parts. STATEMENT OF SIGNIFICANCE: This study investigates the complex textures on walnut shells, which play a vital role in enhancing crashworthiness performance. We discovered that these textures can be described by reaction-diffusion equations, which capture the shell hardening mechanism and simulate texture formation based on observed lignin diffusion patterns. The texture were analyzed using a Convolutional Neural Network classification model to determine the most representative texture classes. The parameter combinations from the control equations, integrated with impact risk assessments and personalized needs, informed the design of a protective helmet. Physical and numerical tests confirmed the helmet's impact-absorption capabilities. These insights pave the way for the development of impact-resistant devices, such as bio-armor and shell for automotive parts.