STRUCTURAL TOPOLOGY OPTIMIZATION FOR BLAST MITIGATION USING HYBRID CELLULAR AUTOMATA

2024-01-3110

11/15/2024

Features
Event
2009 Ground Vehicle Systems Engineering and Technology Symposium
Authors Abstract
Content
ABSTRACT

Design for structural topology optimization is a method of distributing material within a design domain of prescribed dimensions. This domain is discretized into a large number of elements in which the optimization algorithm removes, adds, or maintains the amount of material. The resulting structure maximizes a prescribed mechanical performance while satisfying functional and geometric constraints. Among different topology optimization algorithms, the hybrid cellular automaton (HCA) method has proven to be efficient and robust in problems involving large, plastic deformations. The HCA method has been used to design energy absorbing structures subject to crash impact. The goal of this investigation is to extend the use of the HCA algorithm to the design of an advanced composite armor (ACA) system subject to a blast load. The ACA model utilized consists of two phases: ceramic and metallic. In this work, the proposed algorithm drives the optimal distribution of a metallic phase within the design domain. When the blast pressure wave hits the targeted structure, the fluids kinetic energy is transformed into strain energy (SE) inside the solid medium. Maximum attenuation is reached when SE is maximized. Along with an optimum use of material, this condition is satisfied when SE is uniformly distributed in the design domain. This work makes use of the CONWEP model developed by the Army Research Laboratory. The resulting structure shows the potential of the HCA method when designing ACAs.

Meta TagsDetails
DOI
https://doi.org/10.4271/2024-01-3110
Pages
9
Citation
Goetz, J., Tan, H., Renaud, J., and Tovar, A., "STRUCTURAL TOPOLOGY OPTIMIZATION FOR BLAST MITIGATION USING HYBRID CELLULAR AUTOMATA," SAE Technical Paper 2024-01-3110, 2024, https://doi.org/10.4271/2024-01-3110.
Additional Details
Publisher
Published
Nov 15
Product Code
2024-01-3110
Content Type
Technical Paper
Language
English