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An Innovative Service Load-Agnostic Structural Light-Weighting Design Optimization Methodology
Abstract:
A myriad of topology optimization tools exist today in the market that use automated under-the-hood structural simulations. All the user needs is to provide is the current shape of the part, or the maximum space that the part is allowed to occupy, and the maximum loads that it will experience. Though this technology has existed for over 25 years, recent advances in Additive Manufacturing (AM) have now enabled fabrication of hitherto-infeasible parts, both quickly and inexpensively.
A quick cursory literature search on successful implementation of topology optimization reveals that a majority of the attention has been focused on structural components and assemblies subjected to known service load(s) [1,2,3]. Therein lies one of the disadvantages experienced in the state-of-the-art today, especially for the military industry. The magnitudes of these loads are unknown a priori during design development, but rather only after vehicles are physically available, which is in much later design stages, and often too late to reap the benefits of optimization. In addition, enormous resources are required to measure loads in key components in physical tests, simply for performing topology optimization. In this study, a modeling and simulation (M&S) approach to optimization of structures in the absence of knowledge of service loads is described to determine the best weight save while simultaneously maintaining a similar or better “performance”.
Since the targets are with respect to zero or minimal performance gradation with respect to the baseline design, the premise of this research is that the optimization exercise can be carried out with relative loads, and knowledge of the absolute values are not necessary. This hypothesis has been successfully borne out in this paper, and the two design spaces explored meet all the set performance criteria compared to the baseline, and are able to achieve a weight save of up to 20%.