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Bio-inspired-based structures optimization for additive manufacturing using metaheuristic Kriging
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AI
DOI：10.1080/15376494.2023.2214915.png)
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Lightweight cellular structures are investigated intensively in additive manufacturing and require optimization strategies to distribute both patterns, cross-sections sizes and type, and even materials. There exist several parametric optimization techniques that permit not only obtaining lightweight structures but also ensuring maintaining the rigidity. Among these techniques, design of experiments is time-consuming, and the values of the optimal parameters are estimated based on their possible range rather than being determined precisely. An original scientific strategy is to use the Kriging swarm optimization technique to achieve the global optimum using a minimal amount of computer simulations. Therefore, the objective of this paper is to determine the optimal cross-sections of structures using bio-inspired L-systems. These L-systems-based structures were created and distributed along the directions of the principal stress lines (PSLs), then mimicking material growth and distribution inside biological structures. Two PSLs directions were separately investigated for each load case; the first direction is used as a guide for the growth of L-systems and the second one serves for branch extensions and limitations. To do so, a metamodel is used upon particle swarm optimization technique (PSO) and several case studies are conducted to improve the stiffness-to-weight ratio while respecting the additive manufacturability.
Keyword:
Metamodel optimization
PSO
bio-inspired structures
simulation
L-systems
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4.9K
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