Deep multiobjective design optimization of CFRP isogrid tubes using lichtenberg algorithm

The lattice structures use has increased in several sectors due to the potential for mass reduction without significant rigidity loss. In this paper, an isogrid tube multi-objective optimization considering six objectives is presented. The finite element method was applied to develop a numerical mod...

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Vydané v:Soft computing (Berlin, Germany) Ročník 26; číslo 15; s. 7195 - 7209
Hlavní autori: Pereira, João Luiz Junho, Francisco, Matheus Brendon, Ribeiro, Ronny Francis, Cunha, Sebastião Simões, Gomes, Guilherme Ferreira
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Berlin/Heidelberg Springer Berlin Heidelberg 01.08.2022
Predmet:
Artificial Intelligence
Computational Intelligence
Control
Engineering
Mathematical Logic and Foundations
Mechatronics
Optimization
Robotics
Composites
Multi-objective optimization
Isogrid structure
Buckling
Lichtenberg algorithm
ISSN:1432-7643, 1433-7479
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Shrnutí:The lattice structures use has increased in several sectors due to the potential for mass reduction without significant rigidity loss. In this paper, an isogrid tube multi-objective optimization considering six objectives is presented. The finite element method was applied to develop a numerical model for this complex structure, and a new optimization algorithm called the Multi-objective Lichtenberg Algorithm was used to find all the best possible designs. The optimizations were made considering two methodologies: (i) using a surrogate model derived from the design of experiments considering the response surface model and (ii) finite element updating, a direct link between the meta-heuristic and the numerical model. The latter is unprecedented in the literature for isogrid tubes and proved to be the best methodology, besides not even needing explicit equations. It discovered isogrid tube designs using TOPSIS that reduced at least 45.69% of the mass, 18.4% of the instability coefficient, 61.76% of the TW, and increased the natural frequency by at least 52.57%. The results show that optimizations via finite element updating associated with meta-heuristics not only allow the true interpretation of complex problems nature through real Pareto fronts, but can also deliver innovative results.
ISSN:1432-7643
1433-7479
DOI:10.1007/s00500-022-07105-9