This paper deals with the effect of unit cell configuration on the energy absorption response of different cellular auxetic structures subjected to quasi-static and dynamic loadings through the experimental and numerical methods. Among the various structures, a re-entrant structure was selected due to its fundamental properties underlying the main characteristics of an auxetic material. Computer simulation techniques using ABAQUS software validated by experimental testing were used to conduct the evaluation of such devices. Several re-entrant structures with different geometrical parameters were modeled and compared with the conventional ones. Standard compression tests were carried out on the different structures produced by the 3D printing machine to evaluate the influence of auxeticity phenomenon in the energy absorption capability. It is discovered that the auxetic structures are superior to non-auxetic structures in terms of all studied impact resistance and energy absorption indicators due to their ability to withstand quasi-static axial impact loads. The primary outcome of this research is to extract design information for the use of auxetic materials as energy absorbers where quasi-static loading is expected.
Purpose
This paper aims to present a new hybrid algorithm of Particle Swarm Optimization and the Genetic Algorithm (PSOGA) to optimize the space trusses with continuous design variables. The PSOGA is an efficient hybridized algorithm to solve optimization problems.
Design/methodology/approach
These algorithms have shown outstanding performance in solving optimization problems with continuous variables. The PSO conceptually models the social behavior of birds, in which individual birds exchange information about their position, velocity and fitness. The behavior of a flock is influencing the probability of migration to other regions with high fitness. The GAs procedure is based on the mechanism of natural selection. The present study uses mutation, random selection and reproduction to reach the best genetic algorithm by the operators of natural genetics. Thus, only identical chromosomes or particles can be converged.
Findings
In this research, using the idea of hybridization PSO and GA algorithms are hybridized and a new meta-heuristic algorithm is developed to minimize the space trusses with continuous design variables. To showing the efficiency and robustness of the new algorithm, several benchmark problems are solved and compared with other researchers.
Originality/value
The results indicate that the hybrid PSO algorithm improved in both exploration and exploitation. The PSO algorithm can be used to minimize the weight of structural problems under stress and displacement constraints.
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