Enhanced calculation of eigen-stress field and elastic energy in atomistic interdiffusion of alloys

In this paper, a novel procedure for optimal design of geometrically nonlinear submerged arches is proposed. It is based on the Coral Reefs Optimization with Substrate Layers algorithm, a multi-method ensemble evolutionary approach for solving optimization problems. A novel arch shape parameterization is combined with the Coral Reefs Optimization with Substrate Layers algorithm. This new parameterization allows considering geometrical parameters in the design process, in addition to the reduction of the bending moment carried out by the classical design approach. The importance of considering the second-order behaviour of the arch structure is shown by different numerical experiments. Moreover, it is shown that the use of Coral Reefs Optimization with Substrate Layers algorithm leads to nearly-optimal solutions, ensuring the stability of the structure, reducing the maximum absolute bending moment value, and complying with the serviceability structural restrictions.

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Enhanced calculation of eigen-stress field and elastic energy in atomistic interdiffusion of alloys

Cited by 3 publications

References 16 publications

Hybridizing machine learning with metaheuristics for preventing convergence failures in mechanical models based on compression field theories

Hybridizing machine learning with metaheuristics for preventing convergence failures in mechanical models based on compression field theories

Memetic coral reefs optimization algorithms for optimal geometrical design of submerged arches

Optimum Shape Design of Geometrically Nonlinear Submerged Arches Using the Coral Reefs Optimization with Substrate Layers Algorithm

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