Functionally Graded Extended Isogeometric Material Distribution Optimization Based on the Simple First-Order Shear Deformation Theory

DAI Zhao; CHU Chenxu; MAO Xueming; WANG Chao

doi:10.21656/1000-0887.460011

Volume 47 Issue 5

May 2026

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Article Navigation > Applied Mathematics and Mechanics > 2026 > 47(5): 560-576

DAI Zhao, CHU Chenxu, MAO Xueming, WANG Chao. Functionally Graded Extended Isogeometric Material Distribution Optimization Based on the Simple First-Order Shear Deformation Theory[J]. Applied Mathematics and Mechanics, 2026, 47(5): 560-576. doi: 10.21656/1000-0887.460011

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Functionally Graded Extended Isogeometric Material Distribution Optimization Based on the Simple First-Order Shear Deformation Theory

doi: 10.21656/1000-0887.460011

1.
CCCC Second Navigation Bureau Fourth Engineering Co., Wuhu, Anhui 241000, P.R. China
2.
Key Laboratory of Mechanics, Anhui Polytechnic University, Wuhu, Anhui 241000, P.R. China

Received Date: 2025-01-16
Rev Recd Date: 2025-06-17
Publish Date: 2026-05-01

Abstract

Abstract

In practical engineering applications, solving the mass optimization problem can not only effectively reduce the cost, but also significantly improve the structural properties. To address this mass optimization problem of functional graded material plates with holes, a solution model was proposed based on the simple first-order shear deformation theory (S-FSDT) and the extended isogeometric analysis (XIGA) to solve the mass minimization problem with the first natural frequency and the buckling critical parameter as the constraints. In the optimization procedure, an improved artificial rabbits optimization (IARO) algorithm incorporating the Lévy flight strategies was employed, which substantially enhances the algorithm's global exploration capability and enables effective escape from local optima. In the optimization design, the B-spline function was used to replace the traditional functionally gradient material distribution function, and the control points of the material distribution were used as design variables. The IARO algorithm demonstrates superior optimization performance through comprehensive benchmark testing through the CEC 2019 test functions, and the results of the arithmetic examples show the validity and feasibility of the proposed model, which can be further explored in the future for the application of the model in more complex engineering structures to achieve a more comprehensive structural optimization design.

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References

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