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Optimal design of two-dimensional porosity distribution in shear deformable functionally graded porous beams for stability analysis

机译:剪切可变形功能梯度多孔梁二维孔隙度分布的优化设计

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In the present study, considering two-dimensional porosity distribution through a functionally graded porous (FGP) beam, its optimal distributions are obtained. A multi-objective optimization problem is defined to maximize critical buckling load and minimize mass of the beam, simultaneously. To this end, Timoshenko beam theory is employed and equilibrium equations for two-dimensional functionally graded porous (2D-FGP) beam are derived. For the solution, we present generalized differential quadrature method (GDQM) and consider two symmetric boundary conditions (Clamped-Clamped and Hinged-Hinged). Solving generalized eigenvalue problem, critical buckling load for 2D-FGP beam is then obtained. During optimization procedure, a cubic polynomial spline interpolating on a finite number of design variables is considered as porosity distribution function. Solving the multi-objective optimization problem using bio-inspired genetic algorithm (NSGA II), leads to a set of optimal porosity distributions known as Pareto optimal solutions. To show the validity of the proposed formulation, we compare results with those reported (1D and 2D porosity distributions) in the literature as well as fmite element simulations. We also compare Pareto solutions with optimization result of one dimensional porosity distribution which clearly demonstrates the importance of the presented optimization procedure. In general, optimum porosity distributions are different in each boundary condition. However, in most of the optimum solutions, middle line of the beam is composed of the material with higher values of porosity and outer corners have lower values of porosity. Pareto optimal solutions also indicate that, sharp decreasing of the mass makes a slight decline in critical buckling load when it has large values. The proposed approach can be used for design of porosity distribution in FGP structures.
机译:在本研究中,考虑通过功能梯度多孔(FGP)梁的二维孔隙度分布,可以获得其最佳分布。定义了一个多目标优化问题,以同时最大化临界屈曲载荷和最小化梁的质量。为此,采用了季莫申科束理论,并推导了二维功能梯度多孔(2D-FGP)束的平衡方程。对于解决方案,我们提出了广义差分正交方法(GDQM),并考虑了两个对称边界条件(Clamped-Clamped和Hinged-Hinged)。解决了广义特征值问题,得到了二维FGP梁的临界屈曲载荷。在优化过程中,在有限数量的设计变量上进行插值的三次多项式样条被视为孔隙率分布函数。使用生物启发式遗传算法(NSGA II)解决多目标优化问题,可以得到一组称为Pareto最优解的最优孔隙度分布。为了显示所提出配方的有效性,我们将结果与文献以及有限元模拟中所报道的结果(一维和二维孔隙度分布)进行了比较。我们还将Pareto解与一维孔隙度分布的优化结果进行了比较,这清楚地证明了所提出的优化程序的重要性。通常,最佳孔隙率分布在每种边界条件下都不同。但是,在大多数最佳解决方案中,梁的中线由孔隙率较高的材料组成,而外角处的孔隙率较低。帕累托最优解还表明,当质量值急剧减小时,质量的急剧减小会使临界屈曲载荷略有下降。所提出的方法可用于设计FGP结构中的孔隙度分布。

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