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首页> 外文会议>International conference on high performance and optimum design of structures and materials >Numerical experiments for inverse analysis of material properties and size in functionally graded materials using the Artificial Bee Colony algorithm
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Numerical experiments for inverse analysis of material properties and size in functionally graded materials using the Artificial Bee Colony algorithm

机译：用人工蜂菌落算法在功能梯度材料中逆分析材料特性和尺寸的数值实验

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Functionally graded materials (FGMs) possess properties that vary gradually and are highly heat resistant. When incorporating these FGMs into a structure, the required distribution of material properties must be determined and produced to specification. Thus far, an inverse analysis method has been used for estimating a distribution of a Young's modulus of FGMs. However, minimizing an objective function to estimate a material property using the Davidon-Fletcher-Powell method did not converge under some initial conditions. Therefore, convergence of a solution depends on initial conditions. On the other hand, the Artificial Bee Colony (ABC) algorithm has drawn considerable interest in global optimization of a multimodal function. The objective of the present paper is to propose a method of numerical experimentation to conduct inverse analysis in FGMs with the ABC algorithm. A numerical experiment estimating both size and a graded index of an FGM beam that is based on measured stress values is presented. Next, determining a distribution of thermal conductivity in two-dimensional FGMs using measured steady state temperatures is carried out. The results of the numerical experiments demonstrate the effectiveness of the proposed method.
机译：功能分级材料（FGM）具有逐渐变化的性质，并且具有高耐热性。当将这些FGM掺入结构时，必须确定并产生所需的材料特性分布以规格。到目前为止，逆分析方法已被用于估计FGMS杨氏模量的分布。然而，最小化使用Davidon-Fletcher-Powell方法估计材料特性的目标函数在一些初始条件下不会收敛。因此，解决方案的收敛取决于初始条件。另一方面，人工蜂菌落（ABC）算法对多模式函数的全局优化具有相当大的兴趣。本文的目的是提出一种数值实验方法，以通过ABC算法在FGM中进行逆分析。呈现了基于测量应力值的FGM光束的尺寸和渐变索引的数值实验。接下来，执行使用测量的稳态温度的二维FGM中的导热率的分布。数值实验的结果证明了该方法的有效性。

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