摘要
建立了基于优化算法的估计材料热传导系数和边界条件的热传导反问题求解方法。该方法以观测的温度值与有限元计算模拟的温度值最小二乘极小化原理为基础,然后采用具有全局搜索能力的遗传算法求解。为了加快收敛速度和提高反演识别精度,采用了浮点编码的遗传算法。根据先验信息,建立了高斯变异策略。数值计算结果表明,所建立的数值反演方法可以用来解决未知的热传导系数和边界条件识别问题,并且具有良好的抗观测噪音能力。
The inverse problem of estimating the heat transfer coefficient and surface temperature is formulated. An algorithm is proposed based on the minimization of the least-square errors between the measured temperatures and calculated temperatures by the finite element model. The solution is sought by genetic algorithm which is able to search for optimal solution. To speed up the convergence rate and enhance inversion precision, the real genetic algorithm is applied. Numerical results show that the strategy developed in the paper is capable of dealing with both unknown heat transfer coefficient and unknown surface temperature, and has the ability to suppress measurement noise.
出处
《工程力学》
EI
CSCD
北大核心
2005年第3期72-75,87,共5页
Engineering Mechanics
基金
国家自然科学基金资助项目(10072014)
关键词
工程力学
参数识别
遗传算法
热传导系数
反问题
全局优化
Genetic algorithms
Global optimization
Heat transfer coefficients
Identification (control systems)
Inverse problems
Optimization
Surfaces
Temperature
