Comparison of CS,CGM and CS-CGM for Prediction of Pipe’s Inner Surface in FGMs

• 作者: Bo Yu Haolong Chen Huanlin Zhou Zeng Meng
• 来源期刊: 计算机、材料和连续体(英文)
• 学科: 数学
• 关键词: INVERSE geometry problems transient heat conduction functionally GRADED materials CUCKOO search algorithm CONJUGATE GRADIENT method
• 年，卷（期）: 2017,（4）
• 页码范围: 271-290
• 页数: 20页
• 分类号: O17

摘要

The cuckoo search algorithm(CS)is improved by using the conjugate gradient method(CGM),and the CS-CGM is proposed.The unknown inner boundary shapes are generated randomly and evolved by Lévy flights and elimination mechanism in the CS and CS-CGM.The CS,CGM and CS-CGM are examined for the prediction of a pipe’s inner surface.The direct problem is two-dimensional transient heat conduction in functionally graded materials(FGMs).Firstly,the radial integration boundary element method(RIBEM)is applied to solve the direct problem.Then the three methods are compared to identify the pipe’s inner surface with the information of measured temperatures.Finally,the influences of timepoints,measurement point number and random noise on the inverse results are investigated.It is found that the three algorithms are promising and can be used to identify the pipe’s inner surface.The CS-CGM has higher accuracy and faster convergence speed than the CS and CGM.The CS and CS-CGM are insensitive to the initial values.The CGM and CS-CGM are more insensitive to the measurement noises compared with the CS.With the increase of timepoints and measurement points,and with the decrease of measurement noises,the inverse results are more accurate.