Open Access

ARTICLE

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

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1 School of Civil Engineering, Hefei University of Technology, Hefei, P .R.C .

* Corresponding author: Prof. Huanlin Zhou, .

Computers, Materials & Continua 2017, 53(4), 271-290. https://doi.org/10.3970/cmc.2017.053.271

Abstract

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 surfacewith 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 convergencespeed than the CS and CGM. The CS and CS-CGMare 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 timepointsand measurement points, and with the decrease of measurement noises, the inverse results are more accurate.

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