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Research Papers: Design and Analysis

Improved First-Order Approximate Models of Temperature and Thermal Stresses for Online Fatigue Monitoring

[+] Author and Article Information
Hengliang Zhang

School of Power and Mechanical Engineering,
Wuhan University,
Wuhan 430072, China
e-mail: zhl8111@sina.com.cn

Danmei Xie, Jin Jiang

School of Power and Mechanical Engineering,
Wuhan University,
Wuhan 430072, China

1Corresponding author.

Contributed by the Pressure Vessel and Piping Division of ASME for publication in the JOURNAL OF PRESSURE VESSEL TECHNOLOGY. Manuscript received May 13, 2015; final manuscript received August 24, 2016; published online September 28, 2016. Assoc. Editor: Albert E. Segall.

J. Pressure Vessel Technol 139(2), 021204 (Sep 28, 2016) (6 pages) Paper No: PVT-15-1097; doi: 10.1115/1.4034632 History: Received May 13, 2015; Revised August 24, 2016

Online monitoring of temperature and thermal stresses is an important way to ensure the safety of power plants considering fatigue and creep damages. The effect of online monitoring is determined by the accuracy and calculating time of monitoring models. In this paper, the improved first-order analytical models of temperature and thermal stresses considering temperature-dependent material properties have been derived by using homotopy analysis method (HAM) and superposition principle. The optimal convergence control parameters are obtained by calculating the mean-square residual errors. The validity and accuracy of the proposed models were proved by results comparisons with finite element method (FEM) and artificial parameter method.

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Figures

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Fig. 1

Geometry and boundary conditions of the cylinder

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Fig. 2

Temperature errors calculated by the method presented with different values of convergence control parameter h1 for 1 °C/min

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Fig. 3

Mean square errors of temperature with different values of convergence control parameter h1 for 1 °C/min

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Fig. 4

Axial thermal stresses calculated by FEM and the method presented with different values of convergence control parameter h2 for 1 °C/min

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Fig. 5

Tangential thermal stresses calculated by FEM and the method presented with different values of convergence control parameter h2 for 1 °C/min

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Fig. 6

Mean square errors of thermal stress with different values of h2 for 1 °C/min

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Fig. 7

Mean square errors of temperature with different values of convergence control parameter h1 for 2 °C/min

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Fig. 8

Mean square errors of thermal stresses with different values of convergence control parameters h2 for 2 °C/min

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Fig. 9

Average value of mean square errors of temperature with different values of h1 and boundary temperature rising rates

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Fig. 10

Average value of mean square errors of thermal stresses with different values of h2 and boundary temperature rising rates

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