Thermal Fatigue Life Prediction of Air-Cooled Gas Turbine Vanes

1986 ◽  
Vol 108 (2) ◽  
pp. 414-420 ◽  
Author(s):  
T. Sato ◽  
K. Takeishi ◽  
T. Sakon
Keyword(s):  
Fatigue Life ◽  
Gas Turbine ◽  
Thermal Fatigue ◽  
Life Prediction ◽  
Fatigue Life Prediction ◽  
Thermal Fatigue Life ◽  
Turbine Vanes

scholarly journals Thermal Fatigue Life Prediction of Ventilation Air Methane Oxidation Bed

2016 ◽  
Vol 48 (1) ◽  
pp. 8-13 ◽  
Author(s):  
Y. Q. Liu ◽  
Q. H. Shang ◽  
D. H. Zhang ◽  
Y. X. Wang ◽  
T. T. Sun
Keyword(s):  
Fatigue Life ◽  
Methane Oxidation ◽  
Thermal Fatigue ◽  
Life Prediction ◽  
Fatigue Life Prediction ◽  
Thermal Fatigue Life

scholarly journals Thermal Fatigue Life Prediction of Thermal Barrier Coat on Nozzle Guide Vane via Master–Slave Model

2019 ◽  
Vol 9 (20) ◽  
pp. 4357 ◽  
Author(s):  
Peng Guan ◽  
Yanting Ai ◽  
Chengwei Fei ◽  
Yudong Yao
Keyword(s):  
Fatigue Life ◽  
Thermal Fatigue ◽  
Life Prediction ◽  
Guide Vane ◽  
Leading Edge ◽  
Fatigue Life Prediction ◽  
Trailing Edge ◽  
Thermal Fatigue Life ◽  
Barrier Coat ◽  
Nozzle Guide

The aim of this paper was to develop a master–slave model with fluid-thermo-structure (FTS) interaction for the thermal fatigue life prediction of a thermal barrier coat (TBC) in a nozzle guide vane (NGV). The master–slave model integrates the phenomenological life model, multilinear kinematic hardening model, fully coupling thermal-elastic element model, and volume element intersection mapping algorithm to improve the prediction precision and efficiency of thermal fatigue life. The simulation results based on the developed model were validated by temperature-sensitive paint (TSP) technology. It was demonstrated that the predicted temperature well catered for the TSP tests with a maximum error of less than 6%, and the maximum thermal life of TBC was 1558 cycles around the trailing edge, which is consistent with the spallation life cycle of the ceramic top coat at 1323 K. With the increase of pre-oxidation time, the life of TBC declined from 1892 cycles to 895 cycles for the leading edge, and 1558 cycles to 536 cycles for the trailing edge. The predicted life of the key points at the leading edge was longer by 17.7–40.1% than the trailing edge. The developed master–slave model was validated to be feasible and accurate in the thermal fatigue life prediction of TBC on NGV. The efforts of this study provide a framework for the thermal fatigue life prediction of NGV with TBC.

Thermal Fatigue Life Prediction for Stainless Steel Exhaust Manifold

1998 ◽  
Author(s):  
Yoshimasa Watanabe ◽  
Kazuhiko Shiratani ◽  
Shogo Iwanaga ◽  
Kazuaki Nishino
Keyword(s):  
Stainless Steel ◽  
Fatigue Life ◽  
Thermal Fatigue ◽  
Life Prediction ◽  
Fatigue Life Prediction ◽  
Exhaust Manifold ◽  
Thermal Fatigue Life

A Thermal Fatigue Life Prediction Method of Aluminum Alloy Piston in Material Application Engineering

2012 ◽  
Vol 578 ◽  
pp. 191-196
Author(s):  
Yu Tong He
Keyword(s):  
Aluminum Alloy ◽  
Fatigue Life ◽  
Thermal Fatigue ◽  
Life Prediction ◽  
Prediction Method ◽  
Fatigue Life Prediction ◽  
Elastic Model ◽  
Nonlinear Functions ◽  
Linear Elastic ◽  
Thermal Fatigue Life

In this paper, based on the Manson-Coffin fatigue theory, a thermal fatigue life prediction method for aluminum alloy engine piston is established, by introducing the nonlinear functions between the fatigue strength coefficient, fatigue continuation coefficient and elastic modulus with temperature. Compared with the results from the linear elastic model and the linear plastic model application, this nonlinear thermal fatigue life prediction method’s results fit much better to the experimental results, which means that this method is more accurate and credible than the other models.

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