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<p>The high-temperature operation of gas turbine blades leads to progressive, time-dependent damage, primarily due to creep, which critically impacts component reliability and service life. Accurate life prediction under such conditions is essential for safe and efficient turbine operation. This paper presents a thermo-mechanically coupled mathematical model for predicting cumulative damage and estimating the residual life of turbine blades exposed to variable operating environments. The model incorporates temperature- and time-dependent material behavior, rooted in creep strength theory and refined through experimental data obtained from control specimens cut from service-exposed blades. A logarithmic shift method is proposed to correct long-term creep strength curves, accounting for the degradation of material properties during operation—this correction mechanism addresses the limitation of static strength curves in traditional models and improves prediction accuracy by 12%-15% compared with existing Larson-Miller parameter-based methods. The Larson–Miller parameter is employed to evaluate the creep life under different stress and temperature conditions. Cumulative damage is assessed through discrete time-step analysis, enabling the dynamic tracking of damage progression over the service period. Unlike prior studies that ignored regional environmental variability, the proposed model integrates real-time ambient temperature data to capture climate-induced damage differences, as validated by virtual simulations in Changchun and Beijing. The model is applied to simulate operational scenarios under different environmental conditions, demonstrating its capability to capture regional influences on damage evolution. Results validate the model’s effectiveness in quantifying creep degradation and predicting remaining life with high accuracy (average relative error &lt; 8%). This work offers a valuable tool for proactive maintenance scheduling and structural integrity assessment in turbine systems, contributing to enhanced operational reliability and extended service intervals. The proposed approach can also be extended to other high-temperature components operating under complex thermo-mechanical loads.</p>

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A climate-adaptive thermo-mechanical mathematical model for predicting cumulative creep damage in gas turbine blades

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年4月14日

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  • Xulan Li

摘要

The high-temperature operation of gas turbine blades leads to progressive, time-dependent damage, primarily due to creep, which critically impacts component reliability and service life. Accurate life prediction under such conditions is essential for safe and efficient turbine operation. This paper presents a thermo-mechanically coupled mathematical model for predicting cumulative damage and estimating the residual life of turbine blades exposed to variable operating environments. The model incorporates temperature- and time-dependent material behavior, rooted in creep strength theory and refined through experimental data obtained from control specimens cut from service-exposed blades. A logarithmic shift method is proposed to correct long-term creep strength curves, accounting for the degradation of material properties during operation—this correction mechanism addresses the limitation of static strength curves in traditional models and improves prediction accuracy by 12%-15% compared with existing Larson-Miller parameter-based methods. The Larson–Miller parameter is employed to evaluate the creep life under different stress and temperature conditions. Cumulative damage is assessed through discrete time-step analysis, enabling the dynamic tracking of damage progression over the service period. Unlike prior studies that ignored regional environmental variability, the proposed model integrates real-time ambient temperature data to capture climate-induced damage differences, as validated by virtual simulations in Changchun and Beijing. The model is applied to simulate operational scenarios under different environmental conditions, demonstrating its capability to capture regional influences on damage evolution. Results validate the model’s effectiveness in quantifying creep degradation and predicting remaining life with high accuracy (average relative error < 8%). This work offers a valuable tool for proactive maintenance scheduling and structural integrity assessment in turbine systems, contributing to enhanced operational reliability and extended service intervals. The proposed approach can also be extended to other high-temperature components operating under complex thermo-mechanical loads.