Fatigue Life Prediction Framework for Kaplan Turbine Blades on Unsteady CFD and Quasi-Static Structural Response

Pressure pulsation in fluid machinery is a critical factor that can significantly affect system performance and structural integrity. In particular, medium-to-low head and low-speed turbine systems are often subjected to repetitive pressure loading, making them susceptible to fatigue damage. However, quantitative fatigue evaluation tailored for such conditions remains limited. This study employs Computational Fluid Dynamics (CFD) to predict unsteady pressure loads on turbine blades under a specific operating condition. These loads are then transformed into time-varying stress histories through a quasi-static structural model based on the Finite Element Method (FEM). Standard fatigue assessment tools, including the Rainflow Counting method and Miner’s Rule, are subsequently applied to estimate the fatigue life. The analysis revealed that the dominant excitation frequencies were not harmonics of the rotor speed, but rather low-frequency components significantly lower than the blade’s natural frequencies. This frequency separation ensures minimal risk of resonance. Moreover, the stress amplitudes and number of cycles were found to be very small, indicating that the blades operate under quasi-static loading conditions with negligible fatigue damage. These findings validate the physical soundness of the proposed quasi-static fatigue analysis framework. Importantly, while this framework was developed for medium-to-low speed turbine systems, it also shows strong potential as a rapid fatigue screening tool in other rotating machinery where a clear separation exists between excitation and natural frequencies. By avoiding the need for expensive transient dynamic simulations, the framework provides a practical and efficient approach to fatigue life estimation in both design and diagnostic contexts.

Authors

Publication Details

Journal
The KSFM Journal of Fluid Machinery
Published
2026-04-13
DOI
https://doi.org/10.5293/kfma.2026.29.2.104
Primary Topic
High Temperature Alloys and Creep
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Fatigue Life Prediction Framework for Kaplan Turbine Blades on Unsteady CFD and Quasi-Static Structural Response

YounJea Kim, Hyunsu Kang, Cheoljung Kang, Haram Oh
The KSFM Journal of Fluid Machinery
High Temperature Alloys and Creep
article

Fatigue Life Prediction Framework for Kaplan Turbine Blades on Unsteady CFD and Quasi-Static Structural Response

YounJea Kim, Hyunsu Kang, Cheoljung Kang, Haram Oh
article en

Abstract

Pressure pulsation in fluid machinery is a critical factor that can significantly affect system performance and structural integrity. In particular, medium-to-low head and low-speed turbine systems are often subjected to repetitive pressure loading, making them susceptible to fatigue damage. However, quantitative fatigue evaluation tailored for such conditions remains limited. This study employs Computational Fluid Dynamics (CFD) to predict unsteady pressure loads on turbine blades under a specific operating condition. These loads are then transformed into time-varying stress histories through a quasi-static structural model based on the Finite Element Method (FEM). Standard fatigue assessment tools, including the Rainflow Counting method and Miner’s Rule, are subsequently applied to estimate the fatigue life. The analysis revealed that the dominant excitation frequencies were not harmonics of the rotor speed, but rather low-frequency components significantly lower than the blade’s natural frequencies. This frequency separation ensures minimal risk of resonance. Moreover, the stress amplitudes and number of cycles were found to be very small, indicating that the blades operate under quasi-static loading conditions with negligible fatigue damage. These findings validate the physical soundness of the proposed quasi-static fatigue analysis framework. Importantly, while this framework was developed for medium-to-low speed turbine systems, it also shows strong potential as a rapid fatigue screening tool in other rotating machinery where a clear separation exists between excitation and natural frequencies. By avoiding the need for expensive transient dynamic simulations, the framework provides a practical and efficient approach to fatigue life estimation in both design and diagnostic contexts.

The KSFM Journal of Fluid MachineryVol. 29(2)
Openalex Percentile: Top 9%
High Temperature Alloys and Creep
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.