Probability-based service safety life prediction approach of raw and treated turbine blades regarding combined cycle fatigue

2021 ◽  
Vol 110 ◽  
pp. 106513
Author(s):  
Lei Han ◽  
Cao Chen ◽  
Tongyue Guo ◽  
Cheng Lu ◽  
Chengwei Fei ◽  
...  
Keyword(s):  
Life Prediction ◽  
Turbine Blades ◽  
Combined Cycle ◽  
Cycle Fatigue ◽  
Prediction Approach

A Life Prediction Model for Single-Crystal Nickel-Base Alloys Under Low-Cycle Fatigue

2020 ◽  
Author(s):  
Firat Irmak ◽  
Navindra Wijeyeratne ◽  
Taejun Yun ◽  
Ali Gordon
Keyword(s):  
Single Crystal ◽  
Gas Turbine ◽  
Life Prediction ◽  
Low Cycle Fatigue ◽  
Turbine Blades ◽  
Deformation Model ◽  
Cycle Fatigue ◽  
Nickel Base Superalloys ◽  
Nickel Base ◽  
Prediction Approach

Abstract In the development and assessment of critical gas turbine components, simulations have a crucial role. An accurate life prediction approach is needed to estimate lifespan of these components. Nickel base superalloys remain the material of choice for gas turbine blades in the energy industry. These blades are required to withstand both fatigue and creep at extreme temperatures during their usage time. Nickel-base superalloys present an excellent heat resistance at high temperatures. Presence of chromium in the chemical composition makes these alloys highly resistant to corrosion, which is critical for turbine blades. This study presents a flexible approach to combine creep and fatigue damages for a single crystal Nickel-base superalloy. Stress and strain states are used to compute life calculations, which makes this approach applicable for component level. The cumulative damage approach is utilized in this study, where dominant damage modes are capturing primary microstructural mechanism associated with failure. The total damage is divided into two distinctive modules: fatigue and creep. Flexibility is imparted to the model through its ability to emphasize the dominant damage mechanism which may vary among alloys. Fatigue module is governed by a modified version of Coffin-Manson and Basquin model, which captures the orientation dependence of the candidate material. Additionally, Robinson’s creep rupture model is applied to predict creep damage in this study. A novel crystal visco-plasticity (CVP) model is used to simulate deformation of the alloy under several different types of loading. This model has capability to illustrate the temperature-, rate-, orientation-, and history-dependence of the material. A user defined material (usermat) is created to be used in ANSYS APDL 19.0, where the CVP model is applied by User Programmable Feature (UPF). This deformation model is constructed of a flow rule and internal state variables, where the kinematic hardening phenomena is captured by back stress. Octahedral, cubic and cross slip systems are included to perform simulations in different orientations. An implicit integration process that uses Newton-Raphson iteration scheme is utilized to calculate the desired solutions. Several tensile, low-cycle fatigue (LCF) and creep experiments were conducted to inform modeling parameters for the life prediction and the CVP models.

Advancement of Experimental Methods and Cailletaud Material Model for Life Prediction of Gas Turbine Blades Exposed to Combined Cycle Fatigue

2012 ◽  
Author(s):  
Marcus Thiele ◽  
Swen Weser ◽  
Uwe Gampe ◽  
Roland Parchem ◽  
Samuel Forest
Keyword(s):  
Single Crystal ◽  
Gas Turbine ◽  
Life Prediction ◽  
Kinematic Hardening ◽  
Turbine Blades ◽  
Material Model ◽  
Combined Cycle ◽  
Cycle Fatigue ◽  
Stress Strain ◽  
Gas Turbine Blades

The European project PREMECCY has been conducted to enhance predictive methods for combined cycle fatigue (CCF) of gas turbine blades, i.e. interaction of low cycle fatigue (LCF) and high cycle fatigue (HCF). While design of CCF feature tests, comprising specimen and test rig design, has already been reported, this paper presents experimental HCF/ CCF test results and progress in life prediction. Besides standard lab specimen tests for characterization of single crystal and conventional cast material, also advanced specimens representing critical rotor blade features were tested in a hot gas rig. Based on these experimental data an extended Cailletaud material model for stress-strain analysis has been calibrated and combined with a modified ONERA damage model for creep-fatigue interaction to estimate the lifetime of the advanced test specimens. The model extensions address the effect of ratcheting, which is typical for CMSX-4 at asymmetric cyclic loading at elevated temperature. Caused by limitations of the Armstrong-Frederick kinematic hardening rule regarding ratcheting, three models for improved ratcheting simulation of isotropic material were adopted to anisotropic material. In addition multiple Norton-flow rules for the viscous part of the model are combined with time recovery terms in the kinematic hardening evolution to represent the behaviour of single crystal material in high temperature environment at a wide range of strain rates. Hence, an improved model for stress-strain and lifetime prediction for single crystals has been developed.

Development of a Generalized LCF-TMF Lifing Model for a Nickel-Base Superalloy

2012 ◽  
Author(s):  
Björn Buchholz ◽  
Uwe Gampe ◽  
Tilmann Beck
Keyword(s):  
Power Generation ◽  
Life Prediction ◽  
Power Plants ◽  
Prediction Models ◽  
Low Cycle Fatigue ◽  
Turbine Blades ◽  
Combined Cycle ◽  
Nickel Base Superalloy ◽  
Nickel Base ◽  
Base Superalloy

The growing share of power generation from volatile sources such as wind and photovoltaics requires fossil fuel fired power generation units be available and capable of high load flexibility to adjust to the changing capacity of the electrical grid. Additionally, back-up units with quick start capability and energy storage technologies are needed to fill the power shortfall when volatile sources are not available. Gas turbine and combined-cycle gas and steam turbine power plants are able to meet these demands. However, safe component design for improved cycling capability, combined with optimum utilization of material regarding its mechanical properties, requires design procedures and lifing models for the complex loadings resulting from this increased volatility of power demand. Since hot gas path components like turbine blades and vanes are highly stressed by cyclic thermal and mechanical loadings, resulting Thermo-Mechanical Fatigue (TMF), life prediction models such as the classic strain-life Coffin-Manson-Basquin method do not capture the influences of thermal cycling satisfyingly. Advanced TMF prediction models are thus necessary to accurately predict the durability of hot section components. This paper addresses life prediction of the Nickel-base superalloy René 80 at elevated temperature for various loading conditions. For this purpose, isothermal Low Cycle Fatigue (LCF) and corresponding TMF tests, with various temperature ranges and thermal-mechanical phase shifts, have been performed. On this basis, a systematic approach has been developed which allows assessing the key influences on TMF life. Moreover, a generalized model for fatigue has been derived, which has the potential to predict TMF life on the basis of LCF data. The knowledge gained from the model development allows an improved life prediction and better utilization of the material capabilities. Additionally, the required number of material tests for a general insight in the materials behaviour can be reduced significantly.

Stochastic Fatigue Life Prediction Based on a Reduced Data Set

2020 ◽  
Vol 142 (3) ◽  
Author(s):  
Dino Celli ◽  
M.-H. Herman Shen ◽  
Onome Scott-Emuakpor ◽  
Casey Holycross ◽  
Tommy George
Keyword(s):  
Fatigue Life ◽  
Strain Energy ◽  
Life Prediction ◽  
Prediction Method ◽  
Fatigue Life Prediction ◽  
Cycle Fatigue ◽  
Data Set ◽  
Data Points ◽  
Prediction Approach ◽  
Cycles To Failure

Abstract The aim of this paper is to provide a novel stochastic life prediction approach capable of predicting the total fatigue life of applied uniaxial stress states from a reduced dataset reliably and efficiently. A previously developed strain energy-based fatigue life prediction method is integrated with the stochastic state space approach for prediction of total cycles to failure. The approach under consideration for this study is the Monte Carlo method (MCM) where input is randomly generated to approximate the output of highly complex systems. The strain energy fatigue life prediction method is used to first approximate SN behavior from a set of two SN data points. This process is repeated with another unique set of SN data points to evaluate and approximate distribution of cycles to failure at a given stress amplitude. Uniform, normal, log-normal, and Weibull distributions are investigated. From the MCM, fatigue data are sampled from the approximated distribution and an SN curve is generated to predict high cycle fatigue (HCF) behavior from low cycle fatigue (LCF) data.

Advanced Experimental and Analytical Investigations on Combined Cycle Fatigue (CCF) of Conventional Cast and Single-Crystal Gas Turbine Blades

2011 ◽  
Author(s):  
Swen Weser ◽  
Uwe Gampe ◽  
Mario Raddatz ◽  
Roland Parchem ◽  
Petr Lukas
Keyword(s):  
Gas Turbines ◽  
Rotor Blade ◽  
Low Cycle Fatigue ◽  
Turbine Blades ◽  
Aircraft Engine ◽  
Combined Cycle ◽  
Rotor Blades ◽  
Blade Design ◽  
Cycle Fatigue ◽  
Predictive Methods

Rotor blades are the highest thermal-mechanical loaded components of gas turbines. Their service life is limited by interaction of creep, low cycle fatigue (LCF), high cycle fatigue (HCF) and surface attack. Because assurance of adequate HCF strength of the rotor blade is an important issue of the blade design the European project PREMECCY has been started by the European aircraft engine manufacturers and research institutes to enhance the predictive methods for combined cycle fatigue (CCF), as a superposition of HCF and LCF. Although today’s predictive methods ensure safe blade design, there are certain shortcomings of assessing fatigue life with Haigh or “modified Goodman diagrams”, such as isolated HCF assessment as well as uni-axial and off-resonant testing. HCF and LCF are considered without taking into account their interaction. PREMECCY is aimed to deliver new and improved CCF prediction methods for exploitation in the industrial design process. Beside development of predictive methods the authors are involved in the design and testing of advanced specimens representing rotor blade features. In this connection the paper presents a novel test specimen type and a unique hot gas rig for CCF feature test at mechanical and ambient representative conditions.

scholarly journals A Combined High and Low Cycle Fatigue Model for Life Prediction of Turbine Blades

Materials ◽  
2017 ◽  
Vol 10 (7) ◽  
pp. 698 ◽  
Author(s):  
Shun-Peng Zhu ◽  
Peng Yue ◽  
Zheng-Yong Yu ◽  
Qingyuan Wang
Keyword(s):  
Life Prediction ◽  
Low Cycle Fatigue ◽  
Turbine Blades ◽  
Cycle Fatigue ◽  
Fatigue Model

Extension of an energy-based life prediction method to low and combined cycle fatigue regimes

2014 ◽  
Vol 50 (2) ◽  
pp. 138-147 ◽  
Author(s):  
Casey Holycross ◽  
M-H Herman Shen ◽  
Onome Scott-Emuakpor ◽  
Tommy George
Keyword(s):  
Life Prediction ◽  
Prediction Method ◽  
Combined Cycle ◽  
Cycle Fatigue

Life Prediction Modeling of Combined High-Cycle Fatigue and Creep

2020 ◽  
Author(s):  
Thomas Bouchenot ◽  
Kirtan Patel ◽  
Ali P. Gordon ◽  
Sachin Shinde
Keyword(s):  
Prediction Model ◽  
Turbine Blade ◽  
Life Prediction ◽  
High Cycle Fatigue ◽  
Prediction Models ◽  
Turbine Blades ◽  
Operating Conditions ◽  
Test Method ◽  
Cycle Fatigue ◽  
Life Prediction Model

Abstract Industrial gas turbine blades are subjected to high temperatures and an array of mechanical and dynamic loads, making creep and high-cycle fatigue critical aspects of turbine blade design. The combination of creep and high-cycle fatigue produces a synergistic interaction effect whose explicit consequence to turbine life has been the subject of very little research. This interaction remains unaccounted for by current, decoupled life prediction models, which traditionally incorporate such interactions into conservative design safety factors. Improved lifing models capable of capturing these effects are now needed in order to maintain current reliability standards in next-generation operating conditions. This research identifies the life-limiting aspect of a combined high-cycle fatigue and creep response in conventionally cast Alloy 247 LC, and captures the interaction of the two loads in a novel life prediction model. The proposed model is created from a comprehensive collection of experimental data obtained using an unconventional two-part test method, where test specimens pre-deformed to a prescribed creep strain are fatigue loaded at an elevated temperature and high frequency until failure. A variety of temperatures, creep strains, and fatigue loading conditions are explored to ensure that the resulting model is applicable to the myriad of potential turbine blade operating conditions. Rigorous metallographic assessments accompanying each test are leveraged to create a microstructurally-informed combined life prediction model.

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