Reliability Of Blades Research Articles

Sensitivity Analysis of Fatigue Life for Cracked Carbon-Fiber Structures Based on Surrogate Sampling and Kriging Model under Distribution Parameter Uncertainty

The quality and reliability of wind turbine blades, as core components of wind turbines, are crucial for the operational safety of the entire system. Carbon fiber is the primary material for wind turbine blades. However, during the manufacturing process, manual intervention inevitably introduces minor defects, which can lead to crack propagation under complex working conditions. Due to limited understanding and measurement capabilities of the input variables of structural systems, the distribution parameters of these variables often exhibit uncertainty. Therefore, it is essential to assess the impact of distribution parameter uncertainty on the fatigue performance of carbon-fiber structures with initial cracks and quickly identify the key distribution parameters affecting their reliability through global sensitivity analysis. This paper proposes a sensitivity analysis method based on surrogate sampling and the Kriging model to address the computational challenges and engineering application difficulties in distribution parameter sensitivity analysis. First, fatigue tests were conducted on carbon-fiber structures with initial cracks to study the dispersion of their fatigue life under different initial crack lengths. Next, based on the Hashin fatigue failure criterion, a simulation analysis method for the fatigue cumulative damage life of cracked carbon-fiber structures was proposed. By introducing uncertainty parameters into the simulation model, a training sample set was obtained, and a Kriging model describing the relationship between distribution parameters and fatigue life was established. Finally, an efficient input variable sampling method using the surrogate sampling probability density function was introduced, and a Sobol sensitivity analysis method based on surrogate sampling and the Kriging model was proposed. The results show that this method significantly reduces the computational burden of distribution parameter sensitivity analysis while ensuring computational accuracy.

Comprehensive Insight into the Failure Mechanisms, Modes, and Material Selection of Steam Turbine Blades

Addressing the critical issue of turbine blade failures, particularly in steam turbine systems, this comprehensive review delves into examining and analyzing various failure mechanisms associated with steam turbine blades. The discussion extends to the mode utilized in investigating these failures, with a specific focus on the crucial role of steam turbines in power generation. The review synthesizes various studies that have explored suitable blade materials for optimized performance and reduced failure risks. Findings reveal common failures such as thermal stress, mechanical stress, corrosion, erosion, fatigue, and creep in turbine blades and hubs. Consequently, the review serves as a valuable resource, providing insights into failure mechanisms and advocating for the implementation of suitable materials to enhance the reliability and performance of steam turbine blades.

Distributed-collaborative surrogate modeling approach for creep-fatigue reliability assessment of turbine blades considering multi-source uncertainty

This paper proposes a substructure-based distributed-collaborative surrogate modeling approach for improving the accuracy and efficiency in the estimation of the creep-fatigue reliability of gas turbine blades with the integration of the Least Absolute Shrinkage and Selection Operator (LASSO), kriging, Distributed Collaborative (DC) strategy and substructure simulation method, called as the substructure-based DCLKM. Further, the creep-fatigue reliability assessment framework is set by combining the proposed substructure-based DCLKM with some theoretical models, which takes into account the uncertainties of structural sizes, applied loads and material properties and the nonlinearity of creep/fatigue damage interaction. Firstly, the total strain range, mean stress, absolute temperature and maximum stress at the critical location are regarded as the first-level output responses, and their required samples are predicted through the fitted surrogate models. Secondly, the creep life and Low-Cycle Fatigue (LCF) life are regarded as the second-level output responses and predicted. Finally, the creep-fatigue damage and reliability assessment are performed for several given applied cycles, respectively. The proposed substructure-based DCLKM is validated on a case study. The results show that the proposed substructure-based DCLKM is feasible with high accuracy and efficiency in the creep-fatigue reliability assessment of turbine blades.

Probabilistic analysis of blade flutter based on particle swarm optimization-deep extremum neural network

Abstract The improvement of aero-engine performance has posed a serious threat to aeroelastic stability, thereby compromising the reliability of aero-engines. An effective approach to quantify the risk of compressor blade instability and enhance aeroelastic stability is through flutter probability evaluation. This study proposes a prediction method called the Particle Swarm Optimization-Deep Extremum Neural Network model (PSO-DENN) to improve the modeling accuracy and computational efficiency of compressor blade flutter probability analysis in aero-engines. Through deterministic analysis, the flutter response distribution of the blade is obtained. To account for the randomness of boundary conditions and time-varying loads, the flutter reliability of compressor blades is evaluated, providing insights into distribution characteristics, and reliability associated with aeroelastic instability. Comparative analysis of different methods demonstrates that the proposed PSO-DENN method improves calculation efficiency while ensuring accuracy.

Characterization and Prediction of Wind Turbine Blade Damage Based on Fiber Grating Sensor

INTRODUCTION: As a renewable and clean use of energy, wind power generation has a very important role in the new energy generation industry. For the many parts of various wind turbines, the safety and reliability of wind turbine blades are very important. OBJECTIVES: The energy spectrum simulation algorithm included in the wavelet analysis method is used to simulate and analyzewind turbine blade damage, to verify the correctness and validity of wind turbine blade damage analysis. METHODS: Matlab simulation is used to introduce the experiments related to the static and dynamic detection of fiber grating sensors, analyze the signal characteristics of the wind turbine blade when it is damaged by the impact, and provide a basis for the analysis of the external damage of large wind turbine blade. RESULTS: The main results obtained in this paper are the following. By analyzing the decomposition of wavelet packets, the gradient change of wavelet impact energy spectrum before and after the wavelet damage was obtained and compared with the histogram, and the impact energy spectrum of each three-dimensional wavelet energy packet in the image was compared and analyzed, which can well realize the recognition of wavelet damage gradient for solid composite materials. CONCLUSION: With the help of Matlab simulation to collect the impact response signal, using the wavelet packet energy spectrum method to analyze the signal, can derive the characteristics of wind turbine blade damage.

Experimental and numerical investigations on non-synchronous vibration and frequency lock-in of transonic compressor rotor blades

Non-synchronous vibration (NSV) problems in axial compressors are challenging and frequently result in high vibration stress or structural failure within the frequency lock-in region. A deeper understanding of the lock-in phenomenon in NSV is necessary to improve blade reliability and safety. In this study, an experiment was conducted on a multistage transonic axial compressor to obtain frequency lock-in characteristics. The enforced motion of the flexible blade simulation method was used to study the frequency lock-in mechanism between blade vibration and tip unstable flow. The results showed that the aerodynamic frequency characteristic changed from a broadband spectrum to a distinct frequency peak as the NSV onset. The nonlinear vibration pattern could maintain the limited cycle oscillation for 26 s. The vibration stress of the frequency locked-in case was approximately 19 times that of the frequency unlocked one. The pressure fluctuations generated by the large-scale radial separation vortex structures were stronger than those of the tip leakage flow, and the third-order harmonic frequency of the circumferential instability flow was close to the first-order bending model natural frequency. The periodic shedding and reattachment process of flow separation provided the initial non-synchronous aerodynamic excitation source. The frequency lock-in phenomenon occurred at a maximum vibration amplitude of 2 % and 3 % tip chord length. The tip unstable flow characteristics were consistent and entirely dominated by blade vibration.

Adaptive directed support vector machine method for the reliability evaluation of aeroengine structure

Machine learning methods have been widely applied to structural reliability analysis, due to the excellent performance in modeling precision and efficiency. In this paper, an adaptive directed support vector machine model (ADSVM) is proposed by integrating the adaptive sampling technology (AST) and the developed directed support vector machine (DSVM), to improve the efficiency and accuracy of turbine blade reliability analysis. In the developed method, the AST is adopted to extract high quality samples, in respect of distributed probability density and the distances between sample values and response values. The DSVM was developed by introducing the penalty coefficients for all the slack variables, to improve the modeling accuracy of SVM approach. One numerical example and the reliability analysis of aeroengine high-pressure turbine blade were performed to validate the developed methods. As illustrated in this numerical investigation, the modeling precision of DSVM is improved by alleviating the lag effect of support vector regression. From the comparison of methods, it is demonstrated that the ADSVM has higher accuracy, efficiency and stability in reliability simulations, which are improved by ∼20 % and ∼46.2 %, respectively. The main efforts of this study are to propose a promising approach, ADSVM, for the reliability analysis of complex structures besides turbine blades, which hold the academical significance in enriching and developing mechanical reliability theory.

Effect of Gd doping on phase evolution, mechanical and thermal characteristics of 1La-xGd-2Yb-3.5YSZ solid solutions

Thermal barrier coatings (TBCs) are critical for the reliability and lifespan of aircraft engine turbine blades. In this study, a novel quaternary rare-earth oxide (La2O3, Gd2O3, Yb2O3, and Y2O3) co-doped ZrO2 solid solution, referred to as 1La-xGd-2Yb-3.5YSZ, was synthesized by varying the doping amount of Gd2O3 from 0 to 6 mol. %. The impact of co-doping-induced lattice distortion on the phase composition, high-temperature phase stability, sintering resistance, and mechanical and thermal properties of the solid solution has been explored. It is found that the addition of Gd2O3 stabilizer effectively increased the lattice distortion of the solid solution, which led to improved phase stability and sintering resistance, enhanced mechanical properties, and low thermal conductivity. Our findings highlight the promising properties of the 1La-xGd-2Yb-3.5YSZ solid solution, making it an attractive candidate for TBC materials.

Parametric and numerical Finite Element simulation of wind turbine blades subjected to thermal residual stresses

This study aims to contribute to the ongoing efforts to enhance the reliability and durability of wind turbine blades, a critical component in wind energy generation. Specifically, this research addresses the issue of tunneling cracking and severe damage that can occur in wind turbine blades due to cohesive failure of the trailing edge. To achieve this objective, the study employs a rigorous approach, utilizing a full three-dimensional (3D) modeling strategy with finite element analysis (FEA) to simulate the behavior of wind turbine blades. The effect of cohesive materials and layered simulation methods on the thermal residual stress and crack propagation is thoroughly investigated. In particular, the study assesses the influence of carbon fiber-reinforced polymer (CFRP) and glass fiber-reinforced polymer (GFRP) materials on the phenomenon under consideration. In addition, the study undertakes a comprehensive parametric analysis to identify the independent effects of material properties and numerical simulation on thermal residual stress. Moreover, the research explores the behavior of the cohesive zone model in terms of thermal residual stress and crack propagation. The findings of this study have significant implications for researchers and practitioners in the wind energy industry. The study’s outcomes can aid in the development of improved materials and simulation techniques to mitigate thermal residual stress and prevent the occurrence of tunneling cracking and other types of damage in wind turbine blades. As such, this research contributes to the broader efforts to advance the reliability, efficiency, and sustainability of wind energy generation.

Reliability analysis of 15MW horizontal axis wind turbine rotor blades using fluid-structure interaction simulation and adaptive kriging model

Over the course of the last four decades, the rotor diameter of Horizontal Axis Wind Turbines (HAWTs) has undergone a substantial increase, expanding from 15 m (30 kW) to an impressive 240 m (15MW), primarily aimed at enhancing their power generation capacity. This growth in blade swept area, however, gives rise to heightened loads, stresses and deflections, imposing more rigorous demands on the structural robustness of these components. To prevent sudden failure and to plan effective inspection, maintenance, and repair activities, it is vital to estimate the reliability of the rotor blades by considering all the forces (aerodynamic and structural dynamics) acting on them over the turbine's lifespan. This research proposes a comprehensive methodology that seamlessly combines fluid-structure interaction (FSI) simulation, Kriging model/algorithm and Adaptive Kriging Monte Carlo Simulation (AKMCS) to assess the reliability of the HAWT rotor blades. Firstly, high-fidelity FSI simulations are performed to investigate the dynamic response of the rotor blade under varying wind conditions. Recognizing the computationally intensive nature and time-consuming aspects of FSI simulations, a judicious approach involves harnessing an economical Kriging model as a surrogate. This surrogate model adeptly predicts blade deflection along its length, utilizing training and testing data derived from FSI simulations. Impressively, the Kriging model predicts blade deflection 400 times faster than the FSI simulations, showcasing its enhanced efficiency. The optimized surrogate model is then used to estimate the flap wise blade tip deflection for one million wind speed samples generated using Weibull distribution. Thereafter, to evaluate the reliability of the blades, statistical modeling using methods such as Monte Carlo Simulation (MCS), AKMCS is performed. The results demonstrate the faster convergence of AKMCS requiring only 21 samples, as opposed to 1 million samples for MCS with minimal reduction in the precision of the estimated probability of failure (Pf) and reliability index (β). Demonstrated on the backdrop of an IEA-15MW offshore reference WT rotor blade, the proposed methodology underscores its potential to be seamlessly incorporated into the creation of WT digital twins, due to its near real-time predictive capabilities for Pf and β assessments.

Investigations on the water-jet guided laser scribing of thermal barrier coated IC21 nickel-based superalloy

Ceramic thermal barrier coatings (TBCs) are widely recognized as state-of-the-art for ensuring the stability and reliability of turbine blades operating in extreme conditions. However, the significant disparities between the thermal and mechanical properties of TBCs, bonding layers (BCs), and nickel-based superalloy substrates pose considerable challenges for machining film cooling structures on turbine blades while minimizing coating delamination, heat-affected zones (HAZs), and other potential defects. The utilization of Water-Jet Guided Laser (WJGL) has gained significant attention as a promising approach for the machining of advanced materials, including ceramics and multi-layer composites. In this study, a theoretical model is proposed to describe the transient interaction between WJGL and TBC IC21 nickel-based superalloy. A numerical simulation using the deformation geometry method is employed to investigate the evolution of ablation morphology, which is further validated by experimental data. Specifically, the formation mechanism of the shoulder structure at the material interface is explained. Furthermore, orthogonal experiments are conducted to establish the fundamental influence rule and significance level of machining parameters on the microscopic groove morphology. Based on these findings, multi-row cutting experiments are performed to identify the optimized scanning trajectory for achieving the high-quality thorough cutting of the substrate with a thickness of 2.7 mm, while minimizing oxidation, residue deposition, and delamination. The outcomes of this study contribute to the knowledge of WJGL machining, and could potentially improve the efficiency and accuracy of advanced material processing techniques.

Simulation Evaluation of a Novel Ice-Melting Sprinkling Technique for Blade

The blades of some airborne equipment are prone to icing under supercooled cloud conditions. In this paper, we propose an anti-deicing spray method to prevent blades from icing at low temperatures. Using computational fluid dynamics modeling and orthogonal experimental methods, we investigated the effects of the blade angle of attack, inlet wind speed, and nozzle mass flow rate on the thickness and coverage of the liquid layer of spray material and examined the use of deflectors in this study. We found the magnitude and change rule of the influence of the previously mentioned parameters on the liquid film thickness and coverage of sprayed material to be the nozzle mass flow rate is greater than the blade angle of attack and greater than the inlet wind speed. Under the optimal combination of conditions of α = 30°, u0 = 6 m/s, and Q = 0.003 kg/s, the liquid film thickness was maximized, and the liquid film thickness was 0.037 mm; under the optimal combination of conditions of α = 60°, u0 = 6 m/s, and Q = 0.003 kg/s, the liquid film coverage was maximized, and the liquid film coverage was 99.81%. The anti-deicer spraying method proposed herein for use on blades is effective when considered from a number of perspectives. It provides an innovative and feasible solution to the wind turbine blade freezing problem. However, the method must be explored and modified to maximize its chances of general application, and other factors must also be considered to fully optimize the sprinkler de-icing technique to improve the performance and reliability of blades.

Aerodynamic load evaluation of leading edge and trailing edge windward states of large-scale wind turbine blade under parked condition

The safety and reliability of wind turbine blades are increasingly challenged by extreme wind conditions such as typhoons, as wind turbines tend to become larger. Under these conditions, most units will be shut down and the blades will be pitched to around 90° to minimize the loads. This paper aims to compare a new strategy for the parked condition, i.e., the trailing edge windward state, with the traditional leading edge windward state to verify its technical feasibility. The aerodynamic loads of a 30%-thickness airfoil and a commercial wind turbine blade are comprehensively evaluated by wind tunnel experiment, CFD simulation and engineering analytical model. The two-dimensional airfoil cases indicate that the airfoil resultant force is lower in the trailing edge windward state than in the leading edge windward state for a wide range of angles of attack. Consequently, the three-dimensional blade cases shows that the low load region of the trailing edge windward state is relatively wider than that of the leading edge windward state. The averaged blade root load is reduced by 41.4% ~ 57.8% through trailing edge windward state with prescribed error bounds of windward angular. Besides, it is suggested that the traditional engineering analytical model should improve the precision of the extrapolated airfoil data around AOA = 180 deg. to ensure the accurate load evaluation under the trailing edge windward state. This study suggests a new control strategy for wind turbine blades under the parked condition, which offers significant benefits for load reduction and has a good potential for future applications.

New strategy to improve the overall performance of single-crystal superalloys by designing a bimodal γ′ precipitation microstructure

Advanced single-crystal superalloys, developed to improve the high temperature capability of gas turbines, often underperform in low-temperature conditions. This limitation compromises the overall reliability of turbine blades under complex service environments. This study introduces a novel strategy to enhance the overall performance of a fourth-generation single-crystal superalloy. Rapid liquid-nitrogen quenching following the aging treatment promotes extensive nucleation of ultrafine γ′ particles (γ′γ) with an average size of ∼10 nm, precipitated under extremely low supersaturation, as evidenced by high-resolution transmission electron microscopy (HRTEM) and atom probe tomography investigations. The combination of differential scanning calorimetry analysis, density functional theory calculations, and kinetic models verifies the high stability of γ′γ particles at low-temperature conditions around 900 °C. HRTEM observations reveal Orowan bypassing and dislocation cutting of γ′γ particles, leading to additional precipitation hardening by limiting dislocation motion in the γ phase and shear of primary precipitates. Consequently, a bimodal precipitation microstructure comprising γ′γ particles and primary γ′ phase significantly reduces the strain rate of low-temperature creep and nearly doubles the creep rupture life at 800 °C/735 MPa. Simultaneously, high-temperature properties at 900 °C/392 MPa and 1100 °C/137 MPa remain comparable to those of the original microstructure as the primary γ/γ′ microstructure is minimally affected by rapid cooling. This advancement improves overall performance and redefines the importance of small precipitates, broadening microstructure design concepts for future superalloy development.

Gas turbine blade fracturing fault diagnosis based on broadband casing vibration

Blade fault is a catastrophic failure of gas turbines. In order to improve the reliability of blade during operation, condition monitoring is one of the effective methods. However, there always exist two problems with blade monitoring: 1) challenges in warning of the occurrence of blade failure in advance and 2) difficulties finding the location after blade failure. In this article, we solve these problems by excavating the characteristics of blade-related signals in broadband casing vibration with advanced signal processing methods and machine learning technology. First, a novel method--Sparse Harmonic Product Spectrum (SHPS)--is proposed to accurately calculate blade passing frequency from gas turbine broadband casing vibration. The SPHS relies on Fourier transform, and its calculation utilizes the physical relationship between fundamental frequency and blade passing frequencies. Combining Vold-Kalman filter with adaptive parameter optimization process (AVKF), the blade-related vibration can be separated from casing vibration even in strong noise. Analysis of simulated casing vibration signal is used to verify the effectiveness and superiority of proposed method. Based on blade-related vibration, we build a gas turbine blade condition model in an unsupervised learning manner. The model can excavate potential blade failures earlier and more accurately than conventional threshold methods. Then, three coefficients are constructed according to the blade-related vibration characteristics to identify the blade fault location in multi-stage system. Moreover, the effectiveness of the proposed blade diagnosis framework is verified using actual industrial gas turbine blade fracturing failure data.

Prediction method of non-stationary random vibration fatigue reliability of turbine runner blade based on transfer learning

In order to solve the problems such as lack of fault information, sample variation with time and expensive calculation in the estimation of the vibration fatigue reliability of the turbine runner blade under the non-stationary hydraulic excitation. A prediction method of non-stationary random vibration fatigue reliability of the turbine runner blade based on transfer learning is proposed in this paper. Firstly, the dynamics model of the cracked turbine runner blade under the non-stationary hydraulic excitation is established to analyze the characteristics of the non-stationary random vibration fatigue of the turbine runner blade. Secondly, the transformation matrix between the source domain and target domain in the hidden space is found by the transfer learning method of balanced distribution adaptation (BDA). The adaptation of active learning and Kriging-based system reliability method (AK-SYSi) is applied to estimate the non-stationary random vibration fatigue reliability of the turbine runner blade with multi-failure-mode. Finally, an example is analyzed, and the Monte Carlo simulation (MCS) is used to verify the correctness of the proposed method. The results show that the method proposed in this paper can effectively predict the failure probability of the non-stationary vibration fatigue of the turbine runner blade in future time.

An Overview of Thermal Exposure on Microstructural Degradation and Mechanical Properties in Ni-Based Single Crystal Superalloys

Microstructural stability at elevated temperatures is one of the main concerns for the service reliability of aero-engine turbine blades. Thermal exposure, as an important approach to examine the microstructural degradation, has been widely studied in Ni-based single crystal (SX) superalloys for decades. This paper presents a review on the microstructural degradation induced by high-temperature thermal exposure and the associated damage in mechanical properties in some typical Ni-based SX superalloys. The main factors affecting the microstructural evolution during thermal exposure and the influencing factors in the degradation of mechanical properties are also summarized. Insights into the quantitative estimation of the thermal exposure-affected microstructural evolution and the mechanical properties will be beneficial for the understanding and improvement of reliable service in Ni-based SX superalloys.

Transfer learning and direct probability integral method based reliability analysis for offshore wind turbine blades under multi-physics coupling

Reliability of blades has a profound impact on both serviceability and safety of offshore wind turbines. Reliability estimation of wind turbine blade is a complex and time-consuming problem with multi-physics coupling and multi-failure modes correlation. Developing physics-of-failure modeling and reliability analysis methods with high efficiency and accuracy is a long-term challenge. In this work, a high availability and cost-effectiveness reliability estimation framework for offshore wind turbine blade by combining transfer learning (TL) and direct probability integral method (DPIM) is proposed. Extensive performance simulation of offshore wind turbine blade is a complex and necessary task, this paper develops a new adaptive sampling strategy to improve the validity of sample selection in the design space; On this basis, a physics-of-failure surrogate modeling approach is proposed by introducing TL method to fuse two kinds of multi-physics coupling analysis data, then the performance of all critical loads can be predicted efficiently in advance to provide a reliable design; Further, this paper provides an efficient reliability estimation method for offshore wind turbine blades by combining DPIM and surrogate model. Finally, the validity of the proposed approach is illustrated by numerical example and offshore wind turbine blade reliability estimation. The proposed framework provides a cost-effective alternative to higher loads simulation efforts and safety factors selection.

The Sensitivity of 5MW Wind Turbine Blade Sections to the Existence of Damage

Due to the large size of offshore wind turbine blades (OWTBs) and the corrosive nature of salt water, OWTs need to be safer and more reliable that their onshore counterparts. To ensure blade reliability, an accurate and computationally efficient structural dynamic model is an essential ingredient. If damage occurs to the structure, the intrinsic properties will change, e.g., stiffness reduction. Therefore, the blade’s dynamic characteristics will differ from those of the intact ones. Hence, symptoms of the damage are reflected in the dynamic characteristics that can be extracted from the damaged blade. Thus, damage identification in OWTBs has become a significant research focus. In this study, modal model characteristics were used for developing an effective damage detection method for WTBs. The technique was used to identify the performance of the blade’s sections and discover the warning signs of damage. The method was based on a vibration-based technique. It was adopted by investigating the influence of reduced blade element rigidity and its effect on the other blade elements. A computational structural dynamics model using Rayleigh beam theory was employed to investigate the behaviour of each blade section. The National Renewable Energy Laboratory (NREL) 5MW blade benchmark was used to demonstrate the behaviour of different blade elements. Compared to previous studies in the literature, where only the simple structures were used, the present study offers a more comprehensive method to identify damage and determine the performance of complicated WTB sections. This technique can be implemented to identify the damage’s existence, and for diagnosis and decision support. The element most sensitive to damage was element number 14, which is NACA_64_618.

Stress state mechanism of thickness debit effect in creep performances of a Ni-based single crystal superalloy

Weight reduction and advanced cooling schemes to improve aircraft engine efficiency drive the design of turbine blades toward thin-walled structures. The decrease of wall thickness leads to a decrease of creep rupture life and/or the increase of creep rate, which is termed as the thickness debit effect. To capture the nature of this effect and improve the reliability of turbine blades, creep tests at 1100 °C/130 MPa are carried out on sheet samples of a Ni-based single crystal superalloy with thicknesses from 0.60 to 2.17 mm. The creep rupture life is found to decrease with the decrease of sample thickness linearly, exhibiting an obvious thickness debit effect. The analysis of the microstructure evolution demonstrates that the rafting mechanism of the γ' phase of all samples remains the same (i.e. stress-induced, diffusion-controlled process) and is independent of the sample thickness. The fracture morphology reveals that the fracture mechanism of thin sample is a mixed fracture including micro voids and cleavage-like planes, while that of thick sample is micro voids-dominated. Environmental degradation suggests that surface damage due to oxidation and nitridation is not the primary causes for thickness debit effect, yet promotes the effect integrally. Finite element analyses and the observed dislocation configurations reveal that the thin sample is in a plane stress state, that activates six slip systems of the type {111}<110> and one slip system of the type {111}<112> during creep, while the thick sample is close to the ideal uniaxial stress state which activates all possible eight slip systems of the type {111}<110> and two slip systems of the type {111}<112>. Less slip systems activated in thin sample induce less work hardening, which results in heterogeneous deformation and shorter rupture life.