高温复杂结构的混合概率故障物理建模与疲劳寿命预测
|
摘要
随着现代机械装备向大型化、复杂化和精密化方向发展,诸如航空发动机、重型燃气轮机等重大机械装备的大量零部件在十分恶劣的环境下工作,需满足高性能要求并实现安全可靠地运行。其中,重大机械装备高温复杂结构(如燃汽轮机和航空发动机热端部件)的寿命和可靠性是制约整机寿命和可靠性水平的主要因素之一。在重大机械装备服役过程中,由于不断的起动、停车以及各种任务的需要,其各部件承受复杂载荷作用,同时诸多不确定性因素愈加恶劣的影响使得复杂构件产生多种形式的失效破坏且表现出较大的分散性。特别是疲劳破坏,对装备的安全工作造成极大的威胁。因此,研究并保证此类结构在这些不确定因素影响下因疲劳断裂而失效的可能性降至最低程度具有重要的现实意义。
复杂载荷、多环境因素以及多种失效模式下的寿命预测一直是寿命预测领域的难点和热点。由于重大机械装备复杂结构破坏机理的复杂性、不确定性和分散性,本文针对其寿命预测与可靠性理论中若干亟待解决的重要问题,在复杂载荷、多环境因素以及多种失效模式下的概率寿命预测以及不确定性分析方面展开研究,利用航空发动机涡轮盘用GH4133合金和某型航空发动机实测转速循环数据,并辅以高强度耐热钢试验数据进行模型验证。其主要内容和研究成果如下:
(1)提出了复杂载荷作用下考虑小载荷损伤与强化的模糊Miner法则
为了完善工程中应用较广的Miner法则的理论缺陷和拓展其应用范围,通过考虑载荷和损伤的分散性和随机性对疲劳寿命和疲劳特性分散性的影响,将复杂载荷中小载荷的损伤与强化引入到传统Miner法则的理论框架下,并将载荷之间相互作用和载荷次序效应对疲劳特性的影响定量地纳入Miner法则,提出了模糊Miner法则。该法则的提出为工程中“载荷是否产生损伤”的判据和“低载强化”现象的解释提供了理论支撑,更符合客观实际。
(2)建立了多种失效模式下的寿命预测模型——广义应变能损伤函数模型
为统一表征高温复杂结构在多种失效模式下不同载荷类型造成的损伤而实现不同加载波形下的疲劳-蠕变寿命预测,基于能量准则,提出了广义应变能损伤函数模型。该模型综合考虑了各加载条件对其损伤和寿命的影响,具有较广的适用性。在此基础上,考虑到该模型中给定的应变能与控制裂纹形成与扩展的真实应变能的差异,提出了改进型广义应变能损伤函数模型。研究结果显示,在不同温度、应变比或应力比下,改进模型的寿命预测精度较高,可满足工程实际需要。
(3)提出了多种失效模式下的寿命预测方法——广义能量损伤参数法
针对高温下无荷载保持时间的低周疲劳失效,结合故障物理失效分析技术,从能量角度提出了更具一般性的广义能量损伤参数。在此基础上,应用动粘性来描述损伤累积,提出了一种物理意义更明确和试验依据更充分的延性耗竭模型。广义能量损伤参数和延性耗竭模型均是基于疲劳失效过程中不可逆延性耗散且材料逐渐递减的固有能量吸收能力而提出的,为实现可靠预估重大机械装备复杂构件的剩余寿命提供了有效途径。研究结果显示,相比现有模型和方法,广义能量损伤参数和延性耗竭模型在寿命预测精度和应用范围上有着显著的优势。
(4)构建了混合概率故障物理寿命预测理论框架
为了解决复杂结构寿命预测中诸多因素引入的不确定性问题,应用Bayes推理和故障物理技术,将寿命预测模型参数、载荷历程和材料属性等参数以分布形式输入,构建了由历史记录数据到材料试验、加速寿命数据的混合概率故障物理寿命预测理论框架。同时,设计并应用马尔科夫链蒙特卡洛(MCMC)仿真技术解决了该框架下高维Bayes推理的密集计算问题。该框架的提出,实现了故障物理技术在疲劳寿命预测中的应用,并可依据不同阶段的信息和知识状态进行信息更新,一方面节省了相关试验时间和成本,另一方面为实现重大机械装备的安全评估和寿命周期管理做出最有利的决策和判断提供了理论依据。
(5)提出了基于综合不确定性分析和Bayes推理及信息更新的概率故障物理寿命预测方法
基于混合概率故障物理寿命预测理论框架,系统地研究了物理不确定性、统计不确定性和模型不确定性对寿命和损伤的影响,提出了寿命预测中的综合不确定性分析方法:White-Box法,有效地对重大机械装备复杂构件进行概率故障物理寿命预测。同时,拓展了Black-Box法在疲劳寿命预测中的应用,较好地表征并评估了模型不确定性。相比Black-Box法,White-Box法综合考虑了模型、模型参数、材料属性和模型输入变量的不确定性对疲劳寿命的影响。上述两种方法的提出和拓展,为模型的选择和比较提供了一种更为科学的理论依据。研究结果表明,概率故障物理寿命预测方法较好地解释了同一类设备或复杂构件在相同使用条件下寿命也有很大的分散性问题,可用于重大机械装备复杂构件的安全评定、健康监测、结构设计和剩余寿命估算等一系列工程实际问题中。
With the rapid development of larger, more complex and precise modern mechanical equipments, some special requirements for designing these complex structures, i.e. mechanisms and reliability, have been brought forward correspondingly. Examples of such structures are the turbine disks used in gas turbine aero-engines and/or heavy duty gas turbines. During operation these disks are subjected to high temperature, pressure and rotating speed conditions, for which a failure could lead to catastrophic results. The life and reliability of these complex structures have been one of the primary factors that restricted the development of major mechanical equipments.
For turbine disks during service, the demands of the start-up, normal operation and shut-down phases result in different failure modes, like fatigue and creep which are affected by many uncertainties typically exhibit random behavior. Low cycle fatigue (LCF) at high temperature is a key failure mode of these structures. In order to reduce weight and improve the working life while keeping or increasing reliability, an accurate algorithm for probabilistic LCF life prediction of complex structures is essential, which is the main purpose of this contribution.
LCF at high temperature is an interactive mechanism of different processes such as time-independent plastic strain, time-dependent creep and environmental corrosion, and the complex interaction between them. These damage mechanisms under multi-environmental factors make it difficult to predict LCF life using a unified model that can make accurate life prediction for fatigue-creep interaction. According to the complexity, uncertainty and scatter in the fatigue failure mechanism, the overall objective of this dissertation is to address key challenges and critical issues in life prediction and reliability analysis on major mechanical equipments. In this dissertation, probabilistic LCF life prediction models and uncertainty assessment methodologies were studied systematically in both theoretical and engineering applications. The studied alloys included Ni-base Superalloy GH4133, GH4698 (typically used as the turbine disk material in gas turbine engines) and pearlitic heat resisting steel (which is used in steam turbine items). The main work and innovative contributions of this dissertation are as follows:
(1) Development of a Fuzzy Miner’s rule considering damaging and strengthening of low-amplitude loads under different load sequences
Due to the shortcomings of the traditional Miner’s rule, a Fuzzy Miner’s rule is developed to consider the strengthening and damaging of low-amplitude loads with different load sequences. This model improves the application of the traditional Miner’s rule, by considering not only the damaging and strengthening of low-amplitude loads, but also the load sequence effects. To apply the Fuzzy Miner’s rule, the law of selecting membership functions for different load spectrum is found and different membership functions are investigated to show the important influence on estimating fatigue life. Applicability of the method was validated using experimental and real-time data gained from aircrafts. It was also found that the predicted fatigue life by the proposed rule is more accurate and reliable than that by the traditional methods. In addition, the Fuzzy Miner’s rule provides a criterion for judging if“the loads cause damage or not”and a theoretical basis for explaining the“coaxing effect”phenomenon in engineering.
(2) Development of a generalized strain energy damage function model for fatigue-creep life prediction
The fatigue-creep interaction is a key factor for the failures of many complex structures under high temperature and cyclic loading. These fatigue-creep life prediction issues are significant in selection, design and safety assessments of those components. In order to describe the accumulation and development of damage uniformly and accurately, a generalized strain energy damage function model was developed for fatigue-creep life prediction under different loading waveforms. The approach used in this model to reflect the effects of time-dependent damaging mechanisms on fatigue-creep life is different from those used in all earlier models. In addition, an improved generalized strain energy damage function was used to reduce the difference between the approximate strain energy and real strain energy absorbed during the damage process. This proposed model can describe the effects of different time-dependent damaging mechanisms on fatigue-creep life more accurately than others, which makes it widely applicable and a precise method to predict the life of fatigue-creep interaction.
(3) Development of a generalized energy-based damage parameter for fatigue-creep life prediction
Based on the plastic strain energy density (PSED) and Physics of Failure (PoF) analysis, a generalized energy-based fatigue-creep damage parameter was developed to account for the creep and mean strain/stress effects in the LCF regime. Moreover, the mechanism of cyclic hardening is taken into account within this model. On this basis, it is assumed that damage accrues by means of viscous flow and ductility consumption is only related to plastic strain and creep strain under high temperature LCF conditions. Based on the ductility exhaustion (DE) theory, a new viscosity-based life prediction model was introduced by using dynamic viscosity to describe the flow behavior. Both the proposed damage parameter and viscosity-based model provided a better prediction of GH4133’s fatigue behavior when compared with the SWT and PSED methods. Under mean strain conditions, these two models provide a more accurate life prediction of GH4133 than that under zero-mean strain conditions, which provides an effective, reliable and new way for accessing the remaining life of complex structures.
(4) Construction of a hybrid probabilistic PoF-based LCF life prediction framework
Probabilistic life prediction of complex structures, such as aircraft turbine disks, requires the modeling of multiple complex random phenomenas. The Bayesian approach can potentially give more complete estimates by combining test data with technical knowledge available from theoretical analysis and/or previous experimental results, and provides many practical features such as a fair coverage of uncertainty and the updating concept that reduces costs and saves time. A hybrid probabilistic PoF-based framework for life prediction using Bayes’theorem was developed to quantify the uncertainty of material properties, total inputs and model uncertainty resulting from creation of different deterministic models in a LCF regime. In practice, the statistical inferences in this framework involve high-dimensional integrations that usually are very computationally intensive. The Bayesian inference was solved using the MATLAB platform to run the necessary MCMC simulation, which greatly improves the utility of this framework. Through this framework, a basis for safety assessment and life cycle management of major mechanical equipments was offered.
(5) Development of a hybrid probabilistic PoF-based fatigue life prediction methodology under Bayesian information updating and uncertainty
Under the hybrid probabilistic PoF-based fatigue life prediction framework, a white-box approach for modeling total uncertainty, including physical uncertainty, statistical uncertainty and model uncertainty, was developed for LCF life prediction based on Bayesian information updating. In addition, the black-box approach was expanded to quantify the model uncertainty in LCF life prediction. Compared with the white-box approach, there is no consideration of the uncertainties associated with the inner workings of the model in the black-box approach. The development of white-box approach, the improvement of methodology and expanding of research on black-box approach provided reliable theoretical basis and scientific method for model selection and comparison. The proposed probabilistic PoF-based fatigue life prediction methodology intrinsically explains the scatter of service life of complex structures subjected to the same conditions and has certain conductive significance for structural health monitoring, design, safety evaluation and remaining life assessment of major mechanical equipments.
复杂载荷、多环境因素以及多种失效模式下的寿命预测一直是寿命预测领域的难点和热点。由于重大机械装备复杂结构破坏机理的复杂性、不确定性和分散性,本文针对其寿命预测与可靠性理论中若干亟待解决的重要问题,在复杂载荷、多环境因素以及多种失效模式下的概率寿命预测以及不确定性分析方面展开研究,利用航空发动机涡轮盘用GH4133合金和某型航空发动机实测转速循环数据,并辅以高强度耐热钢试验数据进行模型验证。其主要内容和研究成果如下:
(1)提出了复杂载荷作用下考虑小载荷损伤与强化的模糊Miner法则
为了完善工程中应用较广的Miner法则的理论缺陷和拓展其应用范围,通过考虑载荷和损伤的分散性和随机性对疲劳寿命和疲劳特性分散性的影响,将复杂载荷中小载荷的损伤与强化引入到传统Miner法则的理论框架下,并将载荷之间相互作用和载荷次序效应对疲劳特性的影响定量地纳入Miner法则,提出了模糊Miner法则。该法则的提出为工程中“载荷是否产生损伤”的判据和“低载强化”现象的解释提供了理论支撑,更符合客观实际。
(2)建立了多种失效模式下的寿命预测模型——广义应变能损伤函数模型
为统一表征高温复杂结构在多种失效模式下不同载荷类型造成的损伤而实现不同加载波形下的疲劳-蠕变寿命预测,基于能量准则,提出了广义应变能损伤函数模型。该模型综合考虑了各加载条件对其损伤和寿命的影响,具有较广的适用性。在此基础上,考虑到该模型中给定的应变能与控制裂纹形成与扩展的真实应变能的差异,提出了改进型广义应变能损伤函数模型。研究结果显示,在不同温度、应变比或应力比下,改进模型的寿命预测精度较高,可满足工程实际需要。
(3)提出了多种失效模式下的寿命预测方法——广义能量损伤参数法
针对高温下无荷载保持时间的低周疲劳失效,结合故障物理失效分析技术,从能量角度提出了更具一般性的广义能量损伤参数。在此基础上,应用动粘性来描述损伤累积,提出了一种物理意义更明确和试验依据更充分的延性耗竭模型。广义能量损伤参数和延性耗竭模型均是基于疲劳失效过程中不可逆延性耗散且材料逐渐递减的固有能量吸收能力而提出的,为实现可靠预估重大机械装备复杂构件的剩余寿命提供了有效途径。研究结果显示,相比现有模型和方法,广义能量损伤参数和延性耗竭模型在寿命预测精度和应用范围上有着显著的优势。
(4)构建了混合概率故障物理寿命预测理论框架
为了解决复杂结构寿命预测中诸多因素引入的不确定性问题,应用Bayes推理和故障物理技术,将寿命预测模型参数、载荷历程和材料属性等参数以分布形式输入,构建了由历史记录数据到材料试验、加速寿命数据的混合概率故障物理寿命预测理论框架。同时,设计并应用马尔科夫链蒙特卡洛(MCMC)仿真技术解决了该框架下高维Bayes推理的密集计算问题。该框架的提出,实现了故障物理技术在疲劳寿命预测中的应用,并可依据不同阶段的信息和知识状态进行信息更新,一方面节省了相关试验时间和成本,另一方面为实现重大机械装备的安全评估和寿命周期管理做出最有利的决策和判断提供了理论依据。
(5)提出了基于综合不确定性分析和Bayes推理及信息更新的概率故障物理寿命预测方法
基于混合概率故障物理寿命预测理论框架,系统地研究了物理不确定性、统计不确定性和模型不确定性对寿命和损伤的影响,提出了寿命预测中的综合不确定性分析方法:White-Box法,有效地对重大机械装备复杂构件进行概率故障物理寿命预测。同时,拓展了Black-Box法在疲劳寿命预测中的应用,较好地表征并评估了模型不确定性。相比Black-Box法,White-Box法综合考虑了模型、模型参数、材料属性和模型输入变量的不确定性对疲劳寿命的影响。上述两种方法的提出和拓展,为模型的选择和比较提供了一种更为科学的理论依据。研究结果表明,概率故障物理寿命预测方法较好地解释了同一类设备或复杂构件在相同使用条件下寿命也有很大的分散性问题,可用于重大机械装备复杂构件的安全评定、健康监测、结构设计和剩余寿命估算等一系列工程实际问题中。
With the rapid development of larger, more complex and precise modern mechanical equipments, some special requirements for designing these complex structures, i.e. mechanisms and reliability, have been brought forward correspondingly. Examples of such structures are the turbine disks used in gas turbine aero-engines and/or heavy duty gas turbines. During operation these disks are subjected to high temperature, pressure and rotating speed conditions, for which a failure could lead to catastrophic results. The life and reliability of these complex structures have been one of the primary factors that restricted the development of major mechanical equipments.
For turbine disks during service, the demands of the start-up, normal operation and shut-down phases result in different failure modes, like fatigue and creep which are affected by many uncertainties typically exhibit random behavior. Low cycle fatigue (LCF) at high temperature is a key failure mode of these structures. In order to reduce weight and improve the working life while keeping or increasing reliability, an accurate algorithm for probabilistic LCF life prediction of complex structures is essential, which is the main purpose of this contribution.
LCF at high temperature is an interactive mechanism of different processes such as time-independent plastic strain, time-dependent creep and environmental corrosion, and the complex interaction between them. These damage mechanisms under multi-environmental factors make it difficult to predict LCF life using a unified model that can make accurate life prediction for fatigue-creep interaction. According to the complexity, uncertainty and scatter in the fatigue failure mechanism, the overall objective of this dissertation is to address key challenges and critical issues in life prediction and reliability analysis on major mechanical equipments. In this dissertation, probabilistic LCF life prediction models and uncertainty assessment methodologies were studied systematically in both theoretical and engineering applications. The studied alloys included Ni-base Superalloy GH4133, GH4698 (typically used as the turbine disk material in gas turbine engines) and pearlitic heat resisting steel (which is used in steam turbine items). The main work and innovative contributions of this dissertation are as follows:
(1) Development of a Fuzzy Miner’s rule considering damaging and strengthening of low-amplitude loads under different load sequences
Due to the shortcomings of the traditional Miner’s rule, a Fuzzy Miner’s rule is developed to consider the strengthening and damaging of low-amplitude loads with different load sequences. This model improves the application of the traditional Miner’s rule, by considering not only the damaging and strengthening of low-amplitude loads, but also the load sequence effects. To apply the Fuzzy Miner’s rule, the law of selecting membership functions for different load spectrum is found and different membership functions are investigated to show the important influence on estimating fatigue life. Applicability of the method was validated using experimental and real-time data gained from aircrafts. It was also found that the predicted fatigue life by the proposed rule is more accurate and reliable than that by the traditional methods. In addition, the Fuzzy Miner’s rule provides a criterion for judging if“the loads cause damage or not”and a theoretical basis for explaining the“coaxing effect”phenomenon in engineering.
(2) Development of a generalized strain energy damage function model for fatigue-creep life prediction
The fatigue-creep interaction is a key factor for the failures of many complex structures under high temperature and cyclic loading. These fatigue-creep life prediction issues are significant in selection, design and safety assessments of those components. In order to describe the accumulation and development of damage uniformly and accurately, a generalized strain energy damage function model was developed for fatigue-creep life prediction under different loading waveforms. The approach used in this model to reflect the effects of time-dependent damaging mechanisms on fatigue-creep life is different from those used in all earlier models. In addition, an improved generalized strain energy damage function was used to reduce the difference between the approximate strain energy and real strain energy absorbed during the damage process. This proposed model can describe the effects of different time-dependent damaging mechanisms on fatigue-creep life more accurately than others, which makes it widely applicable and a precise method to predict the life of fatigue-creep interaction.
(3) Development of a generalized energy-based damage parameter for fatigue-creep life prediction
Based on the plastic strain energy density (PSED) and Physics of Failure (PoF) analysis, a generalized energy-based fatigue-creep damage parameter was developed to account for the creep and mean strain/stress effects in the LCF regime. Moreover, the mechanism of cyclic hardening is taken into account within this model. On this basis, it is assumed that damage accrues by means of viscous flow and ductility consumption is only related to plastic strain and creep strain under high temperature LCF conditions. Based on the ductility exhaustion (DE) theory, a new viscosity-based life prediction model was introduced by using dynamic viscosity to describe the flow behavior. Both the proposed damage parameter and viscosity-based model provided a better prediction of GH4133’s fatigue behavior when compared with the SWT and PSED methods. Under mean strain conditions, these two models provide a more accurate life prediction of GH4133 than that under zero-mean strain conditions, which provides an effective, reliable and new way for accessing the remaining life of complex structures.
(4) Construction of a hybrid probabilistic PoF-based LCF life prediction framework
Probabilistic life prediction of complex structures, such as aircraft turbine disks, requires the modeling of multiple complex random phenomenas. The Bayesian approach can potentially give more complete estimates by combining test data with technical knowledge available from theoretical analysis and/or previous experimental results, and provides many practical features such as a fair coverage of uncertainty and the updating concept that reduces costs and saves time. A hybrid probabilistic PoF-based framework for life prediction using Bayes’theorem was developed to quantify the uncertainty of material properties, total inputs and model uncertainty resulting from creation of different deterministic models in a LCF regime. In practice, the statistical inferences in this framework involve high-dimensional integrations that usually are very computationally intensive. The Bayesian inference was solved using the MATLAB platform to run the necessary MCMC simulation, which greatly improves the utility of this framework. Through this framework, a basis for safety assessment and life cycle management of major mechanical equipments was offered.
(5) Development of a hybrid probabilistic PoF-based fatigue life prediction methodology under Bayesian information updating and uncertainty
Under the hybrid probabilistic PoF-based fatigue life prediction framework, a white-box approach for modeling total uncertainty, including physical uncertainty, statistical uncertainty and model uncertainty, was developed for LCF life prediction based on Bayesian information updating. In addition, the black-box approach was expanded to quantify the model uncertainty in LCF life prediction. Compared with the white-box approach, there is no consideration of the uncertainties associated with the inner workings of the model in the black-box approach. The development of white-box approach, the improvement of methodology and expanding of research on black-box approach provided reliable theoretical basis and scientific method for model selection and comparison. The proposed probabilistic PoF-based fatigue life prediction methodology intrinsically explains the scatter of service life of complex structures subjected to the same conditions and has certain conductive significance for structural health monitoring, design, safety evaluation and remaining life assessment of major mechanical equipments.
引文
[1]国家自然科学基金委员会工程与材料科学部.机械工程学科发展战略报告(2011~2020).北京:科学出版社, 2010.
[2] Schütz W. A history of fatigue. Engineering Fracture Mechanics, 1996, 54(2): 263-300.
[3] Schijve J. Fatigue of structures and materials in the 20th century and the state of the art. International Journal of Fatigue, 2003, 25(8): 679-702.
[4] ASTM E206-72. ASTM American National Standard, ANSI/ASTM, E206-72, 1979.
[5]李舜酩.机械疲劳与可靠性设计.北京:科学出版社, 2006, pp. 78-90.
[6]张小丽,陈雪峰,李兵,等.机械重大装备寿命预测综述.机械工程学报, 2011, 47(11): 100-116.
[7]姚卫星.结构疲劳寿命分析.北京:国防工业出版社, 2003.
[8]杨晓华,姚卫星,段成美.确定性疲劳累积损伤理论进展.中国工程科学, 2003, 5(4): 81-87.
[9] Cui W. A state-of-the-art review on fatigue life prediction methods for metal structures. Journal of Marine Science and Technology, 2002, 7(1): 43-56.
[10] Chaboche J. Continuum damage mechanics: Part II-damage growth, crack initiation, and crack growth. Journal of Applied Mechanics, 1988, 55(1): 65-72.
[11] Kwofie S. An exponential stress function for predicting fatigue strength and life due to mean stresses. International Journal of Fatigue, 2001, 23(9): 829-836.
[12] Manson S S, Hirschberg M H. Fatigue: an interdisciplinary approach. Syracuse: Syracuse University Press, 1964.
[13] Ince A, Glinka G. A modification of Morrow and Smith-Watson-Topper mean stress correction models. Fatigue & Fracture of Engineering Materials & Structures, 2011, 34(11): 854-867.
[14] Li J, Liu J, Sun Q, et al. A modification of Smith-Watson-Topper damage parameter for fatigue life prediction under non-proportional loading. Fatigue & Fracture of Engineering Materials & Structures, 2011, in press, doi: 10.1111/j.1460-2695.2011.01620.x.
[15] Miner M A. Cumulative damage in fatigue. Journal of Applied Mechanics, 1945, 12(3): A159-164.
[16] Grover H J. An observation concerning the cycle ratio in cumulative damage. Fatigue in Aircraft Structures, STP-274, American Society for Testing and Materials, Philadelphia, 1960,pp. 120-124.
[17] Manson S S, Freche J C, Ensign C R. Application of a double linear damage rule to cumulative fatigue. In: Fatigue crack propagation, ASTM, STP 415, 1967, pp. 384-412.
[18]朱顺鹏,黄洪钟,谢里阳.考虑小载荷强化的模糊疲劳寿命预测理论.航空学报, 2009, 30(6): 1048-1052.
[19] Zhu S P, Huang H Z, Wang Z L. Fatigue life estimation considering damaging and strengthening of low amplitude loads under different load sequences using fuzzy sets approach. International Journal of Damage Mechanics, 2011, 20(6): 876-899.
[20]黄洪钟,朱顺鹏,汪忠来,等.基于剩余强度衰减退化的非线性累积损伤准则及其可靠性定寿.应用基础与工程科学学报, 2011, 19(2): 323-334.
[21]朱顺鹏,黄洪钟,谢里阳.基于二元疲劳失效判据的非线性疲劳损伤累积模型及其强度退化研究.中国机械工程, 2008, 19(22): 2753-2761.
[22] Fatemi A, Yang L. Cumulative fatigue damage and life prediction theories: a survey of the state of the art for homogeneous materials. International Journal of Fatigue, 1998, 20(1): 9-34.
[23] Yang L, Fatemi A. Cumulative fatigue damage mechanisms and quantifying parameters: a literature review. Journal of Testing and Evaluation, 1998, 26(2): 89-100.
[24] Bui-Quoc T. A simplified model for cumulative fatigue damage with interaction effect. In: Proceedings of the 1982 Joint Conference on Experimental Mechanics. Brookfield center CT, 1982, pp. 144-149.
[25] Cheng G X, Plumtree A. A fatigue damage accumulation model based on continuum damage mechanics and ductility exhaustion. International Journal of Fatigue, 1998, 20(7): 495-501.
[26] Bui-Quoc T. Cumulative damage with interaction effect due to fatigue under torsion loading. Experimental Mechanics, 1982, 22(5): 180-187.
[27]翟红军,姚卫星.化学纤维增强树脂基复合材料的疲劳剩余刚度研究进展.力学进展, 2002, 32(1): 80-88.
[28] Henry D L. A theory of fatigue damage accumulation in steel. Trans. ASME, 1955, 77: 913-918.
[29] Sandor B I. Fundamentals of cyclic stress and strain. Wisconsin: University of Wisconsin Press, 1972.
[30] Lefebvre D, Neale K W, Ellyin F. A criterion for low-cycle fatigue failure under biaxial states of stress. Journal of Engineering Materials and Technology, 1981, 103(1): 1-6.
[31] Tchankov D, Vesselinov K. Fatigue life prediction under random loading using total hysteresis energy. International Journal of Pressure Vessels and Piping, 1998, 75(13): 955-960.
[32] Tong X, Wang D. Investigation of cyclic hysteresis energy in fatigue failure process. International Journal of Fatigue, 1989, 11(5): 353-359.
[33] Koh S K. Fatigue damage evaluation of a high pressure tube steel using cyclic strain energy density. International Journal of Pressure Vessels and Piping, 2002, 79(12): 791-798.
[34] Varvani-Farahani A, Kodric T, Ghahramani A. A method of fatigue life prediction in notched and un-notched components. Journal of Materials Processing Technology, 2005, 169(1): 94-102.
[35] Chiou Y C, Yip M C. An energy-based damage parameter for the life prediction of AISI304 stainless steel subjected to mean strain. Journal of the Chinese Institute of Engineers, 2006, 29(3): 507-517.
[36] Lee K O, Hong S G, Lee S B. A new energy-based fatigue damage parameter in life prediction of high-temperature structural materials. Materials Science and Engineering: A, 2008, 496(1-2): 471-477.
[37] Golos K. A total strain energy density model of metal fatigue. Strength of materials, 1995, 27(1): 32-41.
[38] Ellyin F, Xia Z. A general fatigue theory and its application to out-of-phase cyclic loading. Journal of Engineering Materials and Technology, 1993, 115(4): 411-416.
[39] Xia Z, Kujawski D, Ellyin F. Effect of mean stress and ratcheting strain on fatigue life of steel. International Journal of Fatigue, 1996, 18(5): 335-341.
[40] Park J, Nelson D. Evaluation of an energy-based approach and a critical plane approach for predicting constant amplitude multiaxial fatigue life. International Journal of Fatigue, 2000, 22(1): 23-39.
[41] Knott J F. Fundamentals of fracture mechanics. London: Butterworths, UK, 1973.
[42] Izumi Y, Fine M, Mura T. Energy considerations in fatigue crack propagation. International Journal of Fracture, 1981, 17(1): 15-25.
[43] Mura T. Micromechanics of defects in solids. The Netherlands: Martinus Nijhoff, Dordrecht, 1987.
[44] Feltner C, Morrow J D. Microplastic strain hysteresis energy as a criterion for fatigue fracture. Journal of Basic Engineering, Transactions ASME, 1961, 83D: 15-22.
[45] Morrow J D. Cyclic plastic strain energy and fatigue of metals. In: Internal Friction Damping and Cyclic Plasticity, ASTM, STP 378, 1965, pp. 45-84.
[46] Fargione G, Geraci A, La Rosa G, et al. Rapid determination of the fatigue curve by the thermographic method. International Journal of Fatigue, 2002, 24(1): 11-19.
[47] Walther F, Eifler D. Short-time procedure for the determination of Woehler and fatigue Life curves using mechanical, thermal and electrical data. Journal of Solid Mechanics and Materials Engineering, 2008, 2(4): 507-518.
[48] Meneghetti G. Analysis of the fatigue strength of a stainless steel based on the energy dissipation. International Journal of Fatigue, 2007, 29(1): 81-94.
[49] Plekhov O, Palin-Luc T, Saintier N, et al. Fatigue crack initiation and growth in a 35CrMo4 steel investigated by infrared thermography. Fatigue & Fracture of Engineering Materials & Structures, 2005, 28(1-2): 169-178.
[50] Plekhov O, Naimark O. Theoretical and experimental study of energy dissipation in the course of strain localization in iron. Journal of Applied Mechanics and Technical Physics, 2009, 50(1): 127-136.
[51]陈凌,蒋家羚,范志超,等.低周疲劳寿命预测的能量模型探讨.金属学报, 2006, 42(2): 195-200.
[52] Basaran C, Yan C Y. A thermodynamic framework for damage mechanics of solder joints. Journal of Electronic Packaging, 1998, 120(4): 379-384.
[53] Basaran C, Tang H. Implementation of a thermodynamic framework for damage mechanics of solder interconnects in microelectronics packaging. International Journal of Damage Mechanics, 2002, 11(1): 87-108.
[54] Lemaitre J, Chaboche J L. Mechanics of solid materials. Cambridge: Cambridge University Press, UK, 1990.
[55] Naderi M, Amiri M, Khonsari M. On the thermodynamic entropy of fatigue fracture. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Science, 2010, 466(2114): 423-438.
[56]王坤茜,徐人平,林捷晖.考虑应力比的疲劳裂纹扩展概率模型.航空动力学报, 2009, 24(9): 2012-2018.
[57]赵永翔,杨冰,梁红琴,等.测定概率疲劳长裂纹扩展门槛值的新方法.应用数学和力学, 2005, 26(6): 701-706.
[58]杨冰,赵永翔,何朝明,等.考虑概率与置信度的疲劳裂纹扩展率模型及其参数测定方法.机械工程学报, 2004, 40(6): 183-187.
[59] Kachanov L M. Time of the rupture process under creep conditions. Isv. Akad. Nauk. SSR. Otd Tekh. Nauk, 1958, 8: 26-31.
[60] Chaboche J L, Lesne P M. A non-linear continuous fatigue damage model. Fatigue & Fractureof Engineering Materials & Structures, 1988, 11(1): 1-17.
[61]白曌宇,孟宪红,张行.确定材料概率疲劳曲线的损伤力学方法.北京航空航天大学学报, 2005, 31(9): 1027-1030.
[62] Zhao J, Zhang X. On the process zone of a quasi-static growing tensile crack with power-law elastic-plastic damage. International Journal of Fracture, 2001, 108(4): 383-395.
[63]易当祥,刘春和,封艳文,等.扭力轴三维裂纹扩展寿命仿真研究.应用力学学报, 2008, 25(3): 411-414.
[64]冯西桥,何树延.表面裂纹疲劳扩展的一种损伤力学方法.清华大学学报, 1997, 37(5): 78-82.
[65] Nikolaidis E, Ghiocel D M, Singhal S. Engineering design reliability handbook. New York: CRC Press, 2005.
[66] Natke H G, Ben-Haim Y. Uncertainty: models and measures. New York: John Wiley & Sons, 1998.
[67] Lopez I, Sarigul-Klijn N. A review of uncertainty in flight vehicle structural damage monitoring, diagnosis and control: challenges and opportunities. Progress in Aerospace Sciences, 2010, 46(7): 247-273.
[68]王旭亮.不确定性疲劳寿命预测方法研究: [博士学位论文].南京:南京航空航天大学航空宇航学院, 2009.
[69] Adamson J D. Probabilistic design system development experience. In: The 35 th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference. Hilton Head, SC, USA, 1994, pp. 1086-1094.
[70] Roth P G. Probabilistic rotor design system (PRDS)-gas turbine engine design. AFRL-PR-WP-TR-1999-2122, 1996.
[71]吴大观.关于新版综合高性能涡轮发动机技术计划—兼谈航空发动机研制中“基础技术”和“验证机”的重要作用.航空发动机, 2003, 29(2): 1-4.
[72] Beachkofski B K, Grandhi R V. Probabilistic system reliability for a turbine engine airfoil. In: Proceeding of ASME Turbo Expo 2004 Power for land, sea, and air, Vienna, Austria, GT2004-53381, 2004.
[73] Rusk D, Hoffman P. Developments in probability-based strain-life analysis. In: Fifth Joint NASA/FAA/DoD Aging Aircraft Conference, 2001.
[74] Shen M-H H. Reliability assessment of high cycle fatigue design of gas turbine blades using the probabilistic Goodman diagram. International Journal of Fatigue, 1999, 21(7): 699-708.
[75] Brown J M, Grandhi R V. Probabilistic high cycle fatigue assessment process for integrally bladed rotors. In: ASME Turbo Expo 2005: Power for Land, Sea, and Air (GT2005), Reno, Nevada, USA, 2005.
[76] Cavallini G, Lazzeri R. A probabilistic approach to fatigue risk assessment in aerospace components. Engineering Fracture Mechanics, 2007, 74(18): 2964-2970.
[77] Chan K S, Enright M P. A probabilistic micromechanical code for predicting fatigue life variability: Model development and application. Journal of Engineering for Gas Turbines and Power, 2006, 128(4): 889-895.
[78] Enright M P, Chan K S, Moody J P, et al. Probabilistic fretting fatigue assessment of aircraft engine disks. Journal of Engineering for Gas Turbines and Power, 2010, 132(7): 072502.
[79] Chan K S, Enright M P, Simmons H R, et al. Toward developing a probabilistic methodology for predicting high-cycle fretting fatigue in aero-engines. In: ASME Turbo Expo 2010: Power for Land, Sea, and Air (GT2010), Glasgow, UK, 2010, pp. 659-666.
[80] Jha S, Larsen J, Rosenberger A. Towards a physics-based description of fatigue variability behavior in probabilistic life-prediction. Engineering Fracture Mechanics, 2009, 76(5): 681-694.
[81] Rusk D, Hoppe W. Fatigue life prediction of corrosion-damaged high-strength steel using an equivalent stress riser (ESR) model: Part I: Test development and results. International Journal of Fatigue, 2009, 31(10): 1454-1463.
[82] Rusk D, Hoppe W, Braisted W, et al. Fatigue life prediction of corrosion-damaged high-strength steel using an equivalent stress riser (ESR) model. Part II: Model development and results. International Journal of Fatigue, 2009, 31(10): 1464-1475.
[83] Wang X Y, Rabiei M, Hurtado J, et al. A probabilistic-based airframe integrity management model. Reliability Engineering & System Safety, 2009, 94(5): 932-941.
[84] Brooks J W, Basoalto H C, Sahota R, et al. Probabilistic property prediction of aero-engine components for fatigue. In: ASME Turbo Expo 2010: Power for Land, Sea, and Air (GT2010), Glasgow, UK, 2010, pp. 639-648.
[85] Asayama T, Takasho H, Kato T. Probabilistic prediction of crack depth distributions observed in structures subjected to thermal fatigue. Journal of Pressure Vessel Technology, 2009, 131(1): 011402.
[86] Goode K, Moore J, Roylance B. Plant machinery working life prediction method utilizing reliability and condition-monitoring data. Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering, 2000, 214(2): 109-122.
[87] Wei Z G, Kurth R E, Forte T P. Probabilistic approach for fatigue life assessment based on S-N curve. In: ASME 2010 Pressure Vessels and Piping Division/K-PVP Conference (PVP2010), Bellevue, Washington, USA, 2010, pp. 677-685.
[88] Jesus A M P D, Ripoll M L R, Gon?alves N J, et al. Probabilistic fatigue assessment of a notched detail taking into account mean stress effects. In: ASME 2010 Pressure Vessels and Piping Division/K-PVP Conference (PVP2010), Bellevue, Washington, USA, 2010, pp. 51-60.
[89] Chookah M, Nuhi M, Modarres M. A probabilistic physics-of-failure model for prognostic health management of structures subject to pitting and corrosion-fatigue. Reliability Engineering & System Safety, 2011, 96(2): 1601-1610.
[90] Liu Y M, Mahadevan S. Probabilistic fatigue life prediction using an equivalent initial flaw size distribution. International Journal of Fatigue, 2009, 31(3): 476-487.
[91] Xiang Y, Liu Y M. Application of inverse first-order reliability method for probabilistic fatigue life prediction. Probabilistic engineering mechanics, 2011, 26(2): 148-156.
[92] Guan X, Jha R, Liu Y M. Model selection, updating, and averaging for probabilistic fatigue damage prognosis. Structural Safety, 2011, 33(3): 242-249.
[93] Mao H, Mahadevan S. Reliability analysis of creep-fatigue failure. International Journal of Fatigue, 2000, 22(9): 789-797.
[94] Zhang R X, Mahadevan S. Reliability-based reassessment of corrosion fatigue life. Structural Safety, 2001, 23(1): 77-91.
[95] Karlen K, Olsson M. A probabilistic model for the entire HCF domain based on equivalent stress-simulations and experiments. International Journal of Fatigue, 2012, 36(1): 9-17.
[96] Calvo S, Canales M, Gomez C, et al. Probabilistic formulation of the multiaxial fatigue damage of Liu. International Journal of Fatigue, 2011, 33(3): 460-465.
[97] Grell W, Laz P. Probabilistic fatigue life prediction using AFGROW and accounting for material variability. International Journal of Fatigue, 2010, 32(7): 1042-1049.
[98] Laz P, Craig B, Hillberry B. A probabilistic total fatigue life model incorporating material inhomogeneities, stress level and fracture mechanics. International Journal of Fatigue, 2001, 23(1): 119-127.
[99] Kocanda D, Jasztal M. Probabilistic predicting the fatigue crack growth under variable amplitude loading. International Journal of Fatigue, 2011, in press, doi:10.1016/j.ijfatigue.2011.03.011.
[100] Liao M. Probabilistic modeling of fatigue related microstructural parameters in aluminumalloys. Engineering Fracture Mechanics, 2009, 76(5): 668-680.
[101] Castillo E, Fernandez-Canteli A, Castillo C, et al. A new probabilistic model for crack propagation under fatigue loads and its connection with Wohler fields. International Journal of Fatigue, 2010, 32(4): 744-753.
[102] Bastidas-Arteaga E, Bressolette P, Chateauneuf A, et al. Probabilistic lifetime assessment of RC structures under coupled corrosion-fatigue deterioration processes. Structural Safety, 2009, 31(1): 84-96.
[103]苏清友,孔瑞莲,陈筱雄,等.航空涡喷涡扇发动机主要零部件定寿指南.北京:航空工业出版社, 2004.
[104]吕震宙,刘成立,徐友良.概率分析方法在粉末冶金涡轮盘疲劳蠕变寿命预测中的应用.航空发动机, 2005, 31(3): 27-29.
[105]王卫国.轮盘低循环疲劳寿命预测模型和试验评估方法研究: [博士学位论文].南京:南京航空航天大学能源与动力学院, 2006.
[106]王卫国,龚梦贤,温卫东.两种国产涡轮盘材料疲劳寿命概率分布规律初探.材料工程, 2006, (3): 44-51.
[107]胡殿印,王荣桥.涡轮盘疲劳-蠕变耦合失效模式的概率设计.大型飞机关键技术高层论坛暨中国航空学会2007年学术年会论文集, 2007, pp. 1-7.
[108]裴月,薛飞,王荣桥.涡轮盘低循环疲劳寿命可靠性研究.燃气涡轮试验与研究, 2007, 20(1): 39-43.
[109]钱文学,尹晓伟,谢里阳,等.轮盘疲劳可靠性分析的Monte-Carlo数字仿真.系统仿真学报, 2007, 19(2): 254-256.
[110]李锋.不确定参数下结构疲劳断裂可靠性若干问题的研究: [博士学位论文].长春:吉林大学机械科学与工程学院, 2008.
[111]陆山,高鹏.考虑应力松弛的涡轮盘蠕变-疲劳寿命可靠性分析方法.推进技术, 2009, 30(3): 352-354.
[112]陆山,张鸿,唐俊星,等.考虑尺寸效应的轮盘应力疲劳概率寿命分析方法.航空动力学报, 2011, 26(9): 2039-2043.
[113]高阳,白广忱,张瑛莉.涡轮盘多轴低循环疲劳寿命可靠性分析.航空学报, 2009, 30(9): 1678-1682.
[114]刘辉,白广忱.涡轮盘低循环疲劳两种可靠性分析方法的对比.装备制造技术, 2010, (2): 26-29.
[115]高阳,杨昌军,白广忱,等.涡轮盘低循环疲劳可靠性设计方法.航空发动机, 2011,37(1): 4-8.
[116]朱顺鹏,黄洪钟,凌丹,等.涡轮盘低周疲劳-蠕变寿命的可靠性研究.中国航空学会第五届航空发动机可靠性学术交流会,南宁,中国, 2009, pp. 252-260.
[117]朱顺鹏,黄洪钟,何俐萍,等.基于广义能量损伤参数的涡轮盘高温低周疲劳-概率寿命预测.中国航空学会第六届航空发动机可靠性学术交流会,张家界,中国, 2011, pp. 303-311.
[118]张义民,王鹏,杨周,等.低周疲劳失效的涡轮盘可靠性灵敏度设计.中国机械工程, 2010, 21(10): 1135-1139.
[119]张艳林,张义民,金雅娟,等.考虑T-stress的非正态随机参数疲劳裂纹扩展寿命的可靠性分析.计算力学学报, 2010, 27(6): 1006-1010.
[120]谢里阳,林文强.线性累积损伤的概率准则.机械强度, 1993, 15(3): 41-44.
[121]倪侃,高镇同.疲劳可靠性二维概率Miner准则.固体力学学报, 1996, 17(4): 365-371.
[122]赵少汴.概率疲劳设计方法与设计数据.机械设计, 2000, (4): 8-11.
[123]赵少汴,王忠保.抗疲劳设计―方法与数据.北京:机械工业出版社, 1997.
[124]熊峻江,武哲,高镇同.广义疲劳等寿命曲线与二维疲劳极限概率分布.应用数学和力学, 2002, 23(10): 1055-1060.
[125]邬华芝,郭海丁,高德平.疲劳破坏寿命的概率统计方法研究综述.强度与环境, 2002, 29(4): 38-44.
[126]杨继运.基于损伤力学的概率疲劳曲线获取方法.航天器环境工程, 2005, 22(4): 207-210.
[127]杨冰,赵永翔,梁红琴,等.基于Elber型方程的随机疲劳长裂纹扩展概率模型.工程力学, 2005, 22(5): 99-104.
[128]杨冰,赵永翔,张卫华.基于Forman方程的随机疲劳长裂纹扩展概率模型.交通运输工程学报, 2006, 6(1): 25-28.
[129]赵永翔,杨冰,张卫华.应变疲劳可靠性理论与方法的新进展.机械强度, 2005, 27(5): 604-611.
[130]卢延辉,王文阁,郑联珠.疲劳可靠性计算方法中迈纳理论与概率累加理论之间的关系.吉林大学学报(工学版), 2007, 37(2): 382-385.
[131]王磊,刘文珽.飞机结构疲劳关键部位损伤与可靠性评定技术.北京航空航天大学学报, 2008, 34(1): 84-87.
[132]谢里阳,王正.随机恒幅循环载荷疲劳可靠度异量纲干涉模型.机械工程学报, 2008, 44(1): 1-6.
[133]谢里阳.疲劳概率理论与方法评述.第十四届全国疲劳与断裂学术会议论文集, 2008, pp.89-93.
[134]刘克格,闫楚良.结构疲劳试验寿命数据分布类型对其使用寿命的影响.吉林大学学报(工学版) 2011, 41(2): 419-423.
[135]薛红军,张晓燕,张玉刚.多点失效时结构寿命可靠度的计算方法.机械强度, 2011, 33(3): 363-367.
[136]凌丹,何俐萍,许焕卫,等.基于威布尔分布的疲劳剩余寿命可靠性预测方法.机械设计, 2011, 28(7): 50-53.
[137] Madsen H O. Bayesian fatigue life prediction. In: Eddertz S, Lind N C, editors. Probabilistic methods in the mechanics of solids and structures. Stockholm: Proc IUTAM Symp, 1984, pp. 395-406.
[138] Edwards G, Pacheco L. A Bayesian method for establishing fatigue design curves. Structural Safety, 1984, 2(1): 27-38.
[139] Jiang X, Mahadevan S. Bayesian risk-based decision method for model validation under uncertainty. Reliability Engineering & System Safety, 2007, 92(6): 707-718.
[140] Sankararaman S, Ling Y, Mahadevan S. Uncertainty quantification and model validation of fatigue crack growth prediction. Engineering Fracture Mechanics, 2011, 78(7): 1487-1504.
[141] Guida M, Penta F. A Bayesian analysis of fatigue data. Structural Safety, 2010, 32(1): 64-76.
[142]刘建中,谢里阳,徐灏.疲劳寿命概率分布的模糊贝叶斯确定方法.机械设计, 1994, (2): 4-7.
[143]邹嵘,倪侃,张圣坤.用模糊Bayes方法确定疲劳寿命分布.中国海洋平台, 2001, 16(1): 4-8.
[144]陈勃,鲍蕊,张建宇,等.疲劳强度分布参数的贝叶斯分析.北京航空航天大学学报, 2003, 29(3): 233-236.
[145] Huang H Z, Zuo M J, Sun Z Q. Bayesian reliability analysis for fuzzy lifetime data. Fuzzy Sets and Systems, 2006, 157(12): 1674-1686.
[146]施剑玮,姚卫星.估计构件疲劳极限的Bayes极小样本方法.机械强度, 2007, 29(2): 334-337.
[147] Bowman M, Nordmark G, Yao J. Fuzzy logic approach in metals fatigue. International Journal of Approximate Reasoning, 1987, 1(2): 197-219.
[148] Bardossy A, Bogardi I. Fuzzy fatigue life prediction. Structural Safety, 1989, 6(1): 25-38.
[149] Muc A, Kdziora P. A fuzzy set analysis for a fracture and fatigue damage response of composite materials. Composite Structures, 2001, 54(2-3): 283-287.
[150] Muc A. A fuzzy set approach to interlaminar cracks simulation problems. International Journal of Fatigue, 2002, 24(2-4): 419-427.
[151] Akpan U O, Rushton P A, Koko T S. Fuzzy probabilistic assessment of the impact of corrosion on fatigue of aircraft structures. Paper No. AIAA-2002-1640, 2002.
[152] Akpan U O, Rushton P A, Koko T S. Development of a fuzzy probabilistic methodology for multiple-site fatigue damage. Journal of aircraft, 2004, 41(3): 633-640.
[153] Rao S S, Qing L. Fuzzy approach to the mechanics of fiber-reinforced composite materials. AIAA journal, 2004, 42(1): 159-167.
[154] Sawyer J P, Rao S S. Strength-based reliability and fracture assessment of fuzzy mechanical and structural systems. AIAA journal, 1999, 37(1): 84-92.
[155] Majidian A, Saidi M. Comparison of fuzzy logic and neural network in life prediction of boiler tubes. International Journal of Fatigue, 2007, 29(3): 489-498.
[156]黄洪钟,刘忠贺,孙占全,等.影响疲劳强度可靠性的模糊因素分析.电子产品可靠性与环境试验, 2002, (4): 12-14.
[157]贾星兰,刘文珽.谱载下基于模糊Miner法则的疲劳寿命估算.北京航空航天大学学报, 2003, 29(3): 218-220.
[158]陈胜军.模糊疲劳寿命预测理论的建立与验证.机械设计, 2003, 20(12): 42-44.
[159]刘小云,丛方媛,王小陈.模糊可靠性疲劳寿命的分析与计算.长安大学学报(自然科学版), 2007, 27(1): 99-102.
[160]刘小云.疲劳损伤的模糊性研究.长安大学学报(自然科学版), 2005, 25(4): 107-110.
[161]王旭亮,聂宏.基于模糊理论的疲劳寿命估算方法.中国机械工程, 2008, 19(17): 2095-2097.
[162]王旭亮,聂宏.疲劳寿命估算中的模糊性研究.机械科学与技术, 2008, 27(9): 1139-1141.
[163]刘克格,阎楚良,张书明.模糊数学在疲劳寿命估算中的应用.航空学报, 2006, 27(2): 227-231.
[164]冯刚,孙立德,黄洪钟,等.疲劳寿命的模糊可靠度计算方法.中国机械工程, 2003, 14(19): 1699-1701.
[165]黄洪钟,田志刚.基于广义模糊随机强度的模糊可靠性计算理论.机械工程学报, 2002, 38(8): 50-53.
[166]黄洪钟.模糊机械科学与技术─21世纪机械科学的重要发展方向.机械工程学报, 1996, 32(3): 1-8.
[167] Tan X M, Chen Y L, Jin P. Corrosion fatigue life prediction of aircraft structure based on fuzzyreliability approach. Chinese Journal of Aeronautics, 2005, 18(4): 346-351.
[168]李锋,孟广伟,沙丽荣.考虑模糊失效准则的结构疲劳寿命可靠性.航空学报, 2009, 30(12): 2316-2321.
[169]卢明章,赵海军,崔明芳.模糊疲劳寿命均值及其隶属函数研究.机械强度, 2010, 32(4): 639-645.
[170]蒋文涛,薛彩军.飞机起落架结构模糊疲劳可靠性分析.飞机设计, 2011, 31(1): 17-20.
[171]邱志平,王晓军.结构疲劳寿命的区间估计.力学学报, 2005, 37(5): 653-657.
[172]邱志平,王晓军,马智博.结构疲劳寿命估计的集合理论模型.固体力学学报, 2006, 27(1): 91-97.
[173] Qiu Z P, Wang J. Reliability study of fracture mechanics based non-probabilistic interval analysis model. Fatigue & Fracture of Engineering Materials & Structures, 2010, 33(9): 539-548.
[174] Pierce S G, Worden K, Bezazi A. Uncertainty analysis of a neural network used for fatigue lifetime prediction. Mechanical Systems and Signal Processing, 2008, 22(6): 1395-1411.
[175] Huang H Z, An Z W. A discrete stress-strength interference model with stress dependent strength. IEEE Transactions on Reliability, 2008, 58(1): 118-122.
[176]徐灏.概率疲劳.沈阳:东北大学出版社, 1994, pp. 303-308.
[177]高镇同,熊峻江.疲劳可靠性.北京:北京航空航天大学出版社, 2000.
[178] Knowles I. Is it time for a new approach? IEEE Transactions on Reliability, 1993, 42(1): 2-3.
[179] Matic Z, Sruk V. The Physics-of-Failure approach in reliability engineering. In: Proceeding of 30th International Conference on Information Technology Interfaces, Dubrovnik, 2008, pp. 745-750.
[180]祝耀昌.可靠性故障物理技术及其应用.装备环境工程, 2005, 2(2): 28-33.
[181] Pecht M, Dasgupta A. Physics-of-failure: an approach to reliable product development. Journal of the Institute of Environmental Sciences, 1995, 38(5): 30-34.
[182] Pecht M. Why the traditional reliability prediction models do not work-is there an alternative? Electronics Cooling, 1996, 2: 10-13.
[183] Pecht M, Dasgupta A, Barker D, et al. The reliability physics approach to failure prediction modelling. Quality and Reliability Engineering International, 1990, 6(4): 267-273.
[184] Dasgupta A, Pecht M. Material failure mechanisms and damage models. IEEE Transactions on Reliability, 1991, 40(5): 531-536.
[185] Lall P, Pecht M. An integrated physics-of-failure approach to reliability assessment. Advancesin Electronic Packaging, ASME EEP-Vol.4-I, 1993: 509-524.
[186] Modarres M, Kaminskiy M, Krivtsov V. Reliability engineering and risk analysis: a practical guide, 2nd edition. New York: CRC Press, 2009.
[187] Upadhyayula K, Dasgupta A. Physics-of-failure guidelines for accelerated qualification of electronic systems. Quality and Reliability Engineering International, 1998, 14(6): 433-447.
[188]王云,邵将,曾晨晖,等.航空电子产品基于故障物理的可靠性工程技术.第四届中国航空学会青年科技论坛文集, 2010.
[189] Snook I, Marshall J, Newman R. Physics of failure as an integrated part of design for reliability. In: Proceedings of the Annual Symposium on Reliability and Maintainability, 2003, pp. 46-54.
[190] McLeish J G. Enhancing MIL-HDBK-217 reliability predictions with physics of failure methods. In: Proceedings of the Annual Symposium on Reliability and Maintainability, 2010, pp. 1-6.
[191] Bielen J, Gommans J J, Theunis F. Prediction of high cycle fatigue in aluminum bond wires: A physics of failure approach combining experiments and multi-physics simulations. In: 7th International Conference of Thermal, Mechanical and Multi-physics Simulations and Experiments in Micro-Electronics and Micro-Systems, 2006.
[192] Gu J, Pecht M. Prognostics and health management using physics-of-failure. In: Proceedings of 54th Annual Reliability and Maintainability Symposium (RAMS), Las Vegas, NV, 2008, pp. 481-487.
[193] Oh H, Azarian M H, Pecht M, et al. Physics-of-failure approach for fan PHM in electronics applications. In: Proceeding of Prognostics and Health Management Conference, 2010, pp. 1-6.
[194] Fan J, Yung K C, Pecht M. Physics-of-failure based prognostics and health management for high power white light-emitting diode lighting. IEEE Transactions on Device and Materials Reliability, 2011, 11(3): 407-416.
[195] Hall P, Strutt J. Probabilistic physics-of-failure models for component reliabilities using Monte Carlo simulation and Weibull analysis: a parametric study. Reliability Engineering & System Safety, 2003, 80(3): 233-242.
[196] Drake G S. Engineering design analysis (physics of failure). In: Proceedings of the Annual Symposium on Reliability and Maintainability, 2010.
[197] Chamberlain S S. Development of a physics of failure model and quantitative assessment of the fire fatality risk of compressed natural gas bus cylinders: [PhD. Dissertation]. University ofMaryland, Department of Mechanical Engineering, College Park, USA, 2004.
[198] Azarkhail M. Agent autonomy approach to physics-based reliability modeling of structures and mechanical systems: [PhD. Dissertation]. University of Maryland, Department of Mechanical Engineering, College Park, USA, 2007.
[199] Azarkhail M, Modarres M. A novel Bayesian framework for uncertainty management in physics-based reliability models. In: ASME International Mechanical Engineering Congress and Exposition, Seattle, Washington, 2007.
[200] Alseyabi M C. Structuring a probabilistic model for reliability evaluation of piping subject to corrosion-fatigue degradation: [PhD. Dissertation]. University of Maryland, Department of Mechanical Engineering, College Park, USA, 2009.
[201] Tryon R G, Dey A, Krishnan G. Microstructural-based physics of failure models to predict fatigue reliability. Journal of the IEST, 2007, 50(2): 73-84.
[202] Goswami T. Development of generic creep-fatigue life prediction models. Materials & Design, 2004, 25(4): 277-288.
[203] Halford G R. Evolution of creep-fatigue life prediction models. In: Creep-fatigue interaction at high temperature (Eds Haritos G K and Ochoa O O), ASME, AD, Philadelphia, 1991, 21: 43-57.
[204] Taira S. Lifetime of structures subjected to varying load and temperature. In: Creep in Structures, N. J. Hoff (ed.), Springer-Verlag 1962, pp. 96-124.
[205] Robinson E. Effect of temperature variation on the long-time rupture strength of steels. Journal of Applied Mechanics, 1952, 74(5): 777-780.
[206] Lagneborg R, Attermo R. The effect of combined low-cycle fatigue and creep on the life of austenitic stainless steels. Metallurgical and Materials Transactions B, 1971, 2(7): 1821-1827.
[207] Tomkins B. Inelastic analysis and life prediction in elevated temperature design. In: Pressure Vessels and Piping Conference, 1982, 59: 239-242.
[208] Chen G L. Fatigue-creep interaction fracture maps and life prediction under combined fatigue-creep stress cycling. Chinese Journal of Metal Science & Technology, 1990, 6(6): 391-414.
[209] ASME. ASME Boiler and Pressure Vessel Code, Section III, Code Case N-47, 1995.
[210] Tien J K, Nair S V, Nardone V C. Creep-Fatigue Interaction in Structural Alloys. In: Flow and Fracture at Elevated Temperatures, Edited by Raj R, Carnes Publication Services, Inc., Philadelphia, USA, 1983, pp. 179-213.
[211] Ellison E G, Al-Zamily A. Fracture and life prediction under thermal-mechanical strain cycling.Fatigue & Fracture of Engineering Materials & Structures, 1994, 17(1): 53-67.
[212] Bicego V, Fossati C, Ragazzoni S. Low-cycle fatigue characterization of a Hp-Ip steam turbine rotor. In: Low-cycle fatigue, ASTM STP 942, Soloman H D, Halford G R, Kaisand L R, and Leis B N, Eds., American Society for Testing and Materials, Philadelphia, 1988, pp. 1237-1260.
[213]张国栋,苏彬.高温低周应变疲劳的三参数幂函数能量方法研究.航空学报, 2007, 28(2): 504-507.
[214] Pineau A, Antolovich S D. High temperature fatigue of nickel-base superalloys-A review with special emphasis on deformation modes and oxidation. Engineering Failure Analysis, 2009, 16(8): 2668-2697.
[215] Smith K N, Watson P, Topper T H. A stress-strain function for the fatigue of metals. Journal of Materials, 1970, 5(4): 767-778.
[216] Koh S K, Stephens R I. Mean stress effects on low cycle fatigue for a high strength steel. Fatigue & Fracture of Engineering Materials & Structures, 1991, 14(4): 413-428.
[217]傅惠民.ε? N曲线三参数幂函数公式.航空学报, 1993, 14(3): 173-176.
[218]陈立杰,冮铁强,谢里阳.应用幂变换法构造低周疲劳寿命预测的幂指函数模型.航空学报, 2006, 27(2): 267-271.
[219]张国栋,苏彬,王泓,等.弹性模量对低周疲劳性能参数的影响.航空动力学报, 2005, 20(5): 768-771.
[220] Coffin L F. Fatigue at high temperature-prediction and interpretation. In: Proceedings of Institute of Mechanical Engineers, 1974, 188(9): 109-127.
[221] Viswanathan R. Damage mechanisms and life assessment of high-temperature components. ASM International, 1995.
[222] Coffin L F. The concept of frequency separation in life prediction for time-dependent fatigue. In: 1976 ASME-MPC Symposium on Creep-Fatigue Interaction, MPC-3, American Society for Mechanical Engineers, New York, 1976, pp. 349-364.
[223] Bernstein H. An evaluation of four creep-fatigue models for a nickel-base superalloy. (Edited Claude Amzallag, Leis, Rabbe) Low-Cycle Fatigue and Life Prediction, STP 770, 1982, pp. 105-134.
[224]陈学东,范志超,陈凌,等.三种疲劳蠕变交互作用寿命预测模型的比较及其应用.机械工程学报, 2007, 43(1): 62-68.
[225] Del Puglia A, Manfredi E. High-temperature low-cycle fatigue damage, Creep of Engineering Materials and Structures, edited by Bernasconi G and Piatti G, Applied Science Publishers LTD,London, 1979, pp. 229-265.
[226] Ostergren W J. A damage foundation hold time and frequency effects in elevated temperature low cycle fatigue. Journal of Testing and Evaluation, 1967, 4: 327-339.
[227] Ostergren W J. Correlation of hold time effects in elevated temperature low cycle fatigue using a frequency modified damage function. In: ASME-MPC Symposium on creep-fatigue interaction, 1976, pp. 179-202.
[228] Ellison E G. A review of the interaction of creep and fatigue. Journal of Mechanical Engineering Science, 1969, 11(3): 318-339.
[229] Goswami T. Low cycle fatigue life prediction-a new model. International Journal of Fatigue, 1997, 19(2): 109-115.
[230] Goswami T. Creep-fatigue life prediction: a ductility model. High Temperature Materials and Processes, 1995, 14(2): 101-114.
[231] Goswami T. New creep-fatigue life prediction model. High Temperature Materials and Processes, 1996, 15(1-2): 91-96.
[232]范志超,陈学东,陈凌,等.基于延性耗竭理论的疲劳蠕变寿命预测方法.金属学报, 2006, 42(4): 415-420.
[233] Zhu S P, Huang H Z, Li H Q, et al. A new ductility exhaustion model for high temperature low cycle fatigue life prediction of turbine disk alloys. International Journal of Turbo and Jet Engines, 2011, 28(2): 119-131.
[234] Manson S S, Halford G R, Hirschberg M H. Creep-fatigue analysis by strain-range partitioning. In: Proceedings of symposium on design for elevated temperature environment, ASME, New York, 1971, pp. 12-28.
[235] Nitta A, Kuwabara K, Kitamura T. The characteristics of thermal-mechanical fatigue strength in superalloys for gas turbine. In: Proceedings of 1983 Tokyo International Gas Turbine Congress, 83-TOKYO-IGTC-99, Tokyo, Japan, 1983, pp. 765-772.
[236] Kachanov L M. Introduction to continuum damage mechanics. Dordrecht: Martinus Nijhoof Publishers, 1986.
[237] Chrzanowski M. Use of the damage concept in describing creep-fatigue interaction under prescribed stress. International Journal of Mechanical Sciences, 1976, 18(2): 69-73.
[238] Modarres M. Risk analysis in engineering: techniques, tools, and trends. New York: CRC Press, 2006.
[239]柳恒超,许燕,王力.结构方程模型应用中模型选择的原理和方法.心理学探新, 2007,27(101): 75-78.
[240] Burnham K P, Anderson D R. Model selection and multimodel inference: a practical information-theoretic approach. New York: Springer Verlag, 2002.
[241] Akaike H. Information theory as an extension of the maximum likelihood principle. In: Petrov B N, and Csaki F, (eds.) Second International Symposium on Information Theory. Akademiai Kiado, Budapest, 1973, pp. 267-281.
[242] Akaike H. A new look at the statistical model identi cation. IEEE Transactions on Automatic Control, 1974, 19: 716-723.
[243] Akaike H. Information measures and model selection. International Statistical Institute, 1983, 50(1): 277-291.
[244] Schwarz G. Estimating the dimension of a model. The Annals of Statistics, 1978, 6(2): 461-464.
[245]袁熙,李舜酩.疲劳寿命预测方法的研究现状与发展.航空制造技术, 2005, 12: 80-85.
[246]卢曦,郑松林.考虑小载荷强化的汽车构件疲劳累积损伤试验研究.中国机械工程, 2007, 18(8): 994-997.
[247]郑松林.低幅载荷对汽车前轴疲劳寿命影响的试验研究.机械强度, 2002, 24(4): 547-549.
[248]吴志学,吕文阁,徐灏.疲劳极限下损伤及"锻炼"效应.东北大学学报, 1996, 17(3): 338-341.
[249] Ishihara S, Mcevily A. A coaxing effect in the small fatigue crack growth regime. Scripta Materialia, 1999, 42(5): 617-622.
[250] Nicholas T. Step loading for very high cycle fatigue. Fatigue & Fracture of Engineering Materials & Structures, 2002, 25(8-9): 861-869.
[251] Pereira H, De Jesus A, Fernandes A, et al. Analysis of fatigue damage under block loading in a low carbon steel. Strain, 2008, 44(6): 429-439.
[252] Lu X, Zheng S L. Strengthening and damaging under low-amplitude loads below the fatigue limit. International Journal of Fatigue, 2009, 31(2): 341-345.
[253] Dombi J. Membership function as an evaluation. Fuzzy Sets and Systems, 1990, 35(1): 1-21.
[254]黄洪钟.机械设计模糊优化原理及应用.北京:科学出版社, 1997, pp. 51-64.
[255]董玉革.机械模糊可靠性设计.北京:机械工业出版社, 2000, pp. 20-29.
[256]郦明,奥脱?布克斯鲍姆.结构抗疲劳设计.北京:机械工业出版社, 1987, pp. 224-228.
[257] Nakagawa T. On the strength deteriorating process in reliability engineering. Transactions of the Japan Society of Mechanical Engineers A, 1983, 49(441): 540-546.
[258] Nakagawa T, Ikai Y. Strain aging and the fatigue limit in carbon steel. Fatigue & Fracture of Engineering Materials & Structures, 1979, 2(1): 13-21.
[259] Sinclair G. An investigation of the coaxing effect in fatigue of metals. Proc. ASTM, 1952, 52: 743-758.
[260]陈胜军.基于隶属函数的疲劳寿命预测模型.南京师范大学学报(工程技术版), 2007, 7(2): 6-9.
[261] Shang D G, Yao W X. A nonlinear damage cumulative model for uniaxial fatigue. International Journal of Fatigue, 1999, 21(2): 187-194.
[262]尚德广,姚卫星.单轴非线性连续疲劳损伤累积模型的研究.航空学报, 1998, 19(6): 647-656.
[263]姚卫星,郭盛杰. LC4CS铝合金的超高周疲劳寿命分布.金属学报, 2007, 43(4): 399-403.
[264]张俊善.材料的高温变形与断裂.北京:科学出版社, 2007, pp. 425-430.
[265]尹泽勇.叶片轮盘及主轴强度分析-航空发动机设计手册第18册.北京:航空工业出版社, 2007, pp. 807-853.
[266] Zhu S P, Huang H Z. A generalized frequency separation-strain energy damage function model for low cycle fatigue-creep life prediction. Fatigue & Fracture of Engineering Materials & Structures, 2010, 33(4): 227-237.
[267] Fan Z C, Chen X D, Chen L, et al. Fatigue-creep behavior of 1.25Cr0.5Mo steel at high temperature and its life prediction. International Journal of Fatigue, 2007, 29(6): 1174-1183.
[268] Chen L, Jiang J L, Fan Z C, et al. A new model for life prediction of fatigue-creep interaction. International Journal of Fatigue, 2007, 29(4): 615-619.
[269]中华人民共和国国家标准. GB/T 15248-94,金属材料轴向等幅低循环疲劳试验方法.北京:中国标准出版社, 1995.
[270] Ye D Y, Wang Z L. A new approach to low-cycle fatigue damage based on exhaustion of static toughness and dissipation of cyclic plastic strain energy during fatigue. International Journal of Fatigue, 2001, 23(8): 679-687.
[271]杨显杰,罗艳,高庆,等.循环软化45碳钢和循环硬化304不锈钢的棘轮行为实验研究.固体力学学报, 2005, 26(2): 125-131.
[272] Sadananda K, Sarkar S, Kujawski D, et al. A two-parameter analysis of S-N fatigue life usingΔσandσmax. International Journal of Fatigue, 2009, 31(11-12): 1648-1659.
[273] Zhang R X, Mahadevan S. Model uncertainty and Bayesian updating in reliability-based inspection. Structural Safety, 2000, 22(2): 145-160.
[274] Nelson W, McCool J, Meeker W. Applied life data analysis. New York: John Wiley & Sons, 1982.
[275] Ontiveros V, Cartillier A, Modarres M. An integrated methodology for assessing fire simulation code uncertainty. Nuclear Science and Engineering, 2010, 166(3): 179-201.
[276] Azarkhail M, Ontiveros V, Modarres M. A Bayesian framework for model uncertainty considerations in fire simulation codes. In: 17th International Conference On Nuclear Engineering, Brussels, Belgium, 2009.
[277] Shirazi C H. Data-informed calibration and aggregation of expert opinion in a Bayesian framework: [PhD. Dissertation]. University of Maryland, Department of Mechanical Engineering, College Park, 2009.
[278] Zhang Z, Qiao Y, Sun Q, et al. Theoretical estimation to the cyclic strength coefficient and the cyclic strain-hardening exponent for metallic materials: preliminary study. Journal of Materials Engineering and Performance, 2009, 18(3): 245-254.
[279] Lunn D, Thomas A, Best N, et al. WinBUGS-a Bayesian modelling framework: concepts, structure, and extensibility. Statistics and Computing, 2000, 10(4): 325-337.
[280]唐俊星,陆山.某涡轮盘低循环疲劳概率寿命数值模拟.航空动力学报, 2006, 21(4): 706-710.
[2] Schütz W. A history of fatigue. Engineering Fracture Mechanics, 1996, 54(2): 263-300.
[3] Schijve J. Fatigue of structures and materials in the 20th century and the state of the art. International Journal of Fatigue, 2003, 25(8): 679-702.
[4] ASTM E206-72. ASTM American National Standard, ANSI/ASTM, E206-72, 1979.
[5]李舜酩.机械疲劳与可靠性设计.北京:科学出版社, 2006, pp. 78-90.
[6]张小丽,陈雪峰,李兵,等.机械重大装备寿命预测综述.机械工程学报, 2011, 47(11): 100-116.
[7]姚卫星.结构疲劳寿命分析.北京:国防工业出版社, 2003.
[8]杨晓华,姚卫星,段成美.确定性疲劳累积损伤理论进展.中国工程科学, 2003, 5(4): 81-87.
[9] Cui W. A state-of-the-art review on fatigue life prediction methods for metal structures. Journal of Marine Science and Technology, 2002, 7(1): 43-56.
[10] Chaboche J. Continuum damage mechanics: Part II-damage growth, crack initiation, and crack growth. Journal of Applied Mechanics, 1988, 55(1): 65-72.
[11] Kwofie S. An exponential stress function for predicting fatigue strength and life due to mean stresses. International Journal of Fatigue, 2001, 23(9): 829-836.
[12] Manson S S, Hirschberg M H. Fatigue: an interdisciplinary approach. Syracuse: Syracuse University Press, 1964.
[13] Ince A, Glinka G. A modification of Morrow and Smith-Watson-Topper mean stress correction models. Fatigue & Fracture of Engineering Materials & Structures, 2011, 34(11): 854-867.
[14] Li J, Liu J, Sun Q, et al. A modification of Smith-Watson-Topper damage parameter for fatigue life prediction under non-proportional loading. Fatigue & Fracture of Engineering Materials & Structures, 2011, in press, doi: 10.1111/j.1460-2695.2011.01620.x.
[15] Miner M A. Cumulative damage in fatigue. Journal of Applied Mechanics, 1945, 12(3): A159-164.
[16] Grover H J. An observation concerning the cycle ratio in cumulative damage. Fatigue in Aircraft Structures, STP-274, American Society for Testing and Materials, Philadelphia, 1960,pp. 120-124.
[17] Manson S S, Freche J C, Ensign C R. Application of a double linear damage rule to cumulative fatigue. In: Fatigue crack propagation, ASTM, STP 415, 1967, pp. 384-412.
[18]朱顺鹏,黄洪钟,谢里阳.考虑小载荷强化的模糊疲劳寿命预测理论.航空学报, 2009, 30(6): 1048-1052.
[19] Zhu S P, Huang H Z, Wang Z L. Fatigue life estimation considering damaging and strengthening of low amplitude loads under different load sequences using fuzzy sets approach. International Journal of Damage Mechanics, 2011, 20(6): 876-899.
[20]黄洪钟,朱顺鹏,汪忠来,等.基于剩余强度衰减退化的非线性累积损伤准则及其可靠性定寿.应用基础与工程科学学报, 2011, 19(2): 323-334.
[21]朱顺鹏,黄洪钟,谢里阳.基于二元疲劳失效判据的非线性疲劳损伤累积模型及其强度退化研究.中国机械工程, 2008, 19(22): 2753-2761.
[22] Fatemi A, Yang L. Cumulative fatigue damage and life prediction theories: a survey of the state of the art for homogeneous materials. International Journal of Fatigue, 1998, 20(1): 9-34.
[23] Yang L, Fatemi A. Cumulative fatigue damage mechanisms and quantifying parameters: a literature review. Journal of Testing and Evaluation, 1998, 26(2): 89-100.
[24] Bui-Quoc T. A simplified model for cumulative fatigue damage with interaction effect. In: Proceedings of the 1982 Joint Conference on Experimental Mechanics. Brookfield center CT, 1982, pp. 144-149.
[25] Cheng G X, Plumtree A. A fatigue damage accumulation model based on continuum damage mechanics and ductility exhaustion. International Journal of Fatigue, 1998, 20(7): 495-501.
[26] Bui-Quoc T. Cumulative damage with interaction effect due to fatigue under torsion loading. Experimental Mechanics, 1982, 22(5): 180-187.
[27]翟红军,姚卫星.化学纤维增强树脂基复合材料的疲劳剩余刚度研究进展.力学进展, 2002, 32(1): 80-88.
[28] Henry D L. A theory of fatigue damage accumulation in steel. Trans. ASME, 1955, 77: 913-918.
[29] Sandor B I. Fundamentals of cyclic stress and strain. Wisconsin: University of Wisconsin Press, 1972.
[30] Lefebvre D, Neale K W, Ellyin F. A criterion for low-cycle fatigue failure under biaxial states of stress. Journal of Engineering Materials and Technology, 1981, 103(1): 1-6.
[31] Tchankov D, Vesselinov K. Fatigue life prediction under random loading using total hysteresis energy. International Journal of Pressure Vessels and Piping, 1998, 75(13): 955-960.
[32] Tong X, Wang D. Investigation of cyclic hysteresis energy in fatigue failure process. International Journal of Fatigue, 1989, 11(5): 353-359.
[33] Koh S K. Fatigue damage evaluation of a high pressure tube steel using cyclic strain energy density. International Journal of Pressure Vessels and Piping, 2002, 79(12): 791-798.
[34] Varvani-Farahani A, Kodric T, Ghahramani A. A method of fatigue life prediction in notched and un-notched components. Journal of Materials Processing Technology, 2005, 169(1): 94-102.
[35] Chiou Y C, Yip M C. An energy-based damage parameter for the life prediction of AISI304 stainless steel subjected to mean strain. Journal of the Chinese Institute of Engineers, 2006, 29(3): 507-517.
[36] Lee K O, Hong S G, Lee S B. A new energy-based fatigue damage parameter in life prediction of high-temperature structural materials. Materials Science and Engineering: A, 2008, 496(1-2): 471-477.
[37] Golos K. A total strain energy density model of metal fatigue. Strength of materials, 1995, 27(1): 32-41.
[38] Ellyin F, Xia Z. A general fatigue theory and its application to out-of-phase cyclic loading. Journal of Engineering Materials and Technology, 1993, 115(4): 411-416.
[39] Xia Z, Kujawski D, Ellyin F. Effect of mean stress and ratcheting strain on fatigue life of steel. International Journal of Fatigue, 1996, 18(5): 335-341.
[40] Park J, Nelson D. Evaluation of an energy-based approach and a critical plane approach for predicting constant amplitude multiaxial fatigue life. International Journal of Fatigue, 2000, 22(1): 23-39.
[41] Knott J F. Fundamentals of fracture mechanics. London: Butterworths, UK, 1973.
[42] Izumi Y, Fine M, Mura T. Energy considerations in fatigue crack propagation. International Journal of Fracture, 1981, 17(1): 15-25.
[43] Mura T. Micromechanics of defects in solids. The Netherlands: Martinus Nijhoff, Dordrecht, 1987.
[44] Feltner C, Morrow J D. Microplastic strain hysteresis energy as a criterion for fatigue fracture. Journal of Basic Engineering, Transactions ASME, 1961, 83D: 15-22.
[45] Morrow J D. Cyclic plastic strain energy and fatigue of metals. In: Internal Friction Damping and Cyclic Plasticity, ASTM, STP 378, 1965, pp. 45-84.
[46] Fargione G, Geraci A, La Rosa G, et al. Rapid determination of the fatigue curve by the thermographic method. International Journal of Fatigue, 2002, 24(1): 11-19.
[47] Walther F, Eifler D. Short-time procedure for the determination of Woehler and fatigue Life curves using mechanical, thermal and electrical data. Journal of Solid Mechanics and Materials Engineering, 2008, 2(4): 507-518.
[48] Meneghetti G. Analysis of the fatigue strength of a stainless steel based on the energy dissipation. International Journal of Fatigue, 2007, 29(1): 81-94.
[49] Plekhov O, Palin-Luc T, Saintier N, et al. Fatigue crack initiation and growth in a 35CrMo4 steel investigated by infrared thermography. Fatigue & Fracture of Engineering Materials & Structures, 2005, 28(1-2): 169-178.
[50] Plekhov O, Naimark O. Theoretical and experimental study of energy dissipation in the course of strain localization in iron. Journal of Applied Mechanics and Technical Physics, 2009, 50(1): 127-136.
[51]陈凌,蒋家羚,范志超,等.低周疲劳寿命预测的能量模型探讨.金属学报, 2006, 42(2): 195-200.
[52] Basaran C, Yan C Y. A thermodynamic framework for damage mechanics of solder joints. Journal of Electronic Packaging, 1998, 120(4): 379-384.
[53] Basaran C, Tang H. Implementation of a thermodynamic framework for damage mechanics of solder interconnects in microelectronics packaging. International Journal of Damage Mechanics, 2002, 11(1): 87-108.
[54] Lemaitre J, Chaboche J L. Mechanics of solid materials. Cambridge: Cambridge University Press, UK, 1990.
[55] Naderi M, Amiri M, Khonsari M. On the thermodynamic entropy of fatigue fracture. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Science, 2010, 466(2114): 423-438.
[56]王坤茜,徐人平,林捷晖.考虑应力比的疲劳裂纹扩展概率模型.航空动力学报, 2009, 24(9): 2012-2018.
[57]赵永翔,杨冰,梁红琴,等.测定概率疲劳长裂纹扩展门槛值的新方法.应用数学和力学, 2005, 26(6): 701-706.
[58]杨冰,赵永翔,何朝明,等.考虑概率与置信度的疲劳裂纹扩展率模型及其参数测定方法.机械工程学报, 2004, 40(6): 183-187.
[59] Kachanov L M. Time of the rupture process under creep conditions. Isv. Akad. Nauk. SSR. Otd Tekh. Nauk, 1958, 8: 26-31.
[60] Chaboche J L, Lesne P M. A non-linear continuous fatigue damage model. Fatigue & Fractureof Engineering Materials & Structures, 1988, 11(1): 1-17.
[61]白曌宇,孟宪红,张行.确定材料概率疲劳曲线的损伤力学方法.北京航空航天大学学报, 2005, 31(9): 1027-1030.
[62] Zhao J, Zhang X. On the process zone of a quasi-static growing tensile crack with power-law elastic-plastic damage. International Journal of Fracture, 2001, 108(4): 383-395.
[63]易当祥,刘春和,封艳文,等.扭力轴三维裂纹扩展寿命仿真研究.应用力学学报, 2008, 25(3): 411-414.
[64]冯西桥,何树延.表面裂纹疲劳扩展的一种损伤力学方法.清华大学学报, 1997, 37(5): 78-82.
[65] Nikolaidis E, Ghiocel D M, Singhal S. Engineering design reliability handbook. New York: CRC Press, 2005.
[66] Natke H G, Ben-Haim Y. Uncertainty: models and measures. New York: John Wiley & Sons, 1998.
[67] Lopez I, Sarigul-Klijn N. A review of uncertainty in flight vehicle structural damage monitoring, diagnosis and control: challenges and opportunities. Progress in Aerospace Sciences, 2010, 46(7): 247-273.
[68]王旭亮.不确定性疲劳寿命预测方法研究: [博士学位论文].南京:南京航空航天大学航空宇航学院, 2009.
[69] Adamson J D. Probabilistic design system development experience. In: The 35 th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference. Hilton Head, SC, USA, 1994, pp. 1086-1094.
[70] Roth P G. Probabilistic rotor design system (PRDS)-gas turbine engine design. AFRL-PR-WP-TR-1999-2122, 1996.
[71]吴大观.关于新版综合高性能涡轮发动机技术计划—兼谈航空发动机研制中“基础技术”和“验证机”的重要作用.航空发动机, 2003, 29(2): 1-4.
[72] Beachkofski B K, Grandhi R V. Probabilistic system reliability for a turbine engine airfoil. In: Proceeding of ASME Turbo Expo 2004 Power for land, sea, and air, Vienna, Austria, GT2004-53381, 2004.
[73] Rusk D, Hoffman P. Developments in probability-based strain-life analysis. In: Fifth Joint NASA/FAA/DoD Aging Aircraft Conference, 2001.
[74] Shen M-H H. Reliability assessment of high cycle fatigue design of gas turbine blades using the probabilistic Goodman diagram. International Journal of Fatigue, 1999, 21(7): 699-708.
[75] Brown J M, Grandhi R V. Probabilistic high cycle fatigue assessment process for integrally bladed rotors. In: ASME Turbo Expo 2005: Power for Land, Sea, and Air (GT2005), Reno, Nevada, USA, 2005.
[76] Cavallini G, Lazzeri R. A probabilistic approach to fatigue risk assessment in aerospace components. Engineering Fracture Mechanics, 2007, 74(18): 2964-2970.
[77] Chan K S, Enright M P. A probabilistic micromechanical code for predicting fatigue life variability: Model development and application. Journal of Engineering for Gas Turbines and Power, 2006, 128(4): 889-895.
[78] Enright M P, Chan K S, Moody J P, et al. Probabilistic fretting fatigue assessment of aircraft engine disks. Journal of Engineering for Gas Turbines and Power, 2010, 132(7): 072502.
[79] Chan K S, Enright M P, Simmons H R, et al. Toward developing a probabilistic methodology for predicting high-cycle fretting fatigue in aero-engines. In: ASME Turbo Expo 2010: Power for Land, Sea, and Air (GT2010), Glasgow, UK, 2010, pp. 659-666.
[80] Jha S, Larsen J, Rosenberger A. Towards a physics-based description of fatigue variability behavior in probabilistic life-prediction. Engineering Fracture Mechanics, 2009, 76(5): 681-694.
[81] Rusk D, Hoppe W. Fatigue life prediction of corrosion-damaged high-strength steel using an equivalent stress riser (ESR) model: Part I: Test development and results. International Journal of Fatigue, 2009, 31(10): 1454-1463.
[82] Rusk D, Hoppe W, Braisted W, et al. Fatigue life prediction of corrosion-damaged high-strength steel using an equivalent stress riser (ESR) model. Part II: Model development and results. International Journal of Fatigue, 2009, 31(10): 1464-1475.
[83] Wang X Y, Rabiei M, Hurtado J, et al. A probabilistic-based airframe integrity management model. Reliability Engineering & System Safety, 2009, 94(5): 932-941.
[84] Brooks J W, Basoalto H C, Sahota R, et al. Probabilistic property prediction of aero-engine components for fatigue. In: ASME Turbo Expo 2010: Power for Land, Sea, and Air (GT2010), Glasgow, UK, 2010, pp. 639-648.
[85] Asayama T, Takasho H, Kato T. Probabilistic prediction of crack depth distributions observed in structures subjected to thermal fatigue. Journal of Pressure Vessel Technology, 2009, 131(1): 011402.
[86] Goode K, Moore J, Roylance B. Plant machinery working life prediction method utilizing reliability and condition-monitoring data. Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering, 2000, 214(2): 109-122.
[87] Wei Z G, Kurth R E, Forte T P. Probabilistic approach for fatigue life assessment based on S-N curve. In: ASME 2010 Pressure Vessels and Piping Division/K-PVP Conference (PVP2010), Bellevue, Washington, USA, 2010, pp. 677-685.
[88] Jesus A M P D, Ripoll M L R, Gon?alves N J, et al. Probabilistic fatigue assessment of a notched detail taking into account mean stress effects. In: ASME 2010 Pressure Vessels and Piping Division/K-PVP Conference (PVP2010), Bellevue, Washington, USA, 2010, pp. 51-60.
[89] Chookah M, Nuhi M, Modarres M. A probabilistic physics-of-failure model for prognostic health management of structures subject to pitting and corrosion-fatigue. Reliability Engineering & System Safety, 2011, 96(2): 1601-1610.
[90] Liu Y M, Mahadevan S. Probabilistic fatigue life prediction using an equivalent initial flaw size distribution. International Journal of Fatigue, 2009, 31(3): 476-487.
[91] Xiang Y, Liu Y M. Application of inverse first-order reliability method for probabilistic fatigue life prediction. Probabilistic engineering mechanics, 2011, 26(2): 148-156.
[92] Guan X, Jha R, Liu Y M. Model selection, updating, and averaging for probabilistic fatigue damage prognosis. Structural Safety, 2011, 33(3): 242-249.
[93] Mao H, Mahadevan S. Reliability analysis of creep-fatigue failure. International Journal of Fatigue, 2000, 22(9): 789-797.
[94] Zhang R X, Mahadevan S. Reliability-based reassessment of corrosion fatigue life. Structural Safety, 2001, 23(1): 77-91.
[95] Karlen K, Olsson M. A probabilistic model for the entire HCF domain based on equivalent stress-simulations and experiments. International Journal of Fatigue, 2012, 36(1): 9-17.
[96] Calvo S, Canales M, Gomez C, et al. Probabilistic formulation of the multiaxial fatigue damage of Liu. International Journal of Fatigue, 2011, 33(3): 460-465.
[97] Grell W, Laz P. Probabilistic fatigue life prediction using AFGROW and accounting for material variability. International Journal of Fatigue, 2010, 32(7): 1042-1049.
[98] Laz P, Craig B, Hillberry B. A probabilistic total fatigue life model incorporating material inhomogeneities, stress level and fracture mechanics. International Journal of Fatigue, 2001, 23(1): 119-127.
[99] Kocanda D, Jasztal M. Probabilistic predicting the fatigue crack growth under variable amplitude loading. International Journal of Fatigue, 2011, in press, doi:10.1016/j.ijfatigue.2011.03.011.
[100] Liao M. Probabilistic modeling of fatigue related microstructural parameters in aluminumalloys. Engineering Fracture Mechanics, 2009, 76(5): 668-680.
[101] Castillo E, Fernandez-Canteli A, Castillo C, et al. A new probabilistic model for crack propagation under fatigue loads and its connection with Wohler fields. International Journal of Fatigue, 2010, 32(4): 744-753.
[102] Bastidas-Arteaga E, Bressolette P, Chateauneuf A, et al. Probabilistic lifetime assessment of RC structures under coupled corrosion-fatigue deterioration processes. Structural Safety, 2009, 31(1): 84-96.
[103]苏清友,孔瑞莲,陈筱雄,等.航空涡喷涡扇发动机主要零部件定寿指南.北京:航空工业出版社, 2004.
[104]吕震宙,刘成立,徐友良.概率分析方法在粉末冶金涡轮盘疲劳蠕变寿命预测中的应用.航空发动机, 2005, 31(3): 27-29.
[105]王卫国.轮盘低循环疲劳寿命预测模型和试验评估方法研究: [博士学位论文].南京:南京航空航天大学能源与动力学院, 2006.
[106]王卫国,龚梦贤,温卫东.两种国产涡轮盘材料疲劳寿命概率分布规律初探.材料工程, 2006, (3): 44-51.
[107]胡殿印,王荣桥.涡轮盘疲劳-蠕变耦合失效模式的概率设计.大型飞机关键技术高层论坛暨中国航空学会2007年学术年会论文集, 2007, pp. 1-7.
[108]裴月,薛飞,王荣桥.涡轮盘低循环疲劳寿命可靠性研究.燃气涡轮试验与研究, 2007, 20(1): 39-43.
[109]钱文学,尹晓伟,谢里阳,等.轮盘疲劳可靠性分析的Monte-Carlo数字仿真.系统仿真学报, 2007, 19(2): 254-256.
[110]李锋.不确定参数下结构疲劳断裂可靠性若干问题的研究: [博士学位论文].长春:吉林大学机械科学与工程学院, 2008.
[111]陆山,高鹏.考虑应力松弛的涡轮盘蠕变-疲劳寿命可靠性分析方法.推进技术, 2009, 30(3): 352-354.
[112]陆山,张鸿,唐俊星,等.考虑尺寸效应的轮盘应力疲劳概率寿命分析方法.航空动力学报, 2011, 26(9): 2039-2043.
[113]高阳,白广忱,张瑛莉.涡轮盘多轴低循环疲劳寿命可靠性分析.航空学报, 2009, 30(9): 1678-1682.
[114]刘辉,白广忱.涡轮盘低循环疲劳两种可靠性分析方法的对比.装备制造技术, 2010, (2): 26-29.
[115]高阳,杨昌军,白广忱,等.涡轮盘低循环疲劳可靠性设计方法.航空发动机, 2011,37(1): 4-8.
[116]朱顺鹏,黄洪钟,凌丹,等.涡轮盘低周疲劳-蠕变寿命的可靠性研究.中国航空学会第五届航空发动机可靠性学术交流会,南宁,中国, 2009, pp. 252-260.
[117]朱顺鹏,黄洪钟,何俐萍,等.基于广义能量损伤参数的涡轮盘高温低周疲劳-概率寿命预测.中国航空学会第六届航空发动机可靠性学术交流会,张家界,中国, 2011, pp. 303-311.
[118]张义民,王鹏,杨周,等.低周疲劳失效的涡轮盘可靠性灵敏度设计.中国机械工程, 2010, 21(10): 1135-1139.
[119]张艳林,张义民,金雅娟,等.考虑T-stress的非正态随机参数疲劳裂纹扩展寿命的可靠性分析.计算力学学报, 2010, 27(6): 1006-1010.
[120]谢里阳,林文强.线性累积损伤的概率准则.机械强度, 1993, 15(3): 41-44.
[121]倪侃,高镇同.疲劳可靠性二维概率Miner准则.固体力学学报, 1996, 17(4): 365-371.
[122]赵少汴.概率疲劳设计方法与设计数据.机械设计, 2000, (4): 8-11.
[123]赵少汴,王忠保.抗疲劳设计―方法与数据.北京:机械工业出版社, 1997.
[124]熊峻江,武哲,高镇同.广义疲劳等寿命曲线与二维疲劳极限概率分布.应用数学和力学, 2002, 23(10): 1055-1060.
[125]邬华芝,郭海丁,高德平.疲劳破坏寿命的概率统计方法研究综述.强度与环境, 2002, 29(4): 38-44.
[126]杨继运.基于损伤力学的概率疲劳曲线获取方法.航天器环境工程, 2005, 22(4): 207-210.
[127]杨冰,赵永翔,梁红琴,等.基于Elber型方程的随机疲劳长裂纹扩展概率模型.工程力学, 2005, 22(5): 99-104.
[128]杨冰,赵永翔,张卫华.基于Forman方程的随机疲劳长裂纹扩展概率模型.交通运输工程学报, 2006, 6(1): 25-28.
[129]赵永翔,杨冰,张卫华.应变疲劳可靠性理论与方法的新进展.机械强度, 2005, 27(5): 604-611.
[130]卢延辉,王文阁,郑联珠.疲劳可靠性计算方法中迈纳理论与概率累加理论之间的关系.吉林大学学报(工学版), 2007, 37(2): 382-385.
[131]王磊,刘文珽.飞机结构疲劳关键部位损伤与可靠性评定技术.北京航空航天大学学报, 2008, 34(1): 84-87.
[132]谢里阳,王正.随机恒幅循环载荷疲劳可靠度异量纲干涉模型.机械工程学报, 2008, 44(1): 1-6.
[133]谢里阳.疲劳概率理论与方法评述.第十四届全国疲劳与断裂学术会议论文集, 2008, pp.89-93.
[134]刘克格,闫楚良.结构疲劳试验寿命数据分布类型对其使用寿命的影响.吉林大学学报(工学版) 2011, 41(2): 419-423.
[135]薛红军,张晓燕,张玉刚.多点失效时结构寿命可靠度的计算方法.机械强度, 2011, 33(3): 363-367.
[136]凌丹,何俐萍,许焕卫,等.基于威布尔分布的疲劳剩余寿命可靠性预测方法.机械设计, 2011, 28(7): 50-53.
[137] Madsen H O. Bayesian fatigue life prediction. In: Eddertz S, Lind N C, editors. Probabilistic methods in the mechanics of solids and structures. Stockholm: Proc IUTAM Symp, 1984, pp. 395-406.
[138] Edwards G, Pacheco L. A Bayesian method for establishing fatigue design curves. Structural Safety, 1984, 2(1): 27-38.
[139] Jiang X, Mahadevan S. Bayesian risk-based decision method for model validation under uncertainty. Reliability Engineering & System Safety, 2007, 92(6): 707-718.
[140] Sankararaman S, Ling Y, Mahadevan S. Uncertainty quantification and model validation of fatigue crack growth prediction. Engineering Fracture Mechanics, 2011, 78(7): 1487-1504.
[141] Guida M, Penta F. A Bayesian analysis of fatigue data. Structural Safety, 2010, 32(1): 64-76.
[142]刘建中,谢里阳,徐灏.疲劳寿命概率分布的模糊贝叶斯确定方法.机械设计, 1994, (2): 4-7.
[143]邹嵘,倪侃,张圣坤.用模糊Bayes方法确定疲劳寿命分布.中国海洋平台, 2001, 16(1): 4-8.
[144]陈勃,鲍蕊,张建宇,等.疲劳强度分布参数的贝叶斯分析.北京航空航天大学学报, 2003, 29(3): 233-236.
[145] Huang H Z, Zuo M J, Sun Z Q. Bayesian reliability analysis for fuzzy lifetime data. Fuzzy Sets and Systems, 2006, 157(12): 1674-1686.
[146]施剑玮,姚卫星.估计构件疲劳极限的Bayes极小样本方法.机械强度, 2007, 29(2): 334-337.
[147] Bowman M, Nordmark G, Yao J. Fuzzy logic approach in metals fatigue. International Journal of Approximate Reasoning, 1987, 1(2): 197-219.
[148] Bardossy A, Bogardi I. Fuzzy fatigue life prediction. Structural Safety, 1989, 6(1): 25-38.
[149] Muc A, Kdziora P. A fuzzy set analysis for a fracture and fatigue damage response of composite materials. Composite Structures, 2001, 54(2-3): 283-287.
[150] Muc A. A fuzzy set approach to interlaminar cracks simulation problems. International Journal of Fatigue, 2002, 24(2-4): 419-427.
[151] Akpan U O, Rushton P A, Koko T S. Fuzzy probabilistic assessment of the impact of corrosion on fatigue of aircraft structures. Paper No. AIAA-2002-1640, 2002.
[152] Akpan U O, Rushton P A, Koko T S. Development of a fuzzy probabilistic methodology for multiple-site fatigue damage. Journal of aircraft, 2004, 41(3): 633-640.
[153] Rao S S, Qing L. Fuzzy approach to the mechanics of fiber-reinforced composite materials. AIAA journal, 2004, 42(1): 159-167.
[154] Sawyer J P, Rao S S. Strength-based reliability and fracture assessment of fuzzy mechanical and structural systems. AIAA journal, 1999, 37(1): 84-92.
[155] Majidian A, Saidi M. Comparison of fuzzy logic and neural network in life prediction of boiler tubes. International Journal of Fatigue, 2007, 29(3): 489-498.
[156]黄洪钟,刘忠贺,孙占全,等.影响疲劳强度可靠性的模糊因素分析.电子产品可靠性与环境试验, 2002, (4): 12-14.
[157]贾星兰,刘文珽.谱载下基于模糊Miner法则的疲劳寿命估算.北京航空航天大学学报, 2003, 29(3): 218-220.
[158]陈胜军.模糊疲劳寿命预测理论的建立与验证.机械设计, 2003, 20(12): 42-44.
[159]刘小云,丛方媛,王小陈.模糊可靠性疲劳寿命的分析与计算.长安大学学报(自然科学版), 2007, 27(1): 99-102.
[160]刘小云.疲劳损伤的模糊性研究.长安大学学报(自然科学版), 2005, 25(4): 107-110.
[161]王旭亮,聂宏.基于模糊理论的疲劳寿命估算方法.中国机械工程, 2008, 19(17): 2095-2097.
[162]王旭亮,聂宏.疲劳寿命估算中的模糊性研究.机械科学与技术, 2008, 27(9): 1139-1141.
[163]刘克格,阎楚良,张书明.模糊数学在疲劳寿命估算中的应用.航空学报, 2006, 27(2): 227-231.
[164]冯刚,孙立德,黄洪钟,等.疲劳寿命的模糊可靠度计算方法.中国机械工程, 2003, 14(19): 1699-1701.
[165]黄洪钟,田志刚.基于广义模糊随机强度的模糊可靠性计算理论.机械工程学报, 2002, 38(8): 50-53.
[166]黄洪钟.模糊机械科学与技术─21世纪机械科学的重要发展方向.机械工程学报, 1996, 32(3): 1-8.
[167] Tan X M, Chen Y L, Jin P. Corrosion fatigue life prediction of aircraft structure based on fuzzyreliability approach. Chinese Journal of Aeronautics, 2005, 18(4): 346-351.
[168]李锋,孟广伟,沙丽荣.考虑模糊失效准则的结构疲劳寿命可靠性.航空学报, 2009, 30(12): 2316-2321.
[169]卢明章,赵海军,崔明芳.模糊疲劳寿命均值及其隶属函数研究.机械强度, 2010, 32(4): 639-645.
[170]蒋文涛,薛彩军.飞机起落架结构模糊疲劳可靠性分析.飞机设计, 2011, 31(1): 17-20.
[171]邱志平,王晓军.结构疲劳寿命的区间估计.力学学报, 2005, 37(5): 653-657.
[172]邱志平,王晓军,马智博.结构疲劳寿命估计的集合理论模型.固体力学学报, 2006, 27(1): 91-97.
[173] Qiu Z P, Wang J. Reliability study of fracture mechanics based non-probabilistic interval analysis model. Fatigue & Fracture of Engineering Materials & Structures, 2010, 33(9): 539-548.
[174] Pierce S G, Worden K, Bezazi A. Uncertainty analysis of a neural network used for fatigue lifetime prediction. Mechanical Systems and Signal Processing, 2008, 22(6): 1395-1411.
[175] Huang H Z, An Z W. A discrete stress-strength interference model with stress dependent strength. IEEE Transactions on Reliability, 2008, 58(1): 118-122.
[176]徐灏.概率疲劳.沈阳:东北大学出版社, 1994, pp. 303-308.
[177]高镇同,熊峻江.疲劳可靠性.北京:北京航空航天大学出版社, 2000.
[178] Knowles I. Is it time for a new approach? IEEE Transactions on Reliability, 1993, 42(1): 2-3.
[179] Matic Z, Sruk V. The Physics-of-Failure approach in reliability engineering. In: Proceeding of 30th International Conference on Information Technology Interfaces, Dubrovnik, 2008, pp. 745-750.
[180]祝耀昌.可靠性故障物理技术及其应用.装备环境工程, 2005, 2(2): 28-33.
[181] Pecht M, Dasgupta A. Physics-of-failure: an approach to reliable product development. Journal of the Institute of Environmental Sciences, 1995, 38(5): 30-34.
[182] Pecht M. Why the traditional reliability prediction models do not work-is there an alternative? Electronics Cooling, 1996, 2: 10-13.
[183] Pecht M, Dasgupta A, Barker D, et al. The reliability physics approach to failure prediction modelling. Quality and Reliability Engineering International, 1990, 6(4): 267-273.
[184] Dasgupta A, Pecht M. Material failure mechanisms and damage models. IEEE Transactions on Reliability, 1991, 40(5): 531-536.
[185] Lall P, Pecht M. An integrated physics-of-failure approach to reliability assessment. Advancesin Electronic Packaging, ASME EEP-Vol.4-I, 1993: 509-524.
[186] Modarres M, Kaminskiy M, Krivtsov V. Reliability engineering and risk analysis: a practical guide, 2nd edition. New York: CRC Press, 2009.
[187] Upadhyayula K, Dasgupta A. Physics-of-failure guidelines for accelerated qualification of electronic systems. Quality and Reliability Engineering International, 1998, 14(6): 433-447.
[188]王云,邵将,曾晨晖,等.航空电子产品基于故障物理的可靠性工程技术.第四届中国航空学会青年科技论坛文集, 2010.
[189] Snook I, Marshall J, Newman R. Physics of failure as an integrated part of design for reliability. In: Proceedings of the Annual Symposium on Reliability and Maintainability, 2003, pp. 46-54.
[190] McLeish J G. Enhancing MIL-HDBK-217 reliability predictions with physics of failure methods. In: Proceedings of the Annual Symposium on Reliability and Maintainability, 2010, pp. 1-6.
[191] Bielen J, Gommans J J, Theunis F. Prediction of high cycle fatigue in aluminum bond wires: A physics of failure approach combining experiments and multi-physics simulations. In: 7th International Conference of Thermal, Mechanical and Multi-physics Simulations and Experiments in Micro-Electronics and Micro-Systems, 2006.
[192] Gu J, Pecht M. Prognostics and health management using physics-of-failure. In: Proceedings of 54th Annual Reliability and Maintainability Symposium (RAMS), Las Vegas, NV, 2008, pp. 481-487.
[193] Oh H, Azarian M H, Pecht M, et al. Physics-of-failure approach for fan PHM in electronics applications. In: Proceeding of Prognostics and Health Management Conference, 2010, pp. 1-6.
[194] Fan J, Yung K C, Pecht M. Physics-of-failure based prognostics and health management for high power white light-emitting diode lighting. IEEE Transactions on Device and Materials Reliability, 2011, 11(3): 407-416.
[195] Hall P, Strutt J. Probabilistic physics-of-failure models for component reliabilities using Monte Carlo simulation and Weibull analysis: a parametric study. Reliability Engineering & System Safety, 2003, 80(3): 233-242.
[196] Drake G S. Engineering design analysis (physics of failure). In: Proceedings of the Annual Symposium on Reliability and Maintainability, 2010.
[197] Chamberlain S S. Development of a physics of failure model and quantitative assessment of the fire fatality risk of compressed natural gas bus cylinders: [PhD. Dissertation]. University ofMaryland, Department of Mechanical Engineering, College Park, USA, 2004.
[198] Azarkhail M. Agent autonomy approach to physics-based reliability modeling of structures and mechanical systems: [PhD. Dissertation]. University of Maryland, Department of Mechanical Engineering, College Park, USA, 2007.
[199] Azarkhail M, Modarres M. A novel Bayesian framework for uncertainty management in physics-based reliability models. In: ASME International Mechanical Engineering Congress and Exposition, Seattle, Washington, 2007.
[200] Alseyabi M C. Structuring a probabilistic model for reliability evaluation of piping subject to corrosion-fatigue degradation: [PhD. Dissertation]. University of Maryland, Department of Mechanical Engineering, College Park, USA, 2009.
[201] Tryon R G, Dey A, Krishnan G. Microstructural-based physics of failure models to predict fatigue reliability. Journal of the IEST, 2007, 50(2): 73-84.
[202] Goswami T. Development of generic creep-fatigue life prediction models. Materials & Design, 2004, 25(4): 277-288.
[203] Halford G R. Evolution of creep-fatigue life prediction models. In: Creep-fatigue interaction at high temperature (Eds Haritos G K and Ochoa O O), ASME, AD, Philadelphia, 1991, 21: 43-57.
[204] Taira S. Lifetime of structures subjected to varying load and temperature. In: Creep in Structures, N. J. Hoff (ed.), Springer-Verlag 1962, pp. 96-124.
[205] Robinson E. Effect of temperature variation on the long-time rupture strength of steels. Journal of Applied Mechanics, 1952, 74(5): 777-780.
[206] Lagneborg R, Attermo R. The effect of combined low-cycle fatigue and creep on the life of austenitic stainless steels. Metallurgical and Materials Transactions B, 1971, 2(7): 1821-1827.
[207] Tomkins B. Inelastic analysis and life prediction in elevated temperature design. In: Pressure Vessels and Piping Conference, 1982, 59: 239-242.
[208] Chen G L. Fatigue-creep interaction fracture maps and life prediction under combined fatigue-creep stress cycling. Chinese Journal of Metal Science & Technology, 1990, 6(6): 391-414.
[209] ASME. ASME Boiler and Pressure Vessel Code, Section III, Code Case N-47, 1995.
[210] Tien J K, Nair S V, Nardone V C. Creep-Fatigue Interaction in Structural Alloys. In: Flow and Fracture at Elevated Temperatures, Edited by Raj R, Carnes Publication Services, Inc., Philadelphia, USA, 1983, pp. 179-213.
[211] Ellison E G, Al-Zamily A. Fracture and life prediction under thermal-mechanical strain cycling.Fatigue & Fracture of Engineering Materials & Structures, 1994, 17(1): 53-67.
[212] Bicego V, Fossati C, Ragazzoni S. Low-cycle fatigue characterization of a Hp-Ip steam turbine rotor. In: Low-cycle fatigue, ASTM STP 942, Soloman H D, Halford G R, Kaisand L R, and Leis B N, Eds., American Society for Testing and Materials, Philadelphia, 1988, pp. 1237-1260.
[213]张国栋,苏彬.高温低周应变疲劳的三参数幂函数能量方法研究.航空学报, 2007, 28(2): 504-507.
[214] Pineau A, Antolovich S D. High temperature fatigue of nickel-base superalloys-A review with special emphasis on deformation modes and oxidation. Engineering Failure Analysis, 2009, 16(8): 2668-2697.
[215] Smith K N, Watson P, Topper T H. A stress-strain function for the fatigue of metals. Journal of Materials, 1970, 5(4): 767-778.
[216] Koh S K, Stephens R I. Mean stress effects on low cycle fatigue for a high strength steel. Fatigue & Fracture of Engineering Materials & Structures, 1991, 14(4): 413-428.
[217]傅惠民.ε? N曲线三参数幂函数公式.航空学报, 1993, 14(3): 173-176.
[218]陈立杰,冮铁强,谢里阳.应用幂变换法构造低周疲劳寿命预测的幂指函数模型.航空学报, 2006, 27(2): 267-271.
[219]张国栋,苏彬,王泓,等.弹性模量对低周疲劳性能参数的影响.航空动力学报, 2005, 20(5): 768-771.
[220] Coffin L F. Fatigue at high temperature-prediction and interpretation. In: Proceedings of Institute of Mechanical Engineers, 1974, 188(9): 109-127.
[221] Viswanathan R. Damage mechanisms and life assessment of high-temperature components. ASM International, 1995.
[222] Coffin L F. The concept of frequency separation in life prediction for time-dependent fatigue. In: 1976 ASME-MPC Symposium on Creep-Fatigue Interaction, MPC-3, American Society for Mechanical Engineers, New York, 1976, pp. 349-364.
[223] Bernstein H. An evaluation of four creep-fatigue models for a nickel-base superalloy. (Edited Claude Amzallag, Leis, Rabbe) Low-Cycle Fatigue and Life Prediction, STP 770, 1982, pp. 105-134.
[224]陈学东,范志超,陈凌,等.三种疲劳蠕变交互作用寿命预测模型的比较及其应用.机械工程学报, 2007, 43(1): 62-68.
[225] Del Puglia A, Manfredi E. High-temperature low-cycle fatigue damage, Creep of Engineering Materials and Structures, edited by Bernasconi G and Piatti G, Applied Science Publishers LTD,London, 1979, pp. 229-265.
[226] Ostergren W J. A damage foundation hold time and frequency effects in elevated temperature low cycle fatigue. Journal of Testing and Evaluation, 1967, 4: 327-339.
[227] Ostergren W J. Correlation of hold time effects in elevated temperature low cycle fatigue using a frequency modified damage function. In: ASME-MPC Symposium on creep-fatigue interaction, 1976, pp. 179-202.
[228] Ellison E G. A review of the interaction of creep and fatigue. Journal of Mechanical Engineering Science, 1969, 11(3): 318-339.
[229] Goswami T. Low cycle fatigue life prediction-a new model. International Journal of Fatigue, 1997, 19(2): 109-115.
[230] Goswami T. Creep-fatigue life prediction: a ductility model. High Temperature Materials and Processes, 1995, 14(2): 101-114.
[231] Goswami T. New creep-fatigue life prediction model. High Temperature Materials and Processes, 1996, 15(1-2): 91-96.
[232]范志超,陈学东,陈凌,等.基于延性耗竭理论的疲劳蠕变寿命预测方法.金属学报, 2006, 42(4): 415-420.
[233] Zhu S P, Huang H Z, Li H Q, et al. A new ductility exhaustion model for high temperature low cycle fatigue life prediction of turbine disk alloys. International Journal of Turbo and Jet Engines, 2011, 28(2): 119-131.
[234] Manson S S, Halford G R, Hirschberg M H. Creep-fatigue analysis by strain-range partitioning. In: Proceedings of symposium on design for elevated temperature environment, ASME, New York, 1971, pp. 12-28.
[235] Nitta A, Kuwabara K, Kitamura T. The characteristics of thermal-mechanical fatigue strength in superalloys for gas turbine. In: Proceedings of 1983 Tokyo International Gas Turbine Congress, 83-TOKYO-IGTC-99, Tokyo, Japan, 1983, pp. 765-772.
[236] Kachanov L M. Introduction to continuum damage mechanics. Dordrecht: Martinus Nijhoof Publishers, 1986.
[237] Chrzanowski M. Use of the damage concept in describing creep-fatigue interaction under prescribed stress. International Journal of Mechanical Sciences, 1976, 18(2): 69-73.
[238] Modarres M. Risk analysis in engineering: techniques, tools, and trends. New York: CRC Press, 2006.
[239]柳恒超,许燕,王力.结构方程模型应用中模型选择的原理和方法.心理学探新, 2007,27(101): 75-78.
[240] Burnham K P, Anderson D R. Model selection and multimodel inference: a practical information-theoretic approach. New York: Springer Verlag, 2002.
[241] Akaike H. Information theory as an extension of the maximum likelihood principle. In: Petrov B N, and Csaki F, (eds.) Second International Symposium on Information Theory. Akademiai Kiado, Budapest, 1973, pp. 267-281.
[242] Akaike H. A new look at the statistical model identi cation. IEEE Transactions on Automatic Control, 1974, 19: 716-723.
[243] Akaike H. Information measures and model selection. International Statistical Institute, 1983, 50(1): 277-291.
[244] Schwarz G. Estimating the dimension of a model. The Annals of Statistics, 1978, 6(2): 461-464.
[245]袁熙,李舜酩.疲劳寿命预测方法的研究现状与发展.航空制造技术, 2005, 12: 80-85.
[246]卢曦,郑松林.考虑小载荷强化的汽车构件疲劳累积损伤试验研究.中国机械工程, 2007, 18(8): 994-997.
[247]郑松林.低幅载荷对汽车前轴疲劳寿命影响的试验研究.机械强度, 2002, 24(4): 547-549.
[248]吴志学,吕文阁,徐灏.疲劳极限下损伤及"锻炼"效应.东北大学学报, 1996, 17(3): 338-341.
[249] Ishihara S, Mcevily A. A coaxing effect in the small fatigue crack growth regime. Scripta Materialia, 1999, 42(5): 617-622.
[250] Nicholas T. Step loading for very high cycle fatigue. Fatigue & Fracture of Engineering Materials & Structures, 2002, 25(8-9): 861-869.
[251] Pereira H, De Jesus A, Fernandes A, et al. Analysis of fatigue damage under block loading in a low carbon steel. Strain, 2008, 44(6): 429-439.
[252] Lu X, Zheng S L. Strengthening and damaging under low-amplitude loads below the fatigue limit. International Journal of Fatigue, 2009, 31(2): 341-345.
[253] Dombi J. Membership function as an evaluation. Fuzzy Sets and Systems, 1990, 35(1): 1-21.
[254]黄洪钟.机械设计模糊优化原理及应用.北京:科学出版社, 1997, pp. 51-64.
[255]董玉革.机械模糊可靠性设计.北京:机械工业出版社, 2000, pp. 20-29.
[256]郦明,奥脱?布克斯鲍姆.结构抗疲劳设计.北京:机械工业出版社, 1987, pp. 224-228.
[257] Nakagawa T. On the strength deteriorating process in reliability engineering. Transactions of the Japan Society of Mechanical Engineers A, 1983, 49(441): 540-546.
[258] Nakagawa T, Ikai Y. Strain aging and the fatigue limit in carbon steel. Fatigue & Fracture of Engineering Materials & Structures, 1979, 2(1): 13-21.
[259] Sinclair G. An investigation of the coaxing effect in fatigue of metals. Proc. ASTM, 1952, 52: 743-758.
[260]陈胜军.基于隶属函数的疲劳寿命预测模型.南京师范大学学报(工程技术版), 2007, 7(2): 6-9.
[261] Shang D G, Yao W X. A nonlinear damage cumulative model for uniaxial fatigue. International Journal of Fatigue, 1999, 21(2): 187-194.
[262]尚德广,姚卫星.单轴非线性连续疲劳损伤累积模型的研究.航空学报, 1998, 19(6): 647-656.
[263]姚卫星,郭盛杰. LC4CS铝合金的超高周疲劳寿命分布.金属学报, 2007, 43(4): 399-403.
[264]张俊善.材料的高温变形与断裂.北京:科学出版社, 2007, pp. 425-430.
[265]尹泽勇.叶片轮盘及主轴强度分析-航空发动机设计手册第18册.北京:航空工业出版社, 2007, pp. 807-853.
[266] Zhu S P, Huang H Z. A generalized frequency separation-strain energy damage function model for low cycle fatigue-creep life prediction. Fatigue & Fracture of Engineering Materials & Structures, 2010, 33(4): 227-237.
[267] Fan Z C, Chen X D, Chen L, et al. Fatigue-creep behavior of 1.25Cr0.5Mo steel at high temperature and its life prediction. International Journal of Fatigue, 2007, 29(6): 1174-1183.
[268] Chen L, Jiang J L, Fan Z C, et al. A new model for life prediction of fatigue-creep interaction. International Journal of Fatigue, 2007, 29(4): 615-619.
[269]中华人民共和国国家标准. GB/T 15248-94,金属材料轴向等幅低循环疲劳试验方法.北京:中国标准出版社, 1995.
[270] Ye D Y, Wang Z L. A new approach to low-cycle fatigue damage based on exhaustion of static toughness and dissipation of cyclic plastic strain energy during fatigue. International Journal of Fatigue, 2001, 23(8): 679-687.
[271]杨显杰,罗艳,高庆,等.循环软化45碳钢和循环硬化304不锈钢的棘轮行为实验研究.固体力学学报, 2005, 26(2): 125-131.
[272] Sadananda K, Sarkar S, Kujawski D, et al. A two-parameter analysis of S-N fatigue life usingΔσandσmax. International Journal of Fatigue, 2009, 31(11-12): 1648-1659.
[273] Zhang R X, Mahadevan S. Model uncertainty and Bayesian updating in reliability-based inspection. Structural Safety, 2000, 22(2): 145-160.
[274] Nelson W, McCool J, Meeker W. Applied life data analysis. New York: John Wiley & Sons, 1982.
[275] Ontiveros V, Cartillier A, Modarres M. An integrated methodology for assessing fire simulation code uncertainty. Nuclear Science and Engineering, 2010, 166(3): 179-201.
[276] Azarkhail M, Ontiveros V, Modarres M. A Bayesian framework for model uncertainty considerations in fire simulation codes. In: 17th International Conference On Nuclear Engineering, Brussels, Belgium, 2009.
[277] Shirazi C H. Data-informed calibration and aggregation of expert opinion in a Bayesian framework: [PhD. Dissertation]. University of Maryland, Department of Mechanical Engineering, College Park, 2009.
[278] Zhang Z, Qiao Y, Sun Q, et al. Theoretical estimation to the cyclic strength coefficient and the cyclic strain-hardening exponent for metallic materials: preliminary study. Journal of Materials Engineering and Performance, 2009, 18(3): 245-254.
[279] Lunn D, Thomas A, Best N, et al. WinBUGS-a Bayesian modelling framework: concepts, structure, and extensibility. Statistics and Computing, 2000, 10(4): 325-337.
[280]唐俊星,陆山.某涡轮盘低循环疲劳概率寿命数值模拟.航空动力学报, 2006, 21(4): 706-710.
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |