基于压磁效应的磁性材料力学与疲劳的研究进展

针对目前混凝土疲劳损伤与寿命评估方法存在的耗费大、精度低等问题,迫切需要从宏观和细观相结合的角度,发展一种新型的混凝土疲劳损伤试验方法。系统阐述了基于压磁效应的铁磁性材料疲劳研究进展及基于压磁效应的磁性岩石力学研究进展。指出可将基于压磁效应的磁性材料力学与疲劳的研究方法引入到混凝土疲劳损伤与寿命预测领域。最后,提出了尝试进行人工合成的含磁铁矿粉混凝土压磁实验需要考虑的影响因素与关键问题,旨在探讨将压磁效应用于混凝土等非铁磁性材料疲劳实验及寿命预测研究的可能性,为将来进一步科学研究乃至应用于工程实践提供参考。     

复合材料单钉接头疲劳累积损伤破坏分析

基于时间增量原理 , 推导了层合板接头疲劳加载累积损伤应力2应变分析的虚功方程。同时 , 引入Hashin三维疲劳失效准则进行材料的损伤判定 , 并结合建立的疲劳加载材料退化模型、 4种基本损伤机制相互关联作用的材料性能退化方法及复合材料接头最终失效判据 , 建立了层合板接头疲劳载荷作用下三维累积损伤分析的寿命预测方法。最后 , 对层合板接头拉2拉疲劳载荷作用下的损伤累积扩展与失效规律进行了仿真分析 , 并与试验结果进行了对比 , 结果表明 : 本文中建立的寿命预测方法能够很好地预测层合板接头的寿命以及损伤发生、扩展及最终失效。      

研究材料制备与服役行为,为装备的安全可靠使用、延寿经济运行保驾护航

正腐蚀、疲劳、磨损是材料三大主要失效形式,材料损伤、失效以及制备的构件组织、性能不均一,是关乎高铁、核电、航空、航天、油气、海洋、基础设施等多领域中工程结构安全可靠使用、延寿经济运行的关键问题。材料研究人员致力于设计制备新材料、提高服役性能,并逐渐注重研究服役环境中材料的损伤机理、认识其损伤动力学过程,以定量评价及预测其安全性和寿命,为保障重要工程结构的服役安全和经济运行提供理论与技术支持。     

12Cr1MoV钢低周疲劳损伤研究

为了预测锅炉、压力容器的整体寿命,用连续介质损伤力学理论研究了工程材料的低周疲劳损伤演变过程.采用循环应力幅定义损伤变量D,根据有效应力概念,建立了低周疲劳各向同性连续损伤模型,并通过控制应变的疲劳试验,用该模型对锅炉常用材料12Cr1MoV钢试件进行了疲劳损伤的测量.研究表明,当循环进行到80%寿命时,损伤进入局部化阶段,宏观裂纹开始形成,较好地验证了损伤演变模型;所建立的模型形式简单,参数少,易测量,具有明确的物理意义,对锅炉的寿命估算有参考价值.     

应用悬丝耦合共振法测定25Cr20Ni合金的蠕变损伤

论述了一种测定材料蠕变损伤的方法－悬丝耦合共振法。该法实测２５Ｃｒ２０Ｎｉ合金的损伤结果与局部损伤理论预测值吻合得较好，与电流密度法，加卸载法相比，具有精度高，设备简单和重复性好等优点，为高温材料的寿命预测和判废提供了一条有效的途径。     

金属材料和结构的疲劳寿命预测概率模型及应用研究进展

疲劳过程的不确定性以及影响疲劳寿命的不确定性因素较多,导致疲劳寿命的分散性难以预测,在疲劳寿命预测模型中采用统计学和概率论的概念和方法是描述疲劳过程不确定性和疲劳寿命分散性的一种重要手段。本文针对疲劳寿命预测概率模型进行综述,总结和介绍了疲劳寿命经验公式和参数的随机化模型、表征疲劳寿命离散性的统计模型、基于材料微结构和疲劳物理机制的疲劳寿命预测概率模型以及研究广布疲劳损伤的概率模型,并对金属材料与结构的疲劳寿命预测方法进行了展望。     

大气环境下电网设备金属材料的腐蚀及服役寿命预测研究进展

电网安全是电力企业生存和发展的根本,随着电网的不断发展,对电网的安全性、可靠性提出了更高的要求。但在电网运行过程中安全形势依然面临严重威胁,其中,由于电网设备金属材料的腐蚀造成的设备安全问题较为普遍,输电网中金属部件的腐蚀失效、防护技术,以及服役寿命预测的研究日趋受到各地区电力部门的重视。结合电网设备金属部件的服役环境和腐蚀失效情况,综述了当前电网金属部件大气腐蚀的影响因素及其影响规律,介绍了当前大气环境下电网金属部件材料的服役寿命预测的分析方法,及在预测电网设备金属部件于大气环境中服役寿命的应用。     

考虑应变路径的多轴低周疲劳寿命预测模型

通过分析材料在多轴非比例加载下产生附加强化的机理,该文以拉扭薄壁管试件为研究对象,分析了临界平面上的应变状态,并在此基础上以塑性应变能为控制参数定义表征多轴低周疲劳寿命对应变路径依赖性的非比例度。基于多轴疲劳临界损伤面原理,应用von-Mises 准则和本文定义的应变路径非比例度参数建立起能反映应变路径对非比例附加强化影响的多轴低周疲劳寿命预测模型。利用该模型预测08X18H10T 不锈钢、Ti-6Al-4V合金、S460N 钢和2.25Cr-1Mo 钢这4 种材料的多轴疲劳寿命,并与试验值进行比较。结果表明:该模型的预测结果与试验结果吻合良好,能同时适用于比例与非比例加载,预测精度较高,便于工程应用。     

抽油杆可再制造性检测的研究进展

对抽油杆毛坯进行可再制造性检测和评价是从源头上保证再制造产品质量的第一步。阐述了可再制造性的内涵,分别综述了抽油杆再制造毛坯的无损检测技术和疲劳寿命评估方法在近几年的发展现状,其中重点探讨了适于早期损伤检测、损伤定量检测、损伤动态监测的金属磁记忆法、交流电磁场法和声发射法等新技术,并进行了对比分析;详细介绍了基于疲劳试验手段进行寿命预测、利用力学理论和有限元模拟计算寿命、采用无损检测技术预测疲劳寿命的评估方法。在国内外现有研究的基础上,总结当前抽油杆可再制造性检测存在的问题,并指出进一步研究的思路。     

意大利高温下应用的先进材料研究课题(1989～1990年)

(1)意大利国家电力公司在高温电厂用零件寿命分析和延寿领域的探索和经验。(2)先进材料在发电厂中的应用。(3)用激光沉积混合物涂层。(4)蠕变过程中内应力的测量及其在预测工程材料长期蠕变行为中的应用。(5)Sic、Si_3N_4、Al_2O_3样品蠕变损伤试验的初步结果。(6)先进的剩余寿命方法改进设计和运行。(7)AISI316不锈钢蠕变裂纹扩展损伤     

A reliability-based framework for fatigue damage prognosis of composite aircraft structures

The extensive use of lightweight composite materials in composite aircraft structures drastically increases the sensitivity to both fatigue- and impact-induced damage of their critical structural components during their service life. Within this scenario, an integrated hardware–software system that is capable of monitoring the composite airframe, assessing its structural integrity, identifying a condition-based maintenance, and predicting the remaining service life of its critical components is therefore needed. As a contribution to this goal, this paper presents the theoretical basis of a novel and comprehensive probabilistic methodology for predicting the remaining service life of adhesively bonded joints within the structural components of composite aircraft, with emphasis on a composite wing structure. Non-destructive evaluation techniques and recursive Bayesian inference are used to (i) assess the current state of damage of the system and (ii) update the joint probability distribution function (PDF) of the damage extents at various locations. A probabilistic model for future aerodynamic loads and a damage evolution model for the adhesive are then used to stochastically propagate damage through the joints and predict the joint PDF of the damage extents at future times. This information is subsequently used to probabilistically assess the reduced (due to damage) global aeroelastic performance of the wing by computing the PDFs of its flutter velocity and the velocities associated with the limit cycle oscillations of interest. Combined local and global failure criteria are finally used to compute lower and upper bounds for the reliability index of the composite wing structure at future times.     

加筋复合材料结构分层损伤的贝叶斯诊断及预测

针对复合材料结构疲劳损伤的在线监测和预测问题,提出了一种基于结构健康监测 (Structural health monitoring, SHM) 和贝叶斯理论的结构分层损伤诊断及结构剩余使用寿命预测方法。在贝叶斯概率理论框架下,采用指数模型描述复合材料结构疲劳分层损伤面积的先验演化规律,融合在线SHM数据对结构分层损伤状态,以及损伤面积演化模型的参数进行联合后验估计,即为损伤诊断结果。进一步通过后验估计得到的损伤状态和模型参数预测未来时刻结构分层损伤面积的演化,从而得到当前复合材料结构的剩余使用寿命预测结果。通过有限元仿真的加筋复合材料结构疲劳分层扩展对所提出的方法进行了验证。结果表明,方法可以在线准确地诊断结构分层损伤状态以及预测结构的剩余使用寿命。      

Prediction of the probability of nonfailure of structural elements of heat-and-power-generating equipment from the fracture-toughness characteristics of the material

Conclusions A method was developed to predict the life of important structural elements of heat-and-power-generating equipment from the parameter of the probability of nonfailure on the basis of statistical modeling of the vector of random parameters of crack-resistance characteristics of the metal using criteria of linear fracture mechanics.We also developed an algorithm and a program which automate the computing process with the use of modern computers to predict the life of a structure from the crack resistance of the material in a probabilistic formulation.We will subsequently conduct studies involving the construction and substantiation of the representativeness of samples of mechanical tests of materials for crack resistance, which is very important in predicting the safe life of a structure.Institute of Strength Problems, Academy of Sciences of the Ukrainian SSR, Kiev. Translated from Problemy Prochnosti, No. 1, pp. 7–13, January, 1987.     

Condition Based Structural Health Monitoring and Prognosis of Composite Structures under Uniaxial and Biaxial Loading

This paper presents a condition based structural health monitoring (SHM) and prognosis approach to estimate the residual useful life (RUL) of composite specimens in real time. On-line damage states, which are estimated using real time sensing information, are fed to an off-line predictive model to update future damage states and RUL. The on-line damage index or damage state at any given fatigue cycle is estimated using correlation analysis. Based on the on-line information of the previous and current damage states, an off-line model is developed to predict the future damage state and estimate the RUL. The off-line model is a stochastic model which is developed based on the Gaussian process approach. In this paper, the condition based prognosis model is used to estimate the cumulative fatigue damage in composite test structures under constant amplitude fatigue loading. The proposed procedure is validated under uniaxial fatigue loading as well as biaxial fatigue loading. Experimental validations demonstrate that the prediction capability of the prognosis algorithm is effective in predicting the RUL under complex stress states.     

A structural integrity prognosis system

A science-based structural integrity prognosis system (SIPS) is being developed to provide prompt, informed predictions of the structural viability of individual aircraft based on tracking of their actual use and modeling of anticipated usage. The work is motivated by the need for more efficient use of expensive assets and for enhanced combat readiness of critical vehicles. The prognosis system will be founded on a collaboration between sensor systems, advanced reasoning methods for data fusion and signal interpretation, and modeling and simulation systems.The modeling technology being developed for this program is based on a fundamental understanding of the fatigue process, and traces the structural degradation caused by fatigue back to its physical origins in the microstructure of the metallic component. Sensor systems designed to detect the earliest stages of fatigue damage provide needed input for the models, and the data from the models and the sensors are combined by the reasoning and prediction (RAP) system. The RAP system employs novel reasoning approaches for combining uncertain knowledge from the models and the sensors into a prediction of remaining useful life.     

在役钢筋混凝土结构基于可靠性的疲劳寿命分析

本文以结构的极限疲劳循环次数作为随机变量,基于可靠性理论提出了在役结构疲劳剩余寿命的预测方法,分析了多种工况下结构在未来服役期内的疲劳可靠性和疲劳剩余寿命。算例表明,通过对在役结构疲劳寿命及可靠性的分析,不仅可以预测在目标可靠度下的疲劳寿命,而且可以根据需要确定合适的交变荷载的频率、服役时间以及相应的疲劳可靠指标,从而为结构的合理利用起指导性作用。     

Multiscale finite element modeling of failure process of composite laminates

A multiscale nonlinear finite element modeling technique is developed in this paper to predict the progressive failure process for composite laminates. A micromechanical elastic–plastic bridging constitutive model, which considers the nonlinear material properties of the constituent fiber and matrix materials and their interaction and the damage and failure in fibrous composites at the fiber and matrix level, is proposed to represent the material behavior of fiber-reinforced composite laminates. The micromechanics constitutive model is employed in the macroscale finite element analysis of structural behavior especially progressive failure process of the fiber-reinforced composites based on a 4-node 24-DOF shear-locking free rectangular composite plate element.     

Remaining Life Prediction Based on Wiener Processes with ADT Prior Information

Precisely predicting the remaining life for an individual plays an important role in condition‐based maintenance, so Bayesian inference method, which can integrate useful data from several sources to improve the prediction accuracy, has became a research hot. Aiming at the situation that accelerated degradation tests have been widely applied to assess the reliability of products, a remaining life prediction method based on Bayesian inference by taking accelerated degradation data as prior information is proposed. A Wiener process with random drift, diffusion parameters is used to model degradation data, and conjugate prior distributions of random parameters are adopted. To solve the problem that it is hard to estimate the hyper parameters from accelerated degradation data using an Expectation Maximization algorithm, a data extrapolation method is developed. With acceleration factors, degradation data are extrapolated from accelerated stress levels to the normal use stress level. Acceleration factor constant hypothesis is used to deduce the expression of acceleration factor for a Wiener degradation model. Besides, simulation tests are designed to validate the proposed method. The method of constructing the confidence levels for the remaining life predictions is also provided. Finally, a case study is used to illustrate the application of our developed method. Copyright © 2015 John Wiley & Sons, Ltd.