高强度钢30Cr3SiNiMoVA的疲劳特性研究

为了获得超高强度钢30Cr3SiNiMoVA的疲劳设计数据,对该材料进行了疲劳性能实验。分别对该材料的抛光和未抛光试样进行轴向拉压疲劳实验。用升降试验法测定材料的条件疲劳极限,用成组实验法在四级应力水平下测试其疲劳寿命。结合升降法所得的条件疲劳极限值和成组法实验数据,采用双参数最小二乘法拟合S-N曲线,运用概率方法求得P-S-N曲线。通过对两种试样的S-N曲线分析可知:未抛光试样的疲劳寿命要低于抛光试样的疲劳寿命,并且疲劳载荷级越低,两类试样之间的疲劳寿命差越大,抛光试样的疲劳极限大约是未抛光试样的1.4倍。相关实验现象表明30Cr3SiNiMoVA的疲劳寿命对试样表面粗糙状态非常敏感,建议该类材料在应用过程中要采取有效措施改善构件的表面状态。文中实验数据可为该材料的工程应用提供参考。     

超长寿命疲劳破坏行为的可靠性研究

为了进行超长寿命疲劳破坏行为的可靠性研究,对GCr15钢超长寿命疲劳S-N试验数据进行了统计评估,采用Bansqun模型描述了其S-N曲线关系,建立了其概率S-N曲线模型,并采用SEV方法和Murakami方程分别预测了钢中最大夹杂尺寸和其相对应的疲劳强度。结果表明:其超长寿命疲劳S-N数据能较好地服从三参数威布尔分布,其概率S-N曲线形式都呈现持续下降的趋势;在验证了最大夹杂尺寸服从Gumbel分布的基础上,SEV方法预测的最大夹杂尺寸随着钢体积的增大而线性增加,Murakami方程预测的结果揭示了其概率S-N曲线呈现持续下降的原因。     

基于堆焊成形钛合金高周疲劳实验数据的R-S-N模型

针对应力比对疲劳寿命影响的问题,以TC18钛合金堆焊成形(利用多层堆焊的方法制备)试样为研究对象,进行了3种应力比(R=0.5、R=0.06、R=-1)的疲劳实验,得出相应的疲劳极限,应用"应力幅值寿命模型"和"三参数寿命模型"得到6条S-N曲线。根据裂纹扩展速率与疲劳寿命的积分关系,以两种疲劳寿命数学模型为基础,系统地研究了应力比(R)与疲劳寿命曲线(S-N)的关系,提出了考虑应力比的疲劳寿命(R-S-N)数学模型。根据本文提出的修正公式,建立了适用TC18钛合金堆焊成形材料的两种R-S-N数学模型,结果表明:用应力幅值寿命模型可对中等疲劳寿命区进行准确的预测,而三参数寿命模型更适合中长寿命区域的预测。提出的两种R-S-N数学模型与实验值吻合良好,并可在工程上预测任意应力比下的疲劳寿命曲线。     

小子样测定叶片S-N曲线试验方法研究

根据试验要求,对叶片在样本较少情况下测定其疲劳极限σ-1和S-N曲线。通过振动疲劳试验的方法进行研究,试验采用升降法选择所施加振动应力的水平,采用异方差回归分析方法进行疲劳试验数据的分析。最后获得叶片材料的均值S-N曲线和置信度为95%、可靠度为99.9%的P-S-N曲线,并得到各自曲线上的疲劳极限σ-1。此方法保证试验的顺利进行并且具有较高的可靠性,对于小样本测定材料的S-N曲线具有较好的实用价值。     

基于超高周疲劳多元化失效模式的概率S-N曲线模型构建方法EI北大核心CSCD

对渗碳Cr Mn钢开展了超高周疲劳试验,通过观察断口发现其失效模式分为表面裂纹诱发失效、内部夹杂导致的高周疲劳（5×10^4〈N^10^7）失效以及超高周疲劳（N〉10^7）三种。该文假设每一种失效模式的S-N曲线均相互独立,并基于混合Weibull分布以及Basquin和三参数S-N曲线模型,分别构建出了渗碳Cr Mn钢三种失效模式各自的概率S-N曲线及综合反映渗碳Cr Mn钢多元化失效模式的概率S-N曲线。与试验数据相比,99%存活概率的P-S-N曲线在超长寿命区给出了较为安全的寿命预测。     

基于超高周疲劳多元化失效模式的概率S-N曲线模型构建方法

对渗碳Cr Mn钢开展了超高周疲劳试验,通过观察断口发现其失效模式分为表面裂纹诱发失效、内部夹杂导致的高周疲劳(5×104N10~7)失效以及超高周疲劳(N10~7)失效三种。该文假设每一种失效模式的S-N曲线均相互独立,并基于混合Weibull分布以及Basquin和三参数S-N曲线模型,分别构建出了渗碳Cr Mn钢三种失效模式各自的概率S-N曲线及综合反映渗碳Cr Mn钢多元化失效模式的概率S-N曲线。与试验数据相比,99%存活概率的P-S-N曲线在超长寿命区给出了较为安全的寿命预测。     

舰船用钛-钢复合过渡接头焊接态疲劳性能试验研究

针对舰船用钛-钢复合过渡接头应用要求,进行了钛-钢过渡接头焊接态拉-压、拉-剪和弯曲疲劳试验,结果表明,疲劳寿命为200万次时,钛钢复合过渡接头结构件的拉-压疲劳极限为73.0 MPa,拉-剪疲劳极限为62.96 MPa,弯曲疲劳最大应力达到360 MPa且接头本身未破坏。拉-压疲劳和拉-剪疲劳S-N曲线可为舰船钛-钢复合过渡接头结构的设计提供支撑。     

TC4棒材室温疲劳寿命测定及S-N曲线的建立

本文利用升降法确定TC4棒材的疲劳极限,采用成组法确定高应力下疲劳寿命,数据处理后建立了TC4合金棒材疲劳试验S-N曲线。     

各种平均应力下高周疲劳极限间的定量关系

疲劳极限是材料工程应用中的一个重要特性参数,但它并不是材料常数。在不同循环载荷作用下,材料会有不同的疲劳极限值。疲劳极限值很大程度上依赖于循环载荷中的平均应力或最大应力幅值,两者之间的关系是材料自身固有的特性关系。因为在接近疲劳极限的低循环应力幅下,S-N曲线受疲劳极限控制,所以在工程应用中对其定量关系有迫切的需求,但现有的经典经验关系只能对其进行非常粗略的估算,不能满足工程应用中有关寿命设计的需要。现状是只能通过大量的实验,得出其实验关系。该文提出了一种函数形式的关系式,该关系式可以足够精确地描述各种材料的疲劳极限和平均应力之间的关系,且只包含三个材料常数。只要这三个材料疲劳特性常数被事先确定,则任意疲劳载荷下的疲劳极限值,都可由该关系式估计得到,因此可以作为材料本身固有的疲劳强度的状态关系式使用。     

轴承用20CrMoH钢S-N疲劳曲线的拟合

为了合理并高效地设计20CrMoH钢轴类零件的安全服役应力,根据轴类零件使用工况用标准旋转疲劳试样进行了旋转弯曲疲劳试验,并采用Parabola曲线模型拟合了中寿命区到长寿命区的中值S-N曲线以及在0.1%失效概率和95%置信度条件下的P-S-N曲线,最后利用疲劳应用统计学,对线性数学模型和Parabola曲线模型两种拟合方法进行了对比。初步研究发现:无论是在50%失效概率还是在0.1%失效概率、95%置信度条件下,与线性数学模型拟合方法相比,Parabola曲线模型拟合得到的S-N曲线结果均具有较高的相关系数,在中、低应力区有着较为保守的疲劳寿命估计,而在高应力区也更贴近原始数据。     

A fatigue reliability analysis method including super long life regime

An affordable and feasible method with moderate accuracy is developed to realize fatigue reliability assessment and life prediction including super long life regime (SLLR) through series of experimental researches on a railway axle steel and real axles. A competition damage mechanism for fatigue crack initiation and growth in SLLR is revealed to fascinate an understanding on wide fatigue damage behavior and to provide a weigh and balance on material primary quality control and on-line inspection capacity. Affordable material probabilistic strength-life (S-N) curves including SLLR are presented by an extrapolation approach on a concurrent probability rule between the S-N relations in mid-long life regime and the fatigue limits with a specified life definition. And then, structural probabilistic S-N curves are deduced by considering scale-induced effect on the material curves. Random cyclic stress-strain (CSS) relations are depicted for constructing structural random stressing history. Reliability assessment and fatigue life prediction are conducted by an interference model of the applied stress deduced from the random CSS relations and the strength capacity derived from the structural probabilistic S-N curves. Availability and feasibility of the present method are indicated by a successful application on a railway axle steel.     

Damage tolerance reliability analysis of automotive spot-welded joints

This paper develops a damage tolerance reliability analysis methodology for automotive spot-welded joints under multi-axial and variable amplitude loading history. The total fatigue life of a spot weld is divided into two parts, crack initiation and crack propagation. The multi-axial loading history is obtained from transient response finite element analysis of a vehicle model. A three-dimensional finite element model of a simplified joint with four spot welds is developed for static stress/strain analysis. A probabilistic Miner's rule is combined with a randomized strain-life curve family and the stress/strain analysis result to develop a strain-based probabilistic fatigue crack initiation life prediction for spot welds. Afterwards, the fatigue crack inside the base material sheet is modeled as a surface crack. Then a probabilistic crack growth model is combined with the stress analysis result to develop a probabilistic fatigue crack growth life prediction for spot welds. Both methods are implemented with MSC/NASTRAN and MSC/FATIGUE software, and are useful for reliability assessment of automotive spot-welded joints against fatigue and fracture.     

Probabilistic fatigue crack growth analysis of spot‐welded joints

This paper presents a probabilistic fatigue crack growth life prediction methodology for spot‐welded joints under variable amplitude loading history. The loading is multi‐axial and is obtained from transient response analysis of a vehicle model using finite‐element analysis. A three‐dimensional (3D) finite element model of a simplified joint with four spot welds is developed, and the static stress analysis of this joint is performed. Then the fatigue crack inside the base material sheet is modelled as a surface crack. Probabilistic crack growth model is combined with the stress analysis result to develop a probabilistic fatigue crack growth life prediction methodology for spot welds. This new method is implemented with MSC/NASTRAN and MSC/FATIGUE and is useful for the reliability assessment of spot‐welded joints against fatigue crack growth.     

Research on fatigue reliability prediction model and structural improvement of welded drive axle housing based on master S-N Curve method

Fatigue reliability prediction of welded structures is mainly based on nominal stress or hot spot stress method, but there are some problems such as grid sensitivity and joint geometry dependence. The Master S-N curve method can solve these problems well, but the corresponding reliability model needs to be studied. In this paper, the fatigue reliability model of welded structures based on the Master S-N curve method is studied. Considering the randomness of life and the correlation of failure, a reliability model is proposed, which reduces the computational burden by establishing a median damage-random threshold rule. Taking the welded drive axle housing as an object, the system reliability is analyzed under the bench test condition, and verified by the experimental data. After the verification, this method is used to predict the reliability of the axle housing under variable amplitude loading collected in the test field, and the results are verified by Monte Carlo (MC) method. When the P-S-N curves are parallel, the model is accurate, which is the characteristic of the Master S-N curve method. This method only needs to input the median damage value of the weak part, which is easy to be applied. This method can speed up the reliability prediction cycle of welded structures, which is beneficial to product innovation and optimal design. Finally, an improved design scheme is proposed for the weak parts of welding, and the effects of welding leg width, welding depth, and closed weld on fatigue life are revealed.     

Application of inverse first-order reliability method for probabilistic fatigue life prediction

A general probabilistic life prediction methodology for accurate and efficient fatigue prognosis is proposed in this paper. The proposed methodology is based-on an inverse first-order reliability method (IFORM) to evaluate the fatigue life at an arbitrary reliability level. This formulation is different from the forward reliability problem, which aims to calculate the failure probability at a fixed time instant. The variables in the fatigue prognosis problem are separated into two categories, i.e., random variables and index variables. An efficient searching algorithm for fatigue life prediction is developed to find the corresponding index variable at a certain confidence level. Numerical examples using direct Monte Carlo simulation and the proposed IFORM method are compared for algorithm verification. Following this, various experimental data for metallic materials are used for model prediction validation.     

Übertragbarkeit – ein zentrales Problem der Lebensdauervorhersage schwingbelasteter Bauteile

Transferability – a fundamental problem for fatigue life prediction Frequently specimen fatigue data have to be applied for fatigue life assessment of components and structures. It has to be assured that such data are relevant for the component under consideration. Equally it has to be assured that constant amplitude S-N data can be used for fatigue assessment in the case of spectrum loading. It is shown that application of transfer functions which are often of empirical nature requires an understanding of basic principles of material and component behaviour. Life prediction concepts should acknowledge the existence and relative portion of the crack initiation and crack propagation phases which are dominated by different mechanisms.     

Reliability of deteriorating structures

A method is presented to assess the reliability of structures considering the deterioration of the resistance due to environmental effects (random loading and fatigue corrosion). For modeling the deterioration effects probabilistic fracture mechanical methods are applied. This concept allows the determination of the influence of various parameters (e.g. initial crack length, material toughness etc.) which is not feasible with the more traditional fatigue analysis (S-N curves). The results of the present study show that the initial surface quality (crack length) influences the reliability significantly when less ductile steels are used. As a result, quantitative information for an acceptable initial crack size distribution with regard to application of a high quality (but less ductile) steel can be obtained.     

Influence of inclusion size on S-N curve characteristics of high-strength steels in the giga-cycle fatigue regime

Fatigue fracture of high-strength steels often occurs from small defect on the surface of a material or from non-metallic inclusion in the subsurface zone of a material. Under rotating bending loading, the S-N curve of high-strength steels consists of two curves corresponding to surface defect-induced fracture and internal inclusion-induced fracture. The surface defect-induced fracture occurs at high stress amplitude levels and low cycles. However, the subsurface inclusion-induced fracture occurs at low stress amplitude levels and high-cycle region of more than 10⁶ cycles (giga-cycle fatigue life). There is a definite stress range in the S-N curve obtained from the rotating bending, where the crack initiation site changes from surface to subsurface, giving a stepwise S-N curve or a duplex S-N curve. On the other hand, under cyclic axial loading, the S-N curve of high-strength steels displays a continuous decline and surface defect-induced or internal inclusion-induced fracture occur in the whole range of amplitudes. In this paper, influence factors on S-N curve characteristics of high-strength steels, including size of inclusions and the stress gradient of bending fatigue, were investigated for rotating bending and cyclic axial loading in the giga-cycle fatigue regime. Then, based on the estimated subsurface crack growth rate from the S-N data, effect of inclusion size on the dispersion of fatigue life was explained, and it was clarified that the shape of S-N curve for subsurface inclusion-induced fracture depends on the inclusion size.     

An improved neural computing method for describing the scatter of S–N curves

The reliability evaluation of structural components under random loading is affected by several uncertainties. Proper statistical tools should be used to manage the large amount of causalities and the lack of knowledge on the actual reliability-affecting parameters. For fatigue reliability prediction of a structural component, the probability distribution of material fatigue resistance should be determined, given that the scatter of loading spectra is known and a suitable damage cumulating model is chosen. In the randomness of fatigue resistance of a material, constant amplitude fatigue test results show that at any stress level the fatigue life is a random variable. In this instance fatigue life is affected by a variety of influential factors, such as stress amplitude, mean stress, notch factor, temperature, etc. Therefore a hybrid neural computing method was proposed for describing the fatigue data trends and the statistical scatter of fatigue life under constant loading conditions for an arbitrary set of influential factors. To support the main idea, two examples are presented. It can be concluded that the improved neural computing method is suitable for describing the fatigue data trends and the scatter of fatigue life under constant loading conditions for an arbitrary set of influential factors, once the optimal neural network is designed and trained.