一种基于能量耗散的对接接头疲劳寿命快速预测模型

通过引入ISV(internal state variable)本构模型中的α和β变量,建立了一种与对接接头高周疲劳滞弹性和非弹性行为相关的能量耗散模型,并定义了两个特征应力幅,即标志着可恢复滞弹性和不可恢复非弹性行为开始形成的关键应力幅σ_c0和σ_c1(疲劳极限);借助该能量耗散模型,研究了不同应力幅下的对接接头能量耗散响应情况,发现能量耗散在疲劳极限附近呈现从线性响应到非线性响应的过渡;在此基础上,考虑到当应力幅高于疲劳极限时,全寿命周期的能量耗散存在临界值,结合与损伤相关的非弹性耗散,研发了一种基于损伤累积的疲劳寿命预测模型,并对接头的疲劳寿命进行了快速预测.结果表明,经预测数据和试验数据拟合的中值S-N曲线一致程度较好,从而证明了模型可用于实现对接接头的疲劳寿命快速、精确预测.     

基于Pavlou方法的焊接结构疲劳寿命预测

变幅载荷作用下的疲劳寿命预测一直是焊接结构完整性评估的重要内容.基于Pavlou提出的疲劳损伤区概念,采用BS7608标准中推荐的S-N曲线,运用有限元热传导分析技术,提出了一种焊接结构疲劳寿命的预测方法.针对承载型十字焊接接头、非承载型十字焊接接头和对接焊接接头,开展了二级变幅载荷谱块的拉伸疲劳试验,分别采用Miner模型、M-H模型和Pavlou方法估算了试件的疲劳寿命.结果表明,Pavlou方法的预测精度明显高于其它2种模型,预测寿命与试验寿命误差散射图中数据点的分布形态更加合理,验证了Pavlou方法的精确性和有效性.进一步讨论了焊接接头S-N曲线存活率对疲劳寿命预测精度的影响,提出2.3%存活率可以获得较为满意的预测结果.     

三维曲线焊缝两种建模方法的比较

三维曲线焊缝建模是实现空间焊缝跟踪的关键问题之一.三维焊缝模型有利于减弱噪声干扰,提高系统的稳定性和鲁棒性,使得系统具有容错能力.采用三次参数曲线函数表示空间焊缝,使用最小二乘法建立焊缝的参数函数位置模型,接着使用三次B样条函数建立焊缝位置模型.使用位置模型和其它的特征点坐标之后得到了姿态模型中的方向矢量.分析了两种建模方法的性能,仿真试验证实在同类型和幅度的噪声干扰下,B样条函数模型优于参数曲线函数模型,能够很好地逼近原始三维曲线焊缝.     

钢铝无铆连接疲劳寿命分析

为研究异种板料无铆连接接头在不同工况下的疲劳寿命,通过ABAQUS软件建立无铆连接三维模型模拟接头成形过程.基于6061铝合金和304不锈钢板料的机械性能和应力-寿命曲线,利用Fe-Safe疲劳软件对接头进行剪切式、剥离式和综合式3种工况下的振动疲劳数值模拟.研究结果表明,接头承受的应力越大,疲劳寿命越短;随着接头承受...     

铜合金的疲劳寿命预测

采用平面弯曲疲劳试验,测定了C1100P-1／4H纯铜和C2801P-1／4H黄铜的S-N曲线。结果表明,实验铜合金没有疲劳极限。随外加交变应力增大,疲劳寿命缩短。在相同外加应力条件下,轧制态合金的疲劳寿命高于退火态合金的疲劳寿命。利用Manson—Coffin法则和塑性应变幅与疲劳循环次数的理论关系,通过计算得到了铜合金的理论S-N关系曲线,与实验结果吻合较好,表明该理论S-N关系曲线可用来预测铜合金的疲劳寿命。     

疲劳寿命预测方法综述

综述了疲劳裂纹形成寿命和疲劳裂纹扩展寿命的预测方法,评述了各种不同预测方法的基本假设、估算步骤和特点,并对疲劳寿命预测方法进一步的发展方向作了展望。     

基于Anand模型SnAgCu-X焊点疲劳寿命预测

Anand模型采用有限元法模拟WLCSP器件Sn3.8Ag0.7Cu-X（Ce,Fe）无铅焊点在热循环载荷条件下的应力-应变响应,借助蠕变应变疲劳寿命预测模型SnAgCu,SnAgCuCe,SnAgCuFe焊点疲劳寿命.结果表明,在服役器件整体器件出现明显的变形现象,电路板翘曲严重.从中心到拐角焊点变形-应力-应变逐渐增加,芯片下拐角焊点成为整个结构潜在的危险区域.通过计算WLCSP器件SnAgCu、SnAgCuCe和SnAgCuFe三种焊点的疲劳寿命,证实了SnAgCuCe和SnAgCuFe焊点寿命明显高于SnAgCu焊点,证明了在SnAgCu中添加一定量的铈和铁可以显著提高SnAgCu焊点的使用寿命,分析结果为新型无铅钎料的研发提供理论支撑.     

汽车前轴的疲劳试验及其疲劳寿命的预测

采用成组试验法,对某汽车前轴进行了疲劳寿命试验,对疲劳数据进行了相应的处理后,得到了该汽车前轴P-S-N曲线的数学表达式.通过雨流计数法,得到该汽车前轴各路面载荷谱的均、幅值计数结果,根据Goodman经验疲劳公式,对雨流计数结果进行了零均值应力转换,从而利用Miner线性疲劳累积损伤理论估计随机载荷下该汽车前轴的使用寿命.     

中位数差值及置信区间的两种非参数计算方法及比较

目的: 介绍了两种计算中位数差值及置信区间的非参数方法——Hodges-Lehmann法与Bootstrap法,采用三种不同分布数据实例比较分析两种方法间的差异,对差异产生原因进行了分析。 方法: 用计算机模拟的方法生成正态、对数正态和双峰分布数据各两个,用两种非参数方法计算每种分布的中位数差值及其置信区间。该模拟过程重复500次。 结果: 当数据符合正态分布时两种方法的结果相近,且与用均值取代中位数的参数法接近。当数据为对数正态分布时Bootstrap法的估计值及置信区间比Hodges-Lehmann法偏大,当数据为对称分布时两种方法计算的估计值结果相近,置信区间略有差异。 结论: 对称分布的数据两种方法的估计值基本一致。非对称情况下Bootstrap法更注重中位数的位置,而Hodges-Lehmann法更多体现了数据的值的差异。     

冲裁毛刺对疲劳寿命影响的数值仿真分析

由于冲裁毛刺对疲劳性能具有很大的影响,运用线弹性模型对止动弹簧片冲裁毛刺进行数值仿真模拟,提出一种考虑冲裁毛刺对疲劳性能影响的疲劳计算方法。通过定量计算毛刺对零件结构几何边界应力的影响程度,得出因冲裁毛刺影响而造成的应力集中程度;综合材料应力-寿命曲线与载荷谱,运用疲劳积累损伤理论计算出零件的疲劳寿命;在数值仿真分析中计算出添加毛刺与未添加毛刺单元的零件疲劳寿命。通过实验对零件的疲劳寿命计算值进行对比分析验证,结果表明:定量考虑冲裁毛刺对结构的影响能够提高疲劳寿命的计算精度。     

基于灰色系统理论的7075铝合金板材疲劳寿命研究

在航空用飞机蒙皮制造过程中,7075铝合金是十分理想的材料。为了更精确地研究并预测7075铝合金的疲劳寿命,对7075-T-651铝合金板材进行了疲劳试验,在应力比R=0.1条件下,测得120~320 MPa不同应力下7075-T-651铝合金板材的疲劳寿命。以试验数据为基础,将灰色系统理论运用到7075-T-651铝合金板材的疲劳寿命预测中,生成GM(1,1)模型,在与试验相同的条件下进行疲劳寿命预测,并将得到的疲劳寿命预测模型S-N曲线与试验数据S-N曲线进行对比。研究表明,所建立的灰色系统理论GM(1,1)模型S-N曲线与试验所得S-N曲线基本吻合,因此,可以通过GM(1,1)模型来预测7075铝合金板材的疲劳寿命。     

Examination of a grit-blasting process for thermal spraying using statistical methods

An experimental study was conducted to develop an understanding of how the grit blasting process, prior to plasma spray coating, affects various properties of the substrate and coatings. A statistical design of experiment approach was used and the results were analyzed using both the linear regression method and average response of factors calculations. The following process variables were studied: grit size (20, 36, 54), blasting pressure (20, 35, 50 psi), blasting duration (4, 6, 8 passes), blasting distance (4, 6 in.), and blasting angle (45°, 90°). Properties such as bond strength, grit contamination, surface roughness, and substrate distortion were evaluated and correlated to the process variables. Based on multiple linear regression results, it was shown that the bond strength can be improved by increasing all of the parameters within the range studied here. No relationship between the surface roughness and bond strength was observed. Grit contamination is mostly influenced by grit size, blasting pressure, and number of blasting passes. The average response method provided indications to the direction of modifying the required properties as a function of process variables. While the average response method agreed mostly with the linear regression predication, some differences are further discussed in the study.     

A biophysical implementation of a bidirectional graph search algorithm to solve multiple goal navigation tasks

The model presented here extends formal analysis (Hasselmo et al., Neural Networks, 15, pp. 689-707, 2002b) and abstract modelling (Gorchetchnikov and Hasselmo, Neurocomputing, 44-46, pp. 423-427, 2002a) of interactions within the hippocampal area (or other cortical areas), which can be flexibly used to navigate toward any arbitrary goal or multiple goals that change on a trial-by-trial basis. The algorithm is a version of a bidirectional breadth-first graph search implemented in simulated neurons using two flows of neural activity. The new model changes the continuous firing rate neuronal representations (Gorchetchnikov and Hasselmo 2002a) to more detailed compartmental versions with realistic parameters, while preserving the qualitative properties analysed previously (Hasselmo et al., 2002b, Gorchetchnikov and Hasselmo 2002a). The case of multiple goals being present in the environment is studied in this paper. The first set of simulations tests the algorithm in the selection of the closest goal. A small difference in distance between the simulated animal and different goals is sufficient for a correct selection. The second set of simulations studies the behaviour of the model when the goals have different saliences. A small salience-based difference between firing rates of the cells providing goal-related input to the model is sufficient for the selection of a more salient goal. This behaviour was tested in three types of environments: a linear track, a T-maze and an open field. Further investigation of quantitative properties of the model should allow it to handle cases when the exact location of the goal is uncertain.