用局部应力概念进行相对寿命估算

 借助材质为Metasafe 900（与27MnSiVS6相似）和AlCuMg2的与构件相似试件的工作强度试验的已有寿命数据，研究了将材料疲劳特性转换成构件疲劳特性的可能性。分析了材料、构件几何形状以及载荷的变化对承载能力的影响。算例表明，通过估算取决于构件几何形状和加载次序的材料承载能力，可以使局部应力概念下的这种疲劳特性转换成为可能。     

蠕变/疲劳共同作用下寿命估算方法

通过载荷谱转换，将带保载时间的蠕变／疲劳循环用不带保载时间的纯疲劳循环代替，提出蠕变／疲劳共同作用时的寿命估算方法。对１２Ｃｒ１ＭｏＶ钢母材和焊材的蠕变／疲劳交互作用试验数据的分析结果表明，本方法方便、实用。提出一个表征蠕变／疲劳连续加载时交互作用行为的参数，蠕变／疲劳寿命比。分析认为，材料的蠕变疲劳交互作用行为与该比值的大小腾。材料在蠕变／疲劳共同作用下呈这是呈负交经作用，并非材料固有的特性，还取决于载荷条件。     

一种基于临界平面法的多轴疲劳寿命预测模型

在多轴交变应力作用下,由于非比例循环附加强化效应导致疲劳寿命降低。针对这一问题,以薄壁圆管疲劳试件为研究对象,在分析临界平面上剪应变和正应变随相位角变化特征的基础上,引入了一个新的有效循环变量———临界平面上的等效应力,提出了一种新的多轴疲劳预测模型。新的损伤参量不含经验常数,便于工程实际的运用。通过和铝合金7075-T651多轴疲劳实验数据比较,结果表明,所提出的多轴寿命预测模型具有更好的预测精度,适用于比例与非比例加载条件。     

Integrated Approach for Field Reliability Prediction Based on Accelerated Life Testing

ABSTRACT

To predict field reliability using analytical modeling, several important reliability activities should be conducted, including failure mode and effect analysis, stress and usage condition analysis, physics of failure analysis, accelerated life testing and modeling, and cumulative damage modeling if needed. With all of the mentioned activities and results, the field reliability confidence limit can be predicted at a certain confidence level, if a modeling framework can be established. This article builds such an integrated process and comprehensive modeling framework, especially with cumulative damage rules when the certain field stresses are random processes. An engineering product is provided as an application to illustrate the effectiveness of proposed method.     

蠕变裂纹启裂和扩展的局部损伤理论

根据局部损伤理论和相似原理，给出了蠕谱裂纹启列前的孕育上下限时间并推导了蠕变裂纹扩展率方程。在常载荷下用２．２５Ｃｒ－１Ｍｏ钢作了蠕变裂纹扩展试验，高拘束度使早期局部损伤发展迅速，实验结果与孕育时间下限接近。稳态预测值由于忽略未开裂部分材质劣化而略氏于实验结果值。有限元模拟损伤演变过程。表明稳态裂纹扩展民实验结果吻合。     

Fatigue Strength and Life Prediction of a MAR-M247 Nickel-Base Superalloy Gas Turbine Blade with Multiple Carbide Inclusions

Strength of Materials - Casting of a gas turbine blade from MAR-M247 nickel-base superalloy is followed by multiple carbide precipitates as a result of solidification. The microstructure of carbide...     

气瓶表面裂纹扩展规律与寿命估算的研究

基于Franc3D数值模拟法及子模型技术,对气瓶瓶筒处表面裂纹进行裂纹扩展的动态数值模拟及三维应力强度因子计算,证明该方法的可行性,并用公式迭代法验证该方法的准确性。在此计算结果基础上,对两初始裂纹a_0=3 mm、c_0=6 mm及a_0=3 mm、c_0=9 mm的剩余寿命进行了估算,考虑安全裕度后计算得到两初始裂纹剩余寿命分别为3.5 a和2.6 a。     

A Neuro-Fuzzy Approach to Road Traffic Congestion Prediction

The fast-paced growth of artificial intelligence applications provides unparalleled opportunities to improve the efficiency of various systems. Such as the transportation sector faces many obstacles following the implementation and integration of different vehicular and environmental aspects worldwide. Traffic congestion is among the major issues in this regard which demands serious attention due to the rapid growth in the number of vehicles on the road. To address this overwhelming problem, in this article, a cloud-based intelligent road traffic congestion prediction model is proposed that is empowered with a hybrid Neuro-Fuzzy approach. The aim of the study is to reduce the delay in the queues, the vehicles experience at different road junctions across the city. The proposed model also intended to help the automated traffic control systems by minimizing the congestion particularly in a smart city environment where observational data is obtained from various implanted Internet of Things (IoT) sensors across the road. After due preprocessing over the cloud server, the proposed approach makes use of this data by incorporating the neuro-fuzzy engine. Consequently, it possesses a high level of accuracy by means of intelligent decision making with minimum error rate. Simulation results reveal the accuracy of the proposed model as 98.72% during the validation phase in contrast to the highest accuracies achieved by state-of-the-art techniques in the literature such as 90.6%, 95.84%, 97.56% and 98.03%, respectively. As far as the training phase analysis is concerned, the proposed scheme exhibits 99.214% accuracy. The proposed prediction model is a potential contribution towards smart cities environment.     

Applicability of Fatigue Life Prediction Method to Polymer Composites

A prediction method of fatigue strength under an arbitraryfrequency, temperature, and stress ratio is proposed for polymercomposites and its validity is confirmed for the flexural fatiguestrength of satin-woven CFRP laminates. This method is based upon fourhypotheses: (a) same failure process under constant strain-rate (CSR),creep, and fatigue loadings, (b) same time-temperature superpositionprinciple for all failure strengths, (c) linear cumulative damage lawfor nondecreasing stress process, and (d) linear dependence of fatiguestrength upon stress ratio. This method was applied to the flexuralfatigue strength of various unidirectional CFRPs, and the verificationand limitations of this method were discussed.     

基于机器学习的风机叶片开裂预测研究

为了预测风机叶片开裂的状态,使用机器学习的方法对风机叶片状态进行分类预测.首先对SCADA采集的原始数据进行预处理,然后采用逻辑回归与XGBoost集成学习算法对预处理后的数据进行建模,并通过性能度量的评价指标比较两种算法的效果与泛化能力.结果表明,XGBoost在风机叶片开裂的分类预测上有更好的效果,其预测准确率达到...     

Energetical Theories on Fatigue Life Prediction

Current developments on fatigue life predictionmethods have been systematically reviewed.In con-sideration of the irreversibility of energy dissipationduring fatigue damage process,the main contentsfor fatigue damage estimation and localizedequivalence as well as simulation models have beenestablished.A frame of energy-based fatigue lifeprediction method has been proposed,meanwhile,the procedure in application to a practical structurecomponent has been described.     

Fitting Time Series Models for Prediction

The mathematical theory of the best linear prediction of stationary time series presumes that the model generating the series, which can be specified by either the autocovariance function or the spectral density, is known. The true model is, of course, not known in practice, and the procedure is to fit a model and predict as if this fitted model were the truth. The question then is one of deciding whether the resulting predictions are about as good as could be gotten if the truth were known. This paper describes a method for assessing the predictions of the fitting model by an analysis of residuals. In particular, it is argued that the traditional tests of hypothesis for white noise are inappropriate if prediction is the goal, and a method is described for determining whether or not the mean square errors of the predictions arising from the fitted model can be measurably reduced.     

A Parallel Approach to Discords Discovery in Massive Time Series Data

A discord is a refinement of the concept of an anomalous subsequence of a time series. Being one of the topical issues of time series mining, discords discovery is applied in a wide range of real-world areas (medicine, astronomy, economics, climate modeling, predictive maintenance, energy consumption, etc.). In this article, we propose a novel parallel algorithm for discords discovery on high-performance cluster with nodes based on many-core accelerators in the case when time series cannot fit in the main memory. We assumed that the time series is partitioned across the cluster nodes and achieved parallelization among the cluster nodes as well as within a single node. Within a cluster node, the algorithm employs a set of matrix data structures to store and index the subsequences of a time series, and to provide an efficient vectorization of computations on the accelerator. At each node, the algorithm processes its own partition and performs in two phases, namely candidate selection and discord refinement, with each phase requiring one linear scan through the partition. Then the local discords found are combined into the global candidate set and transmitted to each cluster node. Next, a node performs refinement of the global candidate set over its own partition resulting in the local true discord set. Finally, the global true discords set is constructed as intersection of the local true discord sets. The experimental evaluation on the real computer cluster with real and synthetic time series shows a high scalability of the proposed algorithm.     

Finite Element Approach for Failure Analysis of a Gas Turbine Blade

Journal of Failure Analysis and Prevention - In the present work, a case study on the gas turbine blade is undertaken for failure analysis through finite element approach. The analysis is carried...     

大型水轮机叶片快速检测的新方法

为解决大型水轮机叶片尺寸检测这一行业性难题,实现对叶片型面外型尺寸的快速检测,提出了一种基于视觉测量技术的新方法.该方法以摄影测量原理为理论基础,首先在物体表面待测位置粘贴标志点,然后从不同角度拍摄一组照片,作为测量的原始数据输入计算机中进行解析处理.在测量软件中通过对照片组进行图像检测,识别出各张照片中标志点并定位其中心,匹配同名标志点,最后根据标志点的多个二维坐标重建出对应物体点的三维坐标,从而实现对被测对象的数字化建模和测量.现场实验表明,与传统的水轮机叶片检测方法相比,该方法具有工作量小,速度快,成本低,容易实现在线检测,并且不易受现场灰尘、振动、湿度和温度变化等外界因素的干扰.