衣康酸介质中Cl^—和NO3^—对不锈钢点蚀电位的影响

利用动电位法测定３１６Ｌ奥氏体不锈钢和Ｒ１双相不锈钢在Ｃ５Ｈ６Ｏ４－Ｃｌ＾－－ＮＯ３＾－水溶液体系中的阳极极化曲线和点蚀电位,探讨了衣康酸（Ｃ５Ｈ６Ｏ４）介质中Ｃｌ＾－和ＮＯ３＾－对点蚀的影响。结果表明：（１）Ｃｌ＾－浓度［Ｃｌ＾－］的提高导致不锈钢点蚀电位Ｅｂ降低,其关系为Ｅｂ＝ａ－ｂｌｇ［Ｃｌ＾－］。同样条件下,Ｒ１不锈钢的点蚀电位比３１６Ｌ不锈钢高３００￣４００ｍＶ;（２）在含Ｃｌ＾－的衣康     

金属亚稳态孔蚀行为的电化学研究

综述了国内外近期在亚稳态孔蚀行为的研究方法,亚稳态小孔形核、生长的统计规律 ,亚稳态蚀孔生长和再钝化过程的机制及控制因素,亚稳态蚀孔向稳定蚀孔转变的临界条件等方面的 研究进展,并对进一步的研究作出了展望。     

N80钢点蚀试验数据的统计分析

N80钢在特定的腐蚀介质和腐蚀条件下，试样表面出现大量蚀孔.为了得到蚀孔的统计规律，本文用柏松概率分布函数求得腐蚀活性点出现个数的规律，再用古比极值统计第一类近似函数求得最深腐蚀孔深度的概率分布，以此来评价材料的耐点蚀性能.结果表明，对于大量的点蚀数据均可以按此理论进行统计分析.      

孔蚀发展过程动力学分析

根据物质守恒，电荷守恒关系和电化学动力学，对球形，柱形蚀孔且其孔内存在和不存在沉积层，共四种典型状态下蚀孔的发展过程进行动力学分析。得到孔蚀电流，蚀孔深度和孔径随时间的变化关系。结果表明：孔蚀电流随时间发展共有四种特征函数，ｔ＾１／２，ｔ，ｔ＾２和ｔ＾＊ｌｎ（ｔ），每一函数均对应特定的蚀孔发展状态。此四种函数构成一般蚀孔电流随时间关系的基集合，线性组合后得到普遍性孔蚀发展动力学方程。     

1Cr18Ni9Ti不锈钢形变诱发马氏体相变规律及其对孔蚀敏感性的影响

通过低温（－７０℃）拉伸制备不同马氏体相交量的１Ｃｒ１８Ｎｉ９Ｔｉ试样，用ＸＲＤ、ＴＥＭ及金相观察研究形变诱发马氏体相变的规律。用电化学方法研究。α’马氏体（铁磁相）含量对１Ｃｒ１８Ｎｉ９Ｔｉ钢在含Ｃｌ－溶液中孔蚀敏感性的影响。结果表明：随试样变形量加大，形变诱发马氏体中铁磁性的α’马氏体含量不断增大，而ε马氏体相的量始终较小。材料的孔蚀敏感性先随铁磁相含量的增大而增大；当铁磁相含量达到４．５８％以后，孔蚀敏感性反而渐降；当铁磁相含量超过２５．５％后，孔蚀敏感性又增加。     

1Cr18Ni9Ti不锈钢的马氏体相变量与孔蚀敏感性的相关性 …

研究了ＡＩＳＩ３２１亚稳态奥氏体不锈钢在－７０℃（液氮气氛）经不同程度拉伸形变得到的含有不同α‘－马氏体的试样在中性含氯离子介质中，材料的马氏体相变量与孔蚀敏感性的关系。孔蚀击蚀电位，位蚀诱导期和孔数的测试结果均表明，当α’－马氏体含量约小于５％和大于１５％时，经形变诱发马氏体相变的１Ｃｒ１８Ｎｉ９Ｔｉ奥氏体不锈钢在中性ＮａＣｌ溶液中，孔蚀敏感性随α‘－马氏体含量的增加而增大，当α’－马氏体含量在     

304不锈钢孔蚀过程原位图象采集与分析

建立了恒电位原位图象采集系统和测试方法，用ＶｉｓｕａｌＣ＋＋编制的程序对３０４不锈钢恒电位过程图象进行了分析，结果表明，在蚀孔出现过程中图象的灰度变化与蚀孔的产生和发展有直接关系，当发生孔蚀时，灰度值向小的方向移动，灰度统计直方图上出现双峰，通过分析电化学测试参数与图象信息得知两者之间存在的一定的相关性。     

铝阳极氧化膜的蚀孔形貌与蚀孔生长机理研究

用动电位极化法和扫描电镜研究了工业纯铝阳极氧化膜在NaCl溶液中的孔蚀行为．结果表明，蚀孔的生长控制机制随蚀孔的发展而发生变化，蚀孔生长的初期为扩散控制，然后向欧姆控制发展，在蚀孔生长的后期阶段又转为扩散控制．对蚀孔的形貌观察发现，小孔贯穿阳极氧化膜以后优先在基体中生长，形成“半球型”的蚀孔形貌，阳极氧化膜大部分保留在蚀孔上方形成“膜盖”，膜盖上只有一个直径很小的小孔作为蚀孔生长的扩散通道．讨论了蚀孔的生长机制．     

1Cr18Ni9Ti不锈钢形变诱发马氏体相变规律及其对孔敏感性…

通过低温（－７０℃）拉伸制备不同马氏体相变量１Ｃｒ１８Ｎｉ９Ｔｉ试样，用ＸＲＤ，ＴＥＭ及金相观察研究形变诱发马氏体相变的规律。用电化学方法研究α马氏体（铁磁相）含量对１Ｃｒ１８Ｎｉ９Ｔｉ钢在含Ｃｌ＾－溶液中孔蚀敏感性的影响，结果表明，随试样变形量加大，形变诱发马氏体中铁磁性的α马氏体含量不断增大，而ε马氏体相的量始终较小。材料的孔蚀敏感性失随铁磁相含量的增大而增大，当铁磁相含量达到４．５８％以后，     

碳钢孔蚀期间的电流波动特征

用电化学方法研究了碳钢在含Cl^-D的磷酸盐＋硼酸盐缓冲溶液中，在孔蚀电位附近恒电位条件下电流波动的特征。在孔蚀电位Eb及Eb以上，恒电位和动电位极化时都观察到电流波动现象，在本底电流并未连续增大的情况下多次电流波动后可观察到蚀孔，表明在此体系中围绕表面的孔蚀活性点可能会发生反复的亚稳态局部溶解。恒电位下随时间延长电流波动频率降低，电流波动峰值服从正态分布；电位升高导致本低电流和电流波动峰值电流均增大，但对波动频率无明显影响。电流波动峰形状为快速上升，缓慢下降，即孔蚀活性点快速溶解，慢速再纯化，根据电流下降部分计算的再钝化速率服从指数衰减形式     

Molecular Struct ure of P henylt hiourea as a Corrosion Inhibitor for Mild Steel in Hydrochloric Acid

The application of statistical analysis and quantum chemical models on the corrosion inhibition of mild steel in hydrochloric acid in presence of phenylthiourea(PTU) as corrosion inhibitor have been investigated.Two mathematical models were used,second order polynomial model and Arrhenius type equation model.STATISTICA software based on Levenberg-Marquardt estimation method was used to evaluate the coefficients of two Models.It follows that the two models were suitable to represent the corrosion rate dat...     

检测实验室能力验证中四分位数的计算

检测实验室能力验证计划结果处理时,常用稳健统计技术对试验数据进行统计分析和评价。稳健统计技术涉及到标准四分位数间距、四分位数的计算。四分位数在具体的计算过程中出现多个版本的计算模型,从而导致能力验证活动结果的不唯一,影响能力验证活动的公正性。分析了具有代表性的4种四分位数计算模型,依据现有的能力验证活动的成功案例,提出模型二适用于检测实验室能力验证计划的结果评价,可以统一采用。     

汽车冲压模具成本统计方法与系统开发

通过对模具成本组成进行系统分析,并对其设计和制造各个阶段的成本核算模型进行研究,提出一个基于模具设计成本、材料成本、加工制造成本、装配成本以及调试成本的综合统计模型。在NX软件上进行成本统计系统的二次开发,通过规则自动识别模具特征,获取成本统计的输入参数,与数据库中的单价进行匹配,自动计算出相应的成本,并以Excel的形式输出详细成本数据。最后,以一套模具的成本统计实例来验证该统计模型的准确性及系统的可靠性。结果表明,该成本统计系统可以获得比较精确的成本,有较高统计效率,可以为汽车模具企业的科学决策提供数据支撑。     

Comparison of flow behaviors of near beta Ti-55511 alloy during hot compression based on SCA and BPANN models

The flow behavior of Ti-55511 alloy was studied by hot compression tests at temperatures of 973?1123 K and strain rates of 0.01?10 s^?1. Strain-compensated Arrhenius (SCA) and back-propagation artificial neural network (BPANN) methods were selected to model the constitutive relationship, and the models were further evaluated by statistical analysis and cross-validation. The stress?strain data extended by two models were implanted into finite element to simulate hot compression test. The results indicate that the flow stress is sensitive to deformation temperature and strain rate, and increases with increasing strain rate and decreasing temperature. Both the SCA model fitted by quintic polynomial and the BPANN model with 12 neurons can describe the flow behaviors, but the fitting accuracy of BPANN is higher than that of SCA. Sixteen cross-validation tests also confirm that the BPANN model has high prediction accuracy. Both models are effective and feasible in simulation, but BPANN model is superior in accuracy.     

An empirical study on the robust design of a semiconductor-bumping process

Based on empirical data collection, computer simulation, statistical methods, and optimization techniques, this paper presents a study on optimizing the parameters of the solder bumping process in semiconductor fabrication (FAB). The research first collects a set of experimental data from the production site at the FAB. In this research, the experimental data of interest include bump height (BH) and bump shear (BS). Then, the researchers use the regression method for the experimental data on controllable factors to build an empirical model for problem analysis. The resulting empirical model is used to generate a set of experimental data to determine the critical controllable factors by design of experiments (DOE). Based on these empirical models, the optimum parameter values of controllable factors are found by optimization techniques such as mathematical programming. Because there are two quality characteristics, of interest in this research, a sensitivity analysis is performed during the problem analysis. As a result, a robust parameter design for quality improvement can be achieved for process design and planning.     

Use of a 3D optical measurement technique for stochastic corrosion pattern analysis of reinforcing bars subjected to accelerated corrosion

The 3D corrosion patterns of 23 reinforcing bars subjected to accelerated corrosion are characterised using an optical surface measurement technique. A stochastic signal processing methodology is employed for corrosion pattern analysis of the measured data. The statistical analysis of corrosion pattern data shows that a lognormal distribution model can represent the non-uniform distribution of pitted sections along the corroded bars. It was observed that the frequency of corrosion is independent from the mass loss ratio and the length of the bars. Finally, a set of probabilistic distribution models for the geometrical properties of corroded bars is developed.     

基于速率温度参数计算7075铝合金蠕变本构方程

针对高强铝合金蠕变数据存在幂律失效而难于拟合的问题,采用Monkman-Grant关系式,在经典时间温度参数模型的基础上,推导4种不同形式的速率温度参数模型。根据高强铝合金7075在34.4~148.9℃下的蠕变数据,利用多元线性回归方法,计算得出基于不同形式速率温度参数的材料稳态蠕变方程。结合统计检验方法,评价不同模型下蠕变方程的拟合效果。结果表明:在显著性水平5%的条件下,OSD’模型下稳态蠕变速率实测数据与拟合结果的对数差值不满足正态分布。OSD’、LM’模型下拟合数据的对数值无法完全落入理想拟合线双侧96.5%的置信区间内。RMB’、MH’模型下实测与拟合对数值之间的线性相关系数均大于0.994,对应的残差平方和分别为0.2797、0.2800。基于RMB’、MH’模型的蠕变本构方程可以较好地描述7075铝合金在实验条件范围内的稳态蠕变行为。     

Predictions on surface finish in electrical discharge machining based upon neural network models

Predictions on the surface finish of work-pieces in electrical discharge machining (EDM) based upon physical or empirical models have been reported in the past years. However, when the change of electrode polarity has been considered, very few models have given reliable predictions. In this study, the comparisons on predictions of surface finish for various work materials with the change of electrode polarity based upon six different neural-networks models and a neuro-fuzzy network model have been illustrated. The neural-network models are the Logistic Sigmoid Multi-layered Perceptron (LOGMLP), the Hyperbolic Tangent Sigmoid Multi-layered Perceptron (TANMLP), the Fast Error Back-propagation Hyperbolic Tangent Multi-layered Perceptron (Error TANMLP), the Radial Basis Function Networks (RBFN), the Adaptive Hyperbolic Tangent Sigmoid Multi-layered Perceptron, and the Adaptive Radial Basis Function Networks. The neuro-fuzzy network is the Adaptive Neuro-Fuzzy Inference System (ANFIS). Being trained by experimental data initially screened by the Design of Experiment (DOE) method, the parameters of the above models have been optimally determined for predictions. Based upon the conclusive results from the comparisons on checking errors among these prediction models, the TANMLP, RBFN, Adaptive RBFN, and ANFIS model have shown consistent results. Also, it is concluded that the further experimental results have agreed to the predictions based upon the above four models.     

一次枝晶间距的数值统计模型

从统计学随机性和动力学必然性的角度，通过对定向凝固界面形态演化过程的分析，结合现有的实验观察与已有的枝晶模型，采用统计学随机模拟的方法提出了一个在恒速定向凝固条件下列状晶生长一次枝晶间距的数值统计模型，模型所得数值结果与实验结果吻合得很好。     

Microstructural modeling approach applied to rock material

The importance of the microstructural parameters in rock mechanical behavior has been investigated by several authors. Moreover, the Weibull statistical model has been used to characterize the heterogeneity of several materials on the basis of the concept that the microscopic defects within the material determine their mechanical strength. The modeling of different rocks is a topic that is fundamental for the prediction of rock fragmentation. In this article, the analysis of rock microstructure is performed using the microstructural modeling approach, which consists of the simplification, quantification, and modeling of the main properties of rock microstructure. The grain size, grain shape, and microcracks are modeled by means of statistical density functions, namely, Cauchy, chi-squared, exponential, extreme value, gamma, Laplace, normal, uniform, and Weibull. It is found that the Weibull distribution is the most appropriate statistical model of the grain size and grain shape, when compared with the other eight statistical models. Regarding microcracks, the results show that the gamma distribution is the most appropriate model. The Weibull and gamma distributions are then used to analyze the heterogeneity of the microstructure. This is done by comparison of the statistical models of each microstructural property evaluated in several thin sections of the same rock. It is found that with respect to grain size and grain shape, the rock is homogeneous, while the size distribution of the microcracks shows a clear trend toward less homogeneity. The microstructural modeling approach is important for modeling, characterizing, and analyzing the microstructure of rock material. Among other applications, it can be used to explain differences in the mechanical behavior obtained in testing several specimens.