基于概率指数模型的区域滑坡危险性评价

影响滑坡的因子很多,区域滑坡危险性因子的确定是治理滑坡的关键。以马来西亚金马仑高原作为研究区,选取岩性、地形、地貌、道路、土地利用等环境因子,在GIS平台上运用双变量统计方法,分析了滑坡与各环境因子之间的关系,根据滑坡面积密度建立了概率指数评价模型,进行了研究区滑坡危险性评价,结果表明,此模型具有较好的评价精度。     

客户群及个体服务选择影响因子研究

客户在选择服务过程中,一方面会受到自身不断积累的经验的影响,另一方面也会受到群体当中其他成员意见的影响。通过研究客户个体以及客户之间的相互协作关系,得出客户群及个体服务选择的三个主要影响因子：惯性影响因子、个体影响因子和群体影响因子。通过粒子群优化算法的群体智能仿真工具,对客户服务选择的影响因子与选择结果之间的复杂非线性关系进行模拟仿真实验,通过定量数据的模拟,精确找出各个影响因子对选择结果的影响程度,选择结果对影响因子的敏感度,以及各个影响因子之间的最佳搭配比例。该研究对于优化客户与供应商服务之间双向选择提供了指导方向。     

基于PCA的神经网络在港口货物吞吐量中的预测

分析选取了可能影响港口货物吞吐量的因素,采用PCA技术提取关键因子,最后以提取的关键因子作为神经网络的神经输入元,分别建立BP神经网络预测模型和GRNN神经网络预测模型。以上海港口为例,对港口货物吞吐量进行预测并对预测结果给予分析。     

基于NDVI阈值法反演地表比辐射率的参数敏感性分析

地表比辐射率是反演地表温度的重要因子,普遍应用于自然界中的水热交换和辐射传输过程。本文通过对基于NDVI阈值法反演地表比辐射率的相关参数进行敏感性研究,确定了影响NDVI阈值法反演地表比辐射率的关键参数,以期通过关键参数获取方法的改进和参数不确定性的降低来提高NDVI阈值法的反演精度。研究以Valor和Caselles在1996年提出的植被指数混合模型为理论基础、湖北省荆门市为研究区域,使用Land-sat TM5数据,采用控制变量法,对NDVI阈值法中影响比辐射率反演精度的大气因子、地形因子、纯像元NDVI阈值、纯像元比辐射率值进行敏感程度的数学分析。研究发现,4大因子敏感性程度:纯像元比辐射率值>纯像元NDVI阈值>地形因子>大气因子,其中纯像元比辐射率值和纯像元NDVI阈值为关键参数;4大因子影响程度:大气因子>纯像元比辐射率值>地形因子>纯像元NDVI阈值。     

利用关键因子过滤的正则表达式匹配算法

正则表达式(regular expression,RE)是一种能够提供复杂查询能力的技术,其通过特定的语法结构来描述一类文本的共同特征。正则表达式强大的表达能力和简洁的语法,使得其在各个领域都被广泛地应用。为了提高正则表达式的匹配效率,提出了一种利用关键因子进行过滤的匹配技术,关键因子指的是在文本中具有最小出现频率的有效过滤因子。由于实际文本中字符并不是均匀分布的,子串在文本中出现频率的差异将影响过滤因子的过滤能力。通过考虑有效过滤因子在文本中出现的频率,关键因子能获得更好的过滤能力。提出了利用正则表达式的划分来求取关键因子的算法,进而通过关键因子来过滤候选位置。通过在真实的蛋白序列和英文文本上进行实验,说明了基于关键因子过滤的匹配方法可以有效地提升正则表达式的匹配性能。     

产出率并行加速比模型

针对并行计算系统的性能度量问题,在产出率度量模型的基础上,建立综合系统可靠性、通信、并行化控制和成本投入要素的产出率并行加速比模型,分析总结模型中各要素影响产出率并行加速比的关键因子,包括容错开销因子、通信开销因子、并行控制开销因子及成本开销因子,对上述关键因子进行模拟实验,以验证该模型的有效性。     

基于灰色关联分析的Apriori算法的研究及应用

关联分析是一种重要的数据挖掘技术。本文结合房地产行业的特点,将关联分析方法应用于对消费者购房行为的研究中。传统的关联规则挖掘算法——Apriori算法在实际应用中存在着计算量大、挖掘效率低、产生大量不相关的关联规则等问题。为了减少计算量、提高挖掘效率、发现有价值的关联规则,提出了一种灰色关联度分析算法和Apriori算法结合的研究方法。首先采用灰色关联度分析算法得出影响消费者购房需求和偏好的关键因子,然后采用Apriori算法对关键因子和目标因子之间进行关联规则挖掘。以某市问卷调查的消费者信息记录进行建模,结果表明该关联分析方法具有较高的挖掘效率并且研究结果具有合理性和准确性。     

基于灰色关联分析的Apriori算法的研究及应用

关联分析是一种重要的数据挖掘技术。文中结合房地产行业的特点,将关联分析方法应用于对消费者购房行为的研究中。传统的关联规则挖掘算法-Apriori算法在实际应用中存在着计算量大、挖掘效率低、产生大量不相关的关联规则等问题。为了减少计算量、提高挖掘效率、发现有价值的关联规则,提出了一种灰色关联度分析算法和Apriori算法结合的研究方法。首先采用灰色关联度分析算法得出影响消费者购房需求和偏好的关键因子,然后采用Apriori算法对关键因子和目标因子之间进行关联规则挖掘。以某市问卷调查的消费者信息记录进行建模,结果表明该关联分析方法具有较高的挖掘效率并且研究结果具有合理性和准确性。     

DCT水印中拉伸系数与嵌入位置的选择

DCT域如何确定嵌入位置与拉伸因子α是影响数字水印稳健性的关键。对比了不同嵌入位置和拉伸因子对数字水印鲁棒性的影响，并且据此给出了一种DCT域数字水印的嵌入位置和拉伸因子的确定方法。实验结果表明，该方法简单有效。     

实现准确预报的降水预报模型构建方法研究

研究降水预报模型的构建问题,提高预报准确度.在降水预报技术中,选用较多的预报因子构建预报模型并根据预报因子之间的联系训练得到准确模型,但受空气不稳定特性的影响使得预报因子之间的非线性联系极难准确描述,传统预报模型构建方法不能有效获取预报因子之间的联系,无法训练得到准确的预报模型,造成降水预报准确度不高的问题.为解决上述问题,提出模糊聚类算法构建降水预测模型的方法.根据空气的流动特性,采用模糊聚类算法分析预报因子内部的直接关联特性从而准确表述预报因子之间的联系,构建初始预报模型,并据最小二乘回归方法训练得到降水预报模型.实验表明,模糊聚类算法能够有效获取预报因子之间的联系,准确构建和训练预报模型,实现了降水的准确预报.     

Finite Volume model for diffusion- and activation-controlled pitting corrosion of stainless steel

Steel corrosion plays an adversary, but central role in different technological fields. Reasonable modeling of corrosion calls for a profound theoretical study of the underlying mechanisms. The present paper is concerned with mathematical modeling of (localized) pitting corrosion: We derive the mass conservation law of a dissolving body hosting a metal/solution interface which separates the solid metal electrode from the liquid electrolyte, and we complement the mass balance law by a thermally activated, potential-dependent electrochemical kinetics law for the dissolution reaction and by Fick’s law for ionic transport in the electrolyte solution. As long as the electrolyte solution adjacent to the electrode boundary does not reach its saturation level, the Arrhenius-type dissolution kinetics law governs the dissolution rate, and Fick’s law governs solely the concentration distribution in the electrolyte solution (activation-controlled corrosion mechanism). However, once the saturation level is reached at the electrode boundary, the pit depth evolution is governed by the diffusion of ions from the electrode boundary into the electrolyte-filled pit (diffusion-controlled corrosion mechanism). Corresponding mathematical solutions (time-dependent fields of concentrations) are obtained by means of the Finite Volume Method. For experimentally supported model input values (concerning dissolution activity, corrosion potential, transfer coefficient, metal charge number, ionic saturation concentration, and solid metal concentration), the influence of the overpotential on the corrosion characteristics (pit depth and shape evolution, current density, ionic concentrations in electrolyte) is shown by means of 1D and 2D simulations.     

FEM analyses for influences of stress corrosion and pressure solution on THM coupling in dual-porosity rock mass

With the models of stress corrosion and pressure solution, by Yasuhara et al., two computation conditions were designed for a hypothetical nuclear waste repository in an unsaturated dual-porosity rock mass: (i) the fracture apertures are changed with the stress corrosion and pressure solution (the porosity of rock matrix is also a function of stress); (ii) the fracture apertures and the porosity of rock matrix are constants. Then the corresponding two-dimensional FEM analyses for the coupled thermohydro-mec...     

Numerical analysis on corrosion resistance of mild steel structures

Corrosion resistances of mild steel specimens according to artificial neural network (ANN) analysis were investigated in the scope of this study. Corrosion rate values were taken into numerical analysis as a result of experimental studies under corrosive aggressive media. Mild steel specimens were selected according to the section type varieties such as box, tube and cornier. All steel specimens were subjected to the aggressive media formed using sodium chloride (NaCl with 99.8 % purity) solutions with 3.5, 5.0 and 7.0 % ratios per one liter distilled water and only distilled water. The reduction in corrosion rate has been observed and considered according to some corrosion loss respects. Corrosion rate prediction models were established between corrosion rate and parameters such as mass loss obtained by experimental studies using ANN. ANNs are computing systems that simulate the biological neural systems of the human brain. In this study, ANN analysis was generated to predict the corrosion rate values after experimental studies. Experimental and predicted values were compared by each other and it is seen that a strong relationship was established between them.     

Corrosion behavior of a structural nickel electrodeposit

The corrosion behavior of electrodeposited structural Ni (LIGA Ni) was assessed under aqueous and atmospheric conditions. Corrosion rates were measured and damage morphology was documented for comparison with wrought materials such as commercially available Ni 201 and high purity (99.999) Ni. As-fabricated LIGA Ni showed excellent corrosion resistance in aqueous NaCl solution even when galvanically coupled to a more noble material such as gold. Mechanically polished LIGA Ni showed corrosion resistance comparable to that of Ni 201, whereas polished 99.999 Ni had the best overall corrosion performance. Exposure to an aggressive atmospheric environment resulted in a higher density of corrosion sites on the LIGA material than on the control materials; however, the composition of the corrosion products (nickel-chloride) and the morphology of the attack was nominally the same on all tested samples. Overall, no new corrosion modes or susceptibilities were identified for LIGA Ni compared to wrought Ni materials. The superior corrosion resistance of the as-fabricated LIGA compared to mechanically polished LIGA, is discussed in terms of surface property modification during a chemical processing step.The authors would like to thank Sam Lucero for carrying out the atmospheric exposure testing and Steve Goods for assisting with sample procurement. Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the U.S. Dept. of Energy under Contract DE-AC04-94AL85000.     

基于AM1量子化学方法的醇胺类缓蚀剂在模拟混凝土孔溶液中对钢筋缓蚀作用研究

用电化学极化曲线的方法评价了几种醇胺化合物在混凝土模拟孔溶液中对钢筋的缓蚀效果,用Gaussian03程序中的AM1方法计算了这几种醇胺化合物的量子化学参数,并采用最小二乘法,分别将它们的前线分子轨道能级、氮氧原子上的净电荷、分子偶极距以及热力学参数与相对缓蚀效率进行拟合.用所拟合的方程预测了这些醇胺的缓蚀效率,预测结果与实验结果基本相符.     

Lattice Boltzmann simulation of solution chemistry for crevice corrosion

We apply the two-dimensional lattice Boltzmann method (2D LBM) to the simulation of solution chemistry for crevice corrosion. The 2D distributions of pH and electrical potential are obtained by the numerical simulation. The critical value of pH which brings about the rapid crevice corrosion and the incubation period until the solution reaches this pH are estimated from the simulation results. It is found that the estimated pH and incubation period are in nearly agreement with experiment.     

Application of steel thin film electrical resistance sensor for in situ corrosion monitoring

The corrosion sensor should have high sensitivity enough to measure the corrosion rate in mild corrosive environments and the ability to detect the corrosion mechanism. Therefore, our goal is to develop and apply a steel thin film electrical resistance (TFER) sensor based on the measurement of changes in electrical resistance of the sensing elements in order to follow the corrosion of steel in a wide range of environments. The sensor with a thickness of 600 nm is fabricated by DC magnetron sputter deposition of steel on an Al₂O₃ substrate, followed by silk screen printing to improve the sensitivity of the sensor, especially to measure the corrosion rate in low corrosive environments such as anoxic corrosion in neutral solutions, steel protected by protective measures like a corrosion inhibitor or cathodic protection, and atmospheric corrosion. The sensor also has multiple-line sensing elements to detect the localized corrosion of steel. The TFER sensor is laboratory and field tested. All the studies demonstrate that the newly developed TFER sensor can be a promising and reliable tool for corrosion monitoring of steel exposed to various environments.     

基于改进粒子群算法的模糊神经网络

油气管道腐蚀失效检测具有随机性、复杂性、多因素性和非线性等特点,利用精确的数学模型描述有一定的难度. 本文提出了一种基于混合改进粒子群算法的模糊神经网络的管道腐蚀动态检测方法. 优化粒子群算法的收敛性,加快寻找最优解的速度,将该算法用于模糊神经网络模型构建中,建立了基于模糊神经网络的管道腐蚀动态检测模型. 通过利用实际的管道腐蚀检测数据进行诊断应用,取得了较好的检测效果,验证了该模型及算法的可行性和有效性.     

Comparative study of tuning of microfabrication parameters for improving electrochemical performance of platinum and glassy carbon microelectrodes in neural prosthetics

Neural prosthetics, which are increasingly being considered for the dual functionalities of recording and stimulation, are implanted in a corrosive biochemical environment that requires them to possess superior electrical and electrochemical stability and performance. These probes are required to withstand these operating conditions through billions of cycles of pulses of electrical stimulations and also maintain electrochemical sensitivity for potential applications in voltammetry. In this research, microelectrodes made of two material systems; namely, platinum and glassy carbon, supported on a flexible substrate are fabricated and investigated for correlation between process parameters and the electrochemical efficacy of the neural interfaces, particularly charge storage capacity and corrosion rate. Using scanning electron and atomic force microscopies, the correlation between process parameters, surface morphology and topography in both platinum and glassy carbon were investigated. The results demonstrate that changes in surface topography and the rate of corrosion are correlated to variations in the process parameters. Furthermore, the results indicate a relationship between surface roughness and corrosion rate, in which the increase or decrease of the former corresponds to a similar change in the latter.

     

Boundary identification for a 3D Laplace equation using a genetic algorithm

In this paper we consider the identification of the geometric structure of the boundary of the solution domain for the three-dimensional Laplace equation. We investigate the determination of the shape of an unknown portion of the boundary of a solution domain from Cauchy data on the remaining portion of the boundary. This problem arises in the study of quantitative non-destructive evaluation of corrosion in materials in which boundary measurements of currents and voltages are used to determine the material loss caused by corrosion. The domain identification problem is considered as a variational problem to minimize a defect functional, which utilises some additional data on certain known parts of the boundary. A real coded genetic algorithm (RCGA) is used in order to minimise the objective functional. The unknown boundary is parameterized using B-splines. The Laplace equation is discretised using the method of fundamental solutions (MFS). Numerical results are presented and discussed for several test examples.