Monte Carlo Simulations of Observation Time-Dependent Self-Diffusion in Porous Media Models

Observation time-dependent self-diffusion coefficients can be used to obtain microstructural information of porous media. This paper presents two different kinds of Monte Carlo simulations of the self diffusion process of fluids like water in porous systems, a lattice-free method and a lattice-based method. The results for simple porous media model geometries agree well with each other and with published analytical as well as semi-analytical equations. The use of these equations, which are important for the interpretation of Pulsed Field Gradient-Nuclear Magnetic Resonance (PFG-NMR) time-dependent diffusion data with respect to properties of porous media, is discussed.     

A numerical approach to spherical indentation techniques for material property evaluation

In this work, some inaccuracies and limitations of prior indentation theories, which are based on experimental observations and the deformation theory of plasticity, are investigated. Effects of major material properties on the indentation load-deflection curve are examined via finite element (FE) analyses based on incremental plasticity theory. It is confirmed that subindenter deformation and stress-strain distribution from deformation plasticity theory are quite dissimilar to those obtained from incremental plasticity theory. We suggest an optimal data acquisition location, where the strain gradient is the least and the effect of friction is negligible. A new numerical approach to indentation techniques is then proposed by examining the FE solutions at the optimal point. Numerical regressions of obtained data exhibit that the strain-hardening exponent and yield strain are the two key parameters which govern the subindenter deformation characteristics. The new indentation theory successfully provides a stress-strain curve and material properties with an average error of less than 3%.     

In search of physical parameters influenced by flow patterns in a heterogeneous two-phase mixture in microchannels using concomitant measurements

Space transportation systems require high-performance thermal protection and fluid management for systems ranging from cryogenic fluid devices to primary structures, and for propulsion systems exposed to extremely high temperatures, and other space systems, e.g., integrated circuits and cooling/environment control devices for advanced space suits. Although considerable developmental effort is underway to bring promising technologies to a readiness level for practical use, new and innovative methods are still needed. One such method is the Advanced Micro Cooling Module (AMCM), essentially a compact two-phase heat exchanger constructed of microchannels and designed to rapidly remove large quantities of heat from critical systems by incorporating phase transition. This paper describes the results of experimental research in two-phase flow phenomena, encompassing both an experimental and an analytical approach to the incorporation of flow patterns for air–water mixtures flowing in microchannels. Specifically addressed are: (1) design and construction of a sensitive two-phase experimental system which measures both ac and dc components of in situ physical mixture parameters including spatial concentration, using concomitant methods; (2) data acquisition and analysis in the amplitude, time, and frequency domains; and (3) analysis of results including evaluation of in situ physical parameters, and assessment of their validity for application in flow pattern determination.     

基于变形场测量数据主元压缩的模型参量反求方法

利用主元分析法对数字图像相关技术所测结构变形信息进行数据压缩,并进一步用于力学模型未知参量的反求计算。首先,为降低数字图像相关技术所测庞大数据的应用成本,提出利用主元分析法对结构表面变形场数据进行压缩,实现在保留结构表面变形信息主要特征的前提下显著降低数据量的目的;其次,针对压缩后的数据建立了基于最小二乘法的力学模型参量反求模型,并利用高斯牛顿法进行求解;最后,以具体算例从计算精度、收敛速度和抗噪性等方面验证了数据压缩对模型参量反求的效果。研究结果表明,所提方法在显著降低使用数据量的前提下,能够有效提高力学模型参量反求计算的收敛速度,特别是对于包含多个模型参数的反求问题,具有较高的精度和较好的稳定性。     

异质传感器数据的最优线性融合

研究了异质传感器对参数矢量进行的测量，测量数据基于线性均方估计的最优融合算法。提出和证明了异质传感器数据的最优线性融合定理，并得出“精度再差的传感器参与数据融合后都有利于提高系统的测量精度”这一结论。     

应用增量理论考虑应变硬化效应包辛格效应和温度对机械性质影响的自增强厚壁圆筒分析

本文提出的采用增量理论的分析模型和方法可以定量分析应变硬化、包辛格效应和材料机械性质随温度变化等因素对自增强厚壁圆筒中残余应力和操作应力分布的影响.厚壁圆筒看成由N个同轴薄壁圆筒套在一起组成的构件;采用包括弹性、塑性和温度应变的增量型本构关系和相容条件导出了自增强圆筒的基本方程;设计了计算机程序并给出了分析实例。分析结果表明,应变硬化会减小塑性区并降低残余应力;包辛格效应使反向屈服容易出现;温度升高将使残余应力和热应力松驰.     

大数据时代下的化学经验2.0：基于键能的大规模反应途径预测

报道了一个基于键能数据预测反应途径的可编程算法．运用该算法,成功预测了F₂+CH₃Cl气相反应的最优产物(CF₄)和对应的反应途径．提供了一个启示性的化学经验2.0 的例子,并可能开启大数据时代下的大规模反应途径预测的大门．     

Navier‐Stokes equations,Haar wavelets and Reynolds numbers

The paper deals with global solutions of Navier‐Stokes equations with infrared‐damped initial data in the context of Haar wavelets and function spaces of type where .     

A mesh simplification strategy for a spatial regression analysis over the cortical surface of the brain

We present a new mesh simplification technique developed for a statistical analysis of a large data set distributed on a generic complex surface, topologically equivalent to a sphere. In particular, we focus on an application to cortical surface thickness data. The aim of this approach is to produce a simplified mesh which does not distort the original data distribution so that the statistical estimates computed over the new mesh exhibit good inferential properties. To do this, we propose an iterative technique that, for each iteration, contracts the edge of the mesh with the lowest value of a cost function. This cost function takes into account both the geometry of the surface and the distribution of the data on it. After the data are associated with the simplified mesh, they are analyzed via a spatial regression model for non-planar domains. In particular, we resort to a penalized regression method that first conformally maps the simplified cortical surface mesh into a planar region. Then, existing planar spatial smoothing techniques are extended to non-planar domains by suitably including the flattening phase. The effectiveness of the entire process is numerically demonstrated via a simulation study and an application to cortical surface thickness data.