The method of fundamental solutions for problems in static thermo-elasticity with incomplete boundary data

An inverse problem in static thermo-elasticity is investigated. The aim is to reconstruct the unspecified boundary data, as well as the temperature and displacement inside a body from over-specified boundary data measured on an accessible portion of its boundary. The problem is linear but ill-posed. The uniqueness of the solution is established but the continuous dependence on the input data is violated. In order to reconstruct a stable and accurate solution, the method of fundamental solutions is combined with Tikhonov regularization where the regularization parameter is selected based on the L-curve criterion. Numerical results are presented in both two and three dimensions showing the feasibility and ease of implementation of the proposed technique.     

Real‐time updating of structural mechanics models using Kalman filtering,modified constitutive relation error,and proper generalized decomposition

The paper aims at proposing a new strategy for real‐time identification or updating of structural mechanics models defined as dynamical systems. The main idea is to introduce the modified constitutive relation error concept, which is a practical tool that enables to efficiently solve identification problems with highly corrupted data, into the Kalman filtering, which is a classical framework for data assimilation. Furthermore, a PGD‐based model reduction method is performed in order to optimize capabilities of the online updating strategy. Performances of the proposed approach, in terms of robustness gain and computational cost reduction, are illustrated on several unsteady thermal applications. Copyright © 2015 John Wiley & Sons, Ltd.     

Comparison of the identification performance of conventional FEM updating and integrated DIC

Full‐field identification methods are increasingly used to adequately identify constitutive parameters to describe the mechanical behavior of materials. This paper investigates the more recently introduced one‐step method of integrated digital image correlation (IDIC) with respect to the most commonly used two‐step method of finite element model updating (FEMU), which uses a subset‐based DIC algorithm. To make the comparison as objective as possible, both methods are implemented in the most equivalent manner and use the same FE model. Various virtual test cases are studied to assess the performance of both methods when subjected to different error sources: (1) systematic errors, (2) poor initial guesses for the constitutive parameters, (3) image noise, (4) constitutive model errors, and (5) experimental errors. Results show that, despite the mathematical similarity of both methods, IDIC produces less erroneous and more reliable results than FEMU, particularly for more challenging test cases exhibiting small displacements, complex kinematics, misalignment of the specimen, and image noise. Copyright © 2015 John Wiley & Sons, Ltd.     

获取界面响应不可测数据的频响探针关键技术研究

目的针对传统逆子结构理论在求解过程中界面响应难以实测的问题,提出一种利用频响探针技术来获取该界面响应的关键技术。方法首先基于该频响探针的动力学微分方程,从理论上推导了该频响探针技术的理论公式,然后对建立的二级单点刚性耦合系统进行了有限元数值验证,将利用频响探针技术预测得到的难测原点频响函数与有限元计算值进行比较,并将该预测值代入逆子结构理论公式中,得到了部件频响函数的预测值,将该预测值与有限元计算值进行了对比验证。结果预测值与有限元计算值高度吻合,验证了该理论的准确性。结论该频响探针关键技术在获取界面响应不可测数据方面,有很好的应用价值。     

L-半胱氨酸辅助反相微乳法制备Ag_2S纳米晶

选用TX-100/环己烷/正己醇/水反相微乳体系,以Ag NO_3为Ag源、Na_2S·9H2O为S源、L-半胱氨酸为结构导向剂,室温下制备了高晶化度、直径为10—50 nm的Ag_2S纳米晶,并考察了影响其粒径大小的因素。紫外-可见吸收光谱表明,Ag_2S纳米晶在290 nm处呈现强吸收,与体相Ag2S(1 240 nm)相比,其吸收边发生了明显的蓝移。通过调控微乳体系中ω0(水与表面活性剂物质的量比)、Ag+与L-半胱氨酸的物质的量比、反应物浓度等可以实现对产物尺寸和形貌的调控。     

反蛋白石结构光子晶体及其应用的研究

反蛋白石结构光子晶体因具有完全光子带隙、制备材料广泛、特殊的周期结构、大的比表面积和连通的孔洞结构,近年来在自发辐射的调制、提高光催化反应速率和染料敏化太阳能电池反应速率等领域成为研究热点之一,并且在光、电、催化、传感、显示、检测等领域有着巨大的应用价值。介绍了反蛋白石结构光子晶体的基本概念及制备方法,阐述了反蛋白石结构在材料自发辐射的调制、能量传递的调制、促进物理化学反应、外界环境响应材料等方面的作用及其应用。     

Structural damage identification via time domain response and Markov Chain Monte Carlo method

The present work addresses the problem of structural damage identification built on the statistical inversion approach. Here, the damage state of the structure is continuously described by a cohesion parameter, which is spatially discretized by the finite element method. The inverse problem of damage identification is then posed as the determination of the posterior probability densities of the nodal cohesion parameters. The Markov Chain Monte Carlo method, implemented with the Metropolis–Hastings algorithm, is considered in order to approximate the posterior probabilities by drawing samples from the desired joint posterior probability density function. With this approach, prior information on the sought parameters can be used and the uncertainty concerning the known values of the material properties can be quantified in the estimation of the cohesion parameters. The assessment of the proposed approach has been performed by means of numerical simulations on a simply supported Euler–Bernoulli beam. The damage identification and assessment are performed considering time domain response data. Different damage scenarios and noise levels were addressed, demonstrating the feasibility of the proposed approach.     

Online dynamic cardiac imaging based on the elastic-net model

Purpose: The purpose of this work was to develop an online dynamic cardiac MRI model to reconstruct image frames from partial acquisition of the Cartesian k-space data, which utilizes structural knowledge of consecutive image frames. Materials and methods: Using an elastic-net model, the proposed algorithm reconstructs dynamic images using both L₁ and L₂ norm operations. The L₁ norm enforces the sparsity of the frame difference, while the L₂ norm with motion-adaptive weights catches the internal structure of frame differences. Unlike other online methods such as the Kalman filter (KF) technique, the new model requires no assumption of Gaussian noise, and can faithfully reconstruct the dynamic images within a compressive sensing framework. Results: The proposed method was evaluated using simulated dynamic phantoms with 40 frames of images (128?×?128) and a cardiac MRI cine of 25 frames (256?×?256). Both results showed that the new model offered a better performance than the online KF method in depicting simulated phantom and cardiac dynamics. Conclusion: It is concluded that the proposed imaging model can be used to capture a large variety of objects in motion from highly under-sampled k-space data, and being particularly useful for improving temporal resolution of cardiac MRI.     

Analytical study for the estimation of thermal properties of processed meat based on hyperbolic heat conduction model

This study proposes an analytical method in conjunction with existing experimental temperature to estimate the unknown relaxation time and thermal diffusivity of processed meat based on the hyperbolic heat conduction model. This analytical method is a combination of the Laplace transform and least squares methods. The thermal contact resistance at the interface between adjacent samples at different temperatures is assumed to be negligible. The relaxation time is estimated from the temperature jump at a specific measurement location. The thermal diffusivity is determined from the definition of the dimensionless spatial coordinate and the resulting relaxation time. The results show that the relaxation time and thermal diffusivity obtained are in good agreement with the existing results. The obtained dimensionless temperature history at a specific measurement location is close to the experimental temperature data. This means that the Cattaneo–Vernottee (CV) model can be suitable for this study. The proposed analytical inverse method can be applied to determine a more accurate estimate of such problems. A comparison of the estimate obtained from CV and dual phase lag models is made.