Antiplane elastic wave cloaking using metamaterials,homogenization and hyperelasticity

We consider the problem of how to cloak objects from antiplane elastic waves using two alternative techniques. The first is the use of a layered metamaterial in the spirit of the work of Torrent and Sanchez-Dehesa (2008) who considered acoustic cloaks, motivated by homogenization theories, whilst the second is the use of a hyperelastic cloak in the spirit of the work of Parnell et al. (2012). We extend the hyperelastic cloaking theory to the case of a Mooney–Rivlin material since this is often considered to be a more realistic constitutive model of rubber-like media than the neo-Hookean case studied by Parnell et al. (2012), certainly at the deformations required to produce a significant cloaking effect. Although not perfect, the Mooney–Rivlin material appears to be a reasonable hyperelastic cloak. This is clearly encouraging for applications. We quantify the effectiveness of the various cloaks considered by plotting the scattering cross section as a function of frequency, noting that this would be zero for a perfect cloak.     

Multiscale asymptotic homogenization for multiphysics problems with multiple spatial and temporal scales: a coupled thermo-viscoelastic example problem

A systematic approach for analyzing multiple physical processes interacting at multiple spatial and temporal scales is developed. The proposed computational framework is applied to the coupled thermo-viscoelastic composites with microscopically periodic mechanical and thermal properties. A rapidly varying spatial and temporal scales are introduced to capture the effects of spatial and temporal fluctuations induced by spatial heterogeneities at diverse time scales. The initial-boundary value problem on the macroscale is derived by using the double scale asymptotic analysis in space and time. It is shown that an extra history-dependent long-term memory term introduced by the homogenization process in space and time can be obtained by solving a first order initial value problem. This is in contrast to the long-term memory term obtained by the classical spatial homogenization, which requires solutions of the initial-boundary value problem in the unit cell domain. The validity limits of the proposed spatial–temporal homogenized solution are established. Numerical example shows a good agreement between the proposed model and the reference solution obtained by using a finite element mesh with element size comparable to that of material heterogeneity.     

Structure optimization of quasi one-dimensional acoustic filters with the use of a genetic algorithm

The paper shows how to use a genetic algorithm to design quasi one-dimensional structures with given properties. The superlattices were surrounded by water and made of epoxy resin and glass, with a layer thicknesses selected in such a way that a phononic bandgap occurs in the frequency range of acoustic waves. Multilayer transmission was calculated using the Transfer Matrix Method algorithm. In order to determine the optimal objective function for the genetic algorithm, the entire space of the possibility of the layers’ distribution for a six-layer structure was analyzed. The spread of the transmission integral values even for the 6-layer structure was significant and ranged from 11.9% to 81.5%. Minimizing the value of the transmission integral as an objective function could lead to a large number of high transmission peaks with a small half width. It allowed the determining of the optimal objective functions for minimizing transmission in a given frequency range, and another allowing for its maximization. The phase diagram of the solution space for the transmission integral from the integral of the absolute value of the transmission functions derivative was determined. Transmission of the most and the least optimal six-layer structures was shown depending on the assumed objective function. Then, the analysis of fifteen and thirty-layer structures was carried out. From the dependence of the objective function values for the best individuals for each generation, it was determined that despite carrying out a thousand iterations, the stable state was determined before reaching 250 iterations of the algorithm, and thus the optimal structure was determined. The transmissions ratio of analyzed structures in the studied frequency range (up to 20 kHz) to full transmission (without structures) in this acoustic frequency range for the analyzed optimal 6, 15 and 30-layer structures were 16.78%, 9.6% and 4.41%, respectively.     

Integration of genetic algorithm and a coactive neuro-fuzzy inference system for permeability prediction from well logs data

Permeability is one of the reservoir fundamental properties, which relate to the amount of fluid contained in a reservoir and its ability to flow. These properties have a significant impact on petroleum fields operations and reservoir management. The most reliable data of local permeability are taken from laboratory analysis of cores. Extensive coring is very expensive and this expense becomes reasonable in very limited cases. Thus, the proper determination of the permeability is of paramount importance because it affects the economy of the whole venture of development and operation of a field. In this study, we introduce a new hybrid network based on Coactive Neuro-Fuzzy Inference System (CANFIS). CANFIS is a dependable and robust network that developed to identify a non-linear relationship and mapping between petrophysical data and core samples. Then to improve the system performance, genetic algorithm (GA) was integrated in order to search of optimal network parameters and decrease of noisy data in training samples. An Iranian offshore gas field is located in the Persian Gulf, has been selected as the study area in this paper. Well log data are available on substantial number of wells. Core samples are also available from a few wells. It was shown that the new proposed strategy is an effective method in predicting permeability from well logs.     

基于遗传算法和参数化建模的非线性结构优化

提出了一种对存在接触关系的非线性结构(装配体)进行优化设计的新方法。该方法将遗传算法与结构几何及有限元参数化建模方法相结合，在通用CAE软件的二次开发编程环境中实现对带接触的结构装配体进行结构尺寸和形状优化设计。文中利用该方法对某浮动式闭气结构的重要结构参数和关键构件形状实施了优化设计，使其闭气性能得到大幅度提高，体现了本文方法在解决这类优化问题中的优势。本文的方法有利于拓宽结构优化技术在机械设计领域的应用范围。     

基于ANN-GA协同寻优的动态拉伸试样尺寸优化方法

材料动态拉伸力学性能测试中,动态拉伸试样的几何尺寸对测试结果的准确性与有效性有着较大影响。为对动态拉伸试样的结构进行优化设计,以使其在动态拉伸过程中更好地满足一维应力与变形均匀等基本假设。首先,建立了量化的试样测量准确度指标,即应力平衡达到时间、变形均匀度、非轴向应力相对水平、过渡段相对变形。然后,对试样结构参数进行正交试验设计,通过数值模拟的方法得到了关于试样尺寸与测量准确度指标的正交试验数据库,并对正交试验数据库进行多目标正交试验矩阵分析,得到了试样结构参数对各测量准确度指标影响的主次顺序和规律。最后,以正交试验数据库为训练集,采用人工神经网络（artificial neural network, ANN）协同遗传算法（genetic algorithm, GA）的全局寻优方法对试样的结构尺寸进行优化设计,得到了试样的最优结构尺寸,并对最优尺寸的有效性进行了验证。结果表明,优化后的试样结构在材料动态拉伸力学性能测试精度上的表现明显得以提升。因此,采用ANN-GA协同优化的方法对动态拉伸试样的结构进行优化具有可行性和有效性。     

Inverse method for detection and sizing of cracks in thin sections using a hybrid genetic algorithm based signal parametrisation

A hybrid-GA method, based on signal parameterization, has been reported here for the improved detection and sizing of surface cracks of small sizes/depths in thin sections. The method relies on parameterizing the composite reference from the defect into its individual components i.e., the crack tip diffracted echo and the corner trap echo and subsequently use the relative arrival time technique (RATT). The phased array ultrasonic technique was employed in the investigation. Both experimental and simulated signals were used in the study. It is shown through both simulations and experiments that the hybrid-GA is successful in parameterizing both non-overlapping and overlapping echoes encountered in thin sections. It is additionally shown that the hybrid-GA improves the signal to noise ratio and correct for under-sampling of data.     

Nonintrusive data-based learning of a switched control heating system using POD,DMD and ANN

The aim of this work is to derive an accurate model of two-dimensional switched control heating system from data generated by a Finite Element solver. The nonintrusive approach should be able to capture both temperature fields, dynamics and the underlying switching control rule. To achieve this goal, the algorithm proposed in this paper will make use of three main ingredients: proper orthogonal decomposition (POD), dynamic mode decomposition (DMD) and artificial neural networks (ANN). Some numerical results will be presented and compared to the high-fidelity numerical solutions to demonstrate the capability of the method to reproduce the dynamics.     

An Innovative Method for 3-D Shape,Strain and Temperature Full-Field Measurement Using a Single Type of Camera: Principle and Preliminary Results

An innovative technique for measuring both the shape, the displacement, the strain and the temperature fields at the surface of an object using a single stereovision sensor is proposed. The sensor is based on two off-the-shelf low-cost high-resolution uncooled CCD cameras. To allow both dimensional and thermal measurements, the sensor operates in the visible and near infrared (NIR) spectral band (0.7–1.1 μm), and a radiometric and geometric calibration of the sensor is required. This technique leads to a low-cost camera-based simplified instrumentation that gives simultaneously dimensional/kinematical and thermal field measurements.     

Nonlinear composites: a linearization procedure,exact to second-order in contrast and for which the strain-energy and affine formulations coincideComposites non linéaires : un schéma exact au second ordre pour lequel la formulation en énergie de déformation coı̈ncide avec la formulation affine

This Note presents a new approximate scheme for nonlinear composites. The approximation which is made preserves certain features of the original second-order scheme of Ponte Castañeda, exactness to second-order in the contrast and existence of an effective energy, but improves on one drawback, which is the gap between the strain-energy formulation and the affine formulation. A numerical example shows the accuracy of the present method. To cite this article: N. Lahellec, P. Suquet, C. R. Mecanique 332 (2004).