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Characterization of the interior of an inhomogeneous body using displacement measurements obtained by conducting a simple tension test was investigated. A homogeneous elastic solid body is assumed to have another solid body with arbitrary shape hidden inside it. The shape and physical properties of this inclusion were unknown. The Boundary Element Method (BEM) coupled with a mete heuristic Genetic Algorithm (GA) and Conjugate Gradient Method (CGM) was used in this characterization problem. A fitness function, which is the summation of squared differences between the measured displacements and calculated displacements at the same locations on the boundary, is minimized using GA and CGM. GA is used to find a good initial estimate of the unknown parameters and the CGM was used as the hybrid function to get converged values of the unknown parameters. For the cases that the fitness function fluctuates severely, a regularization function was added to CGM in order to dampen the fluctuations. Inverse problem, Boundary Element Method (BEM), optimization, inclusion, INTRODUCTION In this study, the feasibility of characterizing the internal structure of an inhomogeneous body solely on the basis of surface measurements will be explored. In particular we will examine [...]

The purpose of this work is to identify simultaneously two irregular interfacial boundaries configurations between the components of three connected domains using a discrete number of displacement measurements obtained by a simple tension test. A unique combination of a global optimization method, i.e., the imperialist competitive algorithm and two local optimization methods, i.e., the conjugate gradient method and Simplex method along with the inverse application of the boundary elements method are employed in an inverse software package. A fitness function, which is the summation of squared differences between calculated displacements and measured displacements at identical locations on the outer boundary, is minimized. Due to the complexity and the ill-posed nature of this identification problem, imperialist competitive algorithm is used to find the best initial guesses of the unknown interface boundaries in order to be used by the local optimization techniques, i.e., conjugate gradient method and then Simplex method to accurately converge to the optimal shape of two irregular interfacial boundaries between the components of an inhomogeneous body. Several examples are selected, and the accuracy of the obtained results is discussed. The effect of experimental measurement errors and the influence of material properties of the sub regions on the identification process are also investigated. [ABSTRACT FROM AUTHOR]

An inverse geometry problem of identifying simultaneously two irregular interfacial boundaries along with the mechanical properties of the interface domain located between the components of multiple (three) connected regions is investigated. A discrete number of displacement measurements obtained from a uniaxial tension test are used as extra information to solve this inverse problem. A unique combination of global and local optimization method is used, that is, the imperialist competitive algorithm (ICA) to find the best initial guesses of the unknown parameters to be used by the local optimization methods, that is, the conjugate gradient method (CGM) and the simplex method (SM). The CGM and SM are used in series. The performance of these local optimization methods is dependents on the initial guesses of the unknown boundaries and the mechanical properties, that is, Poisson’s ratio and Young’s modulus, so ICA provides the best initial guesses. The boundary elements method is employed to solve the direct two-dimensional (2D) elastostatics problem. A fitness function, which is the summation of squared differences between measured and computed displacements at identical locations on the exterior boundary, is minimized. Several example problems are solved and the accuracy of the obtained results is discussed. The influence of the value of the material properties of the subregions and the effect of measurement errors on the estimation process are also addressed. [ABSTRACT FROM PUBLISHER]

One of the most important issues in industry, particular casting industry is to determine the internal structure of objects such as identifying the interfacial boundary configurations between material, identification of impurities or mechanical properties of the material. The objective of the present inverse problem is to identified simultaneously two regular interfacial boundary configurations and mechanical properties of the components of a multiple (three) connected domains using a discrete number of displacement measurements obtained from an uniaxial tension test. A unique combination of a global optimization method i.e. the Imperialist Competitive Algorithm (ICA) and local optimization methods i.e. Simplex Method (SM) along with the inverse application of the Boundary Elements Method (BEM) are employed in an inverse software package. A fitness function, which is the summation of squared differences between the measured displacements and computed at identical locations on the exterior boundary, is minimized. The obtained results (run-time and error-rate),clearly demonstrate the efficiency of this present algorithm (the Imperialist Competitive Algorithm and Simplex Method)to optimize the objective function and the estimation simultaneously two regular interfacial boundary configurations and mechanical properties. [ABSTRACT FROM AUTHOR]

The effect of boundary conditions on the solution of the inverse problem of identifying the geometry and location of a cavity inside an elastic solid body using displacement measurements obtained from a tension test is investigated. The boundary elements method (BEM) coupled with the genetic algorithm (GA) and the conjugate gradient method (CGM) are implemented in this identification problem. A fitness function which is defined as the squared differences between the computed and measured displacements is minimized. The best initial guess of the unknown shape and location of the cavity is found by the GA, then this initial guess is used by the CGM to achieve convergence. The imposed boundary conditions, i.e. geometrical constrain and specified tractions are kept constant during all iterations. Certainly changes in the boundary conditions can be effective in the correct identification of the shape and location of the cavity. In this study the effect of different boundary conditions on the convergence is investigated and the best and the most suitable boundary conditions which results in the faster and more accurate convergence are found. [ABSTRACT FROM AUTHOR]