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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]

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]