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 betweenthe 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. Manuscript profile

In this paper, a multi purpose function is presented for optimum design in circular hydrostatic axial bearings. One or more parameters that are directly or indirectly dependent on given data are optimized. Usually in the local optimization methods, it is not possible to optimize several parameters simultaneously. In this research, simultaneous optimization of the power loss and the oil temperature rise as effective parameters for increase in efficiency of bearing is considered. The genetic algorithm is used in simultaneous optimization of the power and the temperature values. The accuracy of the multi purpose optimization is evaluated by a practical sample and the obtained results of simultaneous combination of parameters effect are compared with distinct functions. Manuscript profile

Abstract: In this paper, a new population-based search called the Bees Algorithm (BA) is presented to estimate the time-dependent heat transfer coefficient and the corresponding heat flux at the boundaries of a two-dimensional body subjected to transient heat conduction, using the temperature measurements at discrete nodal locations on the boundaries, where heat flux is specified as the boundary condition. In the forward problem, a two dimensional transient heat conduction problem subjected to heat flux boundary conditions is solved for temperature distribution at the boundaries using the boundary elements method. In the inverse problem the heat transfer coefficient (h) at the boundaries where thermal conditions are over specified is estimated by minimizing an objective function which is defined as the sum of the squared differences between the measured and computed temperatures at the nodal locations on the boundary. The Bees algorithm which is a new global evolutionary optimization method is used to investigate the inverse problem. The average value of the heat transfer coefficient at the boundaries is assumed over each time interval from initial time until the final steady-state time. The optimum parameters of Bees algorithm are found and used to estimate the heat transfer coefficient as a function of time. The effect of temperature measurement errors on the identification process is also investigated. Manuscript profile