in this article the general non-symmetric parametric form of the incremental secant stiffness matrix for nonlinear analysis of solids have been investigated to present a semi analytical sensitivity analysis approach for geometric nonlinear shape optimization. to approach this aim the analytical formulas of secant stiffness matrix are presented. the models were validated and used to perform inve...

design and optimization of a single crystalline silicon (c-si) solar cell is performed to achieve the maximum light conversion efficiency. various parameters such as doping concentration and thicknesses, and geometrical dimension of surface pyramids are studied. the inverted surface pyramid is used to increase the efficiency of the solar cell, and engineered oxide layer is used as the passivati...

in this paper, a non-isothermal two-phase flow in the cathode gas diffusion layer (gdl) of pem fuel cell is modeled. the governing equations including energy, mass and momentum conservation equations are solved by numerical methods. also, the optimal values of the effective parameters such as the electrodes porosity, gas diffusion layer (gdl) thickness and inlet relative humidity are calculated...

The theory of positive bases introduced by C. Davis in 1954 does not appear in most modern texts on linear algebra but has re-emerged in publications in optimization journals. In this paper some simple properties of this highly useful theory are highlighted and applied to both theoretical and practical aspects of the design and implementation of numerical algorithms for nonlinear optimization.

‎In this paper we introduce a numerical approach that solves optimal control problems (OCPs) ‎using collocation methods‎. ‎This approach is based upon B-spline functions‎. ‎The derivative matrices between any two families of B-spline functions are utilized to‎ ‎reduce the solution of OCPs to the solution of nonlinear optimization problems‎. ‎Numerical experiments confirm our heoretical findings‎.

Optimization problems with partial differential equation (PDE) constraints arise in many science and engineering applications. Their robust and efficient solution present many mathematical challenges and requires a tight integration of properties and structures of the underlying problem, of fast numerical PDE solvers, and of numerical nonlinear optimization. This workshop brought together exper...

In signal processing, discrete convolutions are usually involved in fast calculating coefficients of time-frequency decompositions like wavelet and Gabor frames. Depending on the regularity of the mother analyzing functions, one wants to detect the right resolution in order to achieve good approximations of coefficients. Local–global conditions on functions in order to get the convergence rate ...

Engineering design optimization often gives rise to problems in which expensive objective functions are minimized by derivative-free methods. We propose a method for solving such problems that synthesizes ideas from the numerical optimization and computer experiment literatures. Our approach relies on kriging known function values to construct a sequence of surrogate models of the objective fun...

In this paper we present a new algorithm based on ant colony metaphor for examining numerical optimization problems. The ants’ search behavior consists of a parallel searches on distributed randomly points. Using synergetic effect and tandem running ants try to calibrate with another ants to exchange information about the fruitful positions of search space. The position of the searching point i...