Waclaw Kus

Optimization of Structures Using Distributed and Parallel Evolutionary Algorithms

This paper is devoted to applications of evolutionary algorithms into optimal design of nonlinear structures and identification of holes. The parallel and the distributed evolutionary algorithms are considered. The optimum criterion is to minimize the plastic strain areas and stress values or an identification functional. The fitness functions are computed using the finite element method or the coupled finite and boundary element method.

Evolutionary Optimization of Forging Anvils Using Grid Based on Alchemi Framework

The paper presents application of parallel evolutionary algorithm to the optimization of the anvils in two-stage forging. The grid based on Alchemi framework is used during computations. The numerical example with speedup measurements is presented.

Distributed Evolutionary Algorithms in Shape Optimization of Nonlinear Structures

The paper is devoted to an application of the distributed evolutionary methods and the finite and boundary element method (FEM, BEM) to shape optimization of structures with nonlinearities. The minimization of plastic regions an displacements in the structure are taken into account as an optimization criterion.

Multicriteria identification of parameters in microscale heat transfer

Purpose The purpose of this paper is to present the multicriteria identification method used for solving the microscale heat transfer problem. The thin film exposed to ultrashort laser pulse is modeled using the finite difference method. The parameters of the model are tuned on the basis of experimental data. The multicriteria identification of the numerical model parameters is performed for subsets of experimental data. Design/methodology/approach The multicriteria identification method is used in the paper. The Pareto front for two criterions is created. The two-temperature model of heat transfer in microscale is used in the numerical model. Findings The multicriteria identification for two subsets of experimental data leads to different results. The obtained Pareto front allows to choose the most suitable set of numerical model parameters. Originality/value The multicriteria identification method was used for the first time to solve the microscale heat transfer problem.

Evolutionary Optimization of Preform and Die Shape in Forging Using Computational Grid

The paper is devoted to shape optimization of perform and die in forging process[1]. The idea is to use evolutionary optimization in computational grid environment[2]. The shape optimization of structures can be solved using methods based on sensitivity analysis information or non-gradient methods based on genetic algorithms. Applications of evolutionary algorithms in optimization need only information about values of an objective (fitness) function. The fitness function is calculated for each chromosome in each generation by solving the boundary - value problem by means of the Finite Element Method. This approach does not need information about the gradient of the fitness function and gives the great probability of finding the global optimum. The main drawback of this approach is the long time of calculations. The applications of the distributed evolutionary algorithms can shorten the time of calculations. The computational grids allows to use distributed computational resources. The use of grid techniques in optimizations can lead to improvements in hardware and software utilization. The other advantages of grids are simple and uniform end user communication portals and programs.

Optimization of mechanical structures using serial and parallel artificial immune systems

A shape optimization problem of structures can be solved using methods based on sensitivity analysis information or non gradient methods based on genetic algorithms or on artificial immune systems. This paper is devoted to the method based on the serial and parallel artificial immune system. Artificial immune systems are developed on the basis of mechanism discovered in biological immune systems [9]. An immune system is a complicated, distributed group of specialized cells and organs. The main purpose of the immune system is to recognize and destroy pathogens - funguses, viruses, bacteria and improper functioning cells. The artificial immune systems (AIS) [1] take only few elements from the biological immune systems. The most frequently used are mutation of the B cells, proliferation, memory cells, and recognition using the B and T cells. The artificial immune systems are used to optimization, classification and also computer viruses recognition. A parallel artificial immune system (PAIS) was introduced in [2] for classification problems. The applications of an artificial immune system in optimization need only information about values of an objective function. The objective function is calculated for each B cell in each iteration by solving the boundary - value problem of elasticity by means of the finite element method (FEM). The main drawback of this approach is the long time of calculations. The applications of the parallel artificial immune system can shorten the time of calculations but additional requirements are needed: a multiprocessor computer or a cluster of computers are necessary. The message passing paradigm of parallel computations is used in presented approach. An artificial immune system is implemented as one master process, other processes - workers evaluate objective functions for B cells.

Evolutionary computation in identification of a tumor

The paper deals with an application of evolutionary computation in identification of shape and position of a tumor region in the biological tissue domain. The problem is formulated as an inverse problem that is solved by the minimization of a functional formulated as some distance between measured and computed skin surface temperatures. The functional is considered as the fitness function and the minimization is performed by an evolutionary algorithm with the floating point representation of chromosomes. Geometrical parameters or shape and position of the tumor play the role of genes. The evaluation of the fitness function is preceded by the solution of the direct problem for the bioheat transfer (the Pennes equation) by means or the finite element method. Numerical examples of evolutionary computation for 2-D problems are presented.