Wyniki wyszukiwania - BazTech

1

Hybrid parallel evolutionary algorithm in optimization of 2d grapehene-like materials

Mrozek A., Kuś W., Burczyński T.

Computer Methods in Materials Science

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2015

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Vol. 15, No.1

103--110

EN

Development and application of the hybrid parallel evolutionary-conjugated gradient algorithm for searching for new, stable atomic arrangements of the two-dimensional graphene-like carbon lattices was described in this paper. The main goal of the optimization is to find stable arrangements of carbon atoms under imposed conditions (e.g. density, shape and size of the unit cell). Such configurations correspond to the minimal values of the total potential energy of the atomic system. Thus, the fitness function is formulated as the total potential energy of the atoms. Interactions between carbon atoms are modeled using Adaptive Intermolecular Reactive Bond Order potential. The parallel approach used in computations allows significant reduction of computation time. Validation of the achieved results and example of the model of new 2D material obtained using presented method were presented in this paper. The numerical scalability tests of the algorithm were performed on the IBM BlueGcne/Q supercomputer

PL

W artykule przedstawiona została metoda optymalizacji płaskich sieci zbudowanych z atomów węgla. Proponowane podejście bazuje na połączeniu równoległego algorytmu ewolucyjnego z metodą gradientu sprzężonego. Funkcją celu jest wartość energii potencjalnej całego układu atomów. Głównym zadaniem algorytmu jest znalezienie stabilnych położeń atomów w komórce elementarnej - odpowiadających minimum energii potencjalnej całego układu. Algorytm ewolucyjny został zrównoleglony (podział populacji na części), ponadto wspomagający go algorytm gradientowy (wbudowany w program LAMMPS) może również być uruchomiony w wersji sekwencyjnej, jak i równoległej. Jako model oddziaływań między atomami węgla zastosowano potencjał AIREBO, uwzględniający różne stany hybrydyzacji atomów węgla. W pracy zaprezentowano wyniki optymalizacji obejmujące poszukiwania znanych materiałów literatury płaskich materiałów grafenopodobnych, jak i nowych konfiguracji. Ponadto, dla nowych struktur wyznaczono parametry mechaniczne.

2

Two-scale identification of composites’ material constants by means of computational intelligence methods

Beluch W., Burczyński T.

Archives of Civil and Mechanical Engineering

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2014

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Vol. 14, no. 4

636--646

EN

The paper deals with the two-scale approach to the identification of material constants in composite materials. Structures made of unidirectionally fibre-reinforced composites are examined. Composite constituents’ elastic constants in a micro scale are identified on the basis of measurements performed in a macro scale. Numerical homogenization methods using a representative volume element are employed. Static (displacements in sensor points) and dynamic (eigenfrequencies) data are considered as measurements. Ideal and disturbed measurements are taken into account. Computational intelligence methods in the form of evolutionary algorithms and artificial immune systems are used to perform the identification procedure. Finite element method is used to solve the boundary-value problem for composites in both scales. Numerical examples presenting the effectiveness of the proposed approach are attached. Statistical data are considered to compare the efficiency of the identification procedure for both algorithms and different measurement data.

3

Identiﬁcation in multiscale thermoelastic problems

Długosz A., Burczyński T.

Computer Assisted Methods in Engineering and Science

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2013

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Vol. 20, no. 4

325--336

EN

The paper deals with the identiﬁcation in multiscale analysis of structures under thermal and mechanical loads. A two-scale model of porous materials is examined. Direct thermoelastic analyses with representative volume element (RVE) and ﬁnite element method (FEM) are taken into account. Identiﬁcation of material constants of the microstructure and identiﬁcation of the shape of the voids in the microstructure are considered. Identiﬁcation functional is formulated on the basis of information obtained from measurements in mechanical and thermal ﬁelds. Evolutionary algorithm is used for the identiﬁcation as the optimization technique. Numerical examples of identiﬁcation for porous aluminum models are enclosed.

4

Examination of mechanical properties of graphene allotropes by means of computer simulation

Mrozek A., Burczyński T.

Computer Assisted Methods in Engineering and Science

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2013

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Vol. 20, no. 4

309--323

EN

The eﬀective mechanical properties and the stress-strain relations of the eight types of the graphene allotropes are presented in this paper. Series of the tensile and shear tests are performed using the nonequilibrium molecular dynamics (NEMD) and the adaptive intermolecular reactive bond order (AIREBO) potential. The methodology of the investigation as well as obtained results are explained and discussed in detail. Where possible, the achieved results are compared with the data available in the scientiﬁc literature in order to validate our molecular dynamics models and simulations. In other cases, i.e., where only information about structural or electronic properties is available, presented results can complement the knowledge about these particular planar carbon networks.

5

Advanced numerical simulations of selected metallurgical units

Kokot G., Burczyński T., John A.

Journal of Achievements in Materials and Manufacturing Engineering

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2012

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Vol. 55, nr 2

523--528

EN

Purpose: of this paper is to present numerical simulations of large structures in metallurgical industry. Some examples of finite element analysis are presented. The calculations were performed for the determining the stress effort of the metallurgical units mainly blast furnace, throath’s gas pipelines, hot blast stoves, etc. during the working conditions and for the repairing purpose. Design/methodology/approach: The way of conducting simulations and analysis were the finite element method connected with the optimization process. Findings: Performing the numerical analysis the changes in the structures design were applied what extremely influenced on the state effort and the durability of considered structures. Research limitations/implications: Development of the presented approach solving the coupled field and CFD problems, the application of the parallel computing and domain decomposition methods in the large structure simulations. Practical implications: Presented results shows the possibility of application the advanced computational methods in the computer aided engineering processes of designing and analysing the large structure as the metallurgical units are. It can dramatically influence on the recognizing of the effort stets and helps in the monitoring, overhauls and redesigning process. Those methods gives the global very precise information which cannot be obtain in other ways (analytical solutions, experimental methods). Originality/value: The paper present the original research results comes from the complex numerical simulations of the main metallurgical units in the blast furnace train. The original value of the paper is the introduction of the advanced finite element simulation in the field of iron steel industry structures design and developing.

6

Swarm optimization of stiffeners locations in 2-D structures

Szczepanik M., Burczyński T.

Bulletin of the Polish Academy of Sciences. Technical Sciences

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2012

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Vol. 60, nr 2

241-246

EN

The paper is devoted to the application of the swarm methods and the finite element method to optimization of the stiffeners location in the 2-D structures (plane stress, bending plates and shells). The structures are optimized for the stress and displacement criteria. The numerical examples demonstrate that the method based on the swarm computation is an effective technique for solving the computer aided optimal design. The additional comparisons of the effectiveness of the particle swarm optimizer (PSO) and evolutionary algorithms (EA) are presented.

7

Multiobjective shape optimization of selected coupled problems by means of evolutionary algorithms

Długosz A., Burczyński T.

Bulletin of the Polish Academy of Sciences. Technical Sciences

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2012

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Vol. 60, nr 2

215-222

EN

In present paper an improved multi-objective evolutionary algorithm is used for Pareto optimization of selected coupled problems. Coupling of mechanical, electrical and thermal fields is considered. Boundary-value problems of the thermo-elasticity, piezoelectricity and electro-thermo-elasticity are solved by means of finite element method (FEM). Ansys Multiphysics and MSC.Mentat/Marc software are used to solve considered coupled problems. Suitable interfaces between optimization tool and the FEM software are created. Different types of functionals are formulated on the basis of results obtained from the coupled field analysis. Functionals depending on the area or volume of the structure are also proposed. Parametric curves NURBS are used to model some optimized structures. Numerical examples for exemplary three-objective optimization are presented in the paper.

8

OPTIM - library of bioinspired optimization algorithms in engineering applications

Kuś W., Długosz A., Burczyński T.

Computer Methods in Materials Science

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2011

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Vol. 11, No. 1

9-15

EN

The paper is devoted to engineering applications of Optim library. The library, created by paper authors, is devoted to bioinspired optimization algorithms. The Optim contains classes for optimization with use of evolutionary algorithm (single and multiobjective optimization), artificial immune system and particle swarm optimization. The Optim library is well suited for engineering problems with floating point representation of design variables. The paper contains description of library and methodology of transferring data between Optim and auxiliary programs used for objective function calculation. The numerical examples of optimization of mechanical structures by using Finite Element Method for objective function evaluation are shown in the paper.

PL

W artykule przedstawiono bibliotekę Optim, dedykowaną obliczeniom inspirowanym biologicznie. Biblioteka ta jest dedykowana do stosowania w inżynierskich zadaniach optymalizacji. W artykule przedstawiono optymalizację jedno i wielokryterialną z użyciem algorytmów ewolucyjnych. Przedstawiono również zastosowania opisanych metod w zagadnieniu identyfikacji parametrów materiałowych kości beleczkowej oraz optymalizacji kształtu siłownika wykonanego w technologii MEMS.

9

Identification of stochastic material properties in multiscale modelling

Kuś W., Burczyński T.

Computer Methods in Materials Science

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2011

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Vol. 11, No. 4

524-530

EN

The paper is devoted to identification problems in multiscale modeling in stochastic conditions. The multiscale modeling is able to take into account materials or geometrical effects which occur in microscale and obtain more precise results in macroscale analysis. The identification allows to evaluate materials or geometrical parameters of a structure in microscale on the basis of statistical measurements in macroscale. The methodology presented in the paper takes into account stochastic nature of parameters in the microscale and the identification problem is formulated as minimization of a certain stochastic objective function. The problem is transformed into deterministic one in which a new objective functional dependent on mean values and variances is minimized with respect to moments of stochastic parameters. An approach based on evolutionary computing is presented in the minimization problem. The main advantage of the presented approach consists in the fact that a gradient of the objective functional is no needed and moreover there is a great probability of finding the global minimum. The computational homogenization is used to multiscale modelling of the structures. The problem formulation, description of optimization algorithm and a numerical example are shown in the paper.

PL

Artykuł jest poświęcony zagadnieniom identyfikacji parametrów modelu w skali mikro w ujęciu wieloskalowym. Pozwala to uwzględnić wpływ parametrów materiałowych oraz geometrycznych w skali mikro na rozwiązania w skali makro. Rozwiązanie zagadnienia identyfikacji umożliwia określenie parametrów struktury w skali mikro na podstawie pomiarów przeprowadzonych dla skali makro. Przedstawiona w pracy metodologia oparta jest na założeniu, że parametry w skali mikro mają naturę stochastyczną i można je wyznaczyć dysponując wynikami statystycznych pomiarów eksperymentalnych przemieszczeń i odkształceń w skali makro. Zagadnienie sprowadzono do minimalizacji różnicy między charakterystykami probabilistycznymi przemieszczeń i odkształceń obliczonych dla modelu stochastycznego oraz obiektu rzeczywistego. W tym celu zastosowano koncepcję homogenizacji komputerowej, metodę Monte Carlo oraz algorytm ewolucyjny. Opracowaną koncepcję identyfikacji w warunkach stochastycznych zweryfikowano pozytywnie na przykładzie numerycznym.

10

Computational intelligence methods in searching of stable configurations of nanostructures

Mrozek A., Kuś W., Burczyński T.

Computer Methods in Materials Science

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2011

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Vol. 11, No. 1

46-52

EN

Application of evolutionary algorithm, artificial immune system and particle swarm optimization in the minimization atomic cluster's total potential energy is presented in this work. These methods of computational intelligence simulate biological processes of the natural environment and organisms such as theory of evolution and biological immune systems and give a strong probability of finding the global optimum. Some examples and discussion on the results of optimization are also presented in this paper.

PL

W pracy opisane zostało zastosowanie wybranych metod inteligencji obliczeniowej (algorytmu ewolucyjnego, sztucznego systemu immunologicznego oraz optymalizacji rojem cząstek) do optymalizacji klastrów atomowych. Jako kryterium optymalizacji przyjęto minimalizację całkowitej energii potencjalnej nanostruktury. Do modelowania oddziaływań między atomowych użyto potencjałów Morse'a oraz Murrella-Mottrama. W pracy przedstawiono wybrane wyniki optymalizacji oraz ich interpretację.

11

Multiscale modeling of osseous tissues

Burczyński T., Kuś W., Brodacka A.

Journal of Theoretical and Applied Mechanics

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2010

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Vol. 48 nr 4

855-870

EN

The paper presents a methodology of the multiscale bone modeling in which the task of identification of material parameters plays the crucial role. A two-scale analysis of the bone is considered and the problem of identification, formulated as an inverse problem, is examined as an important stage of the modelling process. The human femur bone, built form cancellous and cortical bone, is taken as an example of an osseous tissue, and the computational multiscale approach is considered. The methodology presented in the paper allows one to analyze the two-scale model with the use of computational homogenization. The representative volume element (RVE) is created for the microstructure of the basis of micro-CT scans. The macro and micro model analyses are performed by using the finite element method. The identification of trabeculae material parameters on the micro-level is considered as the minimization problem which is solved using evolutionary computing.

PL

W artykule przedstawiono metodologię wieloskalowego modelowania thanki kostnej, w której zagadnienie identyfikacji parametrów materiałowych odgrywa kluczową rolę. Rozpatrzono analizę dwuskalową kości, a problem identyfikacji sformułowano jako zagadnienie odwrotne, będące ważnym etapem procesu modelowania. Jako przykład tkanki kostnej rozważono kość udową zbudowaną z kości gąbczastej i korowej.

12

Searching of stable configurations of nanostructures using computational intelligence methods

Mrozek A., Kuś W., Burczyński T.

Czasopismo Techniczne. Mechanika

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2010

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R. 107, z. 4-M

85-97

EN

This paper deals with computational intelligence methods: evolutionary algorithms, artificial immune systems and the particle swarm optimization applied to the process of minimization of the potential energy of small nanostructures, such as atomic clusters. These algorithms simulate biological processes of the natural environment and organisms such as the theory of evolution and the biological immune systems. Mentioned approaches, generally, do not need any information about the gradient of the fitness function and give a strong probability of finding the global optimum. The main drawback of these methods is the long time of computations.

PL

W artykule przedstawiono zastosowanie wybranych metod inteligencji obliczeniowej (algorytmy ewolucyjne, sztuczne systemy immunologiczne, optymalizacja rojem cząstek) do minimalizacji energii potencjalnej klastrów atomowych. Do opisu oddziaływań międzyatomowych użyte zostały potencjały Morsa i Murrella-Mottrama.

13

Evolving ensembles of linear classifiers by means of clonal selection algorithm

Bereta M., Burczyński T.

Control and Cybernetics

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2010

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Vol. 39, no 2

325-342

EN

Artificial immune systems (AIS) have become popular among researchers and have been applied to a variety of tasks. Developing supervised learning algorithms based on metaphors from the immune system is still an area in which there is much to explore. In this paper a novel supervised immune algorithm based on clonal selection framework is proposed. It evolves a population of linear classifiers used to construct a set of classification rules. Aggregating strategies, such as bagging and boosting, are shown to work well with the proposed algorithm as the base classifier.

14

Topology optimization of mechanical structures using artificial immune system

Poteralski A., Szczepanik M., Burczyński T.

Zeszyty Naukowe Wyższej Szkoły Informatyki

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2009

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Vol. 8, Nr 2

95-110

EN

The paper deals with an application of the artificial immune system (AIS) and the finite element method to the optimization problems of 2-D, 3-D and the combination of 2-D and 3-D structures. The optimization method concerns the simultaneous optimization of topology, shape, and material. This approach is based on the mechanism discovered in biological immune systems. The main advantage of the AIS is the fact that this approach does not need any information about the gradient of the fitness function and gives a strong probability of finding the global optimum. The numerical examples demonstrate that the method based on evolutionary computation is an effective technique for solving computer aided optimal design.

PL

Artykuł dotyczy zastosowania sztucznego systemu immunologicznego (SSI) i metody elementów skończonych do optymalizacji układów 2-D, 3-D oraz połączonych układów 2-D i 3-D. Metoda optymalizacji dotyczy równoczesnej optymalizacji topologii, kształtu oraz własności materiałowych układu. Podejście to bazuje na mechanizmach zaobserwowanych w biologicznych systemach immunologicznych. Główną zaletą SSI jest fakt, że podejście to nie wymaga informacji o gradiencie funkcji przystosowania i daje duże prawdopodobieństwo znalezienia optimum globalnego. Przykłady numeryczne przedstawiają, że metoda bazująca na obliczeniach immunologicznych jest efektywnym narzędziem komputerowego wspomagania optymalnego projektowania.

15

Parallel evolutionary optimization in multiscale problems

Kuś W., Burczyński T.

Computer Methods in Materials Science

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2009

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Vol. 9, No. 2

347-351

EN

The paper is devoted to optimization in multiscale problems. The composite modelled as a macrostructure with local periodic microstructure is considered. The multiscale analysis is performed with use of homogenization method. The parallel evolutionary algorithm used in computations allows to shorten wall time of optimization. The full paper contains description of parallel evolutionary algorithm, homogenization method, optimization formulation and numerical exmaples.

PL

Artykuł poświęcony jest optymalizacji w problemach wieloskalowych. Rozważany jest kompozyt modelowany jako ciało makroskopowe z mikroskopową strukturą lokalnie periodyczną Analiza wielkoskalowa przeprowadzona jest z użyciem metody homogenizacji komputerowej. Zastosowanie w obliczeniach równoległego algorytmu, ewolucyjnego pozwoliło na skrócenie czasu obliczeń. Wyznaczanie wartości funkcji przystosowania również przeprowadzono stosując obliczenia równoległe. Artykuł zawiera opis równoległego algorytmu ewolucyjnego, metody homogenizacji, sformułowanie problemu optymalizacji oraz przykład numeryczny.

16

Evolutionary computing in optimization and identification of dynamical physical systems

Burczyński T.

Vibrations in Physical Systems

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2008

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Vol. 23

47--58

EN

The paper id devoted to applications of evolutionary algorithms to optimization of dynamical physical systems. Identification of internal defects are also considered. Several numerical examples of shape and topology optimization for various criteria and crack or void detection are presented.

17

The granular computing in uncertain optimization problems

Orantek P., Burczyński T.

Prace Naukowe Politechniki Warszawskiej. Elektronika

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2008

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z. 165

173-180

EN

The paper is devoted to applications of evolutionary algorithms in identification of structures being under the uncertain conditions. Uncertainties can occur in boundary conditions, in material or geometrical parameters of structures and are modelled by three kinds of granularity: interval mathematics, fuzzy sets and theory of probability. In order to formulate the optimization problem for such a class of problems by means of evolutionary algorithms the chromosomes are considered as interval, fuzzy and random vectors whose genes are represented by: (i) interval numbers, (ii) fuzzy numbers and (iii) random variables, respectively. Description of evolutionary algorithms with granular representation of data is presented in this paper. Various concepts of evolutionary operator such as a crossover and a mutation and methods of selections are described. In order to evaluate the fitness functions the interval, fuzzy and stochastic finite element methods are applied. Several numerical tests and examples of identification of uncertain parameters are presented.

18

Evolutionary multi-objective optimization of laminates

Beluch W., Burczyński T., Długosz A.

Prace Naukowe Politechniki Warszawskiej. Elektronika

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2008

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z. 165

43-50

EN

The paper deals with the application of the global optimization methods to the multi-objective optimization of laminates. A multi-layered, fibre-reinforced and hybrid laminates are considered. Different optimization criteria connected with the laminates' cost, modal properties and stiffness are taken into account. As the optimization criteria usually cannot be satisfied simultaneously, the multi-objective optimization methods are employed. The multi-objective evolutionary algorithm with the Pareto approach is used as the global optimization method. The Finite Element Method is used to solve a boundary-value problem for the laminates. The stacking sequence and the number or plies made of different materials are design variables. The discrete as well as continuous fibre orientation angles in particular plies are considered. Numerical example presenting non-dominated solutions for two contradictory optimization criteria is attached.

19

Evolutionary algorithm in identification of stochastic parameters ot laminates

Orantek P., Beluch W., Burczyński T.

Prace Naukowe Politechniki Warszawskiej. Elektronika

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2008

|

z. 165

165-172

EN

The paper deals with the identification of material constants in multi-layered composites. Simple and hybrid (with laminas made of different materials) laminates are considered. Material constants are presented in a stochastic form to model their uncertainty. The Evolutionary Algorithm based on such representation of the data is used as the global optimization method. Chromosomes are represented by multidimensional random vectors consisting of random genes in the form of independent random variables with the Gaussian density probability functions. The Stochastic optimization problem is replaced by a deterministic one by evolutionary computing of chromosomes having genes consisting of mean values and standard deviations. Modal analysis methods are employed to collect measurement data necessary for the identification. The Finite Element Method in Stochastic version is used to solve the boundary-value problem for laminates. Numerical examples showing efficiency of the method are presented.

20

Immune and evolutionary shape optimization in forgin

Kuś W., Burczyński T.

Computer Methods in Materials Science

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2008

|

Vol. 8, No. 2

79-85

EN

The paper deals with applications of methods of artificial intelligence: artificial immune systems and evolutionary algorithms in optimization of a forging process. The shape optimization of the anvils in a two-stage forging process is considered as a numerical example. The paper contains description of the evolutionary algorithm, the artificial immune system and parallel versions of bioinspired algorithms in grid environment.

PL

W artykule przedstawiono zastosowanie dwóch biologicznie inspirowanych metod obliczeniowych - algorytmów ewolucyjnych i sztucznych systemów immunologicznych w optymalizacji procesu kucia. Dwu-etapowy proces kucia swobodnego modelowany jest za pomocą metody elementów skończonych i rozwiązany za pomocą programu MSC Marc. W celu przyspieszenia obliczeń zagadnienie rozważane jest w środowisku gridowym. Przedstawiono przykład numeryczny ilustrujący skuteczność zastosowanych inteligentnych technik optymalizacji.