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1

Evolutionary identification of laminates' granular parameters

Beluch W., Orantek P.

Computer Assisted Mechanics and Engineering Sciences

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2010

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Vol. 17, no. 1

51-58

EN

The paper deals with the identification of material constants in simple and hybrid laminates. It is assumed that identified constants are non-deterministic and can be described by means of different forms of the information granularity represented by interval numbers, fuzzy numbers or random variables. The Two-Stage Granular Strategy combining global (Evolutionary Algorithm) and local (gradient method supported by an Artificial Neural Network) optimization techniques is used to solve the identification problems. Finite Element Method in the granular form is used to solve the direct problem for laminates. Modal analysismethods are employed to collect measurement data for the identification process. Numerical examples presenting effectiveness of the strategy are enclosed.

2

Analiza interwałowa i rozmyta kości biodrowej człowieka

John A., Orantek P.

Zeszyty Naukowe Wyższej Szkoły Informatyki

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2008

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Vol. 7, Nr 1

68-75

PL

Modelowanie numeryczne ludzkiej kości biodrowej jest złożonym procesem, w którym należy wziąć pod uwagę wiele ważnych czynników. Jednym z nich są własności materiału. Obliczenia numeryczne wymagają wprowadzenia parametrów materiałowych, które zależą od wieku, zdrowia, płci, środowiska oraz wielu innych. Aby dobrać prawidłowo parametry materiałowe, należy wziąć pod uwagę różnorodne dane dotyczące pacjentów. Autorzy artykułu założyli wartości przedziałowe wybranych parametrów materiałowych. Zaproponowano interwałową i rozmytą analizę kości biodrowej.

EN

Numerical modeling of the human pelvic bone is a complex process in which many important factors are taken into account. One of them concerns material properties. Numerical calculations require the characteristics of the material properties and the material parameters from the beginning. The material properties of the living body depend on age, health, gender, environment and many others factors. To determine correct material parameters, health details of a group of patients need to be taken into consideration. In this paper authors assumed interval and fuzzy values of the selected material parameters and proposed interval and fuzzy analysis of the pelvic bone.

3

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.

4

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

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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.

5

Evolutionary identification of fuzzy material constants in laminates

Beluch W., Burczyński T., Orantek P.

Prace Naukowe Politechniki Warszawskiej. Elektronika

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2007

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z. 160

17-24

EN

The paper deals with identification of material constans in fibre-reinforced laminates. The Evolutionary Algorithm is used as the global optimization method. The grandiet method supported by the Artificial Neutral Network is used as the local optimization method. Material constans are presented in the form of fuzzy numbers to model their uncertainty. Two types of laminates are considered: simple and hybrid ones. Modal analysis methods are used to collect data necessary for the identification process. The Finite Element Method in fuzzy version is used to solve the direct problem for the laminates. Numerical examples are attached.

6

Analiza interwałowa i rozmyta ludzkiej kości biodrowej

John A., Orantek P., Miarka M.

Modelowanie Inżynierskie

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2007

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T. 3, nr 34

55-60

PL

Modelowanie numeryczne ludzkiej kości biodrowej jest złożonym procesem, w którym należy wziąć pod uwagę wiele ważnych czynników. Jednym z nich są własności materiału. Obliczenia numeryczne wymagają wprowadzenia parametrów materiałowych, które zależą od wieku, zdrowia, płci, środowiska oraz wielu innych. Aby dobrać prawidłowo parametry materiałowe, należy wziąć pod uwagę różnorodne dane dotyczące pacjentów. Autorzy artykułu założyli wartości przedziałowe wybranych parametrów materiałowych. Zaproponowano interwałową i rozmytą analizę kości biodrowej.

EN

Numerical modeling of the human pelvic bone is a complex process in which many important factors are taken into account. One of them concerns material properties. Numerical calculations require the characteristics of the material properties and the material parameters from the beginning. The material properties of the living body depend on age, health, gender, environment and many others factors. To determine correct material parameters, health details of a group of patients need to be taken into consideration. In this paper authors assumed interval values of the selected material parameters and proposed interval and fuzzy analysis of the pelvic bone.

7

The uncertain analysis of human pelvic bone

John A., Orantek P.

Computer Assisted Mechanics and Engineering Sciences

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2007

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Vol. 14, No. 4

631-636

EN

Numerical modeling of the human pelvic bone is a complex process in which many important factors are taken into account. One of them concerns material properties. Numerical calculations require the characteristics of the material properties and the material parameters from the beginning. The material properties of the living body depend on age, health, gender, environment and many others factors. To determine correct material parameters, health details of a group of patients need to be taken into consideration. In this paper authors assumed interval values of the selected material parameters and proposed interval and fuzzy analysis of the pelvic bone.

8

The granular computing in uncertain identification problems

Orantek P., Burczyński T.

Computer Assisted Mechanics and Engineering Sciences

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2007

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Vol. 14, No. 4

695-704

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 parameters or in 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.

9

Fuzzy evolutionary algorithms and neural networks in uncertain optimization problems

Orantek P.

Computer Assisted Mechanics and Engineering Sciences

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2007

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Vol. 14, No. 2

317-329

EN

This paper is devoted to the application of the evolutionary algorithms and artificial neural networks to uncertain optimization problems in which some parameters are described by fuzzy numbers. The special method of global optimization: Two-Stages Fuzzy Strategy (TSFS) for structures in uncertain conditions is proposed. As the first stage of the TSFS the fuzzy evolutionary algorithm is used. As the second stage the local optimization method with neuro-computing is proposed. The presented approach is applied in the identification problems of mechanical structures, in which material parameters and loadings are uncertain. To solve the direct problem the fuzzy boundary element method (FBEM) is used. Several numerical tests and examples are presented.

10

Numerical modeling of selected joints of human body

John A., Orantek P.

Zeszyty Naukowe Katedry Mechaniki Stosowanej / Politechnika Śląska

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2006

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z. 26

173-178

EN

The advanced models require high fidelity of geometry and boundary conditions. In the paper the numerical models of pelvic bone and scapula are prepared on the ground of the geometrical data from 3D scanning and CT. The accuracy of geometrical model depends on number of scanning levels. A numerical routine (numerical code) was built to translate the geometrical data (the set of coordinate points) to the Patran/Nastran code. The way of optimal modeling is found. Next, the results of surgical intervention and reconstruction of damaged joints can be taking into account, too.

11

Numerical analysis of selected joints of human body

John A., Orantek P.

Zeszyty Naukowe Katedry Mechaniki Stosowanej / Politechnika Śląska

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2006

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z. 26

167-172

EN

The numerical modeling makes it possible to prepare FE model of human joints before and after reconstruction. It is particular important when the total arthroplasty operation is performed and the artificial joint is fitted. Here, the results for scapula before arthroplasty and for pelvic bone after THA are presented. For checking the influence of the forces acting in acetabulum on the stress and strain distribution in the surroundings of the artificial acetabulum a simple bench-mark was proposed, with force acting on acetabulum by steel ball.

12

The evolutionary algorithm in stochastic optimization and identification problems

Orantek P., Burczyński T.

Prace Naukowe Politechniki Warszawskiej. Elektronika

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2006

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z. 156

309-319

EN

This paper is devoted to the application of evolutionary computing in optimization and identification problems in uncertain random conditions. The algorithm is based on the stochastic representation of the data. Chromosomes are represented by multidimensional random vectors consisting of random genes in the form of independent random variables with the Gaussian density probability function. The stochastic optimization problem is replaced by a deterministic one by evolutionary computing for vector genes consisting of mean values and standard deviations. Special operators for mutation, crososver and selection are proposed. Two numerical tests are presented.

13

Symulacja oddziaływań dynamicznych w stawie biodrowym ze sztuczną panewką

John A., Orantek P.

Modelowanie Inżynierskie

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2006

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T. 1, nr 32

211-218

PL

W pracy zamodelowano dynamiczne zmiany obciążenia działającego w panewce stawu biodrowego w trakcie wykonywania podstawowych ruchów związanych z przemieszczaniem się na płaszczyźnie poziomej. W pracy analizowano dwa podstawowe przypadki obciążenia: zmianę siły w czasie od zera do maksymalnej wartości (cyklicznie) oraz zmianę kierunku działania w czasie. Model numeryczny uwzględnia skutki rekonstrukcji uszkodzonego stawu (całkowita alloplastyka stawu biodrowego). Wynikiem przeprowadzonej analizy była ocena stanu naprężenia w rejonie panewki.

EN

The numerical modelling makes it possible to prepare FE model of human pelvic bone after reconstruction. It is particular important when the THA operation is performed and the artificial acetabulum is fitted. In the paper the numerical model is prepared on the ground of the geometrical data from 3D scanning or CT. In the aim to create an artificial acetabulum a few procedures were done. All procedures were written in the C++ language. The procedures create the flange (width), the spherical cap (radius), and the bolts of artificial acetabulum (2 angles in spherical coordinates, width, height). On the basis of the above parameters the whole geometry of the structure is created. Next on the ground of the geometry, the finite element model is created and put into the bone finite element model. There is possible to model cemented and cementless acetabulum, with contact element and without. Here, two basic cases of dynamic load are assumed: acting force increases from 0 to maximum value and the direction of acting force changes from 0 to 120 degree.

14

Intelligent computing in inverse problems

Burczyński T., Beluch W., Długosz A., Orantek P., Skrobol A.

Computer Assisted Mechanics and Engineering Sciences

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2006

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Vol. 13, No. 1

161-206

EN

This paper presents a review of intelligent computing techniques in solving inverse mechanics problems. These techniques are based on Evolutionary Algorithms (EAs) and the coupling of Evolutionary Algorithms (EAs) and Artificial Neural Networks (ANNs) in the form of Computational Intelligence Systems (CISs). The main attention was focused on the identification of the defects such as voids or cracks in structures on the basis of the knowledge about displacements, temperature and eigenfrequencies. The identification of the unknown number, position, size and kind of defects in the elastic structures is shown. The paper contains a lot of tests and numerical examples.

15

An intelligent computing technique in identification problems

Orantek P.

Computer Assisted Mechanics and Engineering Sciences

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2006

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Vol. 13, No. 2

351-364

EN

The paper is devoted to the application of the evolutionary algorithms, gradient methods and artificial neural networks to identification problems in mechanical structures. The special intelligent computing technique (ICT) of global optimization is proposed. The ICT is based on the two-stage strategy. In the first stage the evolutionary algorithm is used as the global optimization method. In the second stage the special local method which combines the gradient method and the artificial neural network is applied. The presented technique has many advantages: (i) it can be applied to problems in which the sensitivity is very hard to compute, (ii) it allows shortening the computing time. The key problem of the presented approach is the application of the artificial neural network to compute the sensitivity analysis. Several numerical tests and examples are presented.

16

Rozmyty algorytm ewolucyjny : testowanie i dobór parametrów

Burczyński T., Orantek P.

Zeszyty Naukowe Wyższej Szkoły Informatyki

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2005

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Vol. 4, Nr 1

5-22

PL

Praca poświęcona jest testowaniu rozmytych algorytmów ewolucyjnych. Algorytmy takie mogą być zastosowane jako metody optymalizacji w problemach, w których niektóre parametry są określone z pewnym przybliżeniem. Chromosom i operatory takiego algorytmu zostały dostosowane do reprezentacji liczb rozmytych. Testowanie algorytmu polegało na sprawdzeniu powtarzalności uzyskanych wyników oraz zminimalizowaniu czasu obliczeń poprzez odpowiedni dobór parametrów algorytmu. W celu testowania skonstruowano specjalną funkcję testującą, której zmienne niezależne modelowane są jako liczby rozmyte. Wykonano wiele testów, które pozwoliły wstępnie oszacować optymalne parametry algorytmu.

EN

The paper is devoted to the verification the fuzzy evolutionary algorithm. Presented algorithm for problems with uncertain parameters can be applied. The special type of the chromosome and evolutionary operators was introduced. The aim of the test was fmd to the optimal parameters of fuzzy evolutionary algorithm. In order to verification the algorithm the special benchmark function was defmed. The design variables of the benchmark function as the fuzzy value was assumed. The many tests were carried out. The tests allow to select the optimal parameters of presented algorithm.

17

Hybrydowa optymalizacja topologiczna dynamicznych układów mechanicznych

Burczyński T., Orantek P.

Zeszyty Naukowe Politechniki Rzeszowskiej. Mechanika

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2005

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z. 65 [222]

53--60

EN

In this paper scientific research on using the hybrid algorithm in optimization of the dynamic structures was carried out. The boundary-initial problem for elastodynamics was solved by using boundary element method (BEM) [2]. The hybrid algorithm being the coupling of the evolutionary algorithm, gradient algorithm and the artificial neural network was carried out. Topology and shape optimization problems were considered for different criteria, which concern: mass, displacements, stresses, compliance and natural frequencies. As a tool for the modeling of boundary shape the NURBS curves were applied. Several numerical examples testifying to the effectiveness and efficiency of the proposed methods of optimization were carried out, a few interesting tests are included in the paper.

18

Dwuetapowa metoda identyfikacji defektów w dynamicznych układach mechanicznych

Burczyński T., Skrobol A., Orantek P.

Zeszyty Naukowe Politechniki Rzeszowskiej. Mechanika

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2005

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z. 65 [222]

61-68

EN

The paper presents the connected evolutionary and gradient identification of the internal defects in an elastic body under dynamical load. The identification proceeds on the basis of the knowledge about boundary displacements in some sensor points. In the first step the evolutionary algorithm (EA) identifies the number, kind, position and size of internal defects. The fitness function is computed with the help of the pseudo-gaussian fuzzy inference systems (PGFISs). In the second step the gradient method of identification is used to obtain more precise results. The structure of the chromosome and the connection between the EA and the PGFIS is presented. The results of identification in an elastic rectangular under sinusoidal load with internal defects in the form of crack or circular voids are shown.

19

Optymalizacja ewolucyjna konstrukcji powłokowych

Burczyński T., Szczepanik M., Orantek P.

Zeszyty Naukowe Wyższej Szkoły Informatyki

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2004

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Vol. 3, Nr 1

5-19

PL

Praca poświęcona jest zastosowaniu algorytmów ewolucyjnych i metody elementów skończonych (MES) w zagadnieniach optymalizacji konstrukcji powłokowych. Przedstawiono metodę optymalizacji kształtu, topologii oraz grubości i własności materiałowych układów dla przyjętych kryteriów naprężeniowych lub przemieszczeniowych. Przedstawione w referacie przykłady obliczeń ewolucyjnych dowodzą, że opracowana metoda optymalizacji, bazująca na połączeniu algorytmów ewolucyjnych i metody elementów skończonych, jest efektywnym narzędziem wspomagania komputerowego w zagadnieniach poszukiwania optymalnych rozwiązań konstrukcyjnych.

20

Fuzzy-neural and evolutionary computation in identification of defects

Burczyński T., Orantek P., Skrobol A.

Journal of Theoretical and Applied Mechanics

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2004

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Vol. 42 nr 3

445-460

EN

It is known that an elastic body contains some internal defects such as voids, cracks, additional masses, etc. This paper is devoted to a method based on computational intelligence for non-destructive defect identification. In the presented paper, an elastic body loaded statically is considered. The body contains an unknown number of internal defects. There are a lot of applications based on non-destructive methods. The Evolutionary Algorithm (EA) with the Boundary Element method (BEM) is a very effective tool in the identification of internal defects. In this method, the fitness function is calculated for each chromosome in each generation by the BEM. The number of chromosomes in each generation is quite large, and the number of generations is also large, so the time needed to carry out the identification is very long. Methods based on Artificial Neural Networks (ANN) find the position and shape of internal defects in a very short time. Because ANNs are usually trained using gradient methods, the risk that the solution is in a local optimum is one of disadvantages of such a method. There is also a problem when the ANN has to identify two or more different kinds of defects (cracks, voids and additional masses) in one body. In the present method, an EA is connected with the ANN in one system. This operational allows to avoid main disadvantages of these methods and to use their advantages. The evolutionary algorithm is applied to identify the number of defects and their parameters (position and size). The identification of a defect in the body is performed by minimizing the fitness function which is calculated as a difference between measured and computed displacements in some sensor points on the boundary of the investigated structure. The fitness function is computed using an Artificial Neural Network (ANN).

PL

Obiekty techniczne jako układy mechaniczne zawierają różne defekty wewnętrzne takie jak pustki, pęknięcia itp. Artykuł jest poświęcony nieniszczącym metodom identyfikacji defektów opartym na inteligencji obliczeniowej. Rozważane jako ciało sprężyste znajdujące się pod wpływem obciążenia statycznego zawierające nieznaną liczbę defektów wewnętrznych. Istnieje wiele nieniszczących metod identyfikacji defektów wewnętrznych. Jedną z nich jest metoda oparta na Algorytmach Ewolucyjnych (AE) połączonych z Metodą Elementów Brzegowych (MEB). W tej metodzie dla każdego chromosomu w każdym pokoleniu obliczana jest za pomocą MEB funkcja przystosowania. Ponieważ liczba chromosomów w epoce oraz liczba epok jest dosyć duża, zatem czas potrzebny do przeprowadzenia identyfikacji jest znaczący. Metody bazujące na Sztucznych Sieciach Neuronowych (SSN) identyfikują położenie oraz kształt defektów wewnętrznych w bardzo krótkim czasie. SSN są zazwyczaj uczone z wykorzystaniem metod gradientowych. Isnieje zatem spore ryzyko, że uzyskane rozwiązanie utknęło w minimum lokalnym. Wykorzystując SSN napotykamy na spore trudności również w przypadku identyfikacji dwóch lub więcej różnych rodzajów defektów (pęknięć, pustek itp.), które występują jednocześnie w identyfikowanym układzie. W metodzie opisywanej w niniejszym artykule połączono AE oraz SSn w jeden system. Operacja ta pozwoli ustrzec się przed głównymi wadami i uwypuklić zalety obydwu metod. AE identyfikuje liczbę, położenie oraz wymiary defektów. Identyfikacja następuje przez minimalizację funkcji przystosowania, która jest mierzona jako różnica pomiędzy zmierzonymi i obliczonymi przemieszczeniami na brzegu modelu obiektu w punktach kontrolnych. Funkcja przystosowania jest obliczana z wykorzystaniem SSN.