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Reconstruction of the thermal conductivity coefficient by using the harmony search algorithm

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Języki publikacji
EN
Abstrakty
EN
Purpose: of this paper: Aim of this paper is a presentation of the respectively new tool for solving the optimization problems, which is the Harmony Search algorithm in version slightly modified by the authors, used for identifying the thermal conductivity coefficient. Proposed approach is illustrated with an example confirming its usefulness for solving such kinds of problems. Design/methodology/approach: For solving the considered parametric inverse heat conduction problem the approach is applied in which the essential part consists in minimization of the functional representing the differences between the measurement values of temperature and approximate values calculated with the aid of finite difference method. For minimizing the functional the Harmony Search algorithm is used. Findings: The elaboration shows that approaches involving the algorithms of artificial intelligence for solving the inverse heat conduction problems of that kind are efficient and they ensure to receive satisfying results in shorter time in comparison with the classical procedures. Research limitations/implications: Specific properties of the heuristic algorithms require to execute the procedure several times and to average the obtained results because each running of the algorithm can give slightly different results. Each execution of the procedure means the solution of the direct problem associated with the considered inverse problem by using the finite difference method. Practical implications: In spite of the problem described above the approaches involving the heuristic algorithms of artificial intelligence are successful because they are respectively simple and easy to use and they give satisfying results after short time of working. Another advantage of using optimization algorithms of that kind is the fact that they do not need to satisfy any assumptions about the solved problem, oppositely to the classical optimization algorithms. Originality/value: Proposal of the original approach involving the heuristic optimization algorithm for solving the parametric inverse heat conduction problem is discussed in the paper.
Rocznik
Strony
299--304
Opis fizyczny
Bibliogr. 25 poz., rys.
Twórcy
  • Institute of Mathematics, Silesian University of Technology, ul. Kaszubska 23, 44-100 Gliwice, Poland
autor
  • Institute of Mathematics, Silesian University of Technology, ul. Kaszubska 23, 44-100 Gliwice, Poland
autor
  • Institute of Mathematics, Silesian University of Technology, ul. Kaszubska 23, 44-100 Gliwice, Poland
autor
  • Institute of Mathematics, Silesian University of Technology, ul. Kaszubska 23, 44-100 Gliwice, Poland
Bibliografia
  • [1] J.V. Beck, B. Blackwell, C.R. St.Clair, Inverse heat conduction: ill posed problems, Wiley Interscience, New York, 1985.
  • [2] K. Kurpisz, A.J. Nowak, Inverse thermal problems, Computational Mechanics Publications, Southampton, Boston (1995) 259-298.
  • [3] R. Grzymkowski, M. Pleszczyński, D. Słota, Application of the Adomian decomposition method for solving the heat equation in the cast-mould heterogeneous domain, Archives of Foundry Engineering 9/4 (2009) 57-62.
  • [4] J-H. He, X-H Wu, Variational iteration method: New development and applications, Computers & Mathematics with Applications 54 (2007) 881-894.
  • [5] E. Hetmaniok, D. Słota, A. Zielonka, Solution of the solidification problem by using the variational iteration method, Archives of Foundry Engineering 9/4 (2009) 63-68.
  • [6] J.V. Beck, K.D. Cole, A. Haji-Sheikh, B. Litkouhi, Heat conduction using Green's functions, Hempisphere Publishing Corporation, Philadelphia, 1992.
  • [7] A. Haji-Sheikh, F.P. Buckingham, Multidimensional inverse heat conduction using the Monte Carlo method, Trans. of ASME, Journal of Heat Transfer 115 (1993) 26-33.
  • [8] D.A. Mourio, The mollification method and the numerical solution of ill-posed problems, John Wiley and Sons, New York, 1993.
  • [9] C.Y. Qiu, C.L. Fu, Y.B. Zhu, Wavelets and regularization of the sideways heat equation, Computers & Mathematics with Applications 46 (2003) 821-829.
  • [10] J. Arabas, Lectures in evolutionary algorithms, WNT, Warsaw, 2001 (in Polish).
  • [11] Z. Michalewicz, Genetic algorithms + data structures = evolutionary programs, WNT, Warsaw, 1996 (in Polish).
  • [12] D.E. Goldberg, Genetic algorithms and their applications, WNT, Warsaw, 1998 (in Polish).
  • [13] M. Raudensky, K.A. Woodbury, J. Kral, T. Brezina, Genetic algorithm in solution of inverse heat conduction problem, Numerical Heat Transfer, Part B 28/3 (1995) 293-306.
  • [14] D. Słota, Restoring boundary conditions in the solidification of pure metals, Computers and Structures 89 (2011) 48-54.
  • [15] M. Dorigo, T. Stutzle, Ant Colony Optimization, MlT Press, 2004.
  • [16] M. Dorigo, G.Di Caro, L.M. Gambardella, Ant Algorithms for Discrete Optimization, Artificial Life 5/2 (1999) 137-172.
  • [17] D. Karaboga, B. Basturk, A powerful and efficient algorithm for numerical function optimization: Artificial Bee Colony (ABC) Algorithm, Journal of Global Optimization 39/3 (2007) 459-471.
  • [18] D. Karaboga, B. Basturk, On the performance of artificial bee colony (ABC) algorithm, Applied Soft Computing 8/1 (2008) 687-697.
  • [19] E. Hetmaniok, D. Jama, D. Słota, A. Zielonka, Application of the Harmony Search algorithm in solving the inverse heat conduction problem, Scientific Papers of Silesian University of Technology, Applied Mathematics 1 (2011) 99-108.
  • [20] E. Hetmaniok, A. Zielonka, Solving the inverse heat conduction problem by using the ant colony optimization algorithm, Proceedings of the 18th International Conference on Computer Methods in Mechanics “CMM-2009”, Zielona Góra, 2009, 205-206.
  • [21] E. Hetmaniok, D. Słota, A. Zielonka, Solution of the inverse heat conduction problem by using the ABC algorithm, Lecture Notes in Artificial Intelligence 6086 (2010) 659-668.
  • [22] Z.W. Geem, Improved Harmony Search from ensemble of music players, Lecture Notes in Artificial Intelligence 4251 (2006) 86-93.
  • [23] Z.W. Geem, J.H. Kim, G.V. Loganathan, A new heuristic optimization algorithm: Harmony Search, Simulation 76 (2001) 60-68.
  • [24] Z.W. Geem, K.S. Lee, Y. Park, Application of Harmony Search to vehicle routing, American Journal of Applied Sciences 2 (2005) 1552-1557.
  • [25] Z.W. Geem, Optimal cost design of water distribution networks using Harmony Search, Optimization and Engineering 38 (2006) 259-280.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-a15eec54-0525-4bcb-af3c-96e3d3358c5c
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