Determination of the Heat Flux in the Process of Solidification by Applying the Ant Colony Optimization Algorithm

Article Preview

Abstract:

The paper presents an application of Ant Colony Optimization algorithm as a partof procedure for solving the inverse solidification problem. Investigated task consists in recon-struction of the boundary condition (heat flux) on the basis of temperature measurements inselected points of the cast. First step of the method is based on the finite difference method withapplication of the generalized alternating phase truncation method and serves for solving theappropriate direct solidification problem. In the second step some functional representing thecrucial part of the procedure is minimized with the aid of Ant Colony Optimization algorithm.

You might also be interested in these eBooks

Info:

Periodical:

Key Engineering Materials (Volumes 622-623)

Pages:

764-771

Citation:

Online since:

September 2014

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2014 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] J.V. Beck, B. Blackwell and C.R. St. Clair: Inverse Heat Conduction: Ill Posed Problems (Wiley Intersc., New York 1985).

Google Scholar

[2] I. Nowak, A.J. Nowak and L.C. Wrobel: Inverse analysis of continuous casting processes Int. J. Numer. Methods Heat Fluid Flow Vol. 13 (2003), pp.547-564.

DOI: 10.1108/09615530310482445

Google Scholar

[3] D. Słota: Solving the inverse Stefan design problem using genetic algorithm Inverse Probl. Sci. Eng. Vol. 16 (2008), pp.829-846.

DOI: 10.1080/17415970801925170

Google Scholar

[4] B. Mochnacki: Numerical modeling of solidification process in: Computational Simulations and Applications, edited by J. Zhu, InTech, Rijeka (2011), pp.513-542.

Google Scholar

[5] C.A. Santos, J.M.V. Quaresma and A. Garcia: Determination of transient interfacial heat transfer coefficients in chill mold castings J. Alloys and Compounds Vol. 319 (2001), pp.174-186.

DOI: 10.1016/s0925-8388(01)00904-5

Google Scholar

[6] D. Ionescu, I. Ciobanu, S.I. Munteanu, A. Crisan and V. Monescu: 2D mathematical model for the solidification of alloys within a temperature interval Metalurgia International Vol. 16 (4) (2011), pp.39-44.

Google Scholar

[7] A. Piasecka Belkhayat: Numerical modelling of solidification process using interval boundary element method Arch. Foundry Eng. Vol. 8 (4) (2008), pp.171-176.

Google Scholar

[8] B. Mochnacki, E. Majchrzak and A. Kapusta: Numerical model of heat transfer processes in solidifying and cooling steel ingot (on the basis of BEM) in: Computational Modelling of Free and Moving Boundary Problems 2, edited by L.C. Wrobel and C.A. Brebbia, Heat Transfer, Computational Mech. Publ. Southampton (1992).

DOI: 10.1515/9783110853209-013

Google Scholar

[9] B. Mochnacki and J.S. Suchy: Numerical Methods in Computations of Foundry Processes (PFTA, Cracow 1995).

Google Scholar

[10] D. Słota: Restoring boundary conditions in the solidification of pure metals Comput. Struct. Vol. 89 (2011), pp.48-54.

DOI: 10.1016/j.compstruc.2010.08.002

Google Scholar

[11] R.C. Eberhart, Y. Shi and J. Kennedy: Swarm Intelligence (Morgan Kaufmann, San Francisco 2001).

Google Scholar

[12] G. Beni and J. Wang: Swarm intelligence in cellular robotic systems (Proceed. NATO Advanced Workshop on Robots and Biological Syst., Tuscany 1989).

Google Scholar

[13] M. Dorigo: Optimization, Learning and Natural Algorithms (Ph.D. Thesis, Politecnico di Milano, Milan 1992) (in Italian).

Google Scholar

[14] M. Dorigo and Ch. Blum: Ant colony optimization theory: a survey Theor. Comput. Sci. Vol. 344 (2005), pp.243-278.

DOI: 10.1016/j.tcs.2005.05.020

Google Scholar

[15] M. Duran Toksari: Ant Colony Optimization for finding the global minimum Appl. Math. Comput. Vol. 176 (2006), pp.308-316.

DOI: 10.1016/j.amc.2005.09.043

Google Scholar

[16] T. Stützle and H.H. Hoos: Max-Min Ant System Future Gener. Comp. Sy. Vol. 16 (2000), pp.889-914.

Google Scholar

[17] X. Hu, J. Zhang and Y. Li: Orthogonal methods based ant colony search for solving continuous optimization problems J. Computer Sci. Techn. Vol. 23 (1) (2008), pp.2-18.

DOI: 10.1007/s11390-008-9111-5

Google Scholar

[18] J. Bai, G. -K. Yang, Y. -W. Chen, L. -S. Hu and Ch. -Ch. Pan: A model induced max-min ant colony optimization for asymmetric traveling salesman problem Appl. Soft Comp. Vol. 13 (2013), pp.1365-1375.

DOI: 10.1016/j.asoc.2012.04.008

Google Scholar

[19] R.S. Parpinelli, H.S. Lopes and A.A. Freitas: Data mining with an ant colony optimization algorithm IEEE Transaction on Evolutionary Computation Vol. 6 (4) (2002), pp.321-332.

DOI: 10.1109/tevc.2002.802452

Google Scholar

[20] H. Nezamabadi-pour, S. Saryazdi and E. Rashedi: Edge detection using ant algorithms Soft Computing Vol. 10 (7) (2006), pp.623-628.

DOI: 10.1007/s00500-005-0511-y

Google Scholar

[21] J. Zhang, H. Chung, W.L. Lo and T. Huang: Extended Ant Colony Optimization Algorithm for Power Electronic Circuit Design IEEE Transactions on Power Electronic Vol. 24 (1) (2009), pp.147-162.

DOI: 10.1109/tpel.2008.2006175

Google Scholar

[22] E. Hetmaniok, D. Słota and A. Zielonka: Determination of the heat transfer coefficient by using the ant colony optimization algorithm Lect. Notes Comput. Sc. Vol. 7203 (2011), pp.470-479.

DOI: 10.1007/978-3-642-31464-3_48

Google Scholar

[23] R. Grzymkowski, E. Hetmaniok, D. Słota and A. Zielonka: Application of the Ant Colony Optimization algorithm in solving the inverse Stefan problem Steel Res. Int. special edition Metal Forming (2012), pp.1287-1290.

Google Scholar