New solutions to a multi-objective benchmark problem of induction heating: an application of computational biogeography and evolutionary algorithms

• Autorzy: Di Barba P. , Dughiero F. , Forzan M. , Mognaschi M. E. , Sieni E.

Identyfikatory

DOI

10.24425/118997

• Języki publikacji: EN

Abstrakty

EN

In induction heating the design of the inductor implies the solution of coupled electromagnetic and thermal fields, along with the use of optimal design procedures to identify the best possible device or process. The benchmark model proposed, a graphite disk heated by means of induction, is optimized using different optimization algorithms. The design aim requires to achieve a prescribed and uniform temperature distribution in the workpiece maximizing the system efficiency.

Słowa kluczowe

EN

induction heating; multi-physics analysis; multi-objective optimization; benchmark

• Wydawca: Polish Academy of Sciences, Committee on Electrical Engineering
• Czasopismo: Archives of Electrical Engineering
• Rocznik: 2018
• Tom: Vol. 67, nr 1
• Strony: 139--149
• Opis fizyczny: Bibliogr. 34 poz., rys., tab., wz.

Twórcy

autor

Di Barba P.

• Department of Electrical, Computer and Biomedical Engineering, University of Pavia Via Ferrata 5, 27100 Pavia, Italy

autor

Dughiero F.

• Department of Industrial Engineering, University of Padova Via Gradenigo 6/A, 35131 Padova, Italy

autor

Forzan M.

• Department of Industrial Engineering, University of Padova Via Gradenigo 6/A, 35131 Padova, Italy

autor

Mognaschi M. E.

• Department of Electrical, Computer and Biomedical Engineering, University of Pavia Via Ferrata 5, 27100 Pavia, Italy

autor

Sieni E.

• Department of Industrial Engineering, University of Padova Via Gradenigo 6/A, 35131 Padova, Italy

Bibliografia

• [1] Lozinskii M.G., Industrial applications of induction heating, Pergamon press (1969).
• [2] Barglik J., Induction heating in technological processes – selected examples of application, Przegląd Elektrotechniczny, vol. 86, iss. 5, pp. 294–297 (2010).
• [3] Mach M., Doležel I., Barglik J., Karban P., Electromagnetic contactless heat treatment of nonferrous metals and its selected applications, Proceedings of the 8th International Scientific Conference Electric Power Engineering 2007, EPE 2007, Kouty nad Desnou (Czech Republic), 12–14 June 2007, pp. 110–123 (2007).
• [4] Schlesselmann D., Yu Z., Dalinger A., Nacke B., New applications of numerical simulation in inductive surface hardening with flux concentrators, HTM – Journal of Heat Treatment and Materials, vol. 70, no. 1, pp. 40–49 (2015).
• [5] Baake E., Nacke B., Efficient heating by electromagnetic sources in metallurgical processes: recent applications and development trends, Przegla˛d Elektrotechniczny, vol. 86, no. 7, pp. 11–14 (2010).
• [6] Pleshivtseva Y., Zaikina N., Nacke B., Nikanorov A., Time-optimal control of energy – Efficient heating of aluminium billets rotating in DC magnetic field, Przegla˛d Elektrotechniczny, vol. 84, no. 11, pp. 120–123 (2008).
• [7] Kotlan V., Karban P., Ulrych B., Doležel I., Kůs P., Hard-coupled modeling of induction shrink fit of gas-turbine active wheel, Studies in Computational Intelligence, vol. 483, pp. 325–339 (2013).
• [8] Barglik J.,Wieczorek T., Smalcerz A., Modeling of the surface induction hardening process, Przegląd Elektrotechniczny, vol. 90, no. 2, pp. 1–4 (2014).
• [9] Barglik J., Golak S., Modelling of filling a mold with molten metal in the presence of an electromagnetic field, Magnetohydrodynamics, vol. 51, no. 1, pp. 5–14 (2015).
• [10] Zgraja J., The optimisation of induction heating system based on multiquadric function approximation, COMPEL – The International Journal for Computation and Mathematics in Electrical and Electronic Engineering, vol. 24, no. 1, pp. 305–313 (2005).
• [11] Mach F., Adam L., Kacerovský J., Karban P., Doležel I., Evolutionary algorithm-based multi-criteria optimization of triboelectrostatic separator, Journal of Computational and Applied Mathematics, vol. 270, pp. 134–142 (2014).
• [12] Di Barba P., Dughiero F., Forzan M., Sieni E., Improved solution to a multi-objective benchmark problem of inverse induction heating, International Journal of Applied Electromagnetics and Mechanics, vol. 49, no. 2, pp. 279–288 (2015).
• [13] Di Barba P., Dughiero F., Forzan M., Sieni E., A Paretian Approach to Optimal Design With Uncertainties: Application in Induction Heating, IEEE Transactions on Magnetics, vol. 50, pp. 917–920 (2014).
• [14] Di Barba P., Forzan M., Sieni E., Multiobjective design optimization of an induction heating device: A benchmark problem, International Journal of Applied Electromagnetics and Mechanics, vol. 47, no. 4, pp. 1003–1013 (2015).
• [15] Lupi S., Forzan M., Aliferov A., Induction and direct resistance heating: theory and numerical modelling, Springer (2015).
• [16] Pleshivtseva Y., Di Barba P., Rapoport E., Nacke B., Nikanorov A., Lupi S., Sieni E., Forzan M., Multi-objective optimisation of induction heaters design based on numerical coupled field analysis, International Journal of Microstructure and Materials, vol. 9, no. 6, pp. 532–551 (2014).
• [17] Forzan M., Maccalli G., Valente G., Crippa D., Design of an innovative heating process system for the epitaxial growth of silicon carbide layers wafer, Proc. of MMP – Modelling for Material Proc., (2006).
• [18] Binns K.J., Lawrenson P.J., Trowbridge C.W., The analytical and numerical solution of electric and magnetic fields, Chichester: Wiley (1992).
• [19] Deb K., Multi-Objective Optimisation Using Evolutionary Algorithms, Wiley (2001).
• [20] Deb K., Pratap A., Agarwal S., Meyarivan T., A fast and elitist multiobjective genetic algorithm: NSGA-II, IEEE Transactions on Evolutionary Computation, vol. 6, no. 2, pp. 182–197 (2002).
• [21] Bertani R., Forzan M., Sgarbossa P., Sieni E., Di Barba P., Spizzo F., Del Bianco L., Multi-objective design of a magnetic fluid hyperthermia device, IECON 2015 – 41st Annual Conference of the IEEE Industrial Electronics Society, no. 7392660, pp. 3603–3608 (2015).
• [22] Sieni E., Di Barba P., Forzan M., Migration NSGA: method to improve a non-elitist searching of Pareto front, with application in magnetics, Inverse Problems in Science and Engineering IPSE, vol. 24, no. 4, pp. 543–566 (2016).
• [23] Di Barba P., Dughiero F., Mognaschi M.E., Savini A.,Wiak S., Biogeography-Inspired Multiobjective Optimization and MEMS Design, IEEE Transactions on Magnetics, vol. 52, no. 3, pp. 1–4 (2016).
• [24] Di Barba P., Mognaschi M.E., Savini A., Wiak S., Island biogeography as a paradigm for MEMS optimal design, IJAEM, vol. 51, no. S1, pp. 97–105 (2016).
• [25] Di Barba P., Dolezel I., Karban P., Kus P., Mach F., Mognaschi M.E., Savini A., Multiphysics field analysis and multiobjective design optimization: a benchmark problem, Inverse Problems in Science and Engineering IPSE, vol. 22, no. 7 (2014).
• [26] Zgraja J., Cieslak A., Induction heating in estimation of thermal properties of conductive materials, The International Journal for Computation and Mathematics in Eelectrical and Electronic Engineering, vol. 36, iss. 2, pp. 458–468 (2017).
• [27] Cieslak A., Zgraja J., Induction heating laboratory stand for estimating thermal properties of a charge, Przegląd Elektrotechniczny, vol. 92, iss. 3, pp. 57–60 (2016).
• [28] Stratton, J.A., Electromagnetic Theory, John Wiley & Sons, Inc., Hoboken, NJ (2007).
• [29] Holman, J.P., Heat Transfer, McGrawHill, New York, NY (2001).
• [30] Simon D., Biogeography-Based optimization, IEEE Transactions on Evolutionary Computation, vol. 12, pp. 702–713 (2008).
• [31] Singh U., Kumar H., Kamal T.S., Design of Yagi–Uda Antenna Using Biogeography Based Optimization, IEEE Transactions on Antennas and Propagation, vol. 58, pp. 3375-3379 (2010).
• [32] Dos Santos Coelho L., Alotto P., Electromagnetic optimization using a cultural self-organizing migrating algorithm approach based on normative knowledge, IEEE Transactions on Magnetics, vol. 45, pp. 1446–1449 (2009).
• [33] Di Barba P., Mognaschi M.E., Venini P., Wiak S., Biogeography-inspired multiobjective optimization for helping MEMS synthesis, Archives of Electrical Engineering, vol. 66, no. 3, pp. 607–623 (2017).
• [34] Di Barba P., Mognaschi M.E., Krawczyk A., The biogeography-inspired optimization for the design of coils for nerve stimulation, 17th IEEE International Conference on Smart Technologies, EUROCON 2017 – Conference Proceedings, 6-8 July 2017, pp. 542–545 (2017).

Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).