A design of experiment (DOE) strategy applied to multi-objective optimisation is proposed in order to evaluate the influence of design variables variations to optimised quantities. A secondary objective function is the sensitivity of a primary objective function to design variable variations evaluated by means of DOE strategy. The optimisation problem includes also a thir objective function that considers device constraint because of technological limitations on power generator. The proposed case study deals with the design of an electromagnetic device that will be used to carry out laboratory experiments on magneto-fluid hyperthermia, that is, a clinic treatment for cancer cure. The induction system is designed to apply a controlled time-varying magnetic field to biological cells, cultured in Petri dish and mixed with magnetic nanoparticles. This study presents an original cost-effective method of multi-objective design optimisation taking into account design uncertainties.

Sensitivity-based optimal shape design of induction-heating devices

FORZAN, MICHELE;SIENI, ELISABETTA
2015-01-01

Abstract

A design of experiment (DOE) strategy applied to multi-objective optimisation is proposed in order to evaluate the influence of design variables variations to optimised quantities. A secondary objective function is the sensitivity of a primary objective function to design variable variations evaluated by means of DOE strategy. The optimisation problem includes also a thir objective function that considers device constraint because of technological limitations on power generator. The proposed case study deals with the design of an electromagnetic device that will be used to carry out laboratory experiments on magneto-fluid hyperthermia, that is, a clinic treatment for cancer cure. The induction system is designed to apply a controlled time-varying magnetic field to biological cells, cultured in Petri dish and mixed with magnetic nanoparticles. This study presents an original cost-effective method of multi-objective design optimisation taking into account design uncertainties.
2015
Cost effectiveness; Design; Electromagnets; Hyperthermia therapy; Induction heating; Multiobjective optimization; Nanomagnetics; Nanoparticles; Optimization; Sensitivity analysis
Di Barba, P.; Dughiero, Fabrizio; Forzan, Michele; Sieni, Elisabetta
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11383/2077285
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