Purpose – This paper aims to present the optimal design of an inductor used to heat a magnetic nanoparticle fluid injected in a cell culture inside a Petri dish. Design/methodology/approach – The inductor design is driven by means of a multi-objective optimization algorithm that generalizes the migration-non-dominated sorting genetic algorithm (NSGA); it is called self-adapting migration-NSGA. Findings – The optimized device is able to synthesize a uniform magnetic field in a nanoparticle fluid, substantially helping its heating capability. The ultimate scope is to assist the cancer therapy based on magnetic fluid hyperthermia (MFH). Originality/value – The optimal design of an inductor for MFH applications has been carried out by applying an improved version of migration-based NSGA-II algorithm including automatic stop and a self-adapting concept. The modified optimization algorithm is suitable to find better optimal solutions with respect to a standard version of NSGA-II.
|Data di pubblicazione:||2017|
|Titolo:||Self-adaptive NGSA algorithm and optimal design of inductors for magneto-fluid hyperthermia|
|Digital Object Identifier (DOI):||10.1108/COMPEL-05-2016-0188|
|Codice identificativo ISI:||WOS:000399047400017|
|Codice identificativo Scopus:||2-s2.0-85015829323|
|Parole Chiave:||Magnetic fields; Optimal design; Multi-objective optimization; Finite element analysis; Genetic algorithms; Pareto optimization|
|Appare nelle tipologie:||Articolo su Rivista|