Sensitivity‐based optimal shape design of induction‐heating devices

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

Solving 1D non‐linear magneto quasi‐static Maxwell's equations using neural networks

“…Since we will deal with ferromagnetic materials (mostly metals), frequencies not higher than a hundred of kHz, and small size setups ( m), the last term of Equation (1) could be neglected (magneto quasi‐static—MQS—approximation of the Maxwell's equations) [27–30]. This formulation, just to name a few examples, is broadly used in the field analysis of induction heating [31, 32], inverse B–H identification [33], power transmission lines [34], electrical machines [35]. Combining Equation (3) with the first constitutive law and Equation (1) leads to: …”

Self-adaptive migration NSGA and optimal design of inductors for magneto-fluid hyperthermia

“…The average distance of N p individuals from the Utopia point d f (k) at the k-th iteration is: where, N f is the number of objective functions, while f i,j and u j are the current values of the objective functions and the Utopia point components, respectively. If the Utopia point is not improved with respect to the previous step, the relative movement m f (k) of the front between k-th and (k − 1)-th iteration, is considered (Di Barba et al , 2015a, 2015b, 5015c, 2015d; Bertani, et al 2016): …”

“…The following two equations are solved applying the Coulomb gauge on the magnetic vector potential, i.e. ∇⋅ A ̇ = 0 and suitable boundary conditions (Bertani et al , 2015; Di Barba et al , 2015d; Bertani et al , 2016): where, µ 0 is the permeability of the vacuum and µ r ( H ) is the relative magnetic permeability that depends on magnetic field in a non-linear material like the one the ferrite yoke is made of; in turn, µ r = 1 holds in the other field subregions. Moreover, ρ is the material resistivity and ω is the angular frequency.…”

Induction clamping of high-revolution tools by rotation in a system of unmovable permanent magnets

“…The sensitivity of design variables is computed using Design of Experiments (DOE) method (di Barba et al, 2015aBarba et al, , 2015b in order to obtain the effect of the influence of the shape and position of permanent magnets. The variance may be expressed by a set of fractions expressing the influence of separate input parameters or their groups on the output (e.g., Sobol approach or LHC).…”