Topology optimization of a nonlinear ferrite core for induction heating in injection molding

Purpose Recent progress in additive manufacturing methods alleviated manufacturing constraints on devices. Topology optimization (TO) methods can leverage these reduced limitations and this paper aims to study the use of these algorithms in induction heating for injection molding. Design/methodology/approach In this paper, TO is used to reduce the volume of ferrite in an injection molding tool while aiming at maximizing the performance of the device. Characteristics of the proposed solution such as efficiency and power density are compared to the ones of the original device. Findings The study shows that it is possible to reduce significantly the amount of ferrite used without impacting the efficiency. The thermal performances of the proposed solution present also slight improvements compared to the original solution. Originality/value Optimization algorithms are important for understanding how to design efficient electrical devices. In this paper, the application of TO for injection molding applications presents a new perspective in designing such components.

Authors

Institutions

Publication Details

Journal
COMPEL The International Journal for Computation and Mathematics in Electrical and Electronic Engineering
Published
2024-12-27
DOI
https://doi.org/10.1108/compel-09-2024-0384
Citations
1
Primary Topic
Topology Optimization in Engineering
Type
article
Field-Weighted Citation Impact
0.26
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Topology optimization of a nonlinear ferrite core for induction heating in injection molding

Riccardo Torchio, Fabrizio Dughiero, Michele Forzan, Francesco Lucchini et al.
1 citations
COMPEL The International Journal for Computation and Mathematics in Electrical and Electronic Engineering
Topology Optimization in Engineering
0.26
article

Topology optimization of a nonlinear ferrite core for induction heating in injection molding

Riccardo Torchio, Fabrizio Dughiero, Michele Forzan, Francesco Lucchini, Matteo Zorzetto, Giulio Poggiana
article en
1 citations

Abstract

Purpose Recent progress in additive manufacturing methods alleviated manufacturing constraints on devices. Topology optimization (TO) methods can leverage these reduced limitations and this paper aims to study the use of these algorithms in induction heating for injection molding. Design/methodology/approach In this paper, TO is used to reduce the volume of ferrite in an injection molding tool while aiming at maximizing the performance of the device. Characteristics of the proposed solution such as efficiency and power density are compared to the ones of the original device. Findings The study shows that it is possible to reduce significantly the amount of ferrite used without impacting the efficiency. The thermal performances of the proposed solution present also slight improvements compared to the original solution. Originality/value Optimization algorithms are important for understanding how to design efficient electrical devices. In this paper, the application of TO for injection molding applications presents a new perspective in designing such components.

COMPEL The International Journal for Computation and Mathematics in Electrical and Electronic EngineeringVol. 44(3)
University of Padua (IT)
Affordable and clean energy
Openalex Percentile: Top 42%
Topology Optimization in Engineering
0.26
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Topology optimization of a nonlinear ferrite core for induction heating in injection molding — Riccardo Torchio, Fabrizio Dughiero, et al. · COMPEL The International Journal for Computation and Mathematics in Electrical and Electronic Engineering (2024) | TGRS Research Map | TGRS