Digital Twin for the control of induction cure in composites manufacturing

Heating methods for curing carbon fibre reinforced polymer (CFRP) composites traditionally use ovens and autoclaves, which are often inefficient, slow and energy-intensive. Electromagnetic (EM) induction offers a rapid, volumetric heating alternative, targeting electrically conductive materials, such as carbon, rather than the surrounding medium. However, controlling this process is challenging due to non-uniform Joule heating through the CFRP thickness. The heat supply is highly sensitive to numerous parameters and set-up arrangements, including coil frequency, current density, coil configuration, material-to-coil position, reinforcement electrical properties, material architecture, laminate layup and thickness. These complexities hinder reliable thermal control and broader adoption of induction. To unlock the potential of induction heating, accurate temperature assessment throughout the material volume and reliable prediction of thermal response to coil current changes are essential. These must be achieved in real-time to steer the cure process, reduce exothermic risk, ensure uniform cure, meet glass transition requirements and minimise energy use and duration. Hence a new thermal control strategy based on a Digital Twin of the process is presented. The twin integrates the pulse excitation of the material for gathering information-rich data, Latin Hypercube (LH) sampling for iterative and optimised parameter estimation and a batch Nonlinear Least Squares technique (NLSQ) with Gauss Newton minimisation. The methodology is validated virtually and experimentally using induction and heating mats. A surrogate model is derived from the combined LH and NLSQ estimators. The model predicts material temperature evolution within a error margin and remains effective under evolving thermal properties during CFRP curing. • A system identification methodology is created based on a Digital Twin that represents the interaction of induction heating with electro-conductive composites. • The feasibility of the digital twinning approach that includes the Joule heating and curing phases that occur during induction processing of carbon fibre reinforced polymer (CFRP) composites. • An experimental methodology for calibrating the digital twin is established which identifies the induction parameters, process parameters and material properties. • A novel model-based control strategy is devised for real-time process control and optimisation of CFRP induction curing.

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Publication Details

Journal
Composites Part B Engineering
Published
2026-02-24
DOI
https://doi.org/10.1016/j.compositesb.2026.113550
Primary Topic
Induction Heating and Inverter Technology
Type
article
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article

Digital Twin for the control of induction cure in composites manufacturing

Jason Zheng Jiang, Yusuf Mahadik, Dmitry Ivanov, Anagnostis Samanis et al.
Composites Part B Engineering
Induction Heating and Inverter Technology
article

Digital Twin for the control of induction cure in composites manufacturing

Jason Zheng Jiang, Yusuf Mahadik, Dmitry Ivanov, Anagnostis Samanis, Janice M. Dulieu-Barton
article en

Abstract

Heating methods for curing carbon fibre reinforced polymer (CFRP) composites traditionally use ovens and autoclaves, which are often inefficient, slow and energy-intensive. Electromagnetic (EM) induction offers a rapid, volumetric heating alternative, targeting electrically conductive materials, such as carbon, rather than the surrounding medium. However, controlling this process is challenging due to non-uniform Joule heating through the CFRP thickness. The heat supply is highly sensitive to numerous parameters and set-up arrangements, including coil frequency, current density, coil configuration, material-to-coil position, reinforcement electrical properties, material architecture, laminate layup and thickness. These complexities hinder reliable thermal control and broader adoption of induction. To unlock the potential of induction heating, accurate temperature assessment throughout the material volume and reliable prediction of thermal response to coil current changes are essential. These must be achieved in real-time to steer the cure process, reduce exothermic risk, ensure uniform cure, meet glass transition requirements and minimise energy use and duration. Hence a new thermal control strategy based on a Digital Twin of the process is presented. The twin integrates the pulse excitation of the material for gathering information-rich data, Latin Hypercube (LH) sampling for iterative and optimised parameter estimation and a batch Nonlinear Least Squares technique (NLSQ) with Gauss Newton minimisation. The methodology is validated virtually and experimentally using induction and heating mats. A surrogate model is derived from the combined LH and NLSQ estimators. The model predicts material temperature evolution within a error margin and remains effective under evolving thermal properties during CFRP curing. • A system identification methodology is created based on a Digital Twin that represents the interaction of induction heating with electro-conductive composites. • The feasibility of the digital twinning approach that includes the Joule heating and curing phases that occur during induction processing of carbon fibre reinforced polymer (CFRP) composites. • An experimental methodology for calibrating the digital twin is established which identifies the induction parameters, process parameters and material properties. • A novel model-based control strategy is devised for real-time process control and optimisation of CFRP induction curing.

Composites Part B EngineeringVol. 316
University of Bristol (GB)
Affordable and clean energy
Openalex Percentile: Top 47%
Induction Heating and Inverter Technology
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