Work

Digital Twin for the control of induction cure in composites manufacturing

Year: 2026

Type: article

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 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 5℃ error margin and remains effective under evolving thermal properties during CFRP curing.

Source: Composites Part B Engineering

DOI: 10.1016/j.compositesb.2026.113550

Authors: Anagnostis Samanis, Yusuf Mahadik, Janice M. Dulieu-Barton, Jason Zheng Jiang, Dmitry S. Ivanov

Institution: University of Bristol

Language: English

Topic: Induction Heating and Inverter Technology

Subfield: Mechanical Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: hybrid

Estimated APC paid: $5,210