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Model-based multi-objective optimization of cure process control for a large CFRP panel

Sergey Shevtsov (Laboratory of Aircraft Systems and Technologies, South Center of Russian Academy of Science, Rostov on Don, Russia)
Igor V. Zhilyaev (Laboratory of Aircraft Systems and Technologies, South Center of Russian Academy of Science, Rostov on Don, Russia)
Ilya Tarasov (Perspective Investigations of Composites Co., Saint-Petersburg, Russia)
Jiing-Kae Wu (Department of Marine Engineering, National Kaohsiung Marine University, Kaohsiung, Taiwan)
Natalia G. Snezhina (Department of Aircraft Engineering, Don State Technical University, Rostov on Don, Russia)

Engineering Computations

ISSN: 0264-4401

Article publication date: 16 April 2018

165

Abstract

Purpose

The purpose of this paper is to develop the multi-objective optimization approach and its numerical implementation to synthesise the model-base control for the part curing at autoclave processing, which supplies the stability and uniformity of the structure and mechanical properties of the material within the cured composite part.

Design/methodology/approach

The approach includes conversion of the cured part and mold geometry from their computer-aided design (CAD) to computer-aided engineering (CAE) representation, a finite element (FE) formulation of the coupled forward heat transfer/thermal kinetic problem with the parameters of prepreg, which should be determined by the thermal analysis, and, finally, a mapping of the area of 4D design space (thermal control parameters) to 2D objective space, whose coordinates are the maximum deviations of degree of cure and temperature within the cured part calculated at each call of the FE model.

Findings

The present modeling and optimization approach to the cure process control of the prepreg with thermosetting resin, as well as the means of visualizing optimization results, allow providing insight into complex curing phenomena, estimating the best achievable quality indicators of manufactured composite parts, finding satisfactory parameters of the control law and deciding considering all manufacturing constraints.

Research limitations/implications

The research can be effectively used to optimize the cure process control for a wide class of polymeric composite parts, even with a complex geometry, but it requires the exact conversion of the geometry of the modeled part from the CAD to CAE environment, which implies the need for excluding all topological imperfections of original CAD model to eliminate the possible formation of void elements and other reasons that do not allow the correct FE meshing. Because thermal, rheological and kinetics parameters, which include the governing equations of cure process, depend on the reinforcing fibers, and especially on the resin properties, the thermal testing for the new modeled prepreg needs to be performed.

Practical implications

Computer implementation of the proposed approach and numerical method for model-based optimal control synthesis for composite part cure process can be used in aircraft, rotorcraft, ship and automotive technologies at the design of manufacturing process of the large composite parts with complex shape.

Social implications

This will allow much better quality for large-scale composite parts, excluding very expensive, time-, energy- and material-consuming multiple cure process testing.

Originality/value

This is first time the problem of optimal control synthesis for curing the large-scale composite parts of complex shape was solved.

Keywords

Acknowledgements

This research was supported by the Russian Foundation for the Basic Research (Grants 15-08-99849 and 16-58-52013 MNT_a), by the Russian Academy of Science (Project 0256-2015-0074) at the technical contribution of Rostvertol Helicopters Co. and Beriev Aircraft Co.

Citation

Shevtsov, S., Zhilyaev, I.V., Tarasov, I., Wu, J.-K. and Snezhina, N.G. (2018), "Model-based multi-objective optimization of cure process control for a large CFRP panel", Engineering Computations, Vol. 35 No. 2, pp. 1085-1097. https://doi.org/10.1108/EC-09-2017-0354

Publisher

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Emerald Publishing Limited

Copyright © 2018, Emerald Publishing Limited

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