Borja Ferrándiz, Mabel Palacios, Clément Mailhé, Anaïs Barasinski, Francisco Chinesta
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引用次数: 0
Abstract
This study presents a surrogate model based on the convolutional U-Net architecture to predict the thermal field in a carbon fibre-reinforced thermoplastic tape at the microscale during brief and localized heating. Leveraging microstructure data within a machine learning framework, the proposed model aims to enhance the accuracy of temperature field predictions at a low computational cost. The incorporation of a co-attention mechanism to handle image channels of different nature significantly improves precision, resulting in a strong correlation between the model’s predictions and the ground truth obtained from the numerical solution of the heat equation. This capability enables rapid assessment of diverse microstructures, facilitating optimization and real-time applications in manufacturing settings.
期刊介绍：
The Journal publishes and disseminates original research in the field of material forming. The research should constitute major achievements in the understanding, modeling or simulation of material forming processes. In this respect ‘forming’ implies a deliberate deformation of material.
The journal establishes a platform of communication between engineers and scientists, covering all forming processes, including sheet forming, bulk forming, powder forming, forming in near-melt conditions (injection moulding, thixoforming, film blowing etc.), micro-forming, hydro-forming, thermo-forming, incremental forming etc. Other manufacturing technologies like machining and cutting can be included if the focus of the work is on plastic deformations.
All materials (metals, ceramics, polymers, composites, glass, wood, fibre reinforced materials, materials in food processing, biomaterials, nano-materials, shape memory alloys etc.) and approaches (micro-macro modelling, thermo-mechanical modelling, numerical simulation including new and advanced numerical strategies, experimental analysis, inverse analysis, model identification, optimization, design and control of forming tools and machines, wear and friction, mechanical behavior and formability of materials etc.) are concerned.
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