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Smart material data enrichment using AI, experimental data, and material science
This webinar aims at demonstrating our approach that enables the enrichment of an initial material database by combining advanced material modelling and AI.
On the one hand, advanced material modelling, through multiscale material modelling, and embedded material science laws, bring accuracy and domain knowledge. On the other hand, AI brings efficiency, portability and quantification of the accuracy of the predictions. The database of filled and unfilled plastics is enriched for different temperatures, filling amounts, strain rates and loading angles. The targeted performances are stress strain responses until failure.