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Accelerating and Improving the Accuracy of Parameter Calibration in a Phenomenological Crystal Plasticity Model Through High-Volume Machine Learning Simulations

Phenomenological crystal plasticity (CP) models are widely used in Integrated Computational Materials Engineering (ICME) to link microstructural features with engineering-scale mechanical behaviour. Their practical use, however, is limited by the high computational cost of physics-based simulations...

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Wedi'i Gadw mewn:
Prif Awduron: Dayalan R. Gunasegaram, Najmeh Samadiani, Nathan G. March, Indrajeet Katti, David Howard, Mark Easton
Fformat: Artigo
Iaith:Inglês
Cyhoeddwyd: MDPI AG 2026-03-01
Cyfres:Metals
Pynciau:
phenomenological constitutive model
crystal plasticity
deep neural network
surrogate model
model calibration
materials engineering
Mynediad Ar-lein:https://www.mdpi.com/2075-4701/16/3/295
Tagiau: Ychwanegu Tag
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