Mechanical properties of materials and associated engineered components are controlled
by the material structure at various lengths and time scales. As materials are being further …

In this work, we present a deep neural network architecture that can efficiently surrogate
classical elasto-plastic constitutive relations. The network is enriched with crucial physics …

The variability and uncertainty bring great trouble to the application and in-depth research of
asphalt mixture. This study aimed to detect the microstructural differences between the …

Quantifying uncertainty associated with the microstructure variation of a material can be a
computationally daunting task, especially when dealing with advanced constitutive models …

This paper develops an uncertainty quantified, parametrically homogenized constitutive
model (UQ-PHCM) for microstructure-sensitive modeling and simulation at the structural …

Uncertainty quantification (UQ) plays a major role in verification and validation for
computational engineering models and simulations, and establishes trust in the predictive …

The stochastic modeling and calibration of an anisotropic elasto-plastic model for additive
manufacturing materials are addressed in this work. We specifically focus on 316L stainless …

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The present work addresses multiscale modeling for grain topology of polycrystalline
microstructures under the effects of the microstructural uncertainties. The special focus is on …

In designing accurate constitutive models, it is important to investigate the stability of the
response obtained by means of these models to perturbations in operator and input data …