49 citations · 101 across the 6 of their papers we have counts for
6 papers
Towards a unified nonlocal, peridynamics framework for the coarse-graining of molecular dynamics data with fractures
Huaiqian You, Xiao Xu, Yue Yu +3
Molecular dynamics (MD) has served as a powerful tool for designing materials with reduced reliance on laboratory testing. However, the use of MD directly to treat the deformation…
Bayesian Nonlocal Operator Regression (BNOR): A Data-Driven Learning Framework of Nonlocal Models with Uncertainty Quantification
Yiming Fan, Marta D'Elia, Yue Yu +2
We consider the problem of modeling heterogeneous materials where micro-scale dynamics and interactions affect global behavior. In the presence of heterogeneities in material micro…
Nonlocal Kernel Network (NKN): a Stable and Resolution-Independent Deep Neural Network
Huaiqian You, Yue Yu, Marta D'Elia +2
Neural operators have recently become popular tools for designing solution maps between function spaces in the form of neural networks. Differently from classical scientific machin…
Peridynamic Model for Single-Layer Graphene Obtained from Coarse Grained Bond Forces
Stewart A. Silling, Marta D'Elia, Yue Yu +2
An ordinary state-based peridynamic material model is proposed for single sheet graphene. The model is calibrated using coarse grained molecular dynamics simulations. The coarse gr…
A data-driven peridynamic continuum model for upscaling molecular dynamics
Huaiqian You, Yue Yu, Stewart Silling +1
Nonlocal models, including peridynamics, often use integral operators that embed lengthscales in their definition. However, the integrands in these operators are difficult to defin…
Data-driven learning of nonlocal models: from high-fidelity simulations to constitutive laws
Huaiqian You, Yue Yu, Stewart Silling +1
We show that machine learning can improve the accuracy of simulations of stress waves in one-dimensional composite materials. We propose a data-driven technique to learn nonlocal c…