This is a collaborative proposal that aims to establish theoretical foundations and computational tools that enable uncertainty quantification (UQ) in tightly coupled atomistic-to-continuum multiscale simulations. The program emphasizes the following three research thrusts: 1. UQ and its propagation in atomistic simulations, whether through intrusive or nonintrusive approaches; 2. Extraction of macroscale observables from atomistic simulations and propagation across scales; and 3. Uncertainty quantification and propagation in continuum simulations for macroscale properties tightly coupled with instantaneous states of the atomistic systems. Thus, the project offers to enable the use of multiscale multiphysics simulations as predictive design...
This dissertation discusses uncertainty quantication as posed in the Data Collaboration framework. D...
Effective potentials are an essential ingredient of classical molecular dynamics (MD) simulations. L...
International audienceIn the development of numerical models, uncertainty quantification (UQ) can in...
Simulation has long since joined experiment and theory as a valuable tool to address materials probl...
The needs to assess resilient and antifragile performances for complex systems and to answer tighter...
Uncertainty quantification (UQ) is a key component when using computational models that involve unce...
Abstract. We present a “module-based hybrid ” Uncertainty Quantification (UQ) framework for general ...
Atomistic simulations are an important tool in materials modeling. Interatomic potentials (IPs) are ...
A fully automated computational tool for the study of the uncertainty in a mathematical-computationa...
Uncertainty quantification is a rapidly growing field in computer simulation-based scientific applic...
This paper was presented at the 3rd Micro and Nano Flows Conference (MNF2011), which was held at the...
Mathematical models of complex real-world phenomena result in computational challenges, often necess...
This program has been imported from the CPC Program Library held at Queen's University Belfast (1969...
Uncertainty quantification of multiphysics systems represents numerous mathematical and computationa...
International audienceThis book results from a course developed by the author and reflects both his ...
This dissertation discusses uncertainty quantication as posed in the Data Collaboration framework. D...
Effective potentials are an essential ingredient of classical molecular dynamics (MD) simulations. L...
International audienceIn the development of numerical models, uncertainty quantification (UQ) can in...
Simulation has long since joined experiment and theory as a valuable tool to address materials probl...
The needs to assess resilient and antifragile performances for complex systems and to answer tighter...
Uncertainty quantification (UQ) is a key component when using computational models that involve unce...
Abstract. We present a “module-based hybrid ” Uncertainty Quantification (UQ) framework for general ...
Atomistic simulations are an important tool in materials modeling. Interatomic potentials (IPs) are ...
A fully automated computational tool for the study of the uncertainty in a mathematical-computationa...
Uncertainty quantification is a rapidly growing field in computer simulation-based scientific applic...
This paper was presented at the 3rd Micro and Nano Flows Conference (MNF2011), which was held at the...
Mathematical models of complex real-world phenomena result in computational challenges, often necess...
This program has been imported from the CPC Program Library held at Queen's University Belfast (1969...
Uncertainty quantification of multiphysics systems represents numerous mathematical and computationa...
International audienceThis book results from a course developed by the author and reflects both his ...
This dissertation discusses uncertainty quantication as posed in the Data Collaboration framework. D...
Effective potentials are an essential ingredient of classical molecular dynamics (MD) simulations. L...
International audienceIn the development of numerical models, uncertainty quantification (UQ) can in...