Symposium CM4-Verification, Validation and Uncertainty Quantification in Multiscale Materials Simulation

Methods in computational materials science have now evolved to have sufficient fidelity at different length and time scales that simulations results can often be directly compared with experiments and contribute to materials engineering. Moreover, in many cases a simulation at a given length and time scale receives information from experiments and simulations at other length and time scales that guide the form of the model and imply values of model parameters. The inherent data synthesis in this process influences the fidelity of the resulting model. For materials simulations to provide integral support of materials design and qualification processes, it is important to understand the implications of this coupling of scales in order to make sufficiently accurate predictions with quantified uncertainty.

This symposium will focus on four critical aspects in multiscale simulation:

Verification addresses the issue of the correct implementation of the algorithms in a code. Approaches to verification include ensuring that code delivers intended functionality. Moreover, tests of consistency with fundamental physical laws, such as conservation of energy and momentum, can be applied. Both qualitative and quantitative verification methods are of interest.

Validation is the assessment of the ability of a code or specific simulation to describe salient aspects of physical behavior under study. It may involve comparison to existing exact solutions or other benchmark solutions that are well accepted, as well as comparison between simulation results and experiments.

Sensitivity analysis (SA) is the determination of the relative importance of different mechanisms and model parameters on the predictions of simulations. While methods for sensitivity on one parameter are well-established, there is significant interest in multivariate sensitivity analysis.

Uncertainty quantification (UQ) is the estimation of errors in simulation results arising from the approximations and simplifications in the models or input data. There is significant interest in both aleatoric and epistemic forms of uncertainty.

Contributions are solicited for V&V, SA and UQ within a single computational method, and for applications of these methods in linking multiple methods between disparate length and time scales. Both advances in methodology and specific case studies in all kinds of materials are of interest.

• Validation
• Verification
• Sensitivity Analysis
• Uncertainty Quantification

• CM4_Verification, Validation and Uncertainty Quantification in Multiscale Materials Simulation_0 (Stanford University, USA)
• CM4_Verification, Validation and Uncertainty Quantification in Multiscale Materials Simulation_1 (École polytechnique fédérale de Lausanne, Switzerland)
• CM4_Verification, Validation and Uncertainty Quantification in Multiscale Materials Simulation_2 (Northwestern University, USA)
• CM4_Verification, Validation and Uncertainty Quantification in Multiscale Materials Simulation_3 (Johns Hopkins University, USA)
• CM4_Verification, Validation and Uncertainty Quantification in Multiscale Materials Simulation_4 (ETH Zurich, Switzerland)
• CM4_Verification, Validation and Uncertainty Quantification in Multiscale Materials Simulation_5 (Los Alamos National Laboratory, USA)
• CM4_Verification, Validation and Uncertainty Quantification in Multiscale Materials Simulation_6 (Mississippi State University, USA)
• CM4_Verification, Validation and Uncertainty Quantification in Multiscale Materials Simulation_7 (Iowa State University, USA)
• CM4_Verification, Validation and Uncertainty Quantification in Multiscale Materials Simulation_8 (Sandia National Laboratories, USA)
• CM4_Verification, Validation and Uncertainty Quantification in Multiscale Materials Simulation_9 (University of Texas, USA)
• CM4_Verification, Validation and Uncertainty Quantification in Multiscale Materials Simulation_10 (Cornell University, USA)
• CM4_Verification, Validation and Uncertainty Quantification in Multiscale Materials Simulation_11 (Purdue University, USA)
• CM4_Verification, Validation and Uncertainty Quantification in Multiscale Materials Simulation_12 (Idaho National Laboratory, USA)
• CM4_Verification, Validation and Uncertainty Quantification in Multiscale Materials Simulation_13 (Georgia Institute of Technology, USA)