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Call for Papers

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.

Topics will include:

  • Validation
  • Verification
  • Sensitivity Analysis
  • Uncertainty Quantification

Invited Speakers:

  • Thomas Bligaard (Stanford University, USA)
  • Michele Ceriotti (École polytechnique fédérale de Lausanne, Switzerland)
  • Wei Chen (Northwestern University, USA)
  • Michael Falk (Johns Hopkins University, USA)
  • Andreas Fichtner (ETH Zurich, Switzerland)
  • Timothy Germann (Los Alamos National Laboratory, USA)
  • Mark Horstemeyer (Mississippi State University, USA)
  • Richard LeSar (Iowa State University, USA)
  • Allen Robinson (Sandia National Laboratories, USA)
  • Carolyn Seepersaad (University of Texas, USA)
  • James Sethna (Cornell University, USA)
  • Alejandro Strachan (Purdue University, USA)
  • Michael Tonks (Idaho National Laboratory, USA)
  • Yan Wang (Georgia Institute of Technology, USA)

Symposium Organizers

Simon R. Phillpot
University of Florida
Department of Materials Science and Engineering
352-846-3782, sphil@mse.ufl.edu

Stephen Foiles
Sandia National Laboratories
Computational Material and Data Science
505-844-7064, foiles@sandia.gov

Marisol Koslowski
Purdue University
Department of Mechanical Engineering
765-496-1045, marisol@purdue.edu

David McDowell
Georgia Institute of Technology
Woodruff School of Mechanical Engineering, School of Materials Science and Engineering