Bayesian Inference of Atomic Diffusivity in a Binary Ni/Al System Based on Molecular Dynamics
Name
Marzouk-2011-BAYESIAN INFERENCE OF ATOMIC DIFFUSIVITY IN A BINARY NIAL SYSTEM BASED ON MOLECULAR DYNAMICS.pdf
Size
4.49 MB
Format
Adobe PDF
Checksum (MD5)
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Author(s)
Rizzi, F.
Salloum, M.
Marzouk, Youssef M.
Xu, R.-G.
Falk, M. L.
Weihs, T. P.
Fritz, G.
Knio, O. M.
Date Issued
March 2011
Journal
Multiscale Modeling and Simulation
Publisher
Society for Industrial and Applied Mathematics
Citation
Rizzi, F. et al. “Bayesian Inference of Atomic Diffusivity in a Binary Ni/Al System Based on Molecular Dynamics.” Multiscale Modeling & Simulation 9.1 (2011) : 486. © 2011 Society for Industrial and Applied Mathematics
Version
Final published version
Abstract
This work focuses on characterizing the integral features of atomic diffusion in Ni/Al
nanolaminates based on molecular dynamics (MD) computations. Attention is focused on the simplified
problem of extracting the diffusivity, D, in an isothermal system at high temperature. To this
end, a mixing measure theory is developed that relies on analyzing the moments of the cumulative
distribution functions (CDFs) of the constituents. The mixing measures obtained from replica simulations
are exploited in a Bayesian inference framework, based on contrasting these measures with
corresponding moments of a dimensionless concentration evolving according to a Fickian process.
The noise inherent in the MD simulations is described as a Gaussian process, and this hypothesis is
verified both a priori and using a posterior predictive check. Computed values of D for an initially
unmixed system rapidly heated to 1500 K are found to be consistent with experimental correlation
for diffusion of Ni into molten Al. On the contrary, large discrepancies with experimental predictions
are observed when D is estimated based on large-time mean-square displacement (MSD) analysis,
and when it is evaluated using the Arrhenius correlation calibrated against experimental measurements
of self-propagating front velocities. Implications are finally drawn regarding extension of the
present work and potential refinement of continuum modeling approaches.
MIT Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
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DOI of Published Version
https://doi.org/10.1137/10080590x
