A data-driven multiscale model for reactive wetting simulations

Ray, Jaideep; Horner, Jeffrey Scott; Winter, Ian S.; Kemmenoe, David Jonathan; Arata, Edward Robert; Chandross, Michael E.; Roberts, Scott Alan; Grillet, Anne Mary

doi:10.1016/j.compfluid.2024.106259

Title: A data-driven multiscale model for reactive wetting simulations

Journal Article · 30 March 2024 · Computers and Fluids

DOI: https://doi.org/10.1016/j.compfluid.2024.106259 · OSTI ID:2338252

Ray, Jaideep ^[1]; Horner, Jeffrey Scott ^[2]; Winter, Ian S. ^[2]; Kemmenoe, David Jonathan ^[2]; Arata, Edward Robert ^[2]; Chandross, Michael E. ^[2];

^[2]; Grillet, Anne Mary ^[2]

Sandia National Lab. (SNL-CA), Livermore, CA (United States)
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

Here, we describe a data-driven, multiscale technique to model reactive wetting of a silver–aluminum alloy on a Kovar™ (Fe-Ni-Co alloy) surface. We employ molecular dynamics simulations to elucidate the dependence of surface tension and wetting angle on the drop’s composition and temperature. A design of computational experiments is used to efficiently generate training data of surface tension and wetting angle from a limited number of molecular dynamics simulations. The simulation results are used to parameterize models of the material’s wetting properties and compute the uncertainty in the models due to limited data. The data-driven models are incorporated into an engineering-scale (continuum) model of a silver–aluminum sessile drop on a Kovar™ substrate. Model predictions of the wetting angle are compared with experiments of pure silver spreading on Kovar™ to quantify the model-form errors introduced by the limited training data versus the simplifications inherent in the molecular dynamics simulations. The paper presents innovations in the determination of “convergence” of noisy MD simulations before they are used to extract the wetting angle and surface tension, and the construction of their models which approximate physio-chemical processes that are left unresolved by the engineering-scale model. Together, these constitute a multiscale approach that integrates molecular-scale information into continuum scale models.

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Research Organization:: Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

Sponsoring Organization:: USDOE National Nuclear Security Administration (NNSA)

Grant/Contract Number:: NA0003525

OSTI ID:: 2338252

Alternate ID(s):: OSTI ID: 2335810

Report Number(s):: SAND-2024-04577J; TRN: US2410442

Journal Information:: Computers and Fluids, Vol. 276; ISSN 0045-7930

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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continuum modeling
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Title: A data-driven multiscale model for reactive wetting simulations

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