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A data-driven multiscale model for reactive wetting simulations.

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Title: A data-driven multiscale model for reactive wetting simulations.
Authors: Ray, Jaideep1 (AUTHOR) jairay@sandia.gov, Horner, Jeffrey S.2 (AUTHOR), Winter, Ian2 (AUTHOR), Kemmenoe, David J.2 (AUTHOR), Arata, Edward R.2 (AUTHOR), Chandross, Michael2 (AUTHOR), Roberts, Scott A.2 (AUTHOR), Grillet, Anne M.2 (AUTHOR)
Source: Computers & Fluids. May2024, Vol. 276, pN.PAG-N.PAG. 1p.
Subjects: Surface tension, Multiscale modeling, Molecular dynamics, Wetting, Liquid alloys, Finite element method, Models & modelmaking
Abstract: 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. • Constructed a data-driven wetting model from molecular dynamics simulations. • Studied wetting of molten silver-aluminum alloy on a Kovar™ substrate for brazing. • Performed molecular dynamics simulation to predict surface tension & wetting angle. • Calibrated probabilistic, data-driven surrogate model using limited training data. • Integrated wetting model into engineering-scale finite element brazing model. • Compared model to experiment, identifying missing physics in simulations. [ABSTRACT FROM AUTHOR]
Copyright of Computers & Fluids is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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Header DbId: egs
DbLabel: Engineering Source
An: 177087539
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  Data: A data-driven multiscale model for reactive wetting simulations.
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  Data: <searchLink fieldCode="AR" term="%22Ray%2C+Jaideep%22">Ray, Jaideep</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> jairay@sandia.gov</i><br /><searchLink fieldCode="AR" term="%22Horner%2C+Jeffrey+S%2E%22">Horner, Jeffrey S.</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Winter%2C+Ian%22">Winter, Ian</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Kemmenoe%2C+David+J%2E%22">Kemmenoe, David J.</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Arata%2C+Edward+R%2E%22">Arata, Edward R.</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Chandross%2C+Michael%22">Chandross, Michael</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Roberts%2C+Scott+A%2E%22">Roberts, Scott A.</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Grillet%2C+Anne+M%2E%22">Grillet, Anne M.</searchLink><relatesTo>2</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Computers+%26+Fluids%22">Computers & Fluids</searchLink>. May2024, Vol. 276, pN.PAG-N.PAG. 1p.
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  Data: <searchLink fieldCode="DE" term="%22Surface+tension%22">Surface tension</searchLink><br /><searchLink fieldCode="DE" term="%22Multiscale+modeling%22">Multiscale modeling</searchLink><br /><searchLink fieldCode="DE" term="%22Molecular+dynamics%22">Molecular dynamics</searchLink><br /><searchLink fieldCode="DE" term="%22Wetting%22">Wetting</searchLink><br /><searchLink fieldCode="DE" term="%22Liquid+alloys%22">Liquid alloys</searchLink><br /><searchLink fieldCode="DE" term="%22Finite+element+method%22">Finite element method</searchLink><br /><searchLink fieldCode="DE" term="%22Models+%26+modelmaking%22">Models & modelmaking</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: 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. • Constructed a data-driven wetting model from molecular dynamics simulations. • Studied wetting of molten silver-aluminum alloy on a Kovar™ substrate for brazing. • Performed molecular dynamics simulation to predict surface tension & wetting angle. • Calibrated probabilistic, data-driven surrogate model using limited training data. • Integrated wetting model into engineering-scale finite element brazing model. • Compared model to experiment, identifying missing physics in simulations. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Computers & Fluids is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1016/j.compfluid.2024.106259
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 1
        StartPage: N.PAG
    Subjects:
      – SubjectFull: Surface tension
        Type: general
      – SubjectFull: Multiscale modeling
        Type: general
      – SubjectFull: Molecular dynamics
        Type: general
      – SubjectFull: Wetting
        Type: general
      – SubjectFull: Liquid alloys
        Type: general
      – SubjectFull: Finite element method
        Type: general
      – SubjectFull: Models & modelmaking
        Type: general
    Titles:
      – TitleFull: A data-driven multiscale model for reactive wetting simulations.
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            NameFull: Ray, Jaideep
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            NameFull: Kemmenoe, David J.
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            – D: 30
              M: 05
              Text: May2024
              Type: published
              Y: 2024
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              Value: 276
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