Computational Mechanics

, Volume 42, Issue 4, pp 485–510 | Cite as

Materials integrity in microsystems: a framework for a petascale predictive-science-based multiscale modeling and simulation system

  • Albert C. ToEmail author
  • Wing Kam Liu
  • Gregory B. Olson
  • Ted Belytschko
  • Wei Chen
  • Mark S. Shephard
  • Yip-Wah Chung
  • Roger Ghanem
  • Peter W. Voorhees
  • David N. Seidman
  • Chris Wolverton
  • J. S. Chen
  • Brian Moran
  • Arthur J. Freeman
  • Rong Tian
  • Xiaojuan Luo
  • Eric Lautenschlager
  • A. Dorian Challoner
Original Paper


Microsystems have become an integral part of our lives and can be found in homeland security, medical science, aerospace applications and beyond. Many critical microsystem applications are in harsh environments, in which long-term reliability needs to be guaranteed and repair is not feasible. For example, gyroscope microsystems on satellites need to function for over 20 years under severe radiation, thermal cycling, and shock loading. Hence a predictive-science-based, verified and validated computational models and algorithms to predict the performance and materials integrity of microsystems in these situations is needed. Confidence in these predictions is improved by quantifying uncertainties and approximation errors. With no full system testing and limited sub-system testings, petascale computing is certainly necessary to span both time and space scales and to reduce the uncertainty in the prediction of long-term reliability. This paper presents the necessary steps to develop predictive-science-based multiscale modeling and simulation system. The development of this system will be focused on the prediction of the long-term performance of a gyroscope microsystem. The environmental effects to be considered include radiation, thermo-mechanical cycling and shock. Since there will be many material performance issues, attention is restricted to creep resulting from thermal aging and radiation-enhanced mass diffusion, material instability due to radiation and thermo-mechanical cycling and damage and fracture due to shock. To meet these challenges, we aim to develop an integrated multiscale software analysis system that spans the length scales from the atomistic scale to the scale of the device. The proposed software system will include molecular mechanics, phase field evolution, micromechanics and continuum mechanics software, and the state-of-the-art model identification strategies where atomistic properties are calibrated by quantum calculations. We aim to predict the long-term (in excess of 20 years) integrity of the resonator, electrode base, multilayer metallic bonding pads, and vacuum seals in a prescribed mission. Although multiscale simulations are efficient in the sense that they focus the most computationally intensive models and methods on only the portions of the space–time domain needed, the execution of the multiscale simulations associated with evaluating materials and device integrity for aerospace microsystems will require the application of petascale computing. A component-based software strategy will be used in the development of our massively parallel multiscale simulation system. This approach will allow us to take full advantage of existing single scale modeling components. An extensive, pervasive thrust in the software system development is verification, validation, and uncertainty quantification (UQ). Each component and the integrated software system need to be carefully verified. An UQ methodology that determines the quality of predictive information available from experimental measurements and packages the information in a form suitable for UQ at various scales needs to be developed. Experiments to validate the model at the nanoscale, microscale, and macroscale are proposed. The development of a petascale predictive-science-based multiscale modeling and simulation system will advance the field of predictive multiscale science so that it can be used to reliably analyze problems of unprecedented complexity, where limited testing resources can be adequately replaced by petascale computational power, advanced verification, validation, and UQ methodologies.


Multiscale modeling Petascale computing Microsystems MEMS 


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Copyright information

© Springer-Verlag 2008

Authors and Affiliations

  • Albert C. To
    • 1
    Email author
  • Wing Kam Liu
    • 1
  • Gregory B. Olson
    • 2
  • Ted Belytschko
    • 1
  • Wei Chen
    • 1
  • Mark S. Shephard
    • 3
  • Yip-Wah Chung
    • 2
  • Roger Ghanem
    • 4
  • Peter W. Voorhees
    • 2
  • David N. Seidman
    • 2
  • Chris Wolverton
    • 2
  • J. S. Chen
    • 5
  • Brian Moran
    • 1
  • Arthur J. Freeman
    • 2
    • 6
  • Rong Tian
    • 1
  • Xiaojuan Luo
    • 3
  • Eric Lautenschlager
    • 7
  • A. Dorian Challoner
    • 8
  1. 1.Department of Mechanical EngineeringNorthwestern UniversityEvanstonUSA
  2. 2.Department of Materials Science and EngineeringNorthwestern UniversityEvanstonUSA
  3. 3.Scientific Computation and Research CenterRensselaer Polytechnic InstituteTroyUSA
  4. 4.Department of Aerospace and Mechanical EngineeringUniversity of Southern CaliforniaLos AngelesUSA
  5. 5.Department of Civil and Environmental EngineeringUniversity of California at Los AngelesWestwoodUSA
  6. 6.Department of PhysicsNorthwestern UniversityEvanstonUSA
  7. 7.Honeywell AerospacePlymouthUSA
  8. 8.Boeing Satellite Design CenterLos AngelesUSA

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