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Estimation and Control of Modeling Error: A General Approach to Multiscale Modeling

Other · · Multiscale Methods
 [1]; ; ;
  1. University of Texas at Austin, Institute for Computational Engineering and Sciences
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This chapter describes a class of computational methods designed to handle multiscale modeling of large atomistic or molecular systems. The key to this approach is the estimation of relative modeling error in which errors in quantities of interest produced by averaging or homogenization are computed using a posteriori error estimates. The error is judged to be the relative error between the fine-scale base model and any number of surrogates produced by homogenization. Features of modeling the atomistic to continuum interface are also addressed. Specific applications of the methodology are described that involve analyzing polymer etch barriers that are used in nano-manufacturing of semi-conductors. The basic adaptive modeling strategy employs goal-oriented adaptation in which fine-scale information is systematically added to hybrid molecular-continuum models until the appropriate level of accuracy in certain quantities of interest is achieved.
Research Organization:
Univ. of Texas, Austin, TX (United States). Institute for Computational Engineering and Sciences
Sponsoring Organization:
USDOE SC Office of Advanced Scientific Computing Research (SC-21)
DOE Contract Number:
FG02-05ER25701
OSTI ID:
1092570
Report Number(s):
DOE/ER-25701
Country of Publication:
United States
Language:
English

References (12)

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Estimation of Modeling Error in Computational Mechanics journal November 2002
A stochastic coupling method for atomic-to-continuum Monte-Carlo simulations journal August 2008
The Arlequin method as a flexible engineering design tool journal January 2005
MultiScale Modeling of Physical Phenomena: Adaptive Control of Models journal January 2006
On deterministic error analysis in variational data assimilation journal May 2005
Equation of State Calculations by Fast Computing Machines journal June 1953
An adaptive strategy for the control of modeling error in two-dimensional atomic-to-continuum coupling simulations journal May 2009
Materials for step and flash imprint lithography (S-FIL®) journal January 2007
On the application of the Arlequin method to the coupling of particle and continuum models journal May 2008
Computational analysis of modeling error for the coupling of particle and continuum models by the Arlequin method journal July 2008

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Related Subjects

97 MATHEMATICS AND COMPUTING
adaptive modeling
error estimation
molecular systems
nanomanufacturing