Uncertainty quantification in multiscale materials modeling /

Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Wang, Yan (Editor ), McDowell, David L., 1956- (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cambridge : Woodhead Publishing, 2020
Colección:Elsevier series in mechanics of advanced materials.
Temas:
Materials > Mathematical models.
Uncertainty (Information theory)
Multiscale modeling.
Mat�eriaux > Mod�eles math�ematiques.
Incertitude (Th�eorie de l'information)
Analyse multi�echelle.
Materials > Mathematical models
Multiscale modeling
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Front Cover
  • Uncertainty Quantification in Multiscale Materials Modeling
  • Mechanics of Advanced Materials Series
  • Series editor-in-chief: Vadim V. Silberschmidt
  • Series editor: Thomas B�ohlke
  • Series editor: David L. McDowell
  • Series editor: Zhong Chen
  • Uncertainty Quantification in Multiscale Materials Modeling
  • Copyright
  • Contents
  • Contributors
  • About the Series editors
  • Editor-in-Chief
  • Series editors
  • Preface
  • 1
  • Uncertainty quantification in materials modeling
  • 1.1 Materials design and modeling
  • 1.2 Sources of uncertainty in multiscale materials modeling
  • 1.2.1 Sources of epistemic uncertainty in modeling and simulation
  • 1.2.2 Sources of model form and parameter uncertainties in multiscale models
  • 1.2.2.1 Models at different length and time scales
  • 1.2.3 Linking models across scales
  • 1.3 Uncertainty quantification methods
  • 1.3.1 Monte Carlo simulation
  • 1.3.2 Global sensitivity analysis
  • 1.3.3 Surrogate modeling
  • 1.3.4 Gaussian process regression
  • 1.3.5 Bayesian model calibration and validation
  • 1.3.6 Polynomial chaos expansion
  • 1.3.7 Stochastic collocation and sparse grid
  • 1.3.8 Local sensitivity analysis with perturbation
  • 1.3.9 Polynomial chaos for stochastic Galerkin
  • 1.3.10 Nonprobabilistic approaches
  • 1.4 UQ in materials modeling
  • 1.4.1 UQ for ab initio and DFT calculations
  • 1.4.2 UQ for MD simulation
  • 1.4.3 UQ for meso- and macroscale materials modeling
  • 1.4.4 UQ for multiscale modeling
  • 1.4.5 UQ in materials design
  • 1.5 Concluding remarks
  • Acknowledgments
  • References
  • 2
  • The uncertainty pyramid for electronic-structure methods
  • 2.1 Introduction
  • 2.2 Density-functional theory
  • 2.2.1 The Kohn-Sham formalism
  • 2.2.2 Computational recipes
  • 2.3 The DFT uncertainty pyramid
  • 2.3.1 Numerical errors
  • 2.3.2 Level-of-theory errors
  • 2.3.3 Representation errors
  • 2.4 DFT uncertainty quantification
  • 2.4.1 Regression analysis
  • 2.4.2 Representative error measures
  • 2.5 Two case studies
  • 2.5.1 Case 1: DFT precision for elemental equations of state
  • 2.5.2 Case 2: DFT precision and accuracy for the ductility of a W-Re alloy
  • 2.6 Discussion and conclusion
  • Acknowledgment
  • References
  • 3
  • Bayesian error estimation in density functional theory
  • 3.1 Introduction
  • 3.2 Construction of the functional ensemble
  • 3.3 Selected applications
  • 3.4 Conclusion

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