The Experts below are selected from a list of 21837 Experts worldwide ranked by ideXlab platform

Matthias Morzfeld - One of the best experts on this subject based on the ideXlab platform.

  • small noise analysis and Symmetrization of implicit monte carlo samplers
    Communications on Pure and Applied Mathematics, 2016
    Co-Authors: Jonathan Goodman, Kevin K Lin, Matthias Morzfeld
    Abstract:

    Author(s): Goodman, J; Lin, KK; Morzfeld, M | Abstract: © 2016 Wiley Periodicals, Inc. Implicit samplers are algorithms for producing independent, weighted samples from multivariate probability distributions. These are often applied in Bayesian data assimilation algorithms. We use Laplace asymptotic expansions to analyze two implicit samplers in the small noise regime. Our analysis suggests a Symmetrization of the algorithms that leads to improved implicit sampling schemes at a relatively small additional cost. Computational experiments confirm the theory and show that Symmetrization is effective for small noise sampling problems.© 2016 Wiley Periodicals, Inc.

  • small noise analysis and Symmetrization of implicit monte carlo samplers
    arXiv: Numerical Analysis, 2014
    Co-Authors: Jonathan Goodman, Kevin K Lin, Matthias Morzfeld
    Abstract:

    Implicit samplers are algorithms for producing independent, weighted samples from multi-variate probability distributions. These are often applied in Bayesian data assimilation algorithms. We use Laplace asymptotic expansions to analyze two implicit samplers in the small noise regime. Our analysis suggests a Symmetrization of the algo- rithms that leads to improved (implicit) sampling schemes at a rel- atively small additional cost. Computational experiments confirm the theory and show that Symmetrization is effective for small noise sampling problems.

Eric Baer - One of the best experts on this subject based on the ideXlab platform.

Peter I. Kattan - One of the best experts on this subject based on the ideXlab platform.

  • Chapter 11 – Symmetrization of the effective stress tensor
    Advances in Damage Mechanics, 2006
    Co-Authors: George Z. Voyiadjis, Peter I. Kattan
    Abstract:

    Publisher Summary The aim of this chapter is to provide a solid mathematical basis for Symmetrization methods of the effective stress tensor, and justification for their use and validity. The effective stress tensor is examined within the framework of continuum damage mechanics. For a general state of deformation and damage, it is seen that the effective stress tensor is usually not symmetric. Therefore, its Symmetrization is necessary for a continuum theory to be valid. There are three types of Symmetrization methods: explicit Symmetrization, square root Symmetrization, and implicit Symmetrization. These three Symmetrization methods are compared, and certain recommendations are made regarding their suitability. This chapter concludes that the explicit method produces higher damage effect values, thus resulting in higher effective stresses than the other two methods. The implicit method produces the lowest symmetrized stress values. All three Symmetrization methods display qualitatively the same variation of the damage effect tensor. Only the explicit and implicit Symmetrization methods depict more accurately the physics of the material damage behavior.

Jonathan Goodman - One of the best experts on this subject based on the ideXlab platform.

  • small noise analysis and Symmetrization of implicit monte carlo samplers
    Communications on Pure and Applied Mathematics, 2016
    Co-Authors: Jonathan Goodman, Kevin K Lin, Matthias Morzfeld
    Abstract:

    Author(s): Goodman, J; Lin, KK; Morzfeld, M | Abstract: © 2016 Wiley Periodicals, Inc. Implicit samplers are algorithms for producing independent, weighted samples from multivariate probability distributions. These are often applied in Bayesian data assimilation algorithms. We use Laplace asymptotic expansions to analyze two implicit samplers in the small noise regime. Our analysis suggests a Symmetrization of the algorithms that leads to improved implicit sampling schemes at a relatively small additional cost. Computational experiments confirm the theory and show that Symmetrization is effective for small noise sampling problems.© 2016 Wiley Periodicals, Inc.

  • small noise analysis and Symmetrization of implicit monte carlo samplers
    arXiv: Numerical Analysis, 2014
    Co-Authors: Jonathan Goodman, Kevin K Lin, Matthias Morzfeld
    Abstract:

    Implicit samplers are algorithms for producing independent, weighted samples from multi-variate probability distributions. These are often applied in Bayesian data assimilation algorithms. We use Laplace asymptotic expansions to analyze two implicit samplers in the small noise regime. Our analysis suggests a Symmetrization of the algo- rithms that leads to improved (implicit) sampling schemes at a rel- atively small additional cost. Computational experiments confirm the theory and show that Symmetrization is effective for small noise sampling problems.

George Z. Voyiadjis - One of the best experts on this subject based on the ideXlab platform.

  • Chapter 11 – Symmetrization of the effective stress tensor
    Advances in Damage Mechanics, 2006
    Co-Authors: George Z. Voyiadjis, Peter I. Kattan
    Abstract:

    Publisher Summary The aim of this chapter is to provide a solid mathematical basis for Symmetrization methods of the effective stress tensor, and justification for their use and validity. The effective stress tensor is examined within the framework of continuum damage mechanics. For a general state of deformation and damage, it is seen that the effective stress tensor is usually not symmetric. Therefore, its Symmetrization is necessary for a continuum theory to be valid. There are three types of Symmetrization methods: explicit Symmetrization, square root Symmetrization, and implicit Symmetrization. These three Symmetrization methods are compared, and certain recommendations are made regarding their suitability. This chapter concludes that the explicit method produces higher damage effect values, thus resulting in higher effective stresses than the other two methods. The implicit method produces the lowest symmetrized stress values. All three Symmetrization methods display qualitatively the same variation of the damage effect tensor. Only the explicit and implicit Symmetrization methods depict more accurately the physics of the material damage behavior.