Доступ предоставлен для: Guest
Портал Begell Электронная Бибилиотека e-Книги Журналы Справочники и Сборники статей Коллекции
International Journal for Uncertainty Quantification
Импакт фактор: 3.259 5-летний Импакт фактор: 2.547 SJR: 0.417 SNIP: 0.8 CiteScore™: 1.52

ISSN Печать: 2152-5080
ISSN Онлайн: 2152-5099

Свободный доступ

International Journal for Uncertainty Quantification

DOI: 10.1615/Int.J.UncertaintyQuantification.2013005679
pages 111-132

DATA-FREE INFERENCE OF UNCERTAIN PARAMETERS IN CHEMICAL MODELS

Habib N. Najm
Sandia National Laboratories P.O. Box 969, MS 9051, Livermore, CA 94551, USA
Robert D. Berry
P.O.Box 969, MS 9051; Sandia National Laboratories, Livermore, California 94551, USA
Cosmin Safta
P.O.Box 969, MS 9051; Sandia National Laboratories, Livermore, California 94551, USA
Khachik Sargsyan
Sandia National Laboratories, Livermore, CA, USA
Bert J. Debusschere
P.O.Box 969, MS 9051; Sandia National Laboratories, Livermore, California 94551, USA

Краткое описание

We outline the use of a data-free inference procedure for estimation of uncertain model parameters for a chemical model of methane-air ignition. The method involves a nested pair of Markov chains, exploring both the data and parametric spaces, to discover a pooled joint posterior consistent with available information. We describe the highlights of the method, and detail its particular implementation in the system at hand. We examine the performance of the procedure, focusing on the robustness and convergence of the estimated joint parameter posterior with increasing number of data chain samples. We also comment on comparisons of this posterior with the missing reference posterior density.


Articles with similar content:

GRADIENT-BASED STOCHASTIC OPTIMIZATION METHODS IN BAYESIAN EXPERIMENTAL DESIGN
International Journal for Uncertainty Quantification, Vol.4, 2014, issue 6
Youssef Marzouk, Xun Huan
TRANSITIONAL ANNEALED ADAPTIVE SLICE SAMPLING FOR GAUSSIAN PROCESS HYPER-PARAMETER ESTIMATION
International Journal for Uncertainty Quantification, Vol.6, 2016, issue 4
Alfredo Garbuno-Inigo, F. A. DiazDelaO, Konstantin M. Zuev
VARIABLE-SEPARATION BASED ITERATIVE ENSEMBLE SMOOTHER FOR BAYESIAN INVERSE PROBLEMS IN ANOMALOUS DIFFUSION REACTION MODELS
International Journal for Uncertainty Quantification, Vol.9, 2019, issue 3
Yuming Ba, Na Ou, Lijian Jiang
The affect of flow rotation on local burning velocity
ICHMT DIGITAL LIBRARY ONLINE, Vol.0, 2009, issue
G. K. Hargrave, E. J. Long
A NEW INVERSE METHOD FOR THE UNCERTAINTY QUANTIFICATION OF SPATIALLY VARYING RANDOM MATERIAL PROPERTIES
International Journal for Uncertainty Quantification, Vol.6, 2016, issue 6
Gun Jin Yun, Shen Shang