Southampton Statistical Sciences Research Institute
Research Seminar
Friday 18 May 14.30
Brian Williams (Los Alamos National Laboratory)
Combining Functional Experimental Data and Computer Simulations: An
Application to Fluid Instability Modelling
Lecture room 5B
Maths Building (B54)
Highfield Campus
University of Southampton
Abstract
This work focuses on combining observations from field experiments with
detailed computer simulations of a physical process to carry out inference.
This typically involves calibration of parameters in the simulator and
accounting for inadequate physics. We consider physical applications for
which the field data and simulator output are multivariate. Multivariate
data leads to computational challenges for implementing the framework. We
consider adaptive basis methods to achieve significant dimension reduction.
This methodology is extended to incorporate multiple sources of field data
and simulator output into a joint calibration and prediction analysis.
Different sources of data inform on specific calibration parameter subsets,
which are not required to be disjoint. We illustrate the proposed
methodology with experimental data and simulations that inform on the k-L
fluid instability model.
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