Robert J. Melosh Competition, Professor Jaime Peraire, Massachusetts Institute of Technology

Apr 24

Friday, April 24, 2015

11:10 am - 12:10 pm
Hudson Hall 125

Presenter

Professor Jaime Peraire, Swansea University

Professor Jaime Peraire, Massachusetts Institute of Technology Presentation Title: "Gaussian Functional Regression for State Prediction Using Linear PDE Models and Observations" Partial differential equations (PDEs) are commonly used to model a wide variety of physical phenomena. A PDE model of a physical problem is typically described by conservation laws, constitutive laws, material properties, boundary conditions, boundary data, and geometry. In most practical applications, however, the PDE model is only an approximation to the real physical problem due to both (i) the deliberate mathematical simplification of the model to keep it tractable, and (ii) the inherent uncertainty of the physical parameters. In such cases, the PDE model may not produce a good prediction of the true state of the underlying physical problem. We introduce a Gaussian functional regression method that incorporates observations into a deterministic linear PDE model to improve its prediction of the true state......

Contact

Carpenter, Ruby Nell
660-5200
rubync@duke.edu

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