Demonstration of Bayesian inference and Bayesian experimental design in a model film / substrate inference problem by Raghav Aggarwal
نویسندگان
چکیده
In this thesis, we implement Bayesian inference and Bayesian experiment design in a model materials science problem. We demonstrate that by observing the behavior of a film deposited on a substrate, certain features of the substrate may be inferred, with quantified uncertainty. We show that Bayesian experimental design can be used to design efficient experiments. The substrate in this model problem is a Gaussian random field, and the film is a phase separating mixture modeled by the Cahn-Hilliard equation. A key feature of the inference and the experiment design is a stochastic reduced-order model. Thesis Supervisor: Michael J. Demkowicz Title: Associate Professor Thesis Supervisor: Youssef M. Marzouk Title: Associate Professor
منابع مشابه
Bayesian inference of substrate properties from film behavior
Abstract. We demonstrate that, by observing the behavior of a film deposited on a substrate, certain features of the substrate may be inferred with quantified uncertainty using Bayesian methods. We carry out this demonstration on an illustrative film/substrate model, where the substrate is a Gaussian random field and the film is a two-component mixture that obeys the Cahn-Hilliard equation. We ...
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