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Stochastic PDEs

Random Domain Decomposition Random Domain Decomposition

Simulations of most physical systems are fundamentally stochastic. Even essentially deterministic systems must be treated stochastically when their parameters, boundary and initial conditions, or forcing functions are under-specified by data. Well-characterized probabilistic estimates are the foundation of simulation-based risk analyses. The Stochastic Partial Differential Equations (SPDEs) project addresses one of the most critical problems in SPDEs: efficient computation of uncertainty as it propagates through the dynamics of non-linear systems. This problem lies at the heart of establishing trust in simulation-based stockpile certification; and in environment, energy, and health security. Quantifying uncertainty is a ubiquitous problem in most analyses and assessments performed at LANL, and in statistical characterization of rare events and of highly heterogeneous random fields.

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People

Francis J. Alexander fja@ cut.this.part. lanl.gov Los Alamos National Laboratory
David M. Higdon dhigdon@ cut.this.part. lanl.gov Los Alamos National Laboratory
Shengtai Li sli@ cut.this.part. lanl.gov Los Alamos National Laboratory
David Moulton moulton@ cut.this.part. lanl.gov Los Alamos National Laboratory
Richard R. Picard picard@ cut.this.part. lanl.gov Los Alamos National Laboratory