Inversion of airborne contaminants in a regional model

Authors:
Volkan Akcelik;George Biros;Andrei Draganescu;Omar Ghattas;Judith Hill;Bart van Bloemen Waanders
Affiliations:
Stanford Linear Accelerator Center;Department of Mechanical Engineering and Applied Mechanics, University of Pennsylvania;Optimization and Uncertainty Estimation Department, Sandia National Laboratories;Institute for Computational Engineering and Sciences, The University of Texas at Austin;Optimization and Uncertainty Estimation Department, Sandia National Laboratories;Optimization and Uncertainty Estimation Department, Sandia National Laboratories
Venue:
ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part III
Year:
2006

Citing 5
Cited 1

Streamline upwind/Petrov-Galerkin formulations for convection dominated flows with particular emphasis on the incompressible Navier-Stokes equations

Computer Methods in Applied Mechanics and Engineering - Special edition on the 20th Anniversary
Rank-deficient and discrete ill-posed problems: numerical aspects of linear inversion

Rank-deficient and discrete ill-posed problems: numerical aspects of linear inversion
Parallel Lagrange--Newton--Krylov--Schur Methods for PDE-Constrained Optimization. Part I: The Krylov--Schur Solver

SIAM Journal on Scientific Computing
Parallel Lagrange--Newton--Krylov--Schur Methods for PDE-Constrained Optimization. Part II: The Lagrange--Newton Solver and Its Application to Optimal Control of Steady Viscous Flows

SIAM Journal on Scientific Computing
The effect of stabilization in finite element methods for the optimal boundary control of the Oseen equations

Finite Elements in Analysis and Design

Dynamic Data Driven Application System for Plume Estimation Using UAVs

Journal of Intelligent and Robotic Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

We are interested in a DDDAS problem of localization of airborne contaminant releases in regional atmospheric transport models from sparse observations. Given measurements of the contaminant over an observation window at a small number of points in space, and a velocity field as predicted for example by a mesoscopic weather model, we seek an estimate of the state of the contaminant at the begining of the observation interval that minimizes the least squares misfit between measured and predicted contaminant field, subject to the convection-diffusion equation for the contaminant. Once the “initial” conditions are estimated by solution of the inverse problem, we issue predictions of the evolution of the contaminant, the observation window is advanced in time, and the process repeated to issue a new prediction, in the style of 4D-Var. We design an appropriate numerical strategy that exploits the spectral structure of the inverse operator, and leads to efficient and accurate resolution of the inverse problem. Numerical experiments verify that high resolution inversion can be carried out rapidly for a well-resolved terrain model of the greater Los Angeles area.