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Citation:

M. Sternat, J.C. Ragusa, "Cross Section Inference Based on PDE-Constrained Optimization," International Conference on Advances in Mathematics, Computational Methods, and Reactor Physics, an international conference sponsored by the ANS, Saratoga, NY, in May 3-7, 2009.

Abstract:

The problem of inferring the material properties (cross section) in noninvasive inverse problems is formulated as a PDE-constrained optimization problem, where the governing laws of the chosen physics act as a constraint. A standard Lagrangian functional, containing the objective function to be minimized and the constraints to satisfy, is formed. The resolution of the optimality conditions lead to a nonlinear problem that is tackled with a Gauss-Newton procedure. Results of cross section inference are presented in the case of 1-group 2D neutron diffusion theory.

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Associated Project(s):

  • SHIELD (Smuggled HEU Interdiction through Enhanced anaLysis and Detection): A Framework for Developing Novel Detection Systems Focused on Interdicting Shielded HEU

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