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Title: Multiobjective method for fitting pinhole image intensity profiles of implosion cores driven by a Pareto genetic algorithm

Abstract

We discuss a method for the simultaneous and self-consistent fitting of a set of intensity or emissivity spatial profiles from several narrow-band x-ray pinhole images from argon-doped inertial confinement fusion implosion cores, and the space-integrated line spectrum. A Pareto genetic algorithm (PGA) combines the search and optimization capabilities of a single-objective genetic algorithm with the Pareto domination technique of multiobjective optimization. Further, the PGA search is followed up by a fine-tuning step based on a nonlinear least-squares-minimization procedure. The result is a robust search and reconstruction method that finds the optimal core spatial structure subject to multiple constraints. This method is independent of geometry inversions and could take advantage of not only optically thin but also optically thick image data. Results are shown for two combinations of three-objectives based on gated argon He{beta} and Ly{beta} image data and the line spectrum.

Authors:
; ; ; ; ; ; ; ; ; ; ; ; ;  [1]
  1. Department of Physics, University of Nevada, Reno, Nevada 89557 (United States)
Publication Date:
OSTI Identifier:
20861386
Resource Type:
Journal Article
Journal Name:
Review of Scientific Instruments
Additional Journal Information:
Journal Volume: 77; Journal Issue: 10; Other Information: DOI: 10.1063/1.2338314; (c) 2006 American Institute of Physics; Country of input: International Atomic Energy Agency (IAEA); Journal ID: ISSN 0034-6748
Country of Publication:
United States
Language:
English
Subject:
70 PLASMA PHYSICS AND FUSION TECHNOLOGY; ALGORITHMS; APPROXIMATIONS; ARGON; DOPED MATERIALS; EMISSIVITY; IMAGES; IMPLOSIONS; INERTIAL CONFINEMENT; LEAST SQUARE FIT; MINIMIZATION; NONLINEAR PROBLEMS; PLASMA; PLASMA DIAGNOSTICS; X RADIATION

Citation Formats

Nagayama, T, Mancini, R C, Welser, L A, Louis, S, Golovkin, I E, Tommasini, R, Koch, J A, Izumi, N, Delettrez, J, Marshall, F J, Regan, S P, Smalyuk, V, Haynes, D, Kyrala, G, Department of Computer Science, University of Nevada, Reno, Nevada 89557, Prism Computational Sciences, Madison, Wisconsin 53711, Lawrence Livermore National Laboratory, Livermore, California 94550, Laboratory for Laser Energetics, University of Rochester, New York 14623, and Los Alamos National Laboratory, Los Alamos, New Mexico 87545. Multiobjective method for fitting pinhole image intensity profiles of implosion cores driven by a Pareto genetic algorithm. United States: N. p., 2006. Web. doi:10.1063/1.2338314.
Nagayama, T, Mancini, R C, Welser, L A, Louis, S, Golovkin, I E, Tommasini, R, Koch, J A, Izumi, N, Delettrez, J, Marshall, F J, Regan, S P, Smalyuk, V, Haynes, D, Kyrala, G, Department of Computer Science, University of Nevada, Reno, Nevada 89557, Prism Computational Sciences, Madison, Wisconsin 53711, Lawrence Livermore National Laboratory, Livermore, California 94550, Laboratory for Laser Energetics, University of Rochester, New York 14623, & Los Alamos National Laboratory, Los Alamos, New Mexico 87545. Multiobjective method for fitting pinhole image intensity profiles of implosion cores driven by a Pareto genetic algorithm. United States. https://doi.org/10.1063/1.2338314
Nagayama, T, Mancini, R C, Welser, L A, Louis, S, Golovkin, I E, Tommasini, R, Koch, J A, Izumi, N, Delettrez, J, Marshall, F J, Regan, S P, Smalyuk, V, Haynes, D, Kyrala, G, Department of Computer Science, University of Nevada, Reno, Nevada 89557, Prism Computational Sciences, Madison, Wisconsin 53711, Lawrence Livermore National Laboratory, Livermore, California 94550, Laboratory for Laser Energetics, University of Rochester, New York 14623, and Los Alamos National Laboratory, Los Alamos, New Mexico 87545. Sun . "Multiobjective method for fitting pinhole image intensity profiles of implosion cores driven by a Pareto genetic algorithm". United States. https://doi.org/10.1063/1.2338314.
@article{osti_20861386,
title = {Multiobjective method for fitting pinhole image intensity profiles of implosion cores driven by a Pareto genetic algorithm},
author = {Nagayama, T and Mancini, R C and Welser, L A and Louis, S and Golovkin, I E and Tommasini, R and Koch, J A and Izumi, N and Delettrez, J and Marshall, F J and Regan, S P and Smalyuk, V and Haynes, D and Kyrala, G and Department of Computer Science, University of Nevada, Reno, Nevada 89557 and Prism Computational Sciences, Madison, Wisconsin 53711 and Lawrence Livermore National Laboratory, Livermore, California 94550 and Laboratory for Laser Energetics, University of Rochester, New York 14623 and Los Alamos National Laboratory, Los Alamos, New Mexico 87545},
abstractNote = {We discuss a method for the simultaneous and self-consistent fitting of a set of intensity or emissivity spatial profiles from several narrow-band x-ray pinhole images from argon-doped inertial confinement fusion implosion cores, and the space-integrated line spectrum. A Pareto genetic algorithm (PGA) combines the search and optimization capabilities of a single-objective genetic algorithm with the Pareto domination technique of multiobjective optimization. Further, the PGA search is followed up by a fine-tuning step based on a nonlinear least-squares-minimization procedure. The result is a robust search and reconstruction method that finds the optimal core spatial structure subject to multiple constraints. This method is independent of geometry inversions and could take advantage of not only optically thin but also optically thick image data. Results are shown for two combinations of three-objectives based on gated argon He{beta} and Ly{beta} image data and the line spectrum.},
doi = {10.1063/1.2338314},
url = {https://www.osti.gov/biblio/20861386}, journal = {Review of Scientific Instruments},
issn = {0034-6748},
number = 10,
volume = 77,
place = {United States},
year = {2006},
month = {10}
}