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Title: Modeling of the radiation belt megnetosphere in decisional timeframes

Abstract

Systems and methods for calculating L* in the magnetosphere with essentially the same accuracy as with a physics based model at many times the speed by developing a surrogate trained to be a surrogate for the physics-based model. The trained model can then beneficially process input data falling within the training range of the surrogate model. The surrogate model can be a feedforward neural network and the physics-based model can be the TSK03 model. Operatively, the surrogate model can use parameters on which the physics-based model was based, and/or spatial data for the location where L* is to be calculated. Surrogate models should be provided for each of a plurality of pitch angles. Accordingly, a surrogate model having a closed drift shell can be used from the plurality of models. The feedforward neural network can have a plurality of input-layer units, there being at least one input-layer unit for each physics-based model parameter, a plurality of hidden layer units and at least one output unit for the value of L*.

Inventors:
; ;
Publication Date:
Research Org.:
LANL (Los Alamos National Laboratory (LANL), Los Alamos, NM (United States))
Sponsoring Org.:
USDOE
OSTI Identifier:
1083288
Patent Number(s):
8,428,916
Application Number:
12/390,611
Assignee:
Los Alamos National Security, LLC (Los Alamos, NM) LANL
DOE Contract Number:  
AC52-06NA25396
Resource Type:
Patent
Country of Publication:
United States
Language:
English
Subject:
79 ASTRONOMY AND ASTROPHYSICS

Citation Formats

Koller, Josef, Reeves, Geoffrey D, and Friedel, Reiner H.W. Modeling of the radiation belt megnetosphere in decisional timeframes. United States: N. p., 2013. Web.
Koller, Josef, Reeves, Geoffrey D, & Friedel, Reiner H.W. Modeling of the radiation belt megnetosphere in decisional timeframes. United States.
Koller, Josef, Reeves, Geoffrey D, and Friedel, Reiner H.W. Tue . "Modeling of the radiation belt megnetosphere in decisional timeframes". United States. https://www.osti.gov/servlets/purl/1083288.
@article{osti_1083288,
title = {Modeling of the radiation belt megnetosphere in decisional timeframes},
author = {Koller, Josef and Reeves, Geoffrey D and Friedel, Reiner H.W.},
abstractNote = {Systems and methods for calculating L* in the magnetosphere with essentially the same accuracy as with a physics based model at many times the speed by developing a surrogate trained to be a surrogate for the physics-based model. The trained model can then beneficially process input data falling within the training range of the surrogate model. The surrogate model can be a feedforward neural network and the physics-based model can be the TSK03 model. Operatively, the surrogate model can use parameters on which the physics-based model was based, and/or spatial data for the location where L* is to be calculated. Surrogate models should be provided for each of a plurality of pitch angles. Accordingly, a surrogate model having a closed drift shell can be used from the plurality of models. The feedforward neural network can have a plurality of input-layer units, there being at least one input-layer unit for each physics-based model parameter, a plurality of hidden layer units and at least one output unit for the value of L*.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue Apr 23 00:00:00 EDT 2013},
month = {Tue Apr 23 00:00:00 EDT 2013}
}

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