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:
- Issue Date:
- Research Org.:
- Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1083288
- Patent Number(s):
- 8428916
- Application Number:
- 12/390,611
- Assignee:
- Los Alamos National Security, LLC (Los Alamos, NM)
- Patent Classifications (CPCs):
-
G - PHYSICS G01 - MEASURING G01W - METEOROLOGY
- 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 = {2013},
month = {4}
}
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