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2014

Three-dimensional stochastic modeling of radiation belts in adiabatic invariant coordinates

A 3-D model for solving the radiation belt diffusion equation in adiabatic invariant coordinates has been developed and tested. The model, named Radbelt Electron Model, obtains a probabilistic solution by solving a set of It\^o stochastic differential equations that are mathematically equivalent to the diffusion equation. This method is capable of solving diffusion equations with a full 3-D diffusion tensor, including the radial-local cross diffusion components. The correct form of the boundary condition at equatorial pitch ...

Zheng, Liheng; Chan, Anthony; Albert, Jay; Elkington, Scot; Koller, Josef; Horne, Richard; Glauert, Sarah; Meredith, Nigel;

YEAR: 2014     DOI: 10.1002/jgra.v119.910.1002/2014JA020127

adiabatic invariant coordinates; diffusion equation; fully 3-D model; Radiation belt; stochastic differential equation

Application and testing of the L * neural network with the self-consistent magnetic field model of RAM-SCB

We expanded our previous work on L* neural networks that used empirical magnetic field models as the underlying models by applying and extending our technique to drift shells calculated from a physics-based magnetic field model. While empirical magnetic field models represent an average, statistical magnetospheric state, the RAM-SCB model, a first-principles magnetically self-consistent code, computes magnetic fields based on fundamental equations of plasma physics. Unlike the previous L* neural networks that include McIlwai ...

Yu, Yiqun; Koller, Josef; Jordanova, Vania; Zaharia, Sorin; Friedel, Reinhard; Morley, Steven; Chen, Yue; Baker, Daniel; Reeves, Geoffrey; Spence, Harlan;

YEAR: 2014     DOI: 10.1002/jgra.v119.310.1002/2013JA019350

Van Allen Probes



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