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  • 1
    Publication Date: 2021-07-01
    Description: The radiation belts of the Earth, filled with energetic electrons, comprise complex and dynamic systems that pose a significant threat to satellite operation. While various models of electron flux both for low and relativistic energies have been developed, the behavior of medium energy (120–600 keV) electrons, especially in the MEO region, remains poorly quantified. At these energies, electrons are driven by both convective and diffusive transport, and their prediction usually requires sophisticated 4D modeling codes. In this paper, we present an alternative approach using the Light Gradient Boosting (LightGBM) machine learning algorithm. The Medium Energy electRon fLux In Earth's outer radiatioN belt (MERLIN) model takes as input the satellite position, a combination of geomagnetic indices and solar wind parameters including the time history of velocity, and does not use persistence. MERLIN is trained on 〉15 years of the GPS electron flux data and tested on more than 1.5 years of measurements. Tenfold cross validation yields that the model predicts the MEO radiation environment well, both in terms of dynamics and amplitudes o f flux. Evaluation on the test set shows high correlation between the predicted and observed electron flux (0.8) and low values of absolute error. The MERLIN model can have wide space weather applications, providing information for the scientific community in the form of radiation belts reconstructions, as well as industry for satellite mission design, nowcast of the MEO environment, and surface charging analysis.
    Description: Plain Language Summary: The radiation belts of the Earth, which are the zones of charged energetic particles trapped by the geomagnetic field, comprise complex and dynamic systems posing a significant threat to a variety of commercial and military satellites. While the inner belt is relatively stable, the outer belt is highly variable and depends substantially on solar activity; therefore, accurate and improved models of electron flux in the outer radiation belt are essential to understand the underlying physical processes. Although many models have been developed for the geostationary orbit and relativistic energies, prediction of electron flux in the 120–600 keV energy range still remains challenging. We present a data‐driven model of the medium energies (120–600 keV) differentialelectron flux in the outer radiation belt based on machine learning. We use 17 years of electron observations by Global Positioning System (GPS) satellites. We set up a 3D model for flux prediction in terms of L‐values, MLT, and magnetic latitude. The model gives reliable predictions of the radiation environment in the outer radiation belt and has wide space weather applications.
    Description: Key Points: A machine learning model is created to predict electron flux at MEO for energies 120–600 keV. The model requires solar wind parameters and geomagnetic indices as input and does not use persistence. MERLIN model yields high accuracy and high correlation with observations (0.8).
    Description: Horizon 2020 – The EU Research and Innovation programme
    Keywords: 523.5 ; machine learning ; radiation belts ; electron flux ; empirical modeling ; magnetosphere ; electrons
    Type: article
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  • 2
    Publication Date: 2021-07-21
    Description: In this study we investigate two distinct loss mechanisms responsible for the rapid dropouts of radiation belt electrons by assimilating data from Van Allen Probes A and B and Geostationary Operational Environmental Satellites (GOES) 13 and 15 into a 3-D diffusion model. In particular, we examine the respective contribution of electromagnetic ion cyclotron (EMIC) wave scattering and magnetopause shadowing for values of the first adiabatic invariant μ ranging from 300 to 3,000 MeV G−1. We inspect the innovation vector and perform a statistical analysis to quantitatively assess the effect of both processes as a function of various geomagnetic indices, solar wind parameters, and radial distance from the Earth. Our results are in agreement with previous studies that demonstrated the energy dependence of these two mechanisms. We show that EMIC wave scattering tends to dominate loss at lower L shells, and it may amount to between 10%/hr and 30%/hr of the maximum value of phase space density (PSD) over all L shells for fixed first and second adiabatic invariants. On the other hand, magnetopause shadowing is found to deplete electrons across all energies, mostly at higher L shells, resulting in loss from 50%/hr to 70%/hr of the maximum PSD. Nevertheless, during times of enhanced geomagnetic activity, both processes can operate beyond such location and encompass the entire outer radiation belt.
    Keywords: 538.76 ; data assimilation ; EMIC waves ; magnetopause shadowing ; innovation vector ; Kalman filter ; radiation belt losses
    Language: English
    Type: article
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  • 3
    Publication Date: 2022-03-31
    Description: Radial diffusion is one of the dominant physical mechanisms driving acceleration and loss of radiation belt electrons. A number of parameterizations for radial diffusion coefficients have been developed, each differing in the data set used. Here, we investigate the performance of different parameterizations by Brautigam and Albert (2000), https://doi.org/10.1029/1999ja900344, Brautigam et al. (2005), https://doi.org/10.1029/2004ja010612, Ozeke et al. (2014), https://doi.org/10.1002/2013ja019204, Ali et al. (2015), https://doi.org/10.1002/2014ja020419; Ali et al. (2016), https://doi.org/10.1002/2016ja023002; Ali (2016), and Liu et al. (2016), https://doi.org/10.1002/2015gl067398 on long‐term radiation belt modeling using the Versatile Electron Radiation Belt (VERB) code, and compare the results to Van Allen Probes observations. First, 1‐D radial diffusion simulations are performed, isolating the contribution of solely radial diffusion. We then take into account effects of local acceleration and loss showing additional 3‐D simulations, including diffusion across pitch‐angle, energy, and mixed diffusion. For the L* range studied, the difference between simulations with Brautigam and Albert (2000), https://doi.org/10.1029/1999ja900344, Ozeke et al. (2014), https://doi.org/10.1002/2013ja019204, and Liu et al. (2016), https://doi.org/10.1002/2015gl067398 parameterizations is shown to be small, with Brautigam and Albert (2000), https://doi.org/10.1029/1999ja900344 offering the smallest averaged (across multiple energies) absolute normalized difference with observations. Using the Ali et al. (2016), https://doi.org/10.1002/2016ja023002 parameterization tended to result in a lower flux than both the observations and the VERB simulations using the other coefficients. We find that the 3‐D simulations are less sensitive to the radial diffusion coefficient chosen than the 1‐D simulations, suggesting that for 3‐D radiation belt models, a similar result is likely to be achieved, regardless of whether Brautigam and Albert (2000), https://doi.org/10.1029/1999ja900344, Ozeke et al. (2014), https://doi.org/10.1002/2013ja019204, and Liu et al. (2016), https://doi.org/10.1002/2015gl067398 parameterizations are used.
    Description: Key Points: 3‐D simulations using different radial diffusion coefficients, except Ali et al. (2016), produce similar results. Using Ali et al. (2016) DLL, simulated flux is significantly lower than observations. 3‐D modeling with Brautigam and Albert (2000) DLL results in a slightly smaller normalized difference (averaged over energies) to observations.
    Description: National Aeronautics and Space Administration (NASA) http://dx.doi.org/10.13039/100000104
    Description: European Union's Horizon 2020
    Description: https://doi.org/10.25346/S6/U9WFPD
    Keywords: ddc:538.7
    Language: English
    Type: doc-type:article
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  • 4
    Publication Date: 2016-06-07
    Description: A new type of rotary energy conversion device for obtaining a desired constant frequency output independent of the speed of the prime mover has been developed and tested using the technique of field modulation and solid state alternator output processing. A 10-kilowatt prototype field modulated frequency down converter system was designed, built, and successfully tested. Experimentally obtained performance characteristics are presented.
    Keywords: AUXILIARY SYSTEMS
    Type: NASA. Lewis Res. Center Wind Energy Conversion Systems; p 115-120
    Format: application/pdf
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