Solar Energetic Particle Events: Statistical Modelling and Prediction

Details Solar Energetic Particle Events: Statistical Modelling and Prediction Solar Energetic Particle Events: Statistical Modelling and Prediction

Dec 1996

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1996esasp.392...59g&link_type=abstract

Environment Modelling for Space-based Applications, Symposium Proceedings (ESA SP-392). ESTEC Noordwijk, 18-20 September 1996. E

Statistics

Applications

Scientific paper

Solar energetic particle events (SEPEs) can have a significant effect both on the operations and design of spacecraft. For interplanetary spacecraft, they can be the dominate source of radiation for total ionising dose(TID) calculations for electronic parts, for solar array degradation due to displacement damage and for single event effect(SEE) rate predictions. They can also have an important effect on earth orbiting spacecraft at high inclinations during passage over the poles where there is no or reduced levels of geomagnetic shielding and on astronomy missions in high earth orbit(HEO) outside the earth's magnetosphere. In the latter two cases, interference or noise, induced by protons and alpha particle, in CCD detectors or other sensitive solid state devices can be of particular significance. Accurate models for these events is vital to avoid either over design, which can increase cost and mass, or under-design which can lead to premature performance degradation or even catastrophic failure. The paper will concentrate on the calculations of proton fluences and fluxes, describing the current state-of - the art in statistical modelling. Modern spacecraft data over the last three or so solar cycles has allowed the development of statistical models that can be used to estimate integrated proton fluences for different mission durations of greater than about a year. However, the best model available (JPL-91) still has some inadequacies, including limited, discrete energy range(1 to 60 MeV) and only a very approximate method of handling variations with heliocentric distance. In addition, because of its probabilistic basis, users have to select a confidence level and this can sometimes cause difficulties for spacecraft design; suggestions on how this problem can be alleviated are discussed. Other gaps in modelling capabilities of the SEPE environment, such as a proton flux model, an alpha particle and heavier ion models, distribution for small events and solar cycle variations are described along with the prospects for prediction of events using neural networks.

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