ROSES ID: NNH05ZDA001N Selection Year: 2006
Program Element: Data, Tools, & Methods
Principal Investigator: Lawrence Townsend
Affiliation(s): University of Tennessee
Neal, John S. Consultant null
Hines, J W. Co-I University of Tennessee
Summary:This proposal is a successor to our previously funded proposal, Advanced Warning Methodologies for Solar Particle Event Radiation Exposures (NAG5-12477). The previous work focused on the development of methods using Bayesian inference and artificial intelligence for reliably predicting proton flux, dose and dose rate versus time profiles for use in predicting ionizing dose effects in humans, electronics or other components due to solar energetic particle (SEP) event protons. That work was successful in that the methods developed were shown to be capable of providing reasonably accurate nowcasts of doses from SEP events that are independent of the magnitudes of the events. The methodology is also unaffected by shielding configurations since it depends only upon the magnitudes of the local dose values used as input and is independent of their sources. The work proposed herein would extend our current methodology in two areas: (1) improving numerical techniques to permit faster and more robust calculations and (2) making a connection between our work and ongoing work in the space physics community. The goal of these parallel efforts is to make faster and more reliable forecasts of flux, dose, and dose rate versus time profiles through the use of more efficient numerical methods and the connection to applicable solar observables. We also propose to deliver a prototype dose forecasting software package with an associated user and training manual at the completion of this investigation. This would be the first step in transferring a research product to a user.