Browsing by Author "Townsend, Lawrence W."
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Item Estimates of Maximum Solar Particle Event Proton Fluences That Do Not Exceed Permissible Radiation Exposure Limits(45th International Conference on Environmental Systems, 2015-07-12) Townsend, Lawrence W.; deWet, Wouter C.; Porter, Jamie A; Burton, Krista R.; Smith, Whitney J.Human exposure to solar particle event radiation on deep space missions is a serious concern for mission planners and space crews. Numerous studies of potential exposures to crews from large events that have occurred during the space era have been made. In addition, recent studies have attempted to asses possible exposures from extremely large historical events that have occurred prior to the modern spaceflight era. In this work we investigate maximum proton fluence levels for different energy spectral distributions that would not exceed permissible exposure limits for effective dose or any organ dose. The spectral distributions selected for analyses are representative of two extreme events that have occurred during the past six decades, February 1956 and November 1960. The calculations use the HZETRN 2010 transport code, developed at NASA Langley Research Center to transport incident protons through various aluminum shield thicknesses and body self-shielding, for different mission scenarios, including transits to Mars, and surface operations on the surfaces of Mars and Earth’s moon.Item Solar Particle Event Dose Forecasting Using Regression Techniques(44th International Conference on Environmental Systems, 2014-07-13) Moussa, Hanna; Townsend, Lawrence W.Doses from solar particle events can be a serious threat to the wellbeing of crews traveling through space. Therefore predicting the time that such event will take place, forecasting the dose buildup over time, and the total dose from such event is needed to enable crews to take actions to mitigate the effects by entering a shielded area designed for their protection. Earlier work developed methods that used neural networks and Bayesian methods to forecast the total dose and dose versus time profile from an event. Subsequently, Locally Weighted Regression (LWR) and Kernel Regression (KR) techniques have been investigated to forecast the total dose. In this work, Kernel Regression methods are used to train and dose forecasting software using the dose rate and total accumulated dose. After training, the software predicts the dose buildup over time and the total dose for the test event. In the current research we have divided all of the events in our database into eight groups and use KR to train each group separately. We then test them to determine if the percentage differences between the dose forecast predictions for the test events and the actual event data, for each event in the group, are less than a 15% target value within 4 hours of the onset of the event. Results for the current dose forecasting system are presented.Item Solar Particle Event Dose Forecasting Using Regression Techniques(2018) Lovelace, Alan Mitchel (TTU); Rashid, Al Maqsudur (TTU); de Wet, Wouter C.; Townsend, Lawrence W.; Wesley Hines, J.; Moussa, Hanna (TTU)Doses from solar particle events can be a serious threat to the wellbeing of crews traveling through space. Therefore, methods for predicting the time such events will take place, methods for forecasting the dose buildup over time, and methods for forecasting the potential total dose from such events are needed to enable crews to take actions to mitigate the effects by entering a shielded area designed for their protection. This work focuses on forecasting the total dose expected for an event, based upon doses obtained very early in the event, using the kernel regression method. The model uses tables of calculated doses for historical solar particle events augmented with hypothetical events similar to the actual ones for training purposes. Reasonably accurate predictions of the total dose expected for an event can be made within the first hour after event onset. Predictive accuracies generally increase as the event progresses in time. The only inputs required are doses and times since event onset as provided by dosimetry devices. One hundred thirteen actual events with total doses between 1 and 1,000 cGy were tested using the model. At 1 hr into the event, total dose predictions were within ±30% of the actual total doses for 91 events (81%) and within ±15% for 54 of them (48%). Within the first 4 hr following event onset, total dose predictions were within ±30% for 98 events (87%) and within ±15% for 66 of them (58%). A software package implementing the model has been provided to the Space Radiation Analysis Group at NASA Johnson Space for incorporation into their operational procedures for analyzing possible threats to space crews from solar particle events.