Task 1: Design and fabrication of a Mod1 prototype detector
The purpose of this task was to design, build and assemble a prototype Tissue Equivalent Proportional Counter (TEPC) that would satisfy the basic specifications outlined by NASA for an EVA dosimeter for astronauts during lunar EVAs. This Mod1 design would include the proportional counter, and first stage preamplifier that are contained in a small vacuum chamber suitable for testing with PuBe neutron sources and charged particle beams.
We have used Solid Works to facilitate the design of Mod1. The spherical TEPC is based on a singlewire anode with recessed guard ring insulators to shape the electric field near the poles. The diameter of the gas cavity is 18mm and the wall thickness is 3mm for a total diameter of 24mm (~ 1 inch).
The preamplifier board has been designed and bench tested for noise at TAMU. The stainless steel vacuum chamber designed to accommodate the TEPC and pre amplifier has been fabricated and leak tested. The hemispherical dome surrounding the TEPC has a wall thickness of 1 mm. This is welded to a cylindrical sleeve with a vacuum tight flange that can be easily removed whenever modifications to the components are necessary.
The final printed circuit boards have been designed and are being fabricated. This will serve as the connection between the pre amplifier and the base plate of the vacuum chamber that also contains the voltage and signal feedthroughs.
Task 2: Modeling Detector Response
The objective of this task is to determine the response of the TEPC under ambient conditions and during SPE events on the lunar surface. Computations using the Monte Carlo Code PHITS have been made to determine the energy spectrum of protons entering the gas cavity for monoenergetic protons that are uniformly incident upon the detector. The purpose of this is to establish the low energy cutoff for protons that do not penetrate the vacuum chamber and plastic wall as well as the attenuation of energy for protons that do reach the gas cavity.
These data show that protons incident at 100 MeV have their energy attenuated by about 10%, whereas protons entering at 50 MeV have an energy attenuation of about 40%. Protons less than 30 MeV do not reach the gas cavity and therefore are not detected by the TEPC.
Computations are underway to model these effects using the spectrum of incident protons from various SPE events. This will be important in determining the dose and dose rate response of the EVA dosimeter during high intensity SPE episodes.
Task 3 Modeling the VarianceCovariance Method
The original proposal for the EVA dosimeter was based on the concept of having two independent proportional counters that would be used to obtain estimates of dose, D, and a quality factor, Q, based on estimating using the variancecovariance method. It was recognized that because of size limitations, the proportional counters would have to be located too close to one another to satisfy the condition that a single particle could not intercept both detectors. The additional constraint that one of the detectors must measure the dose at the skin surface and the other at a depth corresponding to the blood forming organs, makes the original variavariancecovariance method with paired detectors impractical.
It was suggested that it might be possible to use one detector in a variancecovariance scheme. The concepts are based on collecting the charge, zi, in a single TEPC for n successive intervals.
One method proposed by Borak at CSU separated the data set into two groups of n/2 entries of values for zi based on odd and even indices. The n/2 pairs of data (odd and even) are used to obtain the covariance and each of the two sets of n/2 values (odd or even) to estimate a variance.
John Lakness, from NASA Ames Research Center, used a method based on the derivative of the discrete data set by taking the difference between successive measurements.
There are clear similarities between the two methods. Both processes rely on summing values of z, z2 and pairs zi,zj.
The Borak process separates the data set into two parts to estimate a covariance for the paired data and then combines them in the end to estimate by taking the average of the variance minus covariance obtained from the two parts.
The Lakness process in effect gets the covariance by pairing successive values of z and sums up z2 twice.
Several data sets were simulated using a constant value of D for each interval and a variable value of D to evaluate dose rate effects on the estimate of which is used to determine quality factor.
The results indicated that both methods converged toward the true value of for the simulated data sets. We plan to continue these investigations to evaluate both methods at very high dose rates and very low dose rates where there may be no events in a given timing interval.
