Monte Carlo Analysis of Dose Profiles near Photon Irradiated Material Interfaces

Garth, J.C.; Chadsey, W. L.; Sheppard, R. L.

doi:10.1109/tns.1975.4328168

Cited by 37 publications

(7 citation statements)

References 4 publications

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“…The reason becomes clear in the Figure function of the incident photon energy and distance from the interface as reported by Garth et al [9]. It can be seen that the maximum enhancement exceeds a factor of 30 and occurs at a photon energy of about 150 keV.…”

Section: Introductionsupporting

confidence: 64%

The direct measurement of dose enhancement in gamma test facilities

Burke¹,

Lowe²,

Snowden³

et al. 1989

IEEE Trans. Nucl. Sci.

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The design and use of a dual cavity ionization chamber for routine measurement of dose enhancement factors in CO-60 gamma test facilities is described. The enhancement factors can be derived directly from the chamber measurements without recourse to reference data that may be difficult to obtain. It is shown, in agreement with earlier work, that the maximum dose enhancement factors can be altered by a factor two as a result of Compton scatter from relatively small amounts of low or high atomic number materials next to the target. The dual chamber permits the ready detection of such effects. This relatively simple device reliably reproduced earlier results obtained by more involved equipment and procedures. Measured enhancement factors are reported for new material combinations not previously examined and compared with recent calculations.

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Section: Introductionsupporting

confidence: 64%

The direct measurement of dose enhancement in gamma test facilities

Burke¹,

Lowe²,

Snowden³

et al. 1989

IEEE Trans. Nucl. Sci.

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show abstract

“…For large bivariate data sets, the computational simplicity of the frequency polygon and the ease of determining exact equiprobable contours may outweigh the increased accuracy of a kernel estimate. Bivariate contour plots based on millions of observations are increasingly required in applications including high-energy physics simulation experiments (Garth et al 1975), cell sorters, and geographical data representation. Furthermore, such data are usually collected in binned form.…”

Section: Introduction and Discussionmentioning

confidence: 99%

Frequency Polygons: Theory and Application

Scott

1985

Journal of the American Statistical Association

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In this article I investigate the theoretical properties and applications of the frequency polygon, which is constructed by connecting with straight lines the mid-bin values of a histogram. For estimating an unknown probability density function using a random sample, the frequency polygon is shown to dominate the histogram with respect to the criterion of integrated mean squared error, achieving the same rate of convergence to zero of the integrated mean squared error as non-negative kernel estimators. Data-based algorithms for constructing frequency polygons are discussed and illustrated. One is based on a histogram with bin width equal to 2.15sn-"', where s is an estimate of the standard deviation from a sample of size n. Another approach is based on the method of generalized crossvalidation. The bivariate frequency polygon is also investigated. Comparisons are made between the frequency polygon and other density estimators, Examples with data in one and two dimensions are presented.

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“…Let ¢(E) be the differential photon energy spectrum, (MeV/MeV) of any given cobalt-60 source, and let S(E) be the energy response function of the ionization chamber as defined in equation (6) The ionization chamber response function (figure 2) was also integrated over the gamma spectra which were measured for some of the source configurations of table 1. These measured spectra are shown in figure 7.…”

Section: Comparison Of Ionization Chamber Data With Calculated and Mementioning

confidence: 99%

“…[5][6][7][8][9] It is therefore clear that it is important to have some knowledge of the low-energy scattered gamma component of the particular cobalt-60 source which one is using for radiation effects testing of microelectronic devices and circuits. It is also unfortunately true, however, that this information is difficult to obtain.…”

Section: Introductionmentioning

confidence: 99%