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This paper describes the recent changes that the authors have perceived in the use of radiation and radioisotope measurement applications. The first change is that due to the increased use of Monte Carlo simulation which has occurred from a normal evolutionary process. This is due in large part to the increased accuracy that is being obtained by the use of detector response functions (DRFs) and the simultaneous increased computational efficiency that has become available with these DRFs, the availability of a greatly improved weight windows variance reduction method, and the availability of inexpensive computer clusters. This first change is a happy one. The other change that is occurring is in response to recent terrorist activities. That change is the replacement or major change in the use of long-lived radioisotopes in radioisotope measurement and other radioisotope source applications. In general this can be done by improving the security of these radioisotope sources or by replacing them altogether by using machine sources of radiation. In either case one would like to preclude altogether or at least minimize the possibility of terrorists being able to obtain radioisotopes and use them for clandestine purposes. [ABSTRACT FROM AUTHOR]

A dual measurement system for monitoring the simultaneous positions of multiple radioactive tracer pebbles in scaled pebble bed reactors (PBRs) has been developed and benchmarked to the prototype stage. The first system (the collimated system) is an updated version of a previously developed system that is now a completely automatic system that uses three collimated directionally variable Nil detectors that are programed to continuously search for a maximum counting rate from a single radioactive pebble. This system can be used by itself when a single radioactive tracer pebble is of interest and the pebble is relatively slow moving. In the present case, its primary use is to provide an independent measurement of the position of a stationary tracer pebble that is used to provide a point for calibration of the second system. The second system (the uncollimated system) is a modified version of a multiple uncollimated NaI detector system commonly called CARPT. The modified version involves those changes necessary to allow for use of the entire gamma-ray spectra for the inverse problem instead of only the gamma-ray full energy peaks. This allows one to use multiple radioisotopes each in a different tracer pebble so that up to ten individual tracer pebbles can be followed simultaneously with the best possible accuracy. The inverse problem is treated with the Monte Carlo library least-squares approach in which Monte Carlo-generated library spectra for each radioisotope are made available for a complete range of reference positions within the scaled PBR. Then, any unknown total gamma-ray spectra can be analyzed in an iterative fashion with the radioisotope library spectra to yield the position of all the radioisotope tracer pebbles. The scaled PBR used was a 30-cm-high and 30-cm-diam circular cylindrical section on the top and a cone with a 25-deg angle on the bottom. The pebbles are 1.2-cm glass marbles. Results have been obtained with both single tracer radioisotope marbles and multiple tracer radioisotope marbles, simultaneously. [ABSTRACT FROM AUTHOR]

Abstract: In many applications, low resolution gamma-ray spectrometers, such as sodium iodide scintillation detectors, are widely used primarily due to their relatively low cost and high detection efficiency. There is widespread interest in improved methods for analyzing spectral data acquired with such devices, using inverse analysis. Peak means and peak areas in gamma- and X-ray spectra are needed for both qualitative and quantitative analysis. This paper introduces the PEAKSI code package that was developed at the Center for Engineering Applications of Radioisotopes (CEAR). The basic approach described here is to use accurate forward models and iterative convolution instead of direct deconvolution. Rather than smoothing and differentiation a combination of linear regression and non-linear searching is used to minimize the reduced chi-square, since this approach retains the capability of establishing uncertainties in the estimated peak parameters. The PEAKSI package uses a Levenberg–Marquardt (LM) non-linear search method combined with multiple linear regression (MLR) to minimize the reduced chi-square value for fitting single or multiple overlapping peaks to determine peak parameters, including peak means, peak standard deviations or full width at half maximum (FWHM), net peak counts, and background counts of peaks in experimental gamma-ray spectra. This approach maintains the natural error structure so that parameter uncertainties can be estimated. The plan is to release this code to the public in the near future. [Copyright &y& Elsevier]

The Monte Carlo – Library Least-Squares (MCLLS) method has been developed by the Center for Engineering Applications of Radioisotopes for various XRF applications of multi-elemental composition analysis and implemented with the CEARXRF code. In the present work, it is successfully applied to the in vivo XRF measurement of lead in bone and benchmarked by the measurement of a plaster of Paris phantom of known lead concentration. It is implicitly assumed that if the approach works for this sample that closely approximates the real problem of interest, it will also work for the real in vivo case when the proper description of the real case is used. Traditional techniques for XRF analysis are reviewed briefly and the full advantages of the MCLLS method are discussed. Simulation results are presented that are in good agreement with experimental results. The applicability of the MCLLS method to the lead in bone measurement is supported by the good fitting results obtained with simulated Monte Carlo elemental library spectra and close agreement between simulated and experimental spectra from a calcium-rich matrix-based calibration standard in a test geometrical configuration. [Copyright &y& Elsevier]

An accurate method for determining elemental analysis using gamma–gamma coincidence counting is presented. To demonstrate the feasibility of this method for PGNAA, a system of three radioisotopes (Na-24, Co-60 and Cs-134) that emit coincident gamma rays was used. Two HPGe detectors were connected to a system that allowed both singles and coincidences to be collected simultaneously. A known mixture of the three radioisotopes was used and data was deliberately collected at relatively high counting rates to determine the effect of pulse pile-up distortion. The results obtained, with the library least-squares analysis, of both the normal and coincidence counting are presented and compared to the known amounts. The coincidence results are shown to give much better accuracy. It appears that in addition to the expected advantage of reduced background, the coincidence approach is considerably more resistant to pulse pile-up distortion. [Copyright &y& Elsevier]

Abstract Prompt gamma-ray neutron activation analysis (PGNAA) has been widely used for elemental analysis of bulk samples as it provides an on-line, rapid and non-destructive means of performing such analysis. The Monte Carlo Library Least-Squares (MCLLS) approach is one of the methods for quantitative analysis providing elemental weight fractions via an assumption that the total prompt gamma-ray spectrum is a linear combination of the contributions from the individual prompt gamma-ray spectra of the sample constituents. For the generation of prompt gamma-ray libraries of each constituent, a specific purpose Monte Carlo code system called Center for Engineering Applications of Radioisotopes Coincidence Prompt Gamma-Ray (CEARCPG) is utilized. In this work, the focus was on detecting and measuring chlorine impurity in crude oil samples, i.e. trace amounts of chlorine. A preliminary study investigating the feasibility of PGNAA method in conjunction with the MCLLS approach for measuring trace amounts of chlorine in oil samples was performed. For this purpose, an extended version of the MCLLS approach, the so-called MCLLSX approach, was proposed and applied for the quantitative analysis. The results presented in this paper prove the feasibility of the proposed approach. Highlights • A measurement system for continuous monitoring of chlorine impurity in crude oil was built. • The MCLLSX approach for quantitative analysis of targeted elements with low-weight-fraction in the sample has been proposed. • The feasibility of determining low chlorine concentrations by using the MCLLSX approach in conjunction with PGNAA was shown. • The chlorine content could be estimated at a few hundred mg/L level. [ABSTRACT FROM AUTHOR]

Abstract: In spite of their relatively poor gamma-ray stopping efficiencies, the Geiger-Müller (GM) counter is still preferred in many radioisotope gauges for industrial measurements. This is because these detectors exhibit a high degree of robustness in harsh environments, are relatively insensitive to temperature changes in the environment, and are inexpensive compared to other types of radiation detectors. These properties could make the use of GM counters very feasible in a number of industrial applications, such as gamma-ray tomography and gamma-ray density gauges, provided that their gamma-ray stopping efficiencies can be improved. The Monte Carlo (MC) method is a powerful computational physics tool that is utilized very often in the design of radiation detectors and radioisotope gauges. In this work a MC model for GM counters that is benchmarked with experiments at the primary photon energy of 59.5keV is proposed. This is a specific purpose MC simulation code that, as opposed to publicly available general purpose MC codes, employs single scatter (or microscopic) electron transport and is currently under development. In this paper, the MC code is described in detail and the results of the specific purpose MC code are benchmarked with experiments and two general purpose MC codes, MCNP5 and PENELOPE. It was observed that the specific purpose MC code improved the reduced chi-square value when compared to MCNP5 and PENELOPE. [Copyright &y& Elsevier]

Abstract: Normal Prompt Gamma-Ray Neutron Activation Analysis (PGNAA) suffers from a large inherent noise or background. The coincidence PGNAA approach is being investigated for eliminating almost all of the interfering backgrounds and thereby significantly improving the signal-to-noise ratio (SNR). This can be done since almost all of the prompt gamma rays from elements of interest are emitted in coincidence except hydrogen. However, it has been found previously that while the use of two normal NaI detectors greatly reduces the background, the signal is also greatly reduced so that very little improvement in standard deviation is obtained. With the help of MCNP5, the general-purpose Monte Carlo N-Particle code, and CEARCPG, the specific purpose Monte Carlo code for Coincidence PGNAA, further optimization of the proposed coincidence system is being accomplished. The idea pursued here is the use of a large area plastic scintillation detector as the trigger for coincidence events together with a normal large NaI detector. In this approach the detection solid angle is increased greatly, which directly increases the probability of coincidence detection. The 2D-coincidence spectrum obtained can then be projected to the axis representing the NaI detector to overcome the drawback of low energy resolution and photopeak intensity of the plastic scintillation detector and utilize the overall higher coincidence counting rate. To reach the best coincidence detection, the placement of detectors, sample, and the moderator of the neutron source have been optimized through Monte Carlo simulation. [Copyright &y& Elsevier]