Modeling and Analysis Methods for an On-line Enrichment Monitor
The International Atomic Energy Agency (IAEA) has developed an On-Line Enrichment Monitor (OLEM) as one possible component in a new generation of safeguards measures for uranium enrichment plants. The OLEM measures 235U emissions from the UF6 gas flowing through a unit header pipe using NaI(Tl) spectrometers, and corrects for gas density changes using pressure and temperature sensors in order to determine the enrichment of the gas as a function of time. In parallel with the OLEM instrument development, a Virtual OLEM (VOLEM) software tool has been developed that is capable of producing synthetic gamma-ray, pressure, and temperature data representative of a wide range of enrichment plant operating conditions. VOLEM complements instrument development activities and allows the study of OLEM for scenarios that will be difficult or impossible to evaluate empirically. Uses of VOLEM include: investigation of hardware design options; inter-comparison of candidate gamma-ray spectral analysis and enrichment estimation algorithms; uncertainty budget analysis and performance prediction for typical and atypical operational scenarios; and testing of the OLEM data acquisition, analysis and reporting software. This paper describes the technical foundations of VOLEM and illustrates how it can be used. An overview of the nominal instrument design and deployment scenario for OLEM is provided, with emphasis on the key online-assay measurement challenge: accurately determining the portion of the total 235U signal that comes from a background that includes solid uranium deposits on the piping walls. Monte Carlo modeling tools, data analysis algorithms and uncertainty quantification methods are described. VOLEM is then used to quantitatively explore the uncertainty budgets and predicted instrument performance for a plausible range of typical plant operating parameters, and one set of candidate analysis algorithms. Additionally, a series of VOLEM case studies illustrates how an online enrichment monitor might respond in scenarios expected to be atypical, for example weak pressure transients or significant changes in background levels.