Self-Authentication of Solution Monitoring Data for Large Reprocessing Facilities (original) (raw)
Related papers
Solution Monitoring: Quantitative and Qualitative Benefits to Nuclear Safeguards
Journal of Nuclear Science and Technology, 2003
Nuclear safeguards includes periodic evaluation of material balances (MB) as a check for whether material is missing. In the case of large facilities that reprocess spent fuel, it is anticipated that the MB measurement uncertainty will be too large to meet statistical loss detection goals. Nonetheless, many believe that large reprocessing facilities can be effectively safeguarded with an appropriate combination of monitoring, MB accounting, and containment/surveillance (C/S) measures. We anticipate that solution monitoring (SM) will be a challenging but extremely useful new safeguards monitoring measure. This paper investigates how SM could improve loss detection in a formal statistical sense and discusses qualitative safeguards benefits of SM.
Nuclear material accounting (NMA) is a component of nuclear safeguards, which are designed to deter and detect illicit diversion of special nuclear material (SNM) from the peaceful fuel cycle to a weapons program. NMA consists of periodically, but at relatively low frequency, comparing measured SNM inputs to measured SNM outputs, and adjusting for measured changes in inventory. Process monitoring (PM) is a relatively recent component of safeguards that consists of data more frequently collected than NMA data. PM data are often only an indirect measurement of the SNM and is typically used as a qualitative measure to supplement NMA, or to support indirect estimation of difficult-to-measure inventory for NMA. This paper introduces quantitative diversion detection options for NMA and PM data, which can be regarded as time series of residuals. Unique statistical challenges in combining NMA and PM residual time series include: PM and NMA data are collected at different frequencies; PM residuals often have a probability distribution that cannot be adequately modeled by a Gaussian distribution, not all PM and NMA data streams are independent, and the monitoring scheme must have reasonably high detection probability for both abrupt and protracted diversion.
Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 2011
The International Atomic Energy Agency will require the development of advanced technologies to effectively safeguard nuclear material at increasingly large-scale nuclear recycling facilities. Ideally, the envisioned technologies would be capable of nondestructive, near-real-time, autonomous process monitoring. This paper describes recent results from model simulations designed to test the Multi-Isotope Process (MIP) monitor, a novel addition to a safeguards system for reprocessing facilities. The MIP monitor combines the detection of intrinsic gamma ray signatures emitted from process solutions with multivariate analysis to detect off-normal conditions in process streams nondestructively and in nearreal-time. Three computer models including ORIGEN-ARP, AMUSE, and SYNTH were used in series to predict spent nuclear fuel composition, estimate element partitioning during separation, and simulate spectra from product and raffinate streams using a variety of gamma detectors, respectively. Simulations were generated for fuel with various irradiation histories and under a variety of plant operating conditions. Principal component analysis was applied to the simulated gamma spectra to investigate pattern variations as a function of acid concentration, burnup, and cooling time. Hierarchical cluster analysis and partial least squares (PLS) were also used in the analysis. The MIP monitor was found to be sensitive to induced variations of several operating parameters including distinguishing 7 2.5% variation from normal process acid concentrations. The ability of PLS to predict burnup levels from simulated spectra was also demonstrated to be within 3.5% of measured values.
Energies, 2015
The aim of nuclear safeguards is to ensure that special nuclear material is used for peaceful purposes. Historically, nuclear material accounting (NMA) has provided the quantitative basis for monitoring for nuclear material loss or diversion, and process monitoring (PM) data is collected by the operator to monitor the process. PM data typically support NMA in various ways, often by providing a basis to estimate some of the in-process nuclear material inventory. We develop options for combining PM residuals and NMA residuals (residual = measurement − prediction), using a hybrid of period-driven and data-driven hypothesis testing. The modified statistical tests can be used on time series of NMA residuals (the NMA residual is the familiar material balance), or on a combination of PM and NMA residuals. The PM residuals can be generated on a fixed time schedule or as events occur.
Nuclear Engineering and Design, 2010
Reprocessing nuclear fuel is becoming more viable in the United States due to the anticipated increase in construction of nuclear power plants, the growing stockpile of existing used nuclear fuel, and a public desire to reduce the amount of this fuel. A new reprocessing facility will likely have state of the art controls and monitoring methods to safeguard special nuclear materials, as well as to provide real-time monitoring for process control. The focus of this research was to create a proof of concept to enable the development of a detection strategy that uses well established gamma and neutron measurement methods to characterize samples from the Uranium Extraction Plus 3a (UREX+3a) reprocessing method using a variety of detector types and measurement times. A facility that implemented real-time gamma detection equipment could improve product quality control and provide additional benefits, such as waste volume reduction. In addition to the spectral analyses, it was determined by Monte Carlo N Particle (MCNP) simulations that there is no noticeable self-shielding for internal pipe diameters less than 5.08 cm, indicating that no self-shielding correction factors are needed. Further, it was determined that High Purity Germanium (HPGe) N-type detectors have the high gamma ray energy resolution and neutron damage resistance that would be required in a reprocessing facility. Finally, the gamma ray spectra for the measured samples were simulated using MCNP and then the model was extended to predict the responses from an actual reprocessing scenario from UREX+3a applied to fuel that had a decay time of 3 years. The 3-year decayed fuel was more representative of commercially reprocessed fuel than the acquired UREX+3a samples. It was determined that the 3-year decayed fuel is easier to apply real-time process monitoring due to an increased number of short lived detectable isotopes. This research found that real-time gamma ray detection for process monitoring would be beneficial to a reprocessing facility and that commercially available detectors may be adequate for the neutron environment.
Nuclear fuel accountancy measurements are conducted at several points through the nuclear fuel cycle to ensure continuity of knowledge (CofK) of special nuclear material (SNM). Non-destructive assay (NDA) measurements are performed on fresh fuel (prior to irradiation in a reactor) and spent nuclear fuel (SNF) post-irradiation. We have developed a fuel assembly characterization system, based on the novel concept of "neutron fingerprinting" with multiplicity signatures to ensure detailed CofK of nuclear fuel through the entire fuel cycle. The neutron fingerprint in this case is determined by the measurement of the various correlated neutron signatures, specific to fuel isotopic composition, and therefore offers greater sensitivity to variations in fissile content among fuel assemblies than other techniques such as gross neutron counting. This neutron fingerprint could be measured at the point of fuel dispatch (e.g. from a fuel fabrication plant prior to irradiation, or from a reactor site post-irradiation), monitored during transportation of the fuel assembly, and measured at a subsequent receiving site (e.g. at the reactor site prior to irradiation, or reprocessing facility post-irradiation); this would confirm that no unexpected changes to the fuel composition or amount have taken place during transportation and/ or reactor operations. Changes may indicate an attempt to divert material for example. Here, we present the current state of the practice of fuel measurements for both fresh mixed oxide (MOX) fuel and SNF (both MOX and uranium dioxide). This is presented in the framework of international safeguards perspectives from the US and UK. We also postulate as to how the neutron fingerprinting concept could lead to improved fuel characterization (both fresh MOX and SNF) resulting in: (a) assured CofK of fuel across the nuclear fuel cycle, (b) improved detection of SNM diversion, and (c) greater confidence in safeguards of SNF transportation.
Nuclear safeguards at inspected facilities aims to deter or detect special nuclear material (SNM) diversion and to do so is increasingly relying on process monitoring (PM) to augment nuclear material accounting (NMA). In NMA, SNM material balances are computed approximately every 30 days, and modeling and simulation are used to predict detector performance, to model SNM flows and inventory, and predict overall NMA performance as measured by the measurement error standard deviation of the material balance, MB. In PM, much more frequent and often shortcut measurements (less than full SNM accountability) are used, and modeling and simulation are increasingly used to predict the effects of SNM diversion on normal operating data under various scenarios. This paper reviews traditional modeling and simulation roles in NMA, describes new roles in PM, and illustrates using a case study.
The Detection of Nuclear Materials Losses
Decision Sciences, 1995
The identification and location of materials losses in nuclear facilities is an important issue. Many complexities arise in monitoring such losses. These complexities include the dependency among materials balance observations and the influence of errors (outliers) on parameter estimates of various monitoring methods. The proposed Joint Estimation procedure is superior to standard methods (control chart and CUSUM) and to methods that build in correlation (ARMA control chart, ARMA CUSUM, and the Generalized M procedure) in the detection of nuclear materials losses. The Joint Estimation procedure is robust to the influence of outliers, is flexible in accommodating a range of dependencies among observations, and provides information on the type of loss. Further, the procedure is reliable in that it yields a probability of false alarms and a probability of detecting losses closer to specifications. Subject Areas: Energy, Quality Control, and Statistical Techniques. *We would like to thank Jack Markins for providing insight into the safeguards systems at nuclear facilities.
Development and evaluation of methods for safeguards use of solution monitoring data
1996
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