Performance of hybrid methods for representative nonproliferationproblems

Adjoint-derived weight windowing is a hybrid deterministic/Monte Carlo method to simulate radiation transport. In adjoint-derived weight windowing, a deterministic adjoint solution is used to create weight windows for a Monte Carlo simulation. The intent of this work is to identify factors that reduce the Figure of Merit (FOM) of Monte Carlo simulations using adjoint derived weight windowing. The method used in this study pairs Transpire's deterministic code Attila™ and MCNP5. Two computationally difficult source/detector problems of interest to nuclear nonproliferation are used as case studies to determine the factors that affect the FOM. Test Case I is an active interrogation problem similar to many radiography problems. The model is used in two sets of trials: in the first, the quality of the deterministic adjoint solution is varied to observe the effect of adjoint solution quality on the FOM. In the second, the shielding density is varied to determine the effect of increased shielding on the FOM. Results from Test Case I suggest that weight windows that decrease monotonically along relevant paths from the source to the detector maximize the FOM. The results also suggest that weight windowing is susceptible to false convergence that could be avoided using a different hybrid method, such as the Local Importance Function Transform (LIFT). A more sophisticated method for generating weight windows relevant to the forward Monte Carlo simulation is described for future work. Test Case II is a detailed model of a detector array passively interrogating a uranium hexafluoride cylinder. Test Case II is used to test the effect of appropriate source biasing on the FOM. Results from Test Case II confirm prior work, that source biasing is important for problems in which the adjoint function varies widely in the source domain. Since spectral information from the detector is very useful for nonproliferation purposes, a new use of the forward weighted consistent adjoint driven importance sampling (FW-CADIS) method is described to model the energy-dependent flux in a region of interest. Properly modeling Test Case II also requires the use of rejection sampling of the source position paired with source biasing, which currently cannot be used together in MCNP5. The new use for the FW-CADIS method and a method to allow the use of rejection sampling with source biasing are described for future work

ADVANTG An Automated Variance Reduction Parameter Generator

The report is the descriptive journey of the ADVANTG An Automated Variance Reduction Parameter Generator

Random Inspection Planning for Misuse Detection in Safeguards

The IAEA uses random inspections (RIs) to, inter alia, provide credible assurance that declared nuclear facilities are not used for undeclared purposes. These inspections are random in the sense that they are scheduled randomly in date and time, with short notice given to the inspected site. The IAEA has interest in employing statistical models for RI planning that take advantage of any potential efficiency gains while maintaining a high level of effectiveness.This paper first introduces the model parameters that are necessary for a quantitative analysis of RI models for misuse inspections (subsequently referred to as RI models) and discusses their importance. Then, using the model parameters, the set of all RI models is introduced, and three example RI models are presented. Next, for any RI model the probability is derived that any facility is selected at least once per year for an RI, and – regarding the objective of an RI – the probability that a misuse is detected within days after its start, where the parameter is the duration of misuse signatures at the facility. Next, the question is addressed which RI model should be chosen for RI planning: If no further constraints from the IAEA are imposed on the RI models (e.g., maximum unpredictability of the number of RIs in each year, resource constraints leading to an upper number of RIs, etc.), then the RI model that maximizes the achieved detection probability for a given set of input parameters should be selected. This maximization problem, however, is by no means trivial, because the maximization is performed over a set of RI models and not over a subset of real numbers.Finally, the functionality and features of the software prototype TRIPS (Tool for Random Inspection Planning in Safeguards) are demonstrated, and future work topics are highlighted

The effectiveness of sampling plans based on both item-by-item tests and the stratum D-statistic

Nuclear fuel cycle facility declarations on nuclear material inventories and transfers are independently verified by the IAEA. These verification activities usually rely on a sampling plan that is designed to achieve a specified probability to detect falsification of operator reports. Currently, the IAEA’s sampling plans assume item-by-item tests in which the difference between the reported and the measured value of each item selected for verification is compared to a threshold. If a difference exceeds this threshold, then an “alarm” occurs, and the cause for the difference is further investigated. In the present paper we analyse sampling plans in which in addition to the usual item-by-item tests, a stratum difference statistic of the verified items is applied as a test statistic. The reason for considering the stratum difference statistic in addition to the item-by-item tests is that it is “better” at detecting bias defect falsifications than the item-by-item tests. Therefore, we investigate the effectiveness in terms of the achieved detection probability of sampling plans in which both tests are applied and analyse whether sample sizes could be reduced while still achieving the required detection probability

Micromechanics of the human vertebral body for forward flexion

To provide mechanistic insight into the etiology of osteoporotic wedge fractures, we investigated the spatial distribution of tissue at the highest risk of initial failure within the human vertebral body for both forward flexion and uniform compression loading conditions. Micro-CT-based linear elastic finite element analysis was used to virtually load 22 human T9 vertebral bodies in either 5° of forward flexion or uniform compression; we also ran analyses replacing the simulated compliant disc (E = 8 MPa) with stiff polymethylmethacrylate (PMMA, E = 2,500 MPa. As expected, we found that, compared to uniform compression, forward flexion increased the overall endplate axial load on the anterior half of the vertebra and shifted the spatial distribution of high-risk tissue within the vertebra towards the anterior aspect of the vertebral body. However, despite that shift, the high-risk tissue remained primarily within the central regions of the trabecular bone and endplates, and forward flexion only slightly altered the ratio of cortical-to-trabecular load sharing at the mid-vertebral level (mean ± SD for n = 22: 41.3% ± 7.4% compression; 44.1% ± 8.2% forward flexion). When the compliant disc was replaced with PMMA, the anterior shift of high-risk tissue was much more severe. We conclude that, for a compliant disc, a moderate degree of forward flexion does not appreciably alter the spatial distribution of stress within the vertebral body