Integration of the H3D-M400 detector and Spot robot for automated area survey missions
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Engineering topics
Publications and source records attributed to Annadevula, Lohith.
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Office of Nuclear Smuggling Detection and Deterrence (NSDD) is charged to identify and develop technologies to detect, disrupt, and investigate smuggling of radiological and nuclear materials •Border protection involves primary inspections using Radiation Portal Monitors (RPM), complimented with secondary and area survey inspections, usually performed manually using portable radiation detectors (PRDs) -RPM rely on fast technologies which provide quick scans of passing cargo/vehicles -Secondary inspections rely on trained, field deployed staff responsible for additional interdiction of screened cargo/vehicle putting them in potentially hazardous environment -Area survey inspections rely on trained, field deployed staff responsible for scanning and identifying presence of radiation while patrolling through a facility or public space •This project explores the use of technology which could reduce risks to field inspectors and add efficiency •The work presented here is a proof of principle of detector-robot integration to perform area survey inspections
The authors built and tested a stochastic simulation to estimate achieved detection probabilities (DPs) on a stratum basis, over a tailorable range of diverted amounts from 0 to 2 significant quantities (SQ), using typical International Atomic Energy Agency (IAEA) inspection data: i.e., SQ in stratum, number of items, number of gross/partial/bias defect measurements conducted, and realistic relative standard deviation (RSD) values for typical IAEA verification measurements. For bulk strata, the model calculates achieved DP at 0.01 SQ diversion increments; for item strata, the model calculates DP using the smallest realistic diversion increment (e.g., a plate, pin, or coupon). After successfully benchmarking against IAEA deterministic models, the simulation was used to test the sensitivity of DP to certain standard assumptions and selected input parameters. First, the equal defect assumption was tested; the results suggest significant complexity in the effectiveness of partial defect measurements. Next, the authors explored the sensitivity of DP to the assumed RSD of attribute tests. Then, the authors compared non-normal models for instrument performance (e.g., logistic, step, or arbitrary functions) to the typical results from a normal distribution (characterized by RSD). This last comparison was supplemented with experimentally derived performance data for an HM-5 gamma spectrometer. The HM-5 was used to make enrichment measurements on both LEU and HEU MTR fuel elements as plates were removed, and the results fit with logistic and step curves and applied in the simulation. These stochastic DP results were compared to DP estimates from a deterministic model assuming a normal curve and typical RSD, yielding insights that could improve effectiveness in the field. These early results illustrate the potential of stochastic models to better understand achieved DP and to improve safeguards effectiveness.