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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

From Count Rates to Quantifying Isotopic Activities – Field Analysis of Radiation Monitoring Data

The Nevada National Security Site (NNSS) provides a comprehensive bicoastal radiological and nuclear emergency response to United States Department of Energy/National Nuclear Security Administration. A major part of the support is to provide systematic radiological search for lost or stolen sources, Radiological search is a core competency of the NNSS with its origin dating back to nuclear weapons test era. Search operations from multiple platforms is the common thread among the various NNSS assets, which include Aerial Measuring System (AMS), Maritime Support Team (MST), National Capitol Response (NCR), National Search Team (NST) and Radiological Assistance Program (RAP). Information collected and analyzed during search operations add to the actionable intelligence for the law enforcement agencies and provide valuable guidance for the tactical resolution of a nuclear or radiological crisis. Search is an intelligence and situational awareness driven operation and most often called upon during a radiological emergency, however it can be brought into play to thwart a potential threat by providing monitoring and surveillance support. The Office of Nuclear Incident Response (NA-84) serves as the technical leader in responding to and resolving nuclear and radiological threats worldwide and integrates its efforts with other NNSA stakeholders (e.g., NNSA office of Defense Nuclear Non-proliferation NA-22). The response includes expertise in the areas of radiological search, render safe, and consequence management. This article will discuss the methodologies, tools, procedures, and techniques to extract maximum radiological characterization information (isotopic composition, activities for individual isotopes, threat assessment etc.) from field monitoring or Search operation data.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2021

Stopping criteria for ending autonomous, single detector radiological source searches

While the localization of radiological sources has traditionally been handled with statistical algorithms, such a task can be augmented with advanced machine learning methodologies. The combination of deep and reinforcement learning has provided learning-based navigation to autonomous, single-detector, mobile systems. However, these approaches lacked the capacity to terminate a surveying/search task without outside influence of an operator or perfect knowledge of source location (defeating the purpose of such a system). Two stopping criteria are investigated in this work for a machine learning navigated system: one based upon Bayesian and maximum likelihood estimation (MLE) strategies commonly used in source localization, and a second providing the navigational machine learning network with a “stop search” action. A convolutional neural network was trained via reinforcement learning in a 10 m × 10 m simulated environment to navigate a randomly placed detector-agent to a randomly placed source of varied strength (stopping with perfect knowledge during training). The network agent could move in one of four directions (up, down, left, right) after taking a 1 s count measurement at the current location. During testing, the stopping criteria for this navigational algorithm was based upon a Bayesian likelihood estimation technique of source presence, updating this likelihood after each step, and terminating once the confidence of the source being in a single location exceeded 0.9. A second network was trained and tested with similar architecture as the previous but which contained a fifth action: for self-stopping. The accuracy and speed of localization with set detector and source initializations were compared over 50 trials of MLE-Bayesian approach and 1000 trials of the CNN with self-stopping. The statistical stopping condition yielded a median localization error of ~1.41 m and median localization speed of 12 steps. The machine learning stopping condition yielded a median localization error of 0 m and median localization speed of 17 steps. This work demonstrated two stopping criteria available to a machine learning guided, source localization system.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2017

Source detection at 100 meter standoff with a time-encoded imaging system

Here, we present the design, characterization, and testing of a laboratory prototype radiological search and localization system. The system, based on time-encoded imaging, uses the attenuation signature of neutrons in time, induced by the geometrical layout and motion of the system. We have demonstrated the ability to detect a ~1 mCi 252 Cf radiological source at 100 m standoff with 90% detection efficiency and 10% false positives against background in 12 min. As a result, this same detection efficiency is met at 15 s for a 40 m standoff, and 1.2 s for a 20 m standoff.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Generation of Synthetic Data for a Radiation Detection Algorithm Competition

This paper details the generation of synthetic radiation data using large-scale Monte Carlo transport models to evaluate radiation search detection algorithms. Modular 3-D Monte Carlo models spanning multiple city blocks were constructed, loosely based on downtown Knoxville, TN, containing buildings composed of multiple materials (brick, granite, and concrete), sidewalks, a four-lane road, side streets, parking lots, and grassy fields. Background and simulated source detector response calculations from these models were used to create synthetic list mode data sets for a 2"×4"×16" NaI(Tl) detector moving through a city street at a constant speed. For the background simulations, major isotopes were computed individually so that background composition and variability could be computed efficiently outside Monte Carlo. The source detector response included six simulated sources placed at 15 source locations. Detector response was developed to be periodic through the city street so that a detector path could begin at one end of the model and wrap around to the other. This framework allowed for the creation of diverse data sets, each with its own unique background and simulated source detector response. Synthetic data allows for high-quality labels, which are useful in developing data-driven radiation detection algorithms. This methodology was used to create synthetic data sets which were released as part of a public data competition to spur the development of new radiation detection algorithms for radiological search applications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Improved learning from data competitions through strategic design of training and test data sets

Leveraging the depth and breadth of solutions generated through crowdsourcing can be a powerful accelerator to method development for high consequence problems. While data science competitions have become quite popular and prevalent, particularly in supervised learning formats, their implementations by the host are highly variable. Without careful planning, a supervised learning competition is vulnerable to overfitting, where the winning solutions are so closely tuned to the particular set of provided data that they cannot generalize to the general underlying problem of interest to the host. This paper outlines important considerations for strategically designing relevant and informative data sets to maximize the learning outcome from hosting a competition. These include: precisely defining the scope of the problem, encouraging participation by competitors from diverse technical backgrounds, specifying the most interesting solution space in order to encourage improvement and distinguish between competitors, strategically generating data sets that enable testing for interpolation and extrapolation to new scenarios of interest, leveraging design of experiment principles for strategic data design while preventing unintentional artifacts in the competition data set that an algorithm could exploit without addressing the real problem of interest, and carefully designing the leaderboard scoring metric to select top solutions that exactly match the overall competition goals. The methods are illustrated with a recently completed competition in the context of urban radiological search to evaluate algorithms capable of detecting, identifying, and locating radioactive materials. Simulated data were used in the urban search competition. Ideas for using measured real data in competitions are also suggested

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

An Ensemble Approach to Computationally Efficient Radiological Anomaly Detection and Isotope Identification

Radiological source search is a challenging task involving detection and identification of weak sources in a constantly changing radiological background. As of now, many radiological source detection algorithms have been proposed; however, their computational complexity, and hence reliance on power intensive processing units inhibit low-power applications of radiological source search systems. In this work, we introduce the anomaly filter (AF) algorithm; a computationally light, yet effective time-series source detection algorithm based on exponential weighted moving average (EWMA) and Poisson deviance statistics. Then, we demonstrate that the proposed algorithm can be used in ensemble with other more computationally intensive source detection and identification algorithms to achieve both increased detection performance and reduced power consumption. The proposed AF algorithm and the ensemble algorithms were thoroughly benchmarked against several existing source detection and identification algorithms. The results show that the AF algorithm outperforms existing conventional source detection algorithms, and the ensemble approach improves the overall performance of existing source detection and isotope identification algorithms. Furthermore, the AF algorithm and the Non-negative Matrix Factorization approach based source identification (NMF-ID) algorithm were combined and implemented on a singleboard microcontroller and the power consumption was measured. This ensemble algorithm reduced the power consumption of the NMF-ID algorithm almost by a factor of 100, while improving the detection performance of the overall system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Consequence Management Cobalt Magnet 2022 Laboratory Analysis: After Action Report

On May 16-20, 2022, federal mission partners (e.g., DOE Consequence Management, CDC, FDA, FBI, DHS) as well as integrated state, local, tribal, and territorial governments took part in Cobalt Magnet 22 (CM22), a large-scale, week-long radiological incident exercise in Austin, Texas, that linked several important national assets (National Search Program, Radiological Assistance Program, and Consequence Management [CM] personnel) into a single response effort. The exercise had nine (9) overarching Objectives and an additional 162 associated Critical Tasks for all the participating organizations. In total, 13 National Core Capabilities spanning 5 Mission Areas were represented in the final exercise. This exercise enabled a full range of capabilities to be fielded together and examine the operational connection between major assets, discover any resource shortages associated with conducting multiple mission areas simultaneously or in close succession, and identify any challenges related to leadership. This report summarizes nearly 100 successes and observations provided from players and controllers supporting the LA Division, Fly Away Laboratory (FAL) and Gamma Spectroscopist operations. The observations were categorized to align with the FRMAC programmatic functional areas to consider for future improvements: Logistics, CBRN Responder, Laboratory Analysis, Sampling and Monitoring, Health and Safety, Gamma Spectroscopist Operations, Fly Away Laboratory, and the FRMAC Interdivision Interoperability Group (FIIG).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Gamma-Ray Point-Source Localization and Sparse Image Reconstruction using Poisson Likelihood

Gamma-ray imaging trys to reconstruct the spatial and intensity distribution of gamma-emitting radionuclides from a set of measurements. Wholly, this problem is solved by discretizing the spatial dimensions and employing the maximum likelihood expectation maximization (ML-EM) algorithm, with or without some form of regularization. While the generality of this formulation enables use in a wide variety of scenarios, it is susceptible to overfitting, limited by the discretization of spatial coordinates, and can be computationally expensive. We present a novel approach to 3D gamma-ray image reconstruction for scenarios where sparsity may be assumed, for example radiological source search. In this work we first formulate a point-source localization (PSL) approach as an optimization problem where both position and source intensity are continuous variables. We then extend and generalize this formulation to an iterative algorithm called additive point-source localization (APSL) for sparse parametric image reconstruction. A set of simulated source search scenarios using a single non-directional detector are considered, finding improved image accuracy and computational efficiency with APSL over traditional grid-based methods.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Differentiating IgG4-related sclerosing cholangiopathy from cholangiocarcinoma using CT and MRI: experience from a tertiary referring center

Purpose: To compare the cross-sectional imaging findings of immunoglobulin G4-related sclerosing cholangiopathy (IgG4-SC) and cholangiocarcinoma (CCA). Methods: Retrospective search of radiology and pathology databases identified 24 patients with IgG4-SC and over 500 patients with CCA from January 2009 to December 2016. Patients with no pre-treatment imaging studies available on PACS, non-contrasted imaging only, presence of mass lesions, metastatic disease or biliary stents were excluded. 17 patients with IgG4-SC and a selected group of 20 (age and gender matched) patients with CCA were obtained. Images were blinded and independently reviewed by two radiologists. Differences in proportions and means between groups were analyzed using Fishers and Mann–Whitney tests, respectively. Results: Both readers identified a statistically significant difference in the presence of abrupt common bile duct narrowing between IgG4-SC and CCA (6.7% vs. 68.4%, p < 0.001; 33.3% vs. 75%, p = 0.019). No difference was seen in biliary wall thickening, wall enhancement, extrahepatic exclusive location of disease, or pancreatic duct dilation. Inter-observer variability was κ = 0.52. Total bilirubin and CA 19-9 were unable to differentiate between IgG4-SC and CCA. Serum IgG4 was positive in two of six IgG4-SC patients who were tested. Conclusion: IgG4-SC and CCA share many clinical and imaging findings on CT and MRI. Abrupt bile duct cut sign strongly favors CCA. In the absence of this finding, IgG4-SC should be considered in the differential diagnosis in all cases of suspected extrahepatic CCA.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Clinical significance of incidentally discovered renal cysts in pediatric patients

Purpose: To determine the clinical significance of incidentally discovered renal cysts in pediatric patients and identify imaging predictors of autosomal dominant polycystic kidney disease (ADPKD). Methods: A retrospective search of radiology reports from 2000 to 2016 was performed to identify patients < 18 years old with an imaging exam identifying at least one renal cyst and a ≥ 1-year follow-up renal imaging exam for cyst evaluation and/or diagnosis of ADPKD. Cysts with clear solid mass components were excluded. Results: 84 pediatric patients with renal cysts were identified (mean age, 9.5 years), including 76 patients with incidentally discovered cysts and 8 patients with cysts identified from screening for ADPKD family history. Among the incidentally discovered cyst group, 7.9% were found to have ADPKD compared with 100% of patients with cysts and ADPKD family history. Maximum cyst diameter was significantly increased in patients with ADPKD compared to patients without ADPKD (22.0 mm vs 12.7 mm; P < 0.001, Fisher’s Exact test). Multiple cysts or bilateral cysts were imaging features associated with a significantly higher (P < 0.01) incidence of ADPKD, both for the entire study population and the incidentally discovered cyst group. An increase in cyst size on the follow-up study was associated with higher incidence of ADPKD (P < 0.05). No malignancies were identified. Conclusions: Incidentally discovered renal cysts in pediatric patients are associated with a small but non-zero risk of ADPKD. Among cyst characteristics, bilaterality, multiplicity, large size, and increased size on follow-up imaging were associated with a statistically significant elevation of ADPKD risk, and should prompt diagnostic evaluation.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Can magnetic resonance imaging differentiate among transurethral bulking agent, urethral diverticulum, and periurethral cyst?

Purpose: To evaluate magnetic resonance imaging findings that differentiate among periurethral bulking agents (primarily collagen), urethral diverticulum, and periurethral cyst. Methods: We searched our radiologic database retrospectively from 2001 to 2017 for periurethral cystic lesions, identifying a total of 50 patients with 68 lesions. Final diagnoses in 68 lesions were bulking agents (27), urethral diverticula (29), and periurethral cysts (12). Two abdominal radiologists, blinded to clinical history, independently evaluated T1, T2, and post-contrast images. The readers assessed number, morphological features, location, connection to urethra and mass effect, signal intensity, and enhancement for each lesion. Fisher exact test and logistic regression analysis were performed for each univariate significant feature. The operative and pathologic reports were the reference standard. Results: Magnetic resonance imaging features found more often in bulking agents versus urethral diverticulum were multiple lesions (P = 0.011), upper or upper-mid-urethral location (P ≤ 0.0001), lack of internal fluid/fluid level (P = 0.002), no urethral connection (P = 0.005), T1 isointensity, and T2 mild hyperintensity compared to muscles but lower T2 signal than urine (P < 0.0001). Most cases of urethral diverticula and periurethral cysts were detected at mid- and lower urethra. Urethral diverticula were larger than bulking agents and periurethral cysts (P = 0.005 and P = 0.023) (mean diameter = 24, 16, 15 mm, respectively). Most bulking agents (93%) and urethral diverticula (90%) showed mass effect on urethra, while periurethral cysts (75%) did not (P < 0.0001). Conclusion: Signal intensity and lesion characterization on magnetic resonance imaging can significantly differentiate bulking agent from urethral diverticulum and periurethral cyst. Radiologists should consider differential diagnosis of a bulking agent, especially when distinguishing characteristics described here are present to prevent incorrect diagnosis and ultimately unnecessary surgical intervention.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

RadMAP: The Radiological Multi-sensor Analysis Platform

The variability of gamma-ray and neutron background during the operation of a mobile detector system greatly limits the ability of the system to detect weak radiological and nuclear threats. The natural radiation background measured by a mobile detector system is the result of many factors, including the radioactivity of nearby materials, the geometric configuration of those materials and the system, the presence of absorbing materials, and atmospheric conditions. Background variations tend to be highly non-Poissonian, making it difficult to set robust detection thresholds using knowledge of the mean background rate alone. The Radiological Multi-sensor Analysis Platform (RadMAP) system is designed to allow the systematic study of natural radiological background variations and to serve as a development platform for emerging concepts in mobile radiation detection and imaging. To do this, RadMAP has been used to acquire extensive, systematic background measurements and correlated contextual data that can be used to test algorithms and detector modalities at low false alarm rates. By combining gamma-ray and neutron detector systems with data from contextual sensors, the system enables the fusion of data from multiple sensors into novel data products. The data are curated in a common format that allows for rapid querying across all sensors, creating detailed multi-sensor datasets that are used to study correlations between radiological and contextual data, and develop and test novel techniques in mobile detection and imaging. Here we will describe the instruments that comprise the RadMAP system, the effort to curate and provide access to multi-sensor data, and some initial results on the fusion of contextual and radiological data.

47 OTHER INSTRUMENTATION↗