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DOE OSTI2022

System Response Characterization for a d–t Neutron Radiography System

We report the system response of a pixelated associated particle imaging (API) neutron radiography system. The detector readout currently consists of a 2x2 array of organic glass scintillator detectors, each with an 8x8 array of optically isolated pixels that match the size and pitch of the ARRAYJ-60035-64P-PCB Silicon Photomultiplier (SiPM) array from SensL/onsemi with 6x6 mm 2 SiPMs. The alpha screen of the API deuterium-tritium neutron generator is read out with the S13361-3050AE-08 from Hamamatsu, which is an 8x8 array of 3x3 mm 2 SiPMs. Data from the 320 channel system is acquired with the TOFPET2-based readout system. We present the predicted imaging capability of an eventual 5x5 detector array, the waveform-based energy and pulse shape characterization of the individual detectors, and the timing and energy response from the TOFPET2 system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2020

Development of a Convolutional Neural Network Classifier for Data Starved Spectra - 20199

The Institute for Clean Energy Technology (ICET) at Mississippi State University is exploring the utility of machine learning in augmenting its mobile radiation surveying platforms, which are currently being developed as means to survey depleted uranium contaminated areas in support of remediation and decommissioning efforts. Mobile survey platforms provide a means to efficiently scan large areas of interest while reducing human exposure to radiation and other hazards. The survey platforms can also be used for scanning for any gamma emitting isotope in addition to depleted uranium. The spectral data that the platforms collect may be data starved with relatively low counts and poorly defined spectral features depending on the speed of the platforms and scintillation detector selection. Such data-starved spectra are difficult to use for isotope identification, requiring advanced knowledge of the possible radionuclides that could be present and environmental factors that could attenuate signals or introduce background noise. These factors in combination with the volume of survey data increases the time it takes to perform analysis of survey data when the source type is unknown. There are a number of algorithms in the field of machine learning that can be used to classify data that would be challenging and time-consuming for a human to identify. Supervised machine learning algorithms train models based on extensive amounts of human-labeled training data. Once sufficiently trained, these models can be used to quickly make high-fidelity predictions on new data. Convolutional neural networks are machine learning algorithms that excel in learning representations of 'shapes'. They do this by taking numerical input data and convolving them with spatial feature detectors referred to as filters. These filters are incrementally adjusted to reduce the prediction error on the data during the backpropagation step of training. Discussed in this paper is the development of a convolutional neural network classifier (CNNC) that can utilize spectral survey data for source discrimination and isotope identification. Bench-top laboratory experiments data using LaBr{sub 3}(Ce) scintillation detectors were used to train and evaluate the performance of the developed CNNC. The CNNC is capable of discriminating a variety of gamma emitting source types, differentiating different forms of uranium (depleted vs. natural), and estimating the amount of uranium for a known geometry. The discussed CNNC may be useful in scenarios where survey systems are deployed in situations where hazardous radioactive material maybe present, but the type is unknown. When used in remediation applications the CNNC can be used to screen-out false positives, helping reduce remediation costs. (authors)

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2024

LLNL measurements of thermally irradiated HEU sample and saltwater-matrixed HEU sample

Two scintillation vials, kindly provided by the PNNL team, were received in the LLNL radiochemistry building on June 10, 2024; one containing approximately 2 mL dissolved thermally-irradiated HEU, and the other containing dried salt from irradiated seawater. A quick, semiquantitative screening count of the salt showed that the activation product activities were very low, with the highest activity being ~1 Bq 24 Na. The dissolved HEU solution was transferred to a Prindle vial (LLNL standard counting geometry) and weighed. Approximately 2 mL 3 M HNO 3 was added so that the solution completely covered the bottom of the vial and Gamanal software would be able to accurately generate an efficiency curve. This sample, called “PNNLFP24” is the irradiated HEU solution received, gravimetrically diluted by a factor of 1.7356 ± 0.0003, and was sent for quick gamma counting prior to further modification. Meanwhile the salt was quantitatively transferred to a 250 mL polyethylene bottle and dissolved in 160 mL 3 M HNO 3 . After counting, 50 µL PNNLFP24 was aliquoted for Resonance Ionization Mass Spectrometry (RIMS) analysis, and then 10.0 mL of the salt solution (6.03% of the total salt, gravimetrically) was added to the remaining PNNLFP24 solution to make “PNNLFPSW24”. After weighing, two 100 µL aliquots were removed for RIMS and DES, and 3 mL was aliquoted for microfluidic chemistry. The remaining “PNNLFPSW24” solution was weighed and proceeded for singles and coincidence counting on the MCBOS system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Multiple Phase Screen Electromagnetic Propagation Simulations of Starfish Prime Event

It has been decided at this point to pause development of the trans-ionospheric model, and the main goal of this document is to record the current status and maintain a list of references for the future. The 2D model appears to work: however, to truly gain meaningful information about the environment, the scintillation model should be integrated into an end-to-end communication link simulation, which includes much more phenomenology. It would be beneficial at this point to specify a particular link or system and import a HANE environments into existing simulations. Multiple realizations of the noise could then be applied, and communication signal budgets could be analyzed for particular systems.

42 ENGINEERING↗

DOE OSTI2019

Large Area Airborne Contamination Monitoring

Current D&D operations at Hanford have demonstrated a flaw in the current state of the art capability of defining airborne contamination boundaries. Airborne particulate emissions of Pu-239 from CM2H operations on the Hanford Pu Finishing Plant were detected well beyond areas controlled for airborne plutonium, putting numerous workers at risk for radiological assimilations. Forty-two Hanford workers had positive bioassay results for plutonium uptake. Work areas determined to be free of airborne contamination as measured by state-of-the-art continuous alpha monitoring (CAM) systems were later discovered not to be. Airborne contamination was scattered to a such degree that CAM systems were surveying insufficient volumes of air to accurately predict where respiratory protection was required. A $\$ 19,000$ state of the art portable CAM system used at both Hanford and at SRS screens air for alpha activity at the rate of 1 CFM. This research project will explore the feasibility of using commercially available air purifying systems to screen significantly larger volumes of air for airborne actinide contamination. Commercial household HEPA based air purifying units screen large volumes of air, a simple $\$ 300$ unit being looked at for this study could screen a volume of air that would require over 300 of the $\$ 19,000$ CAMs. The goal of the project was to determine the feasibility of building a detection system capable of screening the air purifiers pre-filters and HEPA filters for any actinide bearing hot particles that have been captured. The simplest technologies available to Field-Radiological-Protection personnel are hand-held alpha field survey meters. With the size and the corrugated structure of these HEPA filters, hand screening is not practical. This project researched alternatives capable of automating this function. Two potential technologies were examined. One technology evaluated was the measurement of xray emissions from the actinides, taking advantage of the higher emission rates of the L x-rays compared to the gamma emissions of isotopes such as Pu-238 or Pu-239. High resolution to low resolution systems were evaluated. Branching ratio data on the actinides in the literature is incomplete, and a study was initiated to measure branching ratios of the various L emissions of a number of the plutonium isotopes. A Monte Carlo simulation was also run to calculate the effect the attenuating HEPA media would have on x-ray measurements on spectrometers centered in each quadrant above the surface of the HEPA. The second technology evaluated was measuring the light from a scintillating media applied to the surface of the HEPA filter using a ThorLabs Scientific-Grade Digital Camera Model 8051M. A light tight enclosure capable of holding the 2’x2’x1” HEPA filter was fabricated. Numerous scintillation media were evaluated for both the sensitivity and for resolution of measuring alpha activity. Figure 1 shows images of a 4”x4” section of HEPA filter with a 3 x 3 grid of Pu-238 contamination loaded inside the crevices of the HEPA.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗