Results for “screening interval” — Page 3

NASA NTRS1972

Durability tests of a five-centimeter diameter ion thruster system.

A modified Hughes SIT-5 system is being tested for durability at the Lewis Research Center. As of Oct. 1, 1972, the thruster subsystem has logged over 8000 hours of operation. The initial 2023 hours were run with a translating screen thrust vector grid. The thruster is currently operating with an electrostatic type vector grid. Profiles and maps taken at widely separated intervals show that performance and operating characteristics have remained essentially constant. Overall efficiency is about 32 per cent and power to thrust ratio is 170 watts per millipound at a specific impulse of 2500 seconds. Telescopic examination of the vector grid shows some sputtering erosion due to charge exchange and direct impingement ions. An independent test of the propellant storage and cathode-isolator-vaporizer subsystem has demonstrated good reliability under simulated thruster operating conditions.

Nakanishi, S.↗

DOE OSTI2021

Detection of Anomalies in Environmental Gamma Radiation Background with Hopfield Artificial Neural Network - Consortium on Nuclear Security Technologies (CONNECT) Q3 Report

Environmental screening of gamma radiation consists of detecting weak nuisance and anomaly signal in the presence of strong and highly varying background. In a typical scenario, a mobile detector-spectrometer continuously measures gamma radiation spectra in short, e.g., one-second, signal acquisition intervals. The measurement data is a 2D matrix, where one dimension is gamma ray energy, and the other dimension is the number of measurements or total time. In principle, gamma radiation sources can be detected and identified from the measured data by their unique spectral lines. Detecting sources from data measured in a search scenario is difficult due to the highly varying background because of naturally occurring radioactive material (NORM), and low signal-to-noise ratio (S/N) of spectral signal measured during one-second acquisition intervals. The objective of this work is to investigate performance of a Hopfield Neural Network (HNN) in in detection and identification of weak nuisances and anomalies events in the presence of a highly fluctuating background. Performance of HNN algorithm is benchmarked using search data from an environmental screening campaign. One data set contained a 137 Cs source, and another dataset contained a 131 I source.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

Detection of Isotopes in Urban Source Search Low-Count Gamma Spectra Using Hopfield Neural Networks

Source search campaigns involve measurements of background gamma-ray spectra with a mobile detector-spectrometer traveling along arbitrarily chosen trajectories over a wide screening area. Radiation counts are typically measured with a tellurium-doped sodium iodide [NaI(Tl)] scintillator detector-spectrometer in short acquisition intervals, usually 1 s. The objective is to detect orphan isotopes with half-lives shorter than those of the isotopes in the natural background. In principle, radioisotopes can be identified by their unique gamma emission spectrum. However, detecting orphan isotopes in search data is challenging because low counts measured in short acquisition intervals result in incomplete spectral lines. In this study, we investigate the performance of a Hopfield neural network (HNN) that implements an auto-associative memory for the detection of isotopes of interest in an urban search campaign. The HNN is trained on one example of gamma spectra with well-resolved spectral lines of each isotope of interest. During testing, the auto-associative memory implementation of the HNN processes low-count gamma spectra with partially complete isotopic lines by matching incoming measurements to the closest one of its memory-stored patterns. The testing database consisted of almost 10 000 1-s gamma spectra, including measurements of orphan isotopes 137 Cs, 241 Am, and 131 I, obtained during two urban search surveys with a NaI(Tl) detector. The performance of the HNN detection algorithm was evaluated using precision, recall, and F1 scores, and benchmarked with a multiple linear regression (MLR) identification algorithm. In conclusion, the test results demonstrate that HNN outperforms MLR in the detection of all the isotopes of interest.

Auto associative memory↗

NASA NTRS2009

Two-Piece Screens for Decontaminating Granular Material

Two-piece screens have been designed specifically for use in filtering a granular material to remove contaminant particles that are significantly wider or longer than are the desired granules. In the original application for which the twopiece screens were conceived, the granular material is ammonium perchlorate and the contaminant particles tend to be wires and other relatively long, rigid strands. The basic design of the twopiece screens can be adapted to other granular materials and contaminants by modifying critical dimensions to accommodate different grain and contaminant- particle sizes. A two-piece screen of this type consists mainly of (1) a top flat plate perforated with circular holes arranged in a hexagonal pattern and (2) a bottom plate that is also perforated with circular holes (but not in a pure hexagonal pattern) and is folded into an accordion structure. Fabrication of the bottom plate begins with drilling circular holes into a flat plate in a hexagonal pattern that is interrupted, at regular intervals, by parallel gaps. The plate is then folded into the accordion structure along the gaps. Because the folds are along the gaps, there are no holes at the peaks and valleys of the accordion screen. The top flat plate and the bottom accordion plate are secured within a metal frame. The resulting two-piece screen is placed at the bottom opening of a feed hopper containing the granular material to be filtered. Tests have shown that such long, rigid contaminant strands as wires readily can pass through a filter consisting of the flat screen alone and that the addition of the accordion screen below the flat screen greatly increases the effectiveness of removal of wires and other contaminant strands. Part of the reason for increased effectiveness is in the presentation of the contaminant to the filter surface. Testing has shown that wire type contamination will readily align itself parallel to the material direction flow. Since this direction of flow is nearly always perpendicular to the filter surface holes, the contamination is automatically aligned to pass through. The two-filter configuration reduces the likelihood that a given contaminant strand will be aligned with the flow of material by eliminating the perpendicular presentation angle. Thus, for wires of a certain diameter, a two-piece screen is 20 percent more effective than is the corresponding flat perforated plate alone, even if the holes in the flat plate are narrower. An accordion screen alone is similarly effective in catching contaminants, but lumps of agglomerated granules of the desired material often collect in the valleys and clog the screen. The addition of a flat screen above the accordion screen prevents clogging of the accordion screen. Flat wire screens have often been used to remove contaminants from granular materials, and are about as effective as are the corresponding perforated flat plates used alone.

Backes, Douglas↗

DOE OSTI2021

Common risk segment mapping: Streamlining exploration for carbon storage sites, with application to coastal Texas and Louisiana

Large-scale deployment of Carbon Capture and Storage (CCS) will require a commensurately large number of sites. Efficient screening methods are needed to create investment assurance and focus efforts on the most promising sites. The problem is similar to petroleum exploration, for which there are well-developed (though seldom published) workflows, including Common Risk Segment (CRS) mapping. In brief, the process requires 1) defining the key play elements; 2) identifying candidate geologic intervals for each; 3) creating fact-based maps for those intervals; 4) determining minimum criteria for the success of each element; 5) reinterpreting the fact-based maps in terms of chance of success; and 6) combining the individual maps to form a composite, basin-scale view of prospectivity. We adapt the CRS process to screening for CO 2 storage sites. Critically, we redefine the process in terms of cost of characterization and development, rather than chance of success. For illustration, we apply the process to the example of the Lower Miocene on the Texas and Louisiana Gulf Coast. We show that the predictions are consistent with historic hydrocarbon production volumes and rates. The power of the CRS method is that it creates a systematic approach to geologic evaluation and translates complex, multidimensional analysis into clear, graphical and easily comprehended business inputs. The results highlight sweet spots and identifies critical risks, suggesting a focus for further data collection and analysis. Furthermore, the method developed here can be applied to both surface and subsurface factors anywhere that there is interest in geologic storage of CO 2 .

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2025

Components Refurbishment and Chemical Analysis Facility, SWMU #041 - Per- and Polyfluoroalkyl Substances Site Assessment Report Kennedy Space Center, Florida

This PFAS Site Assessment (SA) Report presents the activities and results associated with PFAS investigations at the Components Refurbishment and Chemical Analysis (CRCA) facility located at Kennedy Space Center (KSC), Florida. In 2022, CRCA was identified as an Area of Potential Concern because the facility stores several potential PFAS-containing chemicals. A groundwater sample collected from an onsite monitoring well detected PFOA and PFOS at concentrations greater than State of Florida provisional Groundwater Cleanup Target Levels (pGCTLs). PFAS SA activities were conducted between March 2022 and February 2024. During this timeframe, a total of 16 direct-push technology (DPT) locations and 82 discrete samples were collected from these locations, along with 90 monitoring well samples. The analytical data screening process focused on State of Florida pGCTLs and United States Environmental Protection Agency (USEPA) Regional Screening Level (RSLs) from November 2023 to evaluate the data. Analytical results identified PFOS, PFOA, and PFBA at concentrations exceeding their respective RSLs at each depth interval (shallow, intermediate, and deep). PFOS and PFOA had the largest footprint of RSL exceedances in each depth interval, but pGCTL exceedances were only observed at limited locations in the shallow and intermediate intervals. PFBA had the highest detections of any PFAS compound, with concentrations exceeding 180,000 nanograms per liter (ng/L), which is 100-times the RSL of 1,800 ng/L in the shallow and intermediate intervals and 10-times the RSL in the deep interval. The maximum PFBA detection was 841,000 ng/L at shallow monitoring well, MW0006. The PFAS SA also included samples collected from the onsite hydraulic containment system (HCS) which was installed to control and treat the onsite chlorinated volatile organic compound (CVOC) plume. Influent and effluent aqueous samples were collected monthly from the system. PFAS concentrations were relatively the same for both influent and effluent samples, indicating that while the HCS has been effective for CVOC treatment, it does not provide any additional treatment for PFAS compounds. Since the HCS has achieved its objectives, the system was shut down in December 2024. PFAS data gaps still exist, to include surface water and soil, which were not sampled during this SA. Soil sampling near the Chemical Process Area is recommended. Surface water and soil sampling at select stormwater outfalls is also recommended. Additionally, further groundwater sampling is recommended (DPT and monitoring well) in all depth intervals to delineate the extent of PFAS impacts at CRCA.

K Alex Murphy↗

NASA NTRS1979

Development of inflatable structures for Electron Echo V

The sounding rocket experiment, Electron Echo V, was designed to carry three devices to study the neutralization effects of the rocket upon electron beams emitted into the earth's magnetosphere. One was a 500 square foot current collector screen built on a framework of inflated 'mylar' tubes. The other two were 30 foot long Langmuir probes consisting of inflated tubes with sensor pads at various intervals. These devices were designed to be deployed at an altitude of 92-118 mi (148-190 km) by compressed gas carried in the payload. The development of these large (by sounding rocket standards) inflatables and the methods of packaging and deployment are described.

Oliver, J. A.↗

NASA NTRS1986

High-Performance Heat Pipe With Screen Mesh

Liquid distributed more evenly in evaporator section. Improved heat pipe contains an artery and wick rolled from stainless-steel screen of 180 mesh (openings about 80 micrometers). Screen material helps to prevent dryout in evaporator section by conducting liquid through hotspots and to vaporchannel wall. Insert reduces incidence of dryout at hotspots or during intervals of general thermal overload.

Alario, J. P.↗

DOE OSTI2022

Anomaly Detection in Gamma Spectra Using Hopfield Neural Network with B-SAT and Grover’s Algorithm on a Quantum Computing Simulator

Environmental screening of gamma radiation consists of detecting weak nuisance and anomaly signal in the presence of strong and highly varying background. In a typical scenario, a mobile detector-spectrometer continuously measures gamma radiation spectra in short, e.g., one-second, signal acquisition intervals. In principle, gamma radiation sources can be detected and identified by their unique spectral lines. However, detecting sources from data measured in a search scenario is difficult due to the highly varying background because of naturally occurring radioactive material (NORM), and low signal-to-noise ratio (S/N) of spectral signal measured during one-second acquisition intervals. In recent prior work, we have developed a Hopfield Neural Network (HNN) in conjunction with an image processing algorithm to detect a weak signal anomaly hidden among the highly fluctuating background spectra. The objective of this work is to explore quantum computing methods to increase the speed of HNN. The approach is based on the Grover’s search algorithm in conjunction with a 3-SAT problem formalism. The Grover’s algorithm is implemented on a quantum computing simulator using Qiskit software. Performance of HNN algorithm is benchmarked using search data from an environmental screening campaign, where the anomaly is a subset of measurements containing a 137 Cs source. Results indicate that using Grover’s algorithm on a quantum simulator reduces runtime of HNN by two orders of magnitude.

61 RADIATION PROTECTION AND DOSIMETRY↗

NASA NTRS2015

Cockpit Interfaces, Displays, and Alerting Messages for the Interval Management Alternative Clearances (IMAC) Experiment

This document describes the IM cockpit interfaces, displays, and alerting capabilities that were developed for and used in the IMAC experiment, which was conducted at NASA Langley in the summer of 2015. Specifically, this document includes: (1) screen layouts for each page of the interface; (2) step-by-step instructions for data entry, data verification and input error correction; (3) algorithm state messages and error condition alerting messages; (4) aircraft speed guidance and deviation indications; and (5) graphical display of the spatial relationships between the Ownship aircraft and the Target aircraft. The controller displays for IM will be described in a separate document.

Baxley, Brian T.↗

NASA NTRS2003

The Meteoritic Component in Impact Deposits

This proposal requested support for a broad-based research program designed to understand the chemical and mineralogical record of accretion of extraterrestrial matter to the Earth. The primary goal of this research is to study the accretion history of the Earth, to understand how this accretion history reflects the long-term flux of comets, asteroids, and dust in the inner solar system and how this flux is related to the geological and biological history of the Earth. This goal is approached by seeking out the most significant projects that can be attacked utilizing the expertise of the PI and potential collaborators. The greatest expertise of the PI is the analysis of meteoritic components in terrestrial sediments. This proposal identifies three primary areas of research, involving impact events in the early Archean (3.2 Ga), the late Eocene (35 Ma) and the late Pliocene (2 Ma). In the early Archean we investigate sediments that contain the oldest recorded impacts on Earth. These are thick spherule beds, three of which were deposited within 20 m.y. If these are impact deposits the flux of objects to Earth at this time was much greater than predicted by current models. Earlier work used Cr isotopes to prove that one of these contain extraterrestrial matter, from a projectile with Cr isotopes similar to CV chondrites. We planned to expand this work to other spherule beds and to search for additional evidence of other impact events. With samples from D. Lowe (Stanford Univ.) the PI proposed to screen samples for high Ir and Cr so that appropriate samples can be provided to A. Shukolyukov for Cr-isotopic analyses. This work was expected to provide evidence that at least one interval in the early Archean was a period of intense bombardment and to characterize the composition of objects accreted. The late Eocene is also a period of intense bombardment with multiple spherule deposits and two large craters. Farley et al. (1998) demonstrated an increased (3)He flux to marine sediments that was attributed to an increase in interplanetary dust due to a shower of comets invading the inner solar system. We planned to detect a change in the Cr-isotopic composition in the flux of fine-grained extraterrestrial matter to ocean sediments. This would provide evidence for the comet shower hypothesis. We planned attempt to locate late Eocene impact deposits in a new high resolution, hi-latitude site that had the potential for excellent preservation and new information of the sources and effects of these impacts. Although most impacts on Earth occur in deep-ocean basins, only one such event is known - the late Pliocene impact of the Eltanin asteroid. The ejecta from this impact includes Ir- rich impact melt, spherules, and actual meteorites from the km-sized mesosiderite asteroid. Through a study of the ejecta, we can learn about the formation, distribution, alteration and preservation of Ir-rich deposits. We can also learn about meteorite survival during hypervelocity impacts and we can study pieces of a km-sized object to learn more about the mesosiderite parent body. Analyses of sediment cores and geophysical exploration of the impact site can further our understanding of the processes involved in deep-ocean impacts and potential effects on the terrestrial climate and biosphere. We planned analyses of this ejecta, a search for ejecta 5000 km distant from the impact area, and a new oceanographic expedition to study and sample the impact site. In addition to these three specific areas of research, the PI planned to remain flexible and available to exploit new opportunities presented by new discoveries, and to engage in new collaborations if other researchers require his expertise to develop new projects that fit within the objectives of the overall research program.

Kyte, Frank T.↗

NASA NTRS1976

Pulmonary function evaluation during the Skylab and Apollo-Soyuz missions

Previous experience during Apollo postflight exercise testing indicated no major changes in pulmonary function. Pulmonary function has been studied in detail following exposure to hypoxic and hyperoxic normal gravity environments, but no previous study has reported on men exposed to an environment that was both normoxic at 258 torr total pressure and at null gravity as encountered in Skylab. Forced vital capacity (FVC) was measured during the preflight and postflight periods of the Skylab 2 mission. Inflight measurements of vital capacity (VC) were obtained during the last 2 weeks of the second manned mission (Skylab 3). More detailed pulmonary function screening was accomplished during the Skylab 4 mission. The primary measurements made during Skylab 4 testing included residual volume determination (RV), closing volume (CV), VC, FVC and its derivatives. In addition, VC was measured in flight at regular intervals during the Skylab 4 mission. Vital capacity was decreased slightly (-10%) in flight in all Skylab 4 crewmen. No major preflight-to-postflight changes were observed. The Apollo-Soyuz Test Project (ASTP) crewmen were studied using equipment and procedures similar to those employed during Skylab 4. Postflight evaluation of the ASTP crewmen was complicated by their inadvertent exposure to nitrogen tetroxide gas fumes upon reentry.

Sawin, C. F.↗

NASA NTRS2021

General Services Administration Reclamation Yard (SWMU 010) 2020-2021 Groundwater Monitoring Report

This report presents a summary of the groundwater monitoring activities that occurred from October 2020 through June 2021 at General Services Administration Reclamation Yard, Solid Waste Management Unit 010, located at the John F. Kennedy Space Center (KSC), Florida. For the purposes of this report, two separate plumes, known as the Polychlorinated Biphenyl (PCB)/Volatile Organic Aromatic (VOA) Plume and the Chlorinated Volatile Organic Compound (VOC) Plume were identified for this site. The contaminants of concern (COCs) for the PCB/VOA Plume consists of PCBs, 1,2,4-trichlorobenzene, and breakdown products of 1,2,4-trichlorobenzene. The COCs for the Chlorinated VOC Plume are tetrachloroethene, trichloroethene, cis-1,2-dichloroethene, and vinyl chloride. The activities presented in this report include four field events: (1) October 2020 – Chlorinated VOC Plume groundwater sampling via Direct Push Technology (DPT) – 68 groundwater samples were collected from 14 locations at varying intervals; (2) December 2020 – Site-wide semi-annual water level measurements of 52 monitoring wells and sampling of 39 monitoring wells; (3) May 2021 – Chlorinated VOC Plume monitoring well installation – two monitoring wells were installed and screened from 10 to 20 feet below land surface (bls); and (4) May/June 2021 – Site-wide semi-annual water level measurements of 53 monitoring wells and sampling of 40 monitoring wells. Results showed substantial reduction of both plumes. Conclusions and recommendations are presented.

VOC↗

NASA NTRS2024

Former Central Heat Plant SWMU 045 Year 2 Air Sparge System Performance Monitoring Report

This Air Sparge (AS) Performance Monitoring (PM) Report (PMR) presents Year 2 operation, maintenance, and monitoring (OM&M) activities, PM results, and monitoring well installations supporting the AS Interim Measure (IM) at the Former Central Heat Plant (CHP) at Kennedy Space Center (KSC), Florida. CHP has been designated Solid Waste Management Unit 045 under the KSC Resource Conservation and Recovery Act Corrective Action Program. An AS IM was installed at CHP between 2019 and 2021, which included the installation of an AS system to treat a chlorinated solvent groundwater plume. Contaminants of concern (COCs) identified at CHP for the AS IM include tetrachloroethene (PCE), trichloroethene (TCE), cis-1,2-dichloroethene (cDCE), and vinyl chloride (VC). The completed AS system includes a network of 267 AS wells, which treat approximately 1.3 acres of contaminated groundwater. “Hot” compressor technology is used to treat the source zone, while a “cold” compressor is used to treat two hot spot (HS) areas (HS1 and HS2) and the high concentration plume (HCP). The AS system began operation in June-July 2021 and this document includes Year 2 of operation. The overall runtimes for the AS system for the Year 2 reporting period (October 2022 to September 2023) were approximately 69 percent for the cold trailer and 71 percent for the hot trailer. Air samples and vapor screening results collected during the reporting period showed concentrations less than applicable human health and air emissions permit criteria. Groundwater performance monitoring results show that AS treatment continues to be effective in reducing COC concentrations at CHP. At the shallow interval, COC concentrations were all non-detect, less than, or met their respective State of Florida Groundwater Cleanup Target Levels (GCTLs) at the end of Year 2 in September 2023. In the deep interval, 10 of the 15 PM wells detected COCs greater than their respective GCTLs, with two of these wells also exceeding the Natural Attenuation Default Concentration for VC. Based on Year 2 OM&M and PM results, continued operation of the AS system is required to meet the IM objective. It is therefore recommended to continue with AS IM operations at CHP with the following plan for Year 3.

Kevin Alex Murphy↗

DOE OSTI2021

Comparison of Different Variants of the U.S. Army Occupational Physical Assessment Test

The U.S. Army Occupational Physical Assessment Test (OPAT) is a pre-enlistment physical employment screening assessment developed to place recruits and soldiers into Military Occupational Specialties (MOSs) based on their physical capabilities in order to optimize performance and limit injury. The OPAT consists of the seated power throw (SPT), strength deadlift (SDL), standing long jump, and interval aerobic run. During the scientific validation of the OPAT, two variants of the SPT and two variants of the SDL were used. Although the OPAT was validated using both variants for each test, U.S. Army scientists and policymakers have received queries regarding how these variants compare to each other. Therefore, the purpose of this study was to compare different variants of the SPT and SDL. Thirty-two participants (14 male and 18 female) between the ages of 18 and 42 years visited the laboratory on one occasion and performed two variants of the SPT (seated on the ground [the current OPAT standard] versus seated in a chair with a 35 cm seat height) and two variants of the SDL (using a hex-bar [the current OPAT standard] versus using paired dumbbells). Testing order for the different variants was randomized. The protocol was approved by the U.S. Army Medical Research and Development Command Institutional Review Board. Performing the SPT from a chair significantly (P < .05) increased performance when compared to performing the SPT from the ground (5.4 ± 1.3 m versus 5.0 ± 1.4 m, respectively). Values for the two SPT variants were correlated (tau = 0.90). Performing the SDL using the hex-bar significantly increased the maximal weight lifted when compared to performing the SDL using paired dumbbells (86.9 ± 18.4 kg versus 83.1 ± 18.0 kg, respectively). Values for the two SDL variants were correlated (tau = 0.83). Performing different variants of the SPT and SDL influenced the resulting score. Although these findings do not alter the administration or scoring of the OPAT, they do provide a valuable reference in the event of future inquiries regarding the development of the OPAT.

General & Internal Medicine↗

NASA NTRS2022

Wilson Corners Solid Waste Management Unit (SWMU) 001: 2021 Annual Long-Term Monitoring Report, Kennedy Space Center, Florida

This report presents a summary of the long-term monitoring (LTM) activities that occurred in 2021 at Wilson Corners, Solid Waste Management Unit (SWMU) 001, at Kennedy Space Center (KSC), Florida. The site is monitored under KSC’s Resource Conservation and Recovery Act (RCRA) Corrective Action Program. Adaptive site management is being utilized through ongoing assessment, design, and interim measures (IM). Annual LTM of the groundwater is also being conducted at the site. This approach also meets the requirements of Chapter 62-780, Florida Administrative Code (F.A.C.). The goal of LTM at this site is threefold: to determine groundwater flow characteristics, monitor the downgradient concentration trends, and monitor select locations internal to the groundwater plume. Every 5 years, upgradient and side-gradient monitoring wells are sampled to verify delineation. The last time this was performed was in 2015. The sampling of these wells in 2020 was replaced with the direct push technology (DPT) investigations completed in October 2020 and April 2021. This DPT groundwater data was presented in an Advance Data Package (ADP) in September 2021 and discussed in the Implementation Work Plan (IWP) dated November 2021 for installation of an air sparge (AS) system. Based on results from groundwater sampling activities performed during the previous reporting period, including the 2020 and 2021 DPT groundwater sampling, it was determined that the LTM sampling plan was no longer meeting the goal of LTM because delineation was not verified. The 2021 LTM sampling plan was modified to include the sampling of monitoring wells located around the perimeter of the low concentration plume (LCP); the area with concentrations of contaminants of concern [COCs] greater than Groundwater Cleanup Target Levels [GCTLs]), and sampling of 10 monitoring wells proposed for installation (April 2021 KSC Remediation Team (KSCRT) Meeting, Decision 2104-D32). The modified LTM plan received team consensus at the September 2021 KSCRT Meeting (Decision Number 2109-D03), and sampling of the existing monitoring wells was completed in December 2021. The proposed monitoring wells are planned for installation in late 2022, concurrent with ongoing IM construction activities. December 2021 LTM data was presented at the May 2022 KSCRT Meeting, and activities are summarized in this report. The activities presented in this report include the December 2021 groundwater gauging of 42 monitoring wells and sampling of 44 monitoring wells. During the December 2021 event, the low flow sampling method was used, and samples were analyzed for a select list of volatile organic compounds (VOCs), including 1,1,2-trichloro-1,2,2-trifluoroethane (Freon 113). The following conclusions can be made based on the 2021 LTM results: - In December 2021, groundwater flow for the site was generally to the west at all intervals. This is generally consistent with historical observations at the site, with the exception of a southwest and southeast flow component observed at 34 to 48 feet below land surface (bls). - The vertical extent of VOCs was historically delineated by monitoring wells screened greater than 48 feet bls. The results from the two vertical extent monitoring wells, WILC-MW0078 (screened 65 to 70 feet bls) and WILC-MW0130 (screened 56 to 66 feet bls) that were sampled during the 2021 LTM indicate that groundwater vinyl chloride (VC) concentrations in both wells were greater than the GCTL. The Remediation Team has previously agreed to delay deeper DPT investigations in this area to prevent the creation of additional pathways for vertical migration. - The LCP continues to extend both horizontally, predominantly to the west, and vertically beyond the current monitoring well network, with some retraction observed to the southeast. Evaluation of this data combined with data from the 2020 and 2021 DPT sampling event indicate that the LCP encompasses an estimated 20.7 acres based on an expanded sampling area, as compared to the 2020 LCP footprint of 17.0 acres. - Freon 113 was not detected above GCTLs during the 2021 LTM event. Based on groundwater sampling activities performed in 2021, including April 2021 DPT groundwater sampling, the following recommendations are provided: - Perform the next LTM sampling event, targeted to occur in 2023, concurrently with the IM baseline sampling prior to AS system installation; - Include sampling from nine monitoring wells that are planned to be installed in late 2022, concurrent with upcoming IM construction activities. Installation of one deep vertical well, screened 70 to 80 feet bls, will be delayed to prevent the creation of an additional pathway for vertical migration; - Continue to sample under the modified annual LTM plan as presented in Table 4-1 concurrently with IM baseline sampling; and - Once the AS system install and start-up is complete, select monitoring wells from the LTM program will transition into the performance monitoring plan, and LTM will be temporarily discontinued. Performance monitoring will be performed quarterly, and the monitoring well network will be evaluated following the first performance monitoring sampling event.

long-term monitoring (LTM)↗

DOE OSTI2020

Development of Gamma Background Radiation Digital Twin with Machine Learning Algorithms: Application of Unsupervised Machine Learning to Detection of Anomalies and Nuisances in Gamma Background Radiation Environmental Screening Data

Environmental screening of gamma radiation consists of detecting weak nuisance and anomaly signal in the presence of strong and highly varying background. In a typical scenario, a mobile detector-spectrometer continuously measures gamma radiation spectra in short, e.g., one-second, signal acquisition intervals. The measurement data is a 2D matrix, where one dimension is gamma ray energy, and the other dimension is the number of measurements or total time. In principle, gamma radiation sources can be detected and identified from the measured data by their unique spectral lines. Detecting sources from data measured in a search scenario is difficult due to the highly varying background because of naturally occurring radioactive material (NORM), and low signal-to-noise ratio (S/N) of spectral signal measured during one-second acquisition intervals. The objective of this work is to explore unsupervised machine learning (ML) algorithms for development of a digital twin of gamma radiation background, and for detection and identification of weak nuisances and anomalies events in the presence of highly fluctuating background. In one segment of work, we developed a gamma background estimation model using a Longshort term memory (LSTM) network for one-step CPS time series prediction. The LSTM model was validated with two data sets of measurements from two independent NaI detectors positioned on a mobile platform. The data sets contained background radiation only and no orphan isotope sources. The LSTM model was constructed and tested using data from one of the detectors. Performance of the LSTM model was validate through one-step prediction of CPS time series of another NaI detector without re-training. This approach allows to create a digital twin for nuclear background estimation. Using LSTM, it could be possible to detect a source through subtraction of the estimated counts from the measured background. In another segment of work, we investigated detection of gamma emitting sources in the presence of complex background using unsupervised machine learning. Spectral lines of isotopes are difficult to observe in one-second measurements. Averaging over the entire measurement campaign data set reveals spectral lines of most common background isotopes. Spectral lines of orphan sources, which might appear only in a few measurements during the campaign, will be washed out if averaging is performed over the entire measurement data set. The approach we have explored consists of extracting one-second measurements containing weak spectral features through data clustering. Averaging one-second spectra in a cluster should reveal the presence of anomaly sources. We created two ML models using K-means clustering and Neural Network Self-organizing Map (SOM). Performance of these ML models was benchmarked using search data. One data set contained 137 Cs source, and another dataset contained 131 I source.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Development of Hopfield Artificial Neural Network for Anomaly Detection in Environmental Gamma Radiation Background: Consortium on Nuclear Security Technologies (CONNECT) (Q2 Report)

Environmental screening of gamma radiation consists of detecting weak nuisance and anomaly signal in the presence of strong and highly varying background. In a typical scenario, a mobile detector-spectrometer continuously measures gamma radiation spectra in short, e.g., one-second, signal acquisition intervals. The measurement data is a 2D matrix, where one dimension is gamma ray energy, and the other dimension is the number of measurements or total time. In principle, gamma radiation sources can be detected and identified from the measured data by their unique spectral lines. Detecting sources from data measured in a search scenario is difficult due to the highly varying background because of naturally occurring radioactive material (NORM), and low signal-to-noise ratio (S/N) of spectral signal measured during one-second acquisition intervals. The objective of this work is to explore supervised machine learning (ML) algorithms for development of a Hopfield Neural Network (HNN) in conjunction with an image processing algorithm for detection and identification of weak nuisances and anomalies events in the presence of a highly fluctuating background.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗