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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 OSTI2022

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Investigating the Unique Ability of Trichodesmium To Fix Carbon and Nitrogen Simultaneously Using MiMoSA

The open ocean is an extremely competitive environment, partially due to the dearth of nutrients. Trichodesmium erythraeum, a marine diazotrophic cyanobacterium, is a keystone species in the ocean due to its ability to fix nitrogen and leak 30 to 50% into the surrounding environment, providing a valuable source of a necessary macronutrient to other species. While there are other diazotrophic cyanobacteria that play an important role in the marine nitrogen cycle, Trichodesmium is unique in its ability to fix both carbon and nitrogen simultaneously during the day without the use of specialized cells called heterocysts to protect nitrogenase from oxygen. Here, we use the advanced modeling framework called multiscale multiobjective systems analysis (MiMoSA) to investigate how Trichodesmium erythraeum can reduce dimolecular nitrogen to ammonium in the presence of oxygen. Our simulations indicate that nitrogenase inhibition is best modeled as Michealis-Menten competitive inhibition and that cells along the filament maintain microaerobia using high flux through Mehler reactions in order to protect nitrogenase from oxygen. We also examined the effect of location on metabolic flux and found that cells at the end of filaments operate in distinctly different metabolic modes than internal cells despite both operating in a photoautotrophic mode. These results give us important insight into how this species is able to operate photosynthesis and nitrogen fixation simultaneously, giving it a distinct advantage over other diazotrophic cyanobacteria because they can harvest light directly to fuel the energy demand of nitrogen fixation.

09 BIOMASS FUELS↗
DOE OSTI2016

SU-F-I-56: High-Precision Gamma-Ray Analysis of Medical Isotopes

Purpose: Advanced, time-resolved, Compton-suppressed gamma-ray spectroscopy with germanium detectors is implemented for assaying medical isotopes to study the radioactive decay process leading to a more accurate appraisal of the received dose and treatment planning. Lowell’s Array for Radiological Assay (LARA), a detector array that is comprised of six Compton-suppressed high-purity germanium detectors, is currently under development at UMass-Lowell which combines Compton-suppression and time-and-angle correlations to allow for highly efficient and highly sensitive measurements. Methods: Two isotopes produced Brookhaven Linac Isotope Producer (BLIP) were investigated. {sup 82}Sr which is the parent isotope for producing {sup 82}Rb is often used in cardiac PET. {sup 82}Sr gamma-ray spectrum is dominated by the 511keV photons from positron annihilation which prevent precise measurement of co-produced contaminant isotopes. A second project was to investigate the production of platinum isotopes. Natural platinum was bombarded with protons from 53MeV to 200MeV. The resulting spectrum was complicated due to the large number of stable platinum isotopes in the target, the variety of open reaction channels (p,xn), (p,pxn), (p,axn). Results: By using face-to-face NaI(Tl) counters 90-degrees to the Compton-suppressed germaniums to detect the 511keV photons, a much cleaner and more sensitive measurement of {sup 85}Sr and other contaminants was obtained. For the platinum target, we identified the production of {sup 188–189–191–195}Pt, {sup 191–192–193–194–195–196}Au and {sup 186–188–189–190–192–194–189–190–192–194}Ir. For example, at the lower energies (53 and 65MeV), we measured {sup 191}Pt production cross-sections of 144mb and 157mb. Considerable care was needed in following the process of dissolving and diluting the samples to get consistent results. The new LARA array will help us better ascertain the absolute efficiency of the counting system and more reliable production cross-sections. Conclusion: Modern HPGe spectroscopic techniques provide enhanced sensitivity, promising precise quantification of the quality of radioisotopes used in medical physics. Using new decay information may have non-trivial impact on treatment planning and dose-assessment.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2022

Water level changes in Lake Erie drive 21st century CO 2 and CH 4 fluxes from a coastal temperate wetland

Wetland water depth influences microbial and plant communities, which can alter the above- and below-ground carbon cycling of a wetland. Wetland water depths are likely to change due to shifting precipitation patterns, which will affect projections of greenhouse gas emissions; however, these effects are rarely incorporated into wetland greenhouse gas models. Seeking to address this gap, we used a mechanistic model, ecosys, to simulate a range of water depth scenarios in a temperate wetland, and analyzed simulated predictions of carbon dioxide (CO 2 ) andmethane (CH 4 ) fluxes over the 21st century. We tested our model using eddy covariance measurements of CO 2 and CH 4 fluxes collected at the Old Woman Creek National Estuarine Research Reserve (OWC) during 2015 and 2016. OWC is a lacustrine, estuarine, freshwater, mineral-soil marsh. An empirical model found that the wetland water depth is highly dependent on the water depth of the nearby Lake Erie. Future wetland surface water depths were modeled based on projection of Lake Erie's water depth using four separate NOAA projections, resulting in four wetland water-depth scenarios. Two of the four 21st century projections for Lake Erie water depths used in this study indicated that the water depth of the wetland would remain nearly steady; however, the other two indicated decreases in the wetland water depth. In our scenario where the wetland dries out, we project the wetland's climatological warming effect will decrease due to smaller CH 4 fluxes to the atmosphere and larger CO 2 uptake by the wetland. We also found that increased water level can lower emissions by shifting the site towards more open water areas, which have lower CH 4 emissions. We found that decreased water depths would cause more widespread colonization of the wetland by macrophyte vegetation. Using an empirical relationship, we also found that further drying could result in other, non-wetland vegetation to emerge, dramatically altering soil carbon cycling. In three of our four projections, we found that in general the magnitude of CO 2 and CH 4 fluxes steadily increase over the next 100 years in response to higher temperatures. However, in our driest simulations, we projected a different response due to increased oxidation of soil carbon, with CH 4 emissions decreasing substantially from an annual cumulative peak of 224.6 to a minimum of 104.7 gC m –2 year –1 . In that same simulation, net cumulative flux of CO 2 changed from being a sink of 56.5 gC m –2 year –1 to a source of 369.6 gCm –2 year –1 over the same period, despite a temperature increase from 13.7 °C to 14.2 °C. This temperature shift in our other three cases with greater water depths increased the source strength of CH 4 and the sink strength of CO 2 . Here, we conclude that the magnitude of wetland greenhouse-gas fluxes depended on the water depth primarily as it affected the areal percentage of the wetland available for plant colonization, but dramatic decreases in water depths could cause significant reductions in the wetland CH 4 fluxes, while simultaneously altering the wetland vegetation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

TU-F-CAMPUS-J-03: Elasticity Functions Based On 4DCT Images to Predict Tumor and Normal Tissue Response to Radiation for Patients with Lung Cancers

Purpose: To investigate radiotherapy outcomes by incorporating 4DCT-based physiological and tumor elasticity functions for lung cancer patients. Methods: 4DCT images were acquired from 28 lung SBRT patients before radiation treatment. Deformable image registration (DIR) was performed from the end-inhale to the end-exhale using a B-Spline-based algorithm (Elastix, an open source software package). The resultant displacement vector fields (DVFs) were used to calculate a relative Jacobian function (RV) for each patient. The computed functions in the lung and tumor regions represent lung ventilation and tumor elasticity properties, respectively. The 28 patients were divided into two groups: 16 with two-year tumor local control (LC) and 12 with local failure (LF). The ventilation and elasticity related RV functions were calculated for each of these patients. Results: The LF patients have larger RV values than the LC patients. The mean RV value in the lung region was 1.15 (±0.67) for the LF patients, higher than 1.06 (±0.59) for the LC patients. In the tumor region, the elasticity-related RV values are 1.2 (±0.97) and 0.86 (±0.64) for the LF and LC patients, respectively. Among the 16 LC patients, 3 have the mean RV values greater than 1.0 in the tumors. These tumors were located near the diaphragm, where the displacements are relatively large.. RV functions calculated in the tumor were better correlated with treatment outcomes than those calculated in the lung. Conclusion: The ventilation and elasticity-related RV functions in the lung and tumor regions were calculated from 4DCT image and the resultant values showed differences between the LC and LF patients. Further investigation of the impact of the displacements on the computed RV is warranted. Results suggest that the RV images might be useful for evaluation of treatment outcome for lung cancer patients.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Technical Note: PLASTIMATCH MABS, an open source tool for automatic image segmentation

Purpose: Multiatlas based segmentation is largely used in many clinical and research applications. Due to its good performances, it has recently been included in some commercial platforms for radiotherapy planning and surgery guidance. Anyway, to date, a software with no restrictions about the anatomical district and image modality is still missing. In this paper we introduce PLASTIMATCH MABS, an open source software that can be used with any image modality for automatic segmentation. Methods: PLASTIMATCH MABS workflow consists of two main parts: (1) an offline phase, where optimal registration and voting parameters are tuned and (2) an online phase, where a new patient is labeled from scratch by using the same parameters as identified in the former phase. Several registration strategies, as well as different voting criteria can be selected. A flexible atlas selection scheme is also available. To prove the effectiveness of the proposed software across anatomical districts and image modalities, it was tested on two very different scenarios: head and neck (H&N) CT segmentation for radiotherapy application, and magnetic resonance image brain labeling for neuroscience investigation. Results: For the neurological study, minimum dice was equal to 0.76 (investigated structures: left and right caudate, putamen, thalamus, and hippocampus). For head and neck case, minimum dice was 0.42 for the most challenging structures (optic nerves and submandibular glands) and 0.62 for the other ones (mandible, brainstem, and parotid glands). Time required to obtain the labels was compatible with a real clinical workflow (35 and 120 min). Conclusions: The proposed software fills a gap in the multiatlas based segmentation field, since all currently available tools (both for commercial and for research purposes) are restricted to a well specified application. Furthermore, it can be adopted as a platform for exploring MABS parameters and as a reference implementation for comparing against other segmentation algorithms.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Models and Processes to Extract Drug-like Molecules From Natural Language Text

Researchers worldwide are seeking to repurpose existing drugs or discover new drugs to counter the disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). A promising source of candidates for such studies is molecules that have been reported in the scientific literature to be drug-like in the context of viral research. However, this literature is too large for human review and features unusual vocabularies for which existing named entity recognition (NER) models are ineffective. We report here on a project that leverages both human and artificial intelligence to detect references to such molecules in free text. We present 1) a iterative model-in-the-loop method that makes judicious use of scarce human expertise in generating training data for a NER model, and 2) the application and evaluation of this method to the problem of identifying drug-like molecules in the COVID-19 Open Research Dataset Challenge (CORD-19) corpus of 198,875 papers. We show that by repeatedly presenting human labelers only with samples for which an evolving NER model is uncertain, our human-machine hybrid pipeline requires only modest amounts of non-expert human labeling time (tens of hours to label 1778 samples) to generate an NER model with an F-1 score of 80.5%—on par with that of non-expert humans—and when applied to CORD’19, identifies 10,912 putative drug-like molecules. This enriched the computational screening team’s targets by 3,591 molecules, of which 18 ranked in the top 0.1% of all 6.6 million molecules screened for docking against the 3CLPro protein.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Systematic and objective evaluation of Earth system models: PCMDI Metrics Package (PMP) version 3

Systematic, routine, and comprehensive evaluation of Earth system models (ESMs) facilitates benchmarking improvement across model generations and identifying the strengths and weaknesses of different model configurations. By gauging the consistency between models and observations, this endeavor is becoming increasingly necessary to objectively synthesize the thousands of simulations contributed to the Coupled Model Intercomparison Project (CMIP) to date. The Program for Climate Model Diagnosis and Intercomparison (PCMDI) Metrics Package (PMP) is an open-source Python software package that provides quick-look objective comparisons of ESMs with one another and with observations. The comparisons include metrics of large- to global-scale climatologies, tropical inter-annual and intra-seasonal variability modes such as the El Niño–Southern Oscillation (ENSO) and Madden–Julian Oscillation (MJO), extratropical modes of variability, regional monsoons, cloud radiative feedbacks, and high-frequency characteristics of simulated precipitation, including its extremes. The PMP comparison results are produced using all model simulations contributed to CMIP6 and earlier CMIP phases. An important objective of the PMP is to document the performance of ESMs participating in the recent phases of CMIP, together with providing version-controlled information for all datasets, software packages, and analysis codes being used in the evaluation process. Among other purposes, this also enables modeling groups to assess performance changes during the ESM development cycle in the context of the error distribution of the multi-model ensemble. Quantitative model evaluation provided by the PMP can assist modelers in their development priorities. In this paper, we provide an overview of the PMP, including its latest capabilities, and discuss its future direction.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Exploratory Ice Nucleation Measurements at Oliktok Field Campaign Report

Ice nucleating particles (INPs)—such as mineral dust and bacteria (1)—are a crucial source of seeds for cloud ice crystal formation, and can subsequently impact cloud radiative properties, lifetime, and precipitation formation processes (2-4). The presence of such particles in the atmosphere can be rare, but large concentrations are not required to have substantial impacts on cloud microphysics (3). However, knowledge of INPs, particularly in the Arctic, is limited due to the dearth of measurements in time and space. It is especially important to evaluate the sources and efficiency of INPs in the Arctic due to the role mixed-phase clouds play in facilitating the surface energy budget and thus energy reaching the sea ice and snow surfaces (4, 5). The purpose of this campaign, called INPOP (Ice Nucleating Particles at Oliktok Point), is to address the issue of limited information of Arctic INPs by providing time- and size-resolved INP concentrations over the course of a 3-month springtime campaign. This period is subject to Arctic haze, whereby pollutants from mid-latitudes are frequently transported to the Arctic and influence the relatively clean Arctic atmosphere (6-9). One unique aspect of this study is that the measurements were conducted at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility third ARM Mobile Facility (AMF3) in Oliktok Point, North Slope of Alaska (NSA), which is located in the northwest edge of the Prudhoe Bay oilfield. Typically, oil and natural gas extraction emissions are not thought to serve as a significant source of INPs, since naturally produced primary aerosols are the most efficient and abundant INPs (e.g., 1). However, the goal of INPOP was to evaluate INPs in the context of supporting aerosol and meteorological observations to assess: (1) if local industrial activities due to the oilfield operations can serve as a source of INPs (e.g., such as road dust from routine vehicular operations) and (2) if other regional or long-range transported sources impact a polluted Arctic location by introducing higher concentrations of more efficient INPs (e.g., transport of primary biological aerosol particles (PBAPs) from open ocean water or Arctic haze INPs). Unlike other Arctic coastal locations in the spring, Oliktok Point has a distinct combination of aerosol sources including long-range transported haze, regional/local marine emissions, and the local oilfield activities. Ground-based, immersion-mode, ice nucleation measurements were conducted on samples collected at the AMF3 in Oliktok Point from 1 March to 31 May, 2017. Samples were collected using a Davis Rotating-drum Unit for Monitoring (DRUM; DRUMAir, LLC) cascading impactor in 4 stages (i.e., size bins). Instrument information on the model used, the DA400, can be found at the DRUMAir website (http://www.drumair.com/). Stages A, B, C, and D, had particle size cuts at 2.96, 1.21, 0.34, and 0.15 μm particle diameter. Strips of sample substrate (PFA, perfluoroalkoxy; McMaster) were adhered to each disc in each stage and coated with petrolatum to enable particles to stick on impact. The discs move slowly over time, such that aerosol loading is streaked onto the PFA. Every 24 hours, a blank spot is created on the PFA to separate daily samples. The pump typically pulled 25 lpm at the inlet with all the discs in place in each stage. Daily samples were collected for each of the four stages, equaling 36,000 total L of air per sample. Discs rotated for approximately 24 days before the sampling per strip was complete and a new disc was installed by the ARM operators. Discs were stored frozen after collection until the end of the study.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

The scientific case for concurrent neutron and X-ray scattering and spectroscopy

The interrogation of materials with X-rays or neutrons to determine structure, energetics, and dynamics is fundamental to advancing physical and chemical materials science and enabling innovative material technologies. A persistent challenge in materials development is that progress depends on understanding structure and dynamics across multiple length and time scales in increasingly complex, multicomponent systems featuring interfaces, heterogeneity, and hierarchical organization. Despite rapidly growing demands on materials characterization, current experimental approaches are almost exclusively based on isolated X-ray or neutron scattering and spectroscopy, reflecting a paradigm largely unchanged for decades. To assess the scientific need for a new experimental paradigm, a 3-day workshop sponsored by the U.S. National Science Foundation (NSF) was held at the SpringHill Suites, San Jose, California, from June 2 to 4, 2022. The workshop brought together 70 national and international experts who critically evaluated opportunities enabled by concurrent neutron and X-ray (NeX) scattering, spectroscopy, and imaging experiments. The participants reached a clear consensus that establishing NeX capabilities is crucial for advancing the science of complex materials in the United States. This report illustrates the scientific drivers for NeX experiments through representative examples spanning biomaterials, energy materials, soft matter, nanomaterials, quantum materials, geoscience, and applied materials research. The complementarity of neutrons and X-rays is essential for robust model development and refinement, particularly in multiphase and multicomponent systems. While joint refinement of data from separate experiments is valuable, concurrent measurements uniquely eliminate uncertainties arising from sample evolution, environmental drift, and irreproducibility associated with experiments performed at different locations and times. Realizing NeX capabilities will require the development of new instrumentation, data analysis frameworks, and robust sample environments compatible with both neutron and X-ray probes. Addressing these challenges will enable unambiguous interpretation of complex materials behavior and open new frontiers in materials research.

X-ray↗
DOE OSTI2017

Precision Tests of the Electroweak Interaction using Trapped Atoms and Ions

The objective of the proposed research is to study fundamental aspects of the electroweak interaction via precision measurements in beta decay to test our current understanding of fundamental particles and forces as contained in the so-called "Standard Model" of particle physics. By comparing elegant experiments to rigorous theoretical predictions, we will either confirm the Standard Model to a higher degree and rule out models which seek to extend it, or find evidence of new physics and help guide theorists in developing the New Standard Model. The use of ion and neutral atom traps at radioactive ion beam facilities has opened up a new vista in precision low-energy nuclear physics experiments. Traps provide an ideal source of decaying atoms: they can be extremely cold (~1 mK); they are compact (~1 mm^3); and perhaps most importantly, the daughter particles escape with negligible distortions to their momenta in a scattering-free, open environment. The project is taking advantage of these technologies and applying them to precision beta-decay studies at radioactive beam facilities. The program consists of two complementary efforts: 1) Ion traps are an extremely versatile tool for purifying, cooling and bunching low-energy beams of short-lived nuclei. A large-bore (210~mm) superconducting 7-Tesla solenoid is at the heart of a Penning trap system for which there is a dedicated beamline at T-REX, the upgraded radioactive beam facility at the Cyclotron Institute, Texas A&M University. In addition to providing a general-purpose decay station, the flagship program for this system is measuring the ft-values and beta-neutrino correlation parameters from isospin T=2 superallowed beta-delayed proton decays, complimenting and expanding the already strong program in fundamental interactions at the Institute. 2) A magneto-optical trap is being used at the TRIUMF Neutral Atom Trap facility to observe the (un)polarized angular distribution parameters of isotopes of potassium. We are able to highly polarize laser-cooled atoms and observe their decay with unprecedented precision. The correlation of the daughter beta particle with the initial nuclear spin as well as other correlations are sensitive to physics beyond the Standard Model. Both of these cutting-edge and exciting research efforts will test our understanding of the fundamental symmetries underlying our current theory of electroweak interactions. Complementary to high-energy collider experiments, these low-energy nuclear physics "table-top" experiments will search for new particles and interactions which are not already described by the Standard Model of particle physics. The value of this research is recognized to be cross-disciplinary, exciting and potentially revolutionary in our understanding of nature's fundamental interactions. Accordingly, it has been endorsed by the recent (2007) Nuclear Science Advisory Committee's Long Range Plan as part of their recommendation for a "New Standard Model Initiative." In addition to the near-term benefits of scholarly publications and visibility through description of this work at international conferences, an important benefit of this research program is the training of new, young and enthusiastic nuclear physicists. Participants in this demanding and rewarding field develop a very strong background in physics with experience in a range of its subfields since we use atomic techniques and apply them to a nuclear physics experiment which in the end tests the theories of high-energy physics.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Automatic Analyte-Ion Recognition and Background Removal for Ambient Mass-Spectrometric Data Based on Cross-Correlation

Ambient mass spectrometry is a powerful approach for rapid, high-throughput, and direct sample analysis. Due to the open-air desorption and ionization processes, random fluctuations of ambient conditions can lead to large variances in mass-spectral signals over time. The mass-spectral data also can be further complicated due to multiple analytes present in the sample, background-ion signals stemming from the desorption/ionization source itself, and other laboratory-specific conditions (e.g., ambient laboratory air, nearby hardware). Thus, background removal and analyte-ion recognition can be quite difficult, particularly in non-targeted analyses. Here, we demonstrate the use of a cross-correlation-based approach to exploit chemical information encoded in the time domain to group/categorize mass-spectral peaks from a single analysis dataset. Ions that originate from ambient (or other) background species were readily flagged and removed from spectra; the result was a decrease in mass-spectral complexity by over 70% due to the removal of these background ions. Meanwhile, analyte ions were differentiated and categorized based on their time-domain profiles. With sufficient mass resolving-power and mass-spectral acquisition rate, isolated mass spectra containing ions from the same species in a sample could be extracted, leading to a reduction in mass-spectral complexity by more than 98% in some cases. The cross-correlation approach was tested with different ionization sources as well as reproducible and irreproducible sample introduction. Software built in-house enabled fully automated data processing, which can be performed within a few seconds. Ultimately, this approach provides an additional dimension of analyte separation in ambient mass-spectrometric analyses with information that is already recorded throughout the analysis. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

DABAM: An open-source database of X-ray mirrors metrology

An open-source database containing metrology data for X-ray mirrors is presented. It makes available metrology data (mirror heights and slopes profiles) that can be used with simulation tools for calculating the effects of optical surface errors in the performances of an optical instrument, such as a synchrotron beamline. A typical case is the degradation of the intensity profile at the focal position in a beamline due to mirror surface errors. This database for metrology (DABAM) aims to provide to the users of simulation tools the data of real mirrors. The data included in the database are described in this paper, with details of how the mirror parameters are stored. An accompanying software is provided to allow simple access and processing of these data, calculate the most usual statistical parameters, and also include the option of creating input files for most used simulation codes. In conclusion, some optics simulations are presented and discussed to illustrate the real use of the profiles from the database.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2025

hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware

We present hls4ml, a free and open-source platform that translates machine learning (ML) models from modern deep learning frameworks into high-level synthesis (HLS) code that can be integrated into full designs for field-programmable gate arrays (FPGAs) or application-specific integrated circuits (ASICs). With its flexible and modular design, hls4ml supports a large number of deep learning frameworks and can target HLS compilers from several vendors, including Vitis HLS, Intel oneAPI and Catapult HLS. Together with a wider eco-system for software-hardware co-design, hls4ml has enabled the acceleration of ML inference in a wide range of commercial and scientific applications where low latency, resource usage, and power consumption are critical. In this paper, we describe the structure and functionality of the hls4ml platform. The overarching design considerations for the generated HLS code are discussed, together with selected performance results.

FOS: Computer and information sciences↗
DOE OSTI2020

Radioactive Source Localization via Bayesian Particle Filter

In the event of a misplaced radioactive source or other emergency situation, measuring a radiation field, mapping its distribution, and determining a source location are essential tasks to ameliorating the situation. However, radiation fields may be extremely hazardous to human surveyors and minimizing received radiation doses is just as essential. Robots appear to be a potential solution to these problems. Beyond simply measuring radiation, the robot's computer processing capabilities offer a way to apply complex data analysis methods to radiation measurements in real-time. Methods which predict likely source locations can then feed this information into other processes, potentially improving path planning and enabling more efficient measurements. Given a robot mounted with a gamma-ray detector, can we: develop a methodology to account for detector performance across a wide range of source angles, distances, and photon energies? operate an autonomously navigating robot to effectively survey and characterize an area of interest? implement a data analysis method, conventionally used in measurements of motion, for source localization purposes? An open-source TurtleBot 3 robot, running Robot Operating System (ROS) on Ubuntu 16.04 LTS, was fitted with a Kromek GR1{sup R} Cadmium Zinc Telluride (CZT) solid-state gamma-ray detector. As a part of ROS, the packages OpenSlam, gmapping, and amcl were used to perform Simultaneous Localization and Mapping (SLAM), determining the robot's position and mapping the surrounding area. Data was acquired via Lidar mounted on top the TurtleBot 3. Detector Calibration Fit: The equation was fit to 365 counts of various energies, distances, and angles. A MATLAB{sup R} program was written to simulate measurements taken a robot on a random walk, with count data and positions discretized into finite element pixels. Using this program, a sample of 100 runs was performed on a map with a simulated source at the center, with a total of 200 of 2 pixels each. Similarly, multiple runs of the filter were performed on recorded robot measurement data. In both simulation and real tests, when corrected for errors (particles placed outside of bounds or on the robot, and simulation-specific errors), corresponding t-tests of predicted x and y-coordinates were within a 95% confidence interval of the actual position. For the real trial, these positions are slightly skewed right in the x-axis as the robot remained mainly to the left side of the source within the sample area. These simulations demonstrate potential validity for the usage of a particle filter as method of radioactive source localization. In the future, true real-time implementation and data fusion may further augment the performance of the robot to localize lost sources. Additionally, identification of multiple sources, determination of source types, and usage of a collimator are areas to potentially be explored.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

WE-DE-201-07: Measurement of Real-Time Dose for Tandem and Ovoid Brachytherapy Procedures Using a High Precision Optical Fiber Radiation Detector

Purpose: Development of a novel on-line dosimetry tool is needed to move toward patient-specific quality assurance measurements for Ir-192 HDR brachytherapy to verify accurate dose delivery to the intended location. This work describes the development and use of a nano-crystalline yttrium oxide inorganic scintillator based optical-fiber detector capable of acquiring real-time high-precision dose measurements during tandem and ovoid (T&O) gynecological (GYN) applicator Ir-192 HDR brachytherapy procedures. Methods: An optical-fiber detector was calibrated by acquiring light output measurements in liquid water at 3, 5, 7, and 9cm radial source-detector-distances from an Ir-192 HDR source. A regression model was fit to the data to describe the relative light output per unit dose (TG-43 derived) as a function of source-detector-distance. Next, the optical-fiber detector was attached to a vaginal balloon fixed to a Varian Fletcher-Suit-Delclos-style applicator (to mimic clinical setup), and localized by acquiring high-resolution computed tomography (CT) images. To compare the physical point dose to the TPS calculated values (TG-43 and Acuros-BV), a phantom measurement was performed, by submerging the T&O applicator in a liquid water bath and delivering a treatment template representative of a clinical T&O procedure. The fiber detector collected scintillation signal as a function of time, and the calibration data was applied to calculate both real-time dose rate, and cumulative dose. Results: Fiber cumulative dose values were 100.0cGy, 94.3cGy, and 348.9cGy from the tandem, left ovoid, and right ovoid dwells, respectively (total of 443.2cGy). A plot of real time dose rate during the treatment was also acquired. The TPS values at the fiber location were 458.4cGy using TG-43, and 437.6cGy using Acuros-BV calculated as Dm,m (per TG-186). Conclusion: The fiber measured dose value agreement was 3% vs TG-43 and −1% vs Acuros-BV. This fiber detector opens up new possibilities for performing patient-specific quality assurance for Ir-192 HDR GYN procedures. Funding from Coulter Foundation, Duke Bio-medical Engineering. Company is being created around the detector technology. Duke holds patents on the technology.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Nitrate, ammonium, and DON mass time series output for East River stream, vadose zone and groundwater subwatersheds from HAN-SoMo model

There is a growing understanding of the role that bedrock weathering can play as a source of nitrogen (N) to soils, groundwater and river systems. The significance is particularly apparent in mountainous environments where weathering fluxes can be large. However, our understanding of the relative contributions of rock-derived, or geogenic, N to the total N supply of mountainous watersheds remains poorly understood. This dataset contains model output from the High-Altitude Nitrogen Suite of Models (HAN-SoMo), a watershed-scale ensemble of process-based models to quantify the relative sources, transformations, and sinks of geogenic and atmospheric N through a mountain watershed. Our study is based in the East River Watershed (ERW) in the Upper Colorado River Basin. The East River is a near-pristine headwater watershed underlain primarily by an N-rich Mancos Shale bedrock, enabling the timing and magnitude of geogenic and atmospheric contributions to watershed scale dissolved N-exports to be quantified. Six calibration scenarios were developed to explore equifinality using >1600 N concentration measurements from streams, groundwater, and vadose zone samples collected over the course of four years across the watershed, from 2014-2018. The files in this dataset are named according to which calibration scenario they represent (1, 2, 3, NM1, NM2, and NC), and include daily time series model output of nitrate, ammonium and dissolved organic nitrogen concentrations for all six calibration scenarios described in Maavara et al., 2021, "Modeling geogenic and atmospheric nitrogen through the East River Watershed, Colorado Rocky Mountains," PLOS One (in press), for the stream, vadose zone, and groundwater in the five discretized subwatersheds: Rustlers Gulch, Copper Creek, East above Quigley (EAQ), the Middle East River (ME), and Lower Triangle (LT) from Gothic to the Pumphouse. The READ_ME.txt file includes details on units and naming conventions in each of these files. Model files are in .mat format, to be opened in MATLAB.

54 ENVIRONMENTAL SCIENCES↗