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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 OSTI2019

GADRAS-DRF Version 18 User's Manual

The Gamma Detector Response and Analysis Software Detector Response Function (GADRAS-DRF) application computes the response of gamma-ray and neutron detectors to incoming radiation and provides analysis on measured spectra. This manual provides step-by-step procedures to acquaint new users with the use of the application. The capabilities include characterization of detector response parameters, plotting and viewing measured and computed spectra, analyzing spectra to identify isotopes, estimating source energy distributions from measured spectra, and creating inject data. GADRAS-DRF can compute and provide detector responses quickly and accurately, giving users the ability to obtain usable results in a timely manner (a matter of seconds or minutes).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

GADRAS-DRF Enhancements for Safeguards – Custom Peak Fitting to Enhance Model Fitting and Isotopics

One major software update was accomplished within the Gamma Detector Response and Analysis Software-Detector Response Function (GADRAS-DRF) package. This update allows users to adjust individual peak fits for use in subsequent analysis processes within GADRAS-DRF. A graphical user interface (GUI) was implemented so users can see the effect of their fit adjustments on the spectrum. This new feature will enhance the capability of the previously funded auto-enrichment and peak-based 1D model fit feature that was implemented in FY23 (Fiscal Year). Isotopic analysis was performed using M400 data obtained from uranium standards and the isotopic assessment is given with and without manual peak adjustments.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2025

GADRAS-DRF Validation for Safeguards and Custom Peak Fit Enhancements

In previous years, SGTech funded enhancements to the isotopics routine in the software called Gamma Detector Response and Analysis Software-Detector Response Function (GADRAS-DRF), including the addition of peak fit customization capabilities. A project was also funded that focused on implementing a peak-based model fitting routine, allowing model fitting to be performed without dependence on export-controlled cross-sections. In FY25 significant improvements were made to the custom peak fitting interface, accompanied by several validation studies within GADRAS-DRF. These studies encompassed IsotopeID performance, distributed source analysis, isotopics validation, and activity estimation. Additionally, the peak-only model fitting option was validated using an HPGe measurement of a rotating drum with line sources.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

GADRAS-DRF for Safeguards (FY 2025 Mid-Year/Annual Report)

Task 1 – Extract GADRAS-DRF capabilities for a workflow intuitive to safeguards analysis. This task is almost complete. Significant improvements have been made to the functionality of customizing peak fits for use in the isotopics application, as well as peak-based FSA model analysis. The remaining tasks revolve around bug fixes, testing the application, and adding a density scroll bar to isotopics for real time analysis updates. The density scroll bar values will be reflected in summary tables and the self-shielding form accessed within isotopics.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Validation and uncertainty quantification of detector response functions for a $1"×2"$ NaI collimated detector intended for inverse radioisotope source mapping applications

Detector response functions (DRFs) are often used for inverse analysis. We compute the DRF of a sodium iodide (NaI) nuclear material holdup field detector using the code named g03 developed by the Center for Engineering Applications of Radioisotopes (CEAR) at NC State University. Three measurement campaigns were performed in order to validate the DRF’s constructed by g03: on-axis detection of calibration sources, off-axis measurements of a highly enriched uranium (HEU) disk, and on-axis measurements of the HEU disk with steel plates inserted between the source and the detector to provide attenuation. Furthermore, this work quantifies the uncertainty of the Monte Carlo simulations used in and with g03, as well as the uncertainties associated with each semi-empirical model employed in the full DRF representation. Overall, for the calibration source measurements, the response computed by the DRF for the prediction of the full-energy peak region of responses was good, i.e. within two standard deviations of the experimental response. In contrast, the DRF tended to overestimate the Compton continuum by about 45–65% due to inadequate tuning of the electron range multiplier fit variable that empirically represents physics associated with electron transport that is not modeled explicitly in g03. For the HEU disk measurements, computed DRF responses tended to significantly underestimate (more than 20%) the secondary full-energy peaks (any peak of lower energy than the highest-energy peak computed) due to scattering in the detector collimator and aluminum can, which is not included in the g03 model. We ran a sufficiently large number of histories to ensure for all of the Monte Carlo simulations that the statistical uncertainties were lower than their experimental counterpart’s Poisson uncertainties. The uncertainties associated with least-squares fits to the experimental data tended to have parameter relative standard deviations lower than the peak channel relative standard deviation in most cases and good reduced chi-square values. The highest sources of uncertainty were identified as the energy calibration polynomial factor (due to limited source availability and NaI resolution) and the Ba-133 peak fit (only a very weak source was available), which were 20% and 10%, respectively.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Deployment Readiness Framework Subtask 1.1 (Literature Review)

Island and remote coastal communities face some of the most challenging environments for building, operating, and maintaining energy infrastructure, as well as the highest costs for electricity, fuels, and other essential energy sources. As sea-levels rise and storms become more intense and frequent, these communities and the energy infrastructure that supports coastal lives and livelihoods are also at increasing risk from natural hazards. To address these challenges, many coastal communities are envisioning energy solutions that will support the triple bottom line goals of the blue economy: economic growth, environmental sustainability, and social equity. Yet, island and remote coastal communities often face limited resources and capacity to tackle complex energy and coastal resilience issues. To support community-driven energy transitions in island and remote communities, and to better understand relationships between energy, community, and ecosystem resilience, the Department of Energy’s Water Power Technologies Office (WPTO) has initiated the development of a Deployment Readiness Framework (DRF). The objective of the work is to co-produce and test practical tools and approaches that assess the readiness of coastal communities for marine energy demonstration, deployment, and operation. The DRF aims to build on and support the Energy Transitions Initiative Partnership Program (ETIPP) and other community-oriented energy transition programs. This project is jointly led by Pacific Northwest National Laboratory (PNNL) and the National Renewable Energy Laboratory (NREL). The development of the DRF includes three main phases: 1) a learning phase involving stakeholder engagement and literature review to synthesize metrics of community readiness to advance through an energy transition and to understand the state of the research and practice of participatory science-policy processes in various sectors, 2) a design phase to define readiness approaches and tools that will be developed as part of the DRF, and 3) an implementation phase to create the applications and interfaces for WPTO and the national laboratories to interact with the DRF. All three phases include close collaboration with communities and end-users of the framework, first to identify gaps in the science and tools needed to achieve community-driven energy transition goals and second, to test and improve the framework iteratively. Through technical assistance programs like ETIPP and utilizing the completed DRF to understand the influencing factors which motivate or deter energy transitions, WPTO hopes to engage a number of near-term marine energy demonstration opportunities. Here we report on the results from the literature review (Subtask 1.1) to inform the stakeholder engagement (Subtask 1.2) and design phase (Task 2) of the project.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

Calculating Dose Release Factors to Obtain the Worst-Case Maximally Exposed Location by Sector

The aim of this project was to update the SRS Dose Release Factors (DRF's) for the Maximally Exposed Individual (MEI) for 20 area release points onsite. To update, potential MEIs now include onsite locations and modeled stack heights were updated to match onsite operations. The DRF's and MEI locations are used to ensure DOE and EPA compliance is met for dose standards. The Environmental Protection Agency (EPA) requires the use of the computer model CAP88 to estimate doses for demonstrating compliance with 40 CFR 61, the National Emission Standard for Hazardous Air Pollutants (NESHAP). The location of the maximally exposed individual (MEI) by sector and distance is required for execution of CAP88. The worst-case sector is the sector and distance where an offsite individual would receive the highest dose due to a potential release from a designated release location at a facility. The worst-case sector analysis addresses potential ground-level and stack-height releases from 20 areas of Savannah River Site (SRS). Weather patterns were analyzed at each of these areas relative to sixteen compass points. The analysis makes use of recently updated distance data and meteorological data. The computer model, CAP88 is EPA's software system used by the Department of Energy (DOE) to calculate the receptor dose due to routine atmospheric releases via a gaussian plume at the Savannah River Site (SRS). The dose-release factors (DRFs) are used to estimate the offsite and onsite dose from facility-specific releases and represent the dose to a receptor exposed to 1 Ci of a specified radionuclide being released into the atmosphere. The DRFs are simply a ratio of the TED to the release rate and, therefore, are directly scalable. The DRF values listed in the Appendix can be applied to expected release values from each area to estimate the potential dose to an individual adult at each location. NESHAP DRFs have been supplied to Environmental Compliance and Area Closure Projects (EC and ACP) for many years and are periodically updated to include changes in Cap88. estimate the potential dose to an individual adult at each location DRF in mrem Ci{sup -1} are estimated by modeling the total effective dose (TED) in mrem yr{sup -1} assuming an annual atmospheric release rate of 1 Ci yr-1 of the associated radionuclides. TED = Effective Dose (ED) + Committed Effective Dose (CED). TED = DRF/RR. Approach and Methods: Determine possible MEI locations Onsite/Offsite including buildings and farms; Determine the distances from the release area to the possible MEI location and the direction from the release to the MEI location; Using the most recent meteorological data (2007-2011) and parameters, run CAP88 for each release area for each compass sector and previously calculated distances to MEI locations using a 1 Ci release rate for tritium; Use the calculated the air concentration values to determine the MEI for each sector from CAP88. The relationship between air concentration and received dose is directly proportional and can be used to determine which locations to calculate DRF's and a dose for an MEI; The DRFs are found for each compass sector from 20 SRS release areas using CAP88-PC Version 4.0; Each location is calculated with ground level releases evaluated for each area for a list of radionuclides, some with and some without progenies; Compare the DRFs of the potential onsite MEIs to offsite MEIs. Based on the 2018 MEI Report, the Site worst case sector MEI is located 593 mW of B-Area. This MEI location represents a point along the main road that travels through a tract of land leased to the SC National Guard. While this location is estimated to have the highest exposure, minimal radioactivity is released from B-Area. In 2017, SRS requested and was approved by the EPA to change the location for modeling site releases from the Center of Site to H-Area, and to use six stack heights. H-Area emission account for approximately 90% of all radioactive operations onsite. The MEI for H-Area was found to be 11,458 m NNE which locates the Savannah River Ecology Lab Conference Center. Comparisons for 2018 data and 2014 shows the new methods of calculation are more conservative yet still remain well below the DOE 100 mrem limit.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Investigation of soil properties using different techniques of mid‐infrared spectroscopy

Summary Diffuse reflectance spectroscopy (DRF), attenuated total reflectance spectroscopy (ATR) and Fourier transform infrared photoacoustic spectroscopy (PAS) are useful techniques that are commonly used to characterize soil properties. Here, these techniques were used to evaluate individual properties of 1456 paddy soil samples from Nanjing, China, to explore their features in the mid‐infrared range. The diffuse reflectance spectroscopy showed broad and shouldered peaks that ranged from 4000 to 500 cm −1 . Attenuated total reflectance spectroscopy produced main peaks around 1000 cm −1 . Fourier transform infrared photoacoustic spectroscopy spectra showed several moderate intensity peaks in the regions of 4000–2600 and 2500–500 cm −1 . The effective variables (wavenumbers) were selected using an uninformative variable elimination (UVE) algorithm to predict soil pH, and soil organic matter (SOM), total nitrogen (TN) and available phosphorus (AP) contents; it used a self‐adaptive partial least squares model (SAM–PLS). The results showed that selected wavenumbers improved the accuracy of prediction for pH, and SOM, TN and AP contents. For the prediction of pH, ATR spectra showed marginally better performance than the other spectra. The DRF spectroscopy was the optimal method for SOM and TN prediction. Available phosphorus contents were predicted poorly by all three spectra. Furthermore, mid‐infrared incident light paths, absorption modes, sensing styles, as well as peak interference and the prediction model, were the main factors that affected the assessment of soil properties in the three types of spectroscopy. Highlights Soil spectra data were measured with DRF, ATR and PAS spectrometers over the range 4000–500 cm −1 . A UVE algorithm was used to select effective wavenumbers from the full spectrum. The pH, SOM, TN and AP were estimated using three techniques based on a SAM–PLS model. Mid‐infrared incident light paths and absorption modes affected prediction performance of the three techniques.

Ma, F.↗
DOE OSTI2019

Empirical Refinement of the GADRAS Detector Response Function

The Gamma Detector Response and Analysis Software (GADRAS) was augmented to enable empirical refinement of the Detector Response Function (DRF) for gamma-ray detectors. This capability is included in GADRAS starting with Version 18.8.2, which was released in February 2019 Empirical refinement enables improved computational accuracy for gamma-ray spectra when detectors exhibit characteristics that are essentially unique to a particular sensor. This report discusses how to perform the empirical refinement, and examples are presented for the following scenarios where empirical refinement is appropriate: Large plastic scintillators, which are generally composed of polyvinyl toluene (PVT), often exhibit low-energy peaks that are not associated with incident gamma rays. Regardless of whether they are artifacts produced by poor light collection or pulse processing methods, accurate spectral synthesis requires replication of these features; Some detectors, particularly those using Silicon Photomultipliers (SiPM), exhibit energy shifts of Compton edges and escape peaks relative to the same scintillator material attached to a photomultiplier tube. Empirical refinement compensates for these effects, which derive from nonlinearities in the detector response; The change in the DRF as a function of displacement of the source relative to the detector axis cannot always be replicated adequately using only the few shielding parameters that are used by the response function. Empirical refinement enables improved accuracy for computation of spectra during linear transits or when the detector is close to a large radiation source. This is a particularly important consideration for collimated detectors; and, Gamma-ray imagers exhibit complex relationships between spectral response and spatial locations. Empirical refinement enables substantial improvement of the DRF accuracy for imagers.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

Investigating the Linear Dependence of Direct and Indirect Radiative Forcing on Emission of Carbonaceous Aerosols in a Global Climate Model

Herein, the relationship between forcing and emission is investigated for black carbon (BC) and primary organic carbon (OC) emitted from North America and Asia. Direct and indirect radiative forcing (DRF and IRF) of BC and OC are simulated with CAM5.1. Two diagnostics are introduced to aid policy-relevant discussions: linearity and emission-normalized forcing. DRF is linearly related to emission for both BC and OC from two regions, and the linear relationship is similar, within 15%. IRF is linear in emissions when emissions are lower and regions are far from sources (North American BC and OC). Indirect radiative forcing is sublinear for strong sources and near-source regions (Asian OC). Emission-normalized IRF in North America is two to four times higher than that in Asia. The difference among regions and species is primarily caused by particle density as high density of BC results in fewer emitted particles and by the processes for accumulation mode particles to become cloud condensation nuclei and then to activate into cloud droplet. Lower emission-normalized IRF in more polluted regions means that reductions of OC in these regions would be relatively climate-neutral rather than causing significant warming via IRF reduction. An optimal aggregation area (30° × 30°) is identified for analysis of the forcing-to-emission relationship. For IRF, only 15–40% of the Earth’s surface is significantly affected by an emission region, but forcing in these regions comprises most of the global impact. Emission-normalized forcing can be used to estimate forcing changes due to emission reductions, as long as causes of nonlinearity are identified and considered.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Numerical convergence and validation of the DIMP inverse particle transport model

The data integration with modeled predictions (DIMP) model is a promising inverse radiation transport method for solving the special nuclear material (SNM) holdup problem. Unlike previous methods, DIMP is a completely passive nondestructive assay technique that requires no initial assumptions regarding the source distribution or active measurement time. DIMP predicts the most probable source location and distribution through Bayesian inference and quasi-Newtonian optimization of predicted detector re-sponses (using the adjoint transport solution) with measured responses. DIMP performs well with for-ward hemispherical collimation and unshielded measurements, but several considerations are required when using narrow-view collimated detectors. DIMP converged well to the correct source distribution as the number of synthetic responses increased. DIMP also performed well for the first experimental validation exercise after applying a collimation factor, and sufficiently reducing the source search vol-ume's extent to prevent the optimizer from getting stuck in local minima. DIMP's simple point detector response function (DRF) is being improved to address coplanar false positive/negative responses, and an angular DRF is being considered for integration with the next version of DIMP to account for highly collimated responses. Overall, DIMP shows promise for solving the SNM holdup inverse problem, especially once an improved optimization algorithm is implemented.

42 ENGINEERING↗
DOE OSTI2018

Source apportionments of aerosols and their direct radiative forcing and long-term trends over continental United States

Due to US air pollution regulations, aerosol and precursor emissions have decreased during recent decades, while changes in emissions in other regions of the world also influence US aerosol trends through long-range transport. We examine here the relative roles of these domestic and foreign emission changes on aerosol concentrations and direct radiative forcing (DRF) at the top of the atmosphere over the continental US. Long-term (1980-2014) trends and aerosol source apportionment are quantified in this study using a global aerosol-climate model equipped with an explicit aerosol source tagging technique. Due to US emission control policies, the annual mean near-surface concentration of particles, consisting of sulfate, black carbon, and primary organic aerosol, decreases by about –1.1 (±0.1) / –1.4 (±0.1) μg m -3 in western US and –3.3 (±0.2) / –2.9 (±0.2) μg m -3 in eastern US during 2010–2014, as compared to those in 1980–1984. Meanwhile, decreases in US emissions lead to a warming of +0.48 (±0.03) / –0.46 (±0.03) W m -2 in western US and +1.41 (±0.07) /+1.32 (±0.09) W m -2 in eastern US through changes in aerosol DRF. Increases in emissions from East Asia generally have a modest impact on US air quality, but mitigated the warming effect induced by reductions in US emissions by 25% in western US and 7% in eastern US. Thus, as US domestic aerosol and precursor emissions continue to decrease, foreign emissions may become increasingly important to radiative forcing over the US.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Atmospheric Radiative and Oceanic Biological Productivity Responses to Increasing Anthropogenic Combustion‐Iron Emission in the 1850–2010 Period

Abstract Anthropogenic emission is an important component of the present‐day iron cycle yet its long‐term impacts on climate are poorly understood. Iron mineralogy strongly affects its radiative and oceanic interactions and was unrepresented in previous studies. We perform simulations using a mineralogy‐based inventory and an atmospheric transport model and estimate the 1850–2010 global mean direct radiative forcing (DRF) to be +0.02 to +0.10 W/m 2 . We estimate that the CO 2 sequestration of 0.2–13 ppmv over the last 150 years due to enhanced phytoplankton productivity by anthropogenic iron deposition causes an avoided CO 2 forcing of −0.002 to −0.16 W/m 2 . While globally small, these impacts can be higher in specific regions; the anthropogenic DRF is +0.5 W/m 2 over areas with more coal combustion and metal smelting, and anthropogenic soluble iron sustains >10% of marine net primary productivity in the high‐latitude North Pacific Ocean, a region vulnerable to stratification due to climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Deployment Readiness Framework Subtask 1.2 Outreach Report: Common Themes Among Clean Energy Transition Technical Assistance Projects

Island and remote coastal communities face an uncertain energy future. These communities build, operate, and maintain energy infrastructure in extremely challenging environments and pay the highest prices for electricity and fuels. Moreover, climate change increasingly affects grid reliability, resiliency, and, ultimately, the cost of energy. Marine energy could address many of the challenges faced by island and remote coastal communities, but these communities often have limited resources and capacity to invest in complex energy and coastal resilience issues. The Deployment Readiness Framework (DRF) is being developed to support community-driven energy transitions in these coastal communities and to better understand the readiness of communities for marine energy demonstration and operation. Led by the National Renewable Energy Laboratory and Pacific Northwest National Laboratory, the DRF builds on the Energy Transitions Initiative Partnership Project (ETIPP) supported in part by the U.S. Department of Energy's Water Power Technologies Office. This report details the results from the stakeholder outreach and engagement effort linked to the previously reported literature review.

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

Safeguards Technology Development Program: FY 2024 Mid-Year Report

This project has 2 major thrusts and 2 minor tasks – One of the major ones is a scoping study for improving uranium isotopics by analyzing higher energy, lower yield U-235 gamma emissions. The second major one benefits past projects such as auto-enrichment, and peak-based analysis routines previously added to GADRAS-DRF [1]. The two minor tasks involve an in-person or remote GADRAS-DRF training for the IAEA, and characterizing detectors of interest.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2024

Uncertainty Quantification in GADRAS Inverse Modeling

The Gamma Detector Response and Analysis Software (GADRAS) package includes an inverse modeling tool that is helpful in identifying characteristics of unknown radioactive materials. Traditionally, uncertainties in this analysis were derived solely from measurement data quality and the fit of synthetic spectra. This paper aims to rigorously quantify additional sources of uncertainty, focusing on uncertainties arising from measurements being analyzed, Detector Response Function (DRF) characterization, and DRF extrapolation. Applying these findings to the BeRPBall benchmark data set, we demonstrated the impact of these uncertainties on plutonium and polyethylene estimates. The results underscore the importance of incorporating diverse uncertainty sources to enhance the accuracy and reliability of GADRAS’s inverse modeling capabilities.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗