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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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948 records · Page 53
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Streamlining Stakeholder Data Accessibility Utilizing Web-Based GIS Capabilities - 18672

Environmental data is often complex, and it can be difficult to provide proper context to fully understand and comprehensively analyze the data. One tool identified to better present complicated data is the use of web-based Geographic Information Systems (GIS). Web-based GIS provides much-needed visual context to the complex data collected at Los Alamos National Laboratory (LANL). By overlaying environmental data atop relevant geographical features, such as topography, surface or subsurface geology, hydrogeological features, buildings, roads, and technical areas, LANL's diverse group of stakeholders are better able to understand environmental data collected at the LANL site within the framework of the surrounding geography. Since 2012, Los Alamos has utilized a web-based GIS module in the Intellus New Mexico data-sharing web site. This web site provides unfettered public access to LANL and New Mexico Environment Department (NMED) - Department of Energy (DOE) Oversight Bureau environmental data. Through the past five years of real world experience, LANL identified areas where questions and confusion arose, particularly for those not directly associated with the site's environmental cleanup mission. In order to query the millions of records in Intellus in a meaningful way, users had to have substantial knowledge of the data organization and nomenclature ahead of time. While this was not a challenge for LANL and NMED environmental scientists, it proved to be a substantial barrier for members of the general public to utilize Intellus. In 2017, LANL initiated an Intellus redesign with the goal of deconstructing the type of questions people asked and identifying the types of user personas accessing the site to engineer a simpler path to desired data sets. Greatly simplified click paths ('Quick Paths') were created that walk the user through the basics with a minimum of jargon and a strong reliance on mapping results for easy visualization. The improved mapping was enabled by an upgraded online GIS functionality that allowed LANL to easily integrate their own base-maps to provide users the most up to date views of their data. The integrated Intellus GIS was enhanced to assimilate with LANL's dynamic base maps and site information in relation to data collection activities, to avoid outdated presentations. A simplified user interface (UI) was added and easier data querying was designed. A more robust visual presentation was created that allowed better viewing of spatial data. All data queries in the new simplified 'Quick Path' give the users the option to map the results and save their results to their optional accounts. This brings the power of GIS visualization to all users without the need for GIS knowledge or extensive training. By integrating with Esri{sup R} technologies, base-map layers in ArcGIS Online{sup R} can be updated by LANL or other data providers at any time and reflected immediately in the Intellus mapping application called GIS+ 1. Users can even load additional map layers to GIS+ that contain their own spatial data or information shared from over a million users on ArcGIS Online{sup R}, such as ecological information from the Fish and Wildlife Service, or geology layers from the USGS. The results from the improved quick path search in Intellus can be viewed in GIS+ and analyzed using Esri's{sup R} Smart Mapping technology, which makes it easy to classify results with its visual representation of the results in an interactive histogram, where sliders can be dragged to look at various intervals for each color range for that query. With enhanced GIS+, Los Alamos National Laboratory is able to observe improve Stakeholder engagement and positive Stakeholder interactions within its public environmental database, Intellus New Mexico. (authors)

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

Proposed Muon Radiography Method for Spent Fuel Cask Interrogation

Multiple scattering muon radiography is a technique that was developed at Los Alamos National Laboratory (LANL) to detect high Z material using cosmic ray muons as a radiation source. As a result,there has been considerable interest in using the technique to radiograph nuclear waste inside of storage casks. Recently,the technique has been used to interrogate the inside of a MC-10 dry fuel cask at Idaho National Laboratory (INL).This is the only technique that has been successful in imaging the interior of a spent fuel cask.The measurement was performed with the LANL Mini Muon Tracker (MMT), composed of two super-modules of drift tubes and readout electronics placed on each side of the fuel cask. The final result was a one dimensional histogram (projection) that showed areal scattering density within the cask binned according to horizontal position within the cask. While successful, the MMT is not designed for an optimal measurement of a fuel cask. The MMT only covers a limited solid angle around the cask and needs to be orientated so as to be aligned with the grid of stored fuel bundles. Even when properly aligned, the resulting areal scattering density projection indicates that a fuel bundle within a column is missing, but is ambiguous as to which row is lacking the fuel bundle. This paper discusses a potential new detector and analytical technique that may be used to better radiograph the nuclear material inside of a storage cask. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

An improved methodology to determine pore size distribution and pore density in the high burnup structure

The formation of the high burnup structure (HBS) on the peripheral region of the light water reactor (LWR) UO{sub 2} fuel pellet is characterized by a steep increase in porosity. The newly formed micron-size intergranular pores trap most of the created fission gas. The study of the pore size distribution and its evolution with burnup is fundamental to estimate the fission gas pressure in the pores and can influence the burst release in accidental conditions. Quantitative image analysis is usually employed to quantify the pore size-distribution. It is determined mainly in two dimension (2D) using a histogram. Few attempts have been made in the past to derive also three-dimensional (3D) pore size-distribution employing the Schwartz-Saltykov (ScSa) method. In this work, we determine experimentally the pore size-distribution in the HBS and apply a new procedure to determine the distribution, both in 2D and 3D. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Determining Cs-137 Background body burdens for Wild Pigs At Savannah River Site

Savannah River Site (SRS) is a unique U.S. Department of Energy facility in that most of the 310-square miles of land has not be industrialized since operations began in 1953. This has allowed abundant, undisturbed vegetation structure to exists as well as an increase in herd sizes among wildlife populations onsite. Cs-137 is widespread across SRS due to the production of nuclear materials, but is mostly from global atmospheric fallout from nuclear weapons testing. Due to most of SRS being undisturbed land, the concentrations of Cs-137 are higher on site than off site. The SRS began conducting annual deer harvests that were open to the public beginning in 1965. All animals harvested during these hunts are monitored for Cs-137, which is measured using a Sodium Iodide detector. There has been an effective method for calculating the background Cs-137 body burden for the deer population at the SRS, developed by Gaines and Novak using data collected during hunts and gamma overflight data to determine the areas contaminated by site activities. For animals that have a Cs-137 concentration above the established background level, a dose is assigned to the hunter. By applying the same method for wild pigs using data collected from hunts, gamma overflight, and developing a site-specific home range of wild pigs, we were able to calculate the Cs-137 background body burden concentrations of wild pigs on site. Objectives: Develop site-specific home range for wild pigs at SRS; Determine the average concentrations of Cs-137 in wild pigs from background; Use Gaines and Novak method for determining background Cs-137 body burdens wild pigs on SRS. Methods and Materials: Development of site-specific home range of wild pigs was determined to be 2.5 miles using: Four studies conducted between 1969 and 1992 for the SRS wild pig population. (Mayer and Brisbin) The background compartments were determined using: Gamma overflight data showing contaminated areas; Site-specific home range of the wild pigs. Results and Conclusion: All data were generated through the JMP software to provide a histogram and summary statistics. The estimate of an upper tolerance limit for the background contamination with 95% confidence is 1.965 pCi/g for the wild pigs. This means that for wild pigs on SRS from the background compartments are expected to have Cs-137 concentrations of less than 1.965 pCi/g. The current background for the deer is 2.59 pCi/g. For the background compartments Cs-137 concentrations from 2012-2018: Mean: 0.815 pCi/g, Maximum: 2.341 pCi/g, Minimum: -0.704 pCi/g.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2014

A Grid Intensity Map-Based Source Model for Monte Carlo Modeling of IMRT Field Irradiation - Paper 5

An accurate source model is important for TPS (Treatment Planning System) dose calculation and verification, especially for IMRT (Intensity Modulated Radiotherapy) irregular and inhomogeneous fields. Monte Carlo simulation is the most accurate way to calculate dose distributions in the heterogeneous media like human bodies. A full radiotherapy modeling generally includes Linac modeling and phantom dose calculation. Full Linac modeling is very time-consuming and requires highly detailed knowledge of the accelerator composition and structure, however, which is very difficult to obtain for commercial interests. Often all relevant parameters are not known with sufficient accuracy, and thus a time-consuming tuning of e.g. the electron beam spot size and energy must be performed. A multiple source model (MSM) regards particles coming from different parts of an accelerator as if they are coming from different virtual sources. MSM uses a set of virtual sources representing the treatment beam (e.g. primary photons, head scatter, electron contamination) by a set of analytic functions or histograms with parameters derived from dosimetric measurements or a full MC simulation. Tillikainen et al built a three sub-source model by matching with measurement data using an automatic process to optimize the free model parameters for a Varian 2100 C/D accelerator. Lin et al have built a convenient five-photon-sub-source model for Varian 2300C 6 MV-X beam based on Monte Carlo simulated Linac for ARTS (Accurate Radiotherapy System). The particle generation of MSM is very fast compared to full Linac simulation, and its sampling efficiency is not limited by the size of the phase space file (PSF). However, generally MSM is generated based on regular field PSF and needs an irregular component to form the beam shape meanwhile apt to bringing error Linac modeling and MSM producing from PSF analysis actually both are multi-freedom optimization process by adjusting several parameters (e.g. electron energy and angular divergence). Linac modeling adjusts its parameters from the beginning of electron hitting target through all components to fit the simulation to the measurement. MSM tunes its PSF-derived parameters by optimizing to minimize the deviations between the simulation and the measurement. Since the full Linac modeling and the MSM model both need to fine tune their parameters to match the simulation to the measurement, and sometimes maybe offsets the real accelerator for its multi-parameter optimization process. So, why not fine tune directly all source model parameters just behind all Linac components to fit the simulation to the measurement? A grid intensity-based surface source model was suggested here, which assumed the particle emitting from the bottom surface of Linac last beam trimmer MLC (Multi Leaf Collimator). The particle emitting position is sampled on the grid intensity map optimized by TPS, and the particle weight is adjusted by its original grid intensity. This source model not only takes advantage of the Monte Carlo method in the heterogeneous media, but also avoids effectively the transportation speed shortcoming of Monte Carlo simulation through Linac components. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2026

HDSense: An efficient method for ranking observable sensitivity

Identifying which observables most effectively constrain model parameters can be computationally prohibitive when considering full likelihoods of many correlated observables. This is especially important for, e.g., hadronization models, where high precision is required to interpret the results of collider experiments. We introduce the High-Dimensional Sensitivity (HDSense) score, a computationally efficient metric for ranking observable sets using only one-dimensional histograms. Derived by profiling over unknown correlations in the Fisher information framework, the score balances total information content against redundancy between observables. We apply HDSense to rank a set observables in terms of their constraining power with respect to five parameters of the Lund string model of hadronization implemented in Pythia using simulated leptonic collider events at the $Z$ pole. Validation against machine-learning--based full-likelihood approximations demonstrates that HDSense successfully identifies near-optimal observable subsets. The framework naturally handles data from multiple experiments with different acceptances and incorporates detector effects. While demonstrated on hadronization models, the methodology applies broadly to generic parameter estimation problems where correlations are unknown or difficult to model.

Assi, Benoît [Cincinnati U.] (ORCID:00000003092433↗
DOE OSTI2026

Computing the Critical Temperature of the Affine-Transformed $D=3$ Ising Model Using Masked Autoregressive Flow

The simple Ising model provides a rich environment to build and study lattice field theories. As part of an ongoing project to construct a conformal field theory (CFT) on an arbitrarily curved manifold, in this work we develop methods to measure the critical temperature $β_c$ of the affine-transformed Ising model on the face-centered cubic (FCC) lattice. The main challenge in this endeavor is finding a computationally efficient and accurate method of interpolating and extrapolating Monte Carlo observables with respect to coupling coefficients and temperature. Herein, we compare two such methods. A traditional statistical approach uses the multiple histogram (MH) method, while a newer machine learning approach uses a masked autoregressive flow (MAF) to estimate the underlying probability density function of a set of observables. While the MH method is specifically designed to interpolate and extrapolate Monte Carlo observables, we find that MAF is a viable alternative for measuring $β_c$ with a computational cost that scales more favorably. Furthermore, we comment on additional advantages of MAF relevant to our work, such as extrapolating in system volume.

Svenson, Kai [Texas U.]↗
DOE OSTI2021

Monte Carlo simulations for water adsorption in porous materials: Best practices and new insights

Technologies based on water adsorption such as water harvesting from air have tremendous potential in mitigating important global crises such as water scarcity. An important challenge to the deployment of such technologies is finding optimal adsorbent materials. Given the large materials space of available adsorbents, large-scale computational screening can be extremely helpful for this task. This work explores the methods and details associated with such screening procedures and recommends best practices. We also shed light on the limitations of traditionally used and inexpensive to compute prescreening approaches involving geometric and energetic features to predict water adsorption behavior of porous materials. Such approaches can provide general trends to predict adsorption behavior but may lead to the overlook of potentially important structures due to the complex nature of water adsorption. Finally, this study offers insights for future water adsorption simulations to facilitate the development of optimal water adsorbents.

42 ENGINEERING↗
DOE OSTI2023

Integrated Ion-Exchange Membrane Resin Wafer Assemblies for Aromatic Organic Acid Separations Using Electrodeionization

Aromatic acids, such as p-coumaric acid, are valuable chemical intermediates that are used in the specialty chemical industries because they are precursors to phenylpropanoid compounds. The separation of p-coumaric acid from fermentation broths is a critical step in the biochemical production process and more broadly the circular carbon economy. Electrodeionization (EDI) has been applied toward separations of low-carbon chain acids, but purifying p-coumaric acid has been challenging due to fouling and irreversible binding with ion-exchange membranes and resins. Here, we report a new membrane wafer assembly (MWA) consisting of laminated ion exchange membranes to porous ionomer-binder resin wafers for EDI. The MWAs in an EDI stack showed a 7-fold increase in p-coumaric acid capture while also using 70% less specific energy consumption when benchmarked against state-of-the-art resin wafer EDI modules. The more efficient p-coumaric acid recovery was ascribed to (i) the 38% reduction in interfacial transport resistance between the membrane and resin wafer and (ii) using imidazolium anion exchange membranes and ionomer binders in the MWA. MD simulations revealed enhanced transport rates for p-coumarate in imidazolium ionomers through π–π interactions. As a result, adopting the new MWA significantly reduced the amount of ion-exchange membranes in EDI and may lead to drastic capital cost savings.

42 ENGINEERING↗
DOE OSTI2016

Response Variability in Commercial MOSFET SEE Qualification

Single-event effects (SEE) evaluation of five different part types of next generation, commercial trench MOSFETs indicates large part-to-part variation in determining a safe operating area (SOA) for drain-source voltage (V DS ) following a test campaign that exposed >50 samples per part type to heavy ions. These results suggest a determination of a SOA using small sample sizes may fail to capture the full extent of the part-to-part variability. An example method is discussed for establishing a Safe Operating Area using a one-sided statistical tolerance limit based on the number of test samples. Finally, burn-in is shown to be a critical factor in reducing part-to-part variation in part response. Implications for radiation qualification requirements are also explored.

43 PARTICLE ACCELERATORS↗
DOE OSTI2019

Visualizing Hierarchical Performance Profiles of Parallel Codes Using CallFlow

Calling context trees (CCTs) couple performance metrics with call paths, helping understand the execution and performance of parallel programs. To identify performance bottlenecks, programmers and performance analysts visually explore CCTs to form and validate hypotheses regarding degraded performance. However, due to the complexity of parallel programs, existing visual representations do not scale to applications running on a large number of processors. In this work, we present CallFlow, an interactive visual analysis tool that provides a high-level overview of CCTs together with semantic refinement operations to progressively explore CCTs. Using a flow-based metaphor, we visualize a CCT by treating execution time as a resource spent during the call chain, and demonstrate the effectiveness of our design with case studies on large-scale, production simulation codes.

97 MATHEMATICS AND COMPUTING↗