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All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Used Nuclear Fuel-Storage, Transportation & Disposal Analysis Resource and Data System (UNF-ST&DARDS) 4.x

A new, integrated data and analysis system has been designed to simplify and automate the performance of accurate and efficient evaluations for characterizing the input to the overall waste management system-UNF-Storage, Transportation & Disposal Analysis Resource and Data System (UNF-ST&DARDS). A relational database has been assembled to provide a standard means by which UNF-ST&DARDS can succinctly store and retrieve M&S parameters for specific SNF analysis. Users can import SNF data into this database for user-specific analysis. A library of various analysis model templates provides the ability to communicat the various set of M&S parameters to the most appropriate M&S application. A process manager facilitates performance of actual, as-loaded, assembly-specific and cask-specific evaluations. Interactive visualization capabilities facilitate data analysis and results interpretation.

Banerjee, Kaushik↗
DOE OSTI2013

Disposal Systems Evaluation Framework DSEF User Manual (V.3.0)

The Disposal Systems Evaluation Framework (DSEF) has been developed at Lawrence Livermore National Laboratory (LLNL) to formalize and facilitate the development and documentation of repository conceptual design options for a range of waste forms, geologic environments, repository design concepts, and repository operating modes. DSEF is one component of the Engineered Barrier System (EBS) family of work packages at several national laboratories led by Sandia National Laboratories (SNL), in support of the DOE Office of Nuclear Energy, specifically of the Used Fuel Disposition (UFD) Campaign within the Office of Used Nuclear Fuel Disposition Research and Development (NE-53). DSEF is a knowledge management system that allows the user to intelligently access and draw data from a case library of hundreds of completed thermal analyses (currently 721 cases in the library), and draw input from databases of material properties and repository development cost data (currently the data in these databases are drawn from more than 100 references). The core functionality of DSEF is provided by a Microsoft Office Excel 2010 workbook with macros and form controls that create a structured environment and walk the user through the steps of creating the input data required to perform disposal system evaluations internally and by interfacing with external programs. The user can choose to work with built-in data from the case library of previous analysis cases, from the material property databases, or can define their own input descriptions and data. DSEF uses the Excel worksheet protection (implemented on a sheet by sheet basis) to prevent inadvertent over-writing of formulas with data. When worksheet protection is enabled, the user can see all underlying formulas, and enter data in unprotected cells (the unprotected cells generally correspond to the yellow highlighted cells). Worksheet protection also prevents restructuring the files (adding or deleting rows or columns) and changing the formatting, as well as preventing access to the Visual Basic Editor to prevent modification of the macros. If the user needs to modify the worksheet structure, formulas, or macros, they can contact LLNL to get the password to unprotect the worksheets. However, care should be taken in making any modifications, since the macros and formulas are dependent in some cases on the current structure, range names, and macro subroutines DSEF is set up to retrieve the results of external thermal analysis program runs, summarize them graphically, and provide a template for adding the new results to the Case Library. The Case Library worksheet in DSEF is set up to create a Case Library data record for each new analysis case, at the top of the list of prior cases. Therefore, a separate DSEF file (with unique name) should be saved for each run that is to be archived. Users should submit a copy of their DSEF files to LLNL so that their results can be added to the overall Case Library and made available to other laboratories and stakeholders. LLNL will maintain the DSEF Case Library and make the most current files available on the SNL SharePoint site. The Revision History sheet documents the file evolution. One of the key objectives of DSEF is to allow the user to compare the results of thermal analyses to the thermal constraints of the design components. These comparisons can then be used to consider design, layout, and operating mode modifications to find combinations that can meet the thermal constraints for a given combination of waste form, geologic medium, surface storage time, and system concept of operation.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

Sustainable network design for multi-purpose pellet processing depots under biomass supply uncertainty

This work develops a two-stage stochastic mixed-integer programming model to manage multi- purpose pellet processing depots under feedstock supply uncertainty. The proposed optimization model would help to minimize cost and to mitigate emissions from the supply chain network. We consider three alternative Biomass Processing and Densi cation Depot (BPDD) technologies; namely, conventional pellet processing, high moisture pellet processing, and ammonia ber expansion. These three technologies pre-process/pre-treat and densify different types of biomass into more highly densi ed intermediate products for different markets in order to improve movability and overall supply network performance in terms of costs and emissions. A hybrid decomposition algorithm was developed that combines sample average approximation with an enhanced Progressive Hedging (PH) algorithm to solve this challenging NP -hard problem. Some heuristics such as Rolling Horizon (RH) heuristic, variable xing technique were later applied to further enhance the PH algorithm. Mississippi and Alabama were selected as a testing ground and ArcGIS was employed to visualize and validate the modeling results. The results of the analysis reveal promising insights that could lead to recommendations to help decision makers achieve a more cost-effective environmentally-friendly supply chain network.

09 BIOMASS FUELS↗
DOE OSTI2023

ZeoNet: 3D convolutional neural networks for predicting adsorption in nanoporous zeolites

Zeolites are one of the most widely used materials in the chemical industry due to their nanometer-sized pores that can adsorb and react upon molecules selectively. With hundreds of known framework topologies and hundreds of thousands of computationally predicted structures, the ability to rapidly predict zeolite performance allows researchers to prioritize their efforts on the most promising structures for a given application. Although the accuracy of forcefield-based atomistic simulations has advanced significantly in the past two decades, these simulations can be computationally expensive, especially for long-chain, complex molecules. Here, we present ZeoNet, a representation learning framework using convolutional neural networks (ConvNets) and 3D volumetric representations for predicting adsorption in zeolites. ZeoNet was trained on the task of predicting Henry's constants for adsorption, k H , of n-octadecane in more than 330 000 known and predicted zeolite materials. Employing a 3D grid based on the distances to solvent-accessible surfaces, a volumetric representation that can be generated efficiently, the best-performing ZeoNet achieved a correlation coefficient r 2 = 0.977 and a mean-squared error MSE = 3.8 in ln k H , which corresponds to an error of 9.3 kJ mol -1 in adsorption free energy. In comparison, a model based on hand-designed geometric features has values of r 2 = 0.783 and MSE = 35.7. ZeoNet is also relatively efficient and can process ≈8 structures per second on an Nvidia RTX 2080TI GPU, orders of magnitude faster than forcefield-based simulations. A systematic analysis was conducted to investigate how the choice of ConvNet architectures, the linear dimension (L) and spatial resolution (Δd) of the distance grids, batch size, optimizer, and learning rate impact the model performance. We found that ConvNets based on the ResNet architecture offer the best tradeoff between expressiveness and efficiency. The performance for all models reaches a plateau at L = 30–45 Å and depends less sensitively on grid resolution, with a small benefit around Δd = 0.30–0.45 Å. Finally, saliency maps were visualized to identify which regions of the materials contributed the most to model predictions. It was found, interestingly, that the predictions are driven primarily by the accessible pore volume rather than the region occupied by the framework atoms.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Localization and Quantification of Trace-gas Fugitive Emissions Using a Portable Optical Spectrometer

We present a portable optical spectrometer for fugitive emissions monitoring of methane (CH4). The sensor operation is based on tunable diode laser absorption spectroscopy (TDLAS), using a 5 cm open path design, and targets the 2ν3 R(4) CH4 transition at 6057.1 cm-1 (1651 nm) to avoid cross-talk with common interfering atmospheric constituents. Sensitivity analysis indicates a normalized precision of 2.0 ppmv∙Hz-1/2, corresponding to a noise-equivalent absorption (NEA) of 4.4×10-6 Hz-1/2 and minimum detectible absorption (MDA) coefficient of αmin = 8.8×10-7 cm-1∙Hz-1/2. Our TDLAS sensor is deployed at the Methane Emissions Technology Evaluation Center (METEC) at Colorado State University (CSU) for initial demonstration of single-sensor based source localization and quantification of CH4 fugitive emissions. The TDLAS sensor is concurrently deployed with a customized chemi-resistive metal-oxide (MOX) sensor for accuracy benchmarking, demonstrating good visual correlation of the concentration time-series. Initial angle-of-arrival (AOA) results will be shown, and development towards source magnitude estimation will be described.

03 NATURAL GAS↗
DOE OSTI2016

TU-H-CAMPUS-TeP1-04: Novel 3D Printed Plastic Cutouts Filled with Aluminum Oxide for Same Day Electron Radiotherapy

Purpose: Clinics that outsource electron cutout manufacturing may be unable to simulate and treat patients on the same day. To enable same day treatment, we investigate the use of 3D printed hollow cutouts filled with 30 grit Al{sub 2}O{sub 3} powder. We verified the dosimetric equivalence of such a cutout relative to an outsourced Copper cutout. Methods: Printing was performed using a Ultibots Kossel 250 V-Slot 3D printer and polylactic acid filament. Printing files were derived from an in-house 3D model designed to mate with a Varian 6 cm electron cone. Relative to conventional cutouts (Copper or Cerrobend), the height of the hollow plastic cutout was extended by 1.0 cm to increase attenuation. Measurements were performed for 6 MeV in solid water at dmax (1.4 cm) with Gafchromic™ EBT3 film; the cutout was kidney-shaped with a long and short axis of approximately 5 and 2 cm, respectively. The Copper cutout was based on an outline of the 3D printed cutout.A calibration film was exposed immediately after the electron irradiations. All films, including an un-irradiated one, were from the same batch. Films were scanned on an Epson 10000XL flatbed scanner. Film analysis was performed in DoseLab (MOBIUS Medical Systems, Houston, Tx). Results: Visual comparison of the physical cutouts revealed that the Copper cutout had a slightly smaller opening than the printed cutout. Line profiles through the registered films indicated agreement within 5% in the open section. 99.9% of pixels passed gamma analysis with 2% local percent difference, 2 mm DTA, and a 25% threshold. Conclusion: Same day simulation and treatment with electrons is feasible with 3D printing of a hollow cutout filled with Al{sub 2}O{sub 3}. Future work will include evaluations of additional cutout shapes at different depths for higher energies. Other printing materials, such as bismuth, are being tested.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Water Network Tool for Resilience (WNTR). User Manual, Version 0.2.3

The Water Network Tool for Resilience (WNTR, pronounced winter) is a Python package designed to simulate and analyze resilience of water distribution networks. Here, a network refers to the collection of pipes, pumps, valves, junctions, tanks, and reservoirs that make up a water distribution system. WNTR has an application programming interface (API) that is flexible and allows for changes to the network structure and operations, along with simulation of disruptive incidents and recovery actions. WNTR is based upon EPANET, which is a tool to simulate the movement and fate of drinking water constituents within distribution systems. Users are encouraged to be familiar with the use of EPANET and/or should have background knowledge in hydraulics and pressurized pipe network modeling before using WNTR. EPANET has a graphical user interface that might be a useful tool to facilitate the visualization of the network and the associated analysis results. Information on EPANET can be found at https://www.epa.gov/water-research/epanet. WNTR is compatible with EPANET 2.00.12 [Ross00]. In addition, users should have experience using Python, including the installation of additional Python packages. General information on Python can be found at https://www.python.org/.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Theoretical study of chromophores for biological sensing: Understanding the mechanism of rhodol based multi-chromophoric systems

Development of two-photon fluorescent probes can aid in visualizing the cellular environment. Multi-chromophore systems display complex manifolds of electronic transitions, enabling their use for optical sensing applications. Time-Dependent Density Functional Theory (TDDFT) methods allow for accurate predictions of the optical properties. These properties are related to the electronic transitions in the molecules, which include two-photon absorption cross-sections. We use TDDFT to understand the mechanism of aza-crown based fluorescent probes for metals sensing applications. Here our findings suggest changes in local excitation in the rhodol chromophore between unbound form and when bound to the metal analyte. These changes are caused by a charge transfer from the aza-crown group and pyrazol units toward the rhodol unit. Understanding this mechanism leads to an optimized design with higher two-photon excited fluorescence to be used in medical applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Dual wavelength imaging of a scrape-off layer in an advanced beam-driven field-reversed configuration

A dual wavelength imaging system has been developed and installed on C-2U to capture 2D images of a He jet in the Scrape-Off Layer (SOL) of an advanced beam-driven Field-Reversed Configuration (FRC) plasma. The system was designed to optically split two identical images and pass them through 1 nm FWHM filters. Dual wavelength images are focused adjacent on a large format CCD chip and recorded simultaneously with a time resolution down to 10 μs using a gated micro-channel plate. The relatively compact optical system images a 10 cm plasma region with a spatial resolution of 0.2 cm and can be used in a harsh environment with high electro-magnetic noise and high magnetic field. The dual wavelength imaging system provides 2D images of either electron density or temperature by observing spectral line pairs emitted by He jet atoms in the SOL. A large field of view, combined with good space and time resolution of the imaging system, allows visualization of macro-flows in the SOL. First 2D images of the electron density and temperature observed in the SOL of the C-2U FRC are presented.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

Lithium metal stripping beneath the solid electrolyte interphase

Lithium stripping is a crucial process coupled with lithium deposition during the cycling of Li metal batteries. Lithium deposition has been widely studied, whereas stripping as a subsurface process has rarely been investigated. Here we reveal the fundamental mechanism of stripping on lithium by visualizing the interface between stripped lithium and the solid electrolyte interphase (SEI). We observed nanovoids formed between lithium and the SEI layer after stripping, which are attributed to the accumulation of lithium metal vacancies. High-rate dissolution of lithium causes vigorous growth and subsequent aggregation of voids, followed by the collapse of the SEI layer, i.e., pitting. We systematically measured the lithium polarization behavior during stripping and find that the lithium cation diffusion through the SEI layer is the rate-determining step. Nonuniform sites on typical lithium surfaces, such as grain boundaries and slip lines, greatly accelerated the local dissolution of lithium. As a result, the deeper understanding of this buried interface stripping process provides beneficial clues for future lithium anode and electrolyte design.

25 ENERGY STORAGE↗
DOE OSTI2022

Efficient Clustering of Software Vulnerabilities using Self Organizing Map (SOM)

The common vulnerabilities and exposures (CVE) database was created with a mission to ``identify, define, and catalog publicly disclosed cybersecurity vulnerabilities''. This rich body of information can be used to enable rapid and efficient response to secure and defend cyber operations and protect critical cyber infrastructure. The main goal of this paper is to develop a visual analytics tool to enable deep analysis of CVEs using unsupervised clustering techniques. We enhance our analysis by first mapping CVEs to hierarchical-classes in Common Weakness Enumeration (CWE) using information in the National Vulnerability Database (NVD). Both the mapping and the numerical representation of CVEs are enabled by V2W-BERT, which uses natural language processing of the extensive information in NVD to generate a large tabular database of 137,226 CVE entries from 1999 to 2020, where each CVE is represented by a vector of 768 numerical features. The vectorized data is processed by Self-Organizing Maps (SOM), which is an unsupervised machine learning technique for dimensionality reduction, visual representation and clustering. Using a Torus map of 6417 units, we achieve ~10-fold data compression of ~140k CVEs using SOM. The trained map is further clustered using standard K-means clustering into 138 clusters of CVEs. We conducted a brief investigation of the rich mapping of CVEs to best-matching-units to K-means clusters, as well as CVEs to CWEs. For example, this novel mapping provided insight into the role of CWE-59 and CWE-264 in several CVEs that is otherwise hard to explore in the original data. We conclude that our this novel approach will not only enable deep analysis of the complex relationships between CVEs and CWEs, but also a mechanism to quickly respond to and design mitigation actions for rapidly evolving vulnerabilities that have not been mapped to existing CWEs.

Panchal, Khyati↗
DOE OSTI2025

Advanced Model Development for Large Eddy Simulation of Oxy-Combustion and Supercritical Carbon Dioxide Power Cycles

A joint experimental and numerical study is performed to observe the characteristics of a supercritical carbon dioxide turbulent mixing layer in the presence of strong nonlinearities in the thermodynamic and transport properties. A bespoke experimental setup is designed and employed for this purpose and provides insight into macroscopic mixing behavior. The mixing is experimentally observed using two techniques: shadowgraphy and spontaneous Raman scattering. Qualitative and quantitative intensity fields obtained via these techniques yield instantaneous and mean density data. Spanwise temperature data is also collected using analogue resistance temperature detectors. These measurements are used to quantify the level of mixed material within the field. The experimental data are supplemented by a companion high-fidelity numerical study. The numerical results are obtained through fully resolved, three-dimensional direct numerical simulation. The numerical dataset permits observation of the near-field mixing characteristics, which are difficult to measure experimentally due to the rapid dynamics and sharp thermophysical gradients in this area. Qualitative field visualizations are presented, followed by quantitative mixed material results and observations regarding thermodynamic property trends at select locations within the field. One-dimensional spectra of the turbulent kinetic energy and solenoidal dissipation are provided to observe the spectral characteristics of the flow. Reynolds stress anisotropy is analyzed graphically through anisotropy invariance maps (Lumley triangles). The mixing quantification, spectral data and anisotropy analysis of a flow at these thermodynamic conditions represent the main outcomes of the work.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2022

Visualization of defect induced in-gap states in monolayer MoS 2

Atomic-scale intrinsic defects play a key role in controlling functional electronic properties of two-dimensional (2D) materials. Here, we present a low-temperature scanning–tunneling microscopy and spectroscopy investigation of a common point-defect in monolayer molybdenum disulfide (MoS 2 ). We employ a sample preparation method in which the film surface is never exposed to air so that the native dangling bonds surrounding the defects in the film are preserved. Molybdenum vacancies are identified by their three characteristic in-gap resonances by combining scanning–tunneling measurements with parallel Green’s function-based theoretical modeling. The relative energy shifts between the various in-gap states allow us to identify a relative charge difference between two of the observed vacancies. The role of the substrate on the band structure of the defective MoS 2 monolayer is unveiled. Our study highlights the effects of the substrate on the in-gap states of common defects found in MoS 2 providing a pathway in designing and optimizing 2D materials for electronic applications.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Designs for Risk Evaluation and Management

The Designs for Risk Evaluation and Management (DREAM) tool was developed as part of the effort to quantify the risk of geologic storage of carbon dioxide (CO 2 ) under the U.S. Department of Energy's National Risk Assessment Partnership (NRAP). DREAM is an optimization tool created to identify optimal monitoring schemes that minimize the time to first detection of CO 2 leakage from a subsurface storage formation. DREAM acts as a post-processer on user-provided output from subsurface leakage simulations. While DREAM was developed for CO 2 leakage scenarios, it is applicable to any subsurface leakage simulation of the same output format. The DREAM tool is comprised of three main components: (1) a Java wizard used to configure and execute the simulations, (2) a visualization tool to view the domain space and optimization results, and (3) a plotting tool used to analyze the results. A secondary Java application is provided to aid users in converting common American Standard Code for Information Interchange (ASCII) output data to the standard DREAM hierarchical data format (HDF5). DREAM employs a simulated annealing approach that searches the solution space by iteratively mutating potential monitoring schemes built of various configurations of monitoring locations and leak detection parameters. This approach has proven to be orders of magnitude faster than an exhaustive search of the entire solution space. The user's manual illustrates the program graphical user interface (GUI), describes the tool inputs, and includes an example application.

(Ruprecht) Yonkofski, Catherine↗
DOE OSTI2018

Guide to Nondestructive Evaluation Techniques

Nondestructive evaluation (NDE), alternately known as nondestructive examination (NDE), (commonly used within the nuclear industry), nondestructive testing (NDT) (commonly used in the aerospace and petrochemical industry), and nondestructive inspection (NDI) (commonly used within the military), are as the name implies test and assessment technologies designed to detect and characterize components without damaging or compromising the component’s ability to perform its design function. The most common application is detection of flaws caused either by manufacturing anomalies, service or environmental stresses, or natural material aging. More generally, applications may include estimation of mechanical and material properties, stress/strain, and dynamic response behavior. Post-manufacturing inspections frequently enjoy unfettered access to the component or part that may allow more thorough examinations, while in-service examinations after components have been in use may impose severe access limitations for in-situ testing. If flaws are detected, they must then be evaluated relative to their size, location, growth rate, growth mechanism, and likelihood that they are or will become a liability to the component’s function or performance. NDE is comprised of a large family of specific test disciplines including visual inspection, dimensional metrology, ultrasound, radiography, penetrant test, magnetic particle test, leak test, eddy current tests, potential drop tests, flash and vibro thermography, shearography, acoustic emissions, and many other methods. This section provides discussion on general NDE science and considerations for specific technique selection.

nondestructive, examination, inspection, NDE, NDT↗
DOE OSTI2015

SU-E-J-158: Audiovisual Biofeedback Reduces Image Artefacts in 4DCT: A Digital Phantom Study

Purpose: Irregular breathing motion has a deleterious impact on 4DCT image quality. The breathing guidance system: audiovisual biofeedback (AVB) is designed to improve breathing regularity, however, its impact on 4DCT image quality has yet to be quantified. The purpose of this study was to quantify the impact of AVB on thoracic 4DCT image quality by utilizing the digital eXtended Cardiac Torso (XCAT) phantom driven by lung tumor motion patterns. Methods: 2D tumor motion obtained from 4 lung cancer patients under two breathing conditions (i) without breathing guidance (free breathing), and (ii) with guidance (AVB). There were two breathing sessions, yielding 8 tumor motion traces. This tumor motion was synchronized with the XCAT phantom to simulate 4DCT acquisitions under two acquisition modes: (1) cine mode, and (2) prospective respiratory-gated mode. Motion regularity was quantified by the root mean square error (RMSE) of displacement. The number of artefacts was visually assessed for each 4DCT and summed up for each breathing condition. Inter-session anatomic reproducibility was quantified by the mean absolute difference (MAD) between the Session 1 4DCT and Session 2 4DCT. Results: AVB improved tumor motion regularity by 30%. In cine mode, the number of artefacts was reduced from 61 in free breathing to 40 with AVB, in addition to AVB reducing the MAD by 34%. In gated mode, the number of artefacts was reduced from 63 in free breathing to 51 with AVB, in addition to AVB reducing the MAD by 23%. Conclusion: This was the first study to compare the impact of breathing guidance on 4DCT image quality compared to free breathing, with AVB reducing the amount of artefacts present in 4DCT images in addition to improving inter-session anatomic reproducibility. Results thus far suggest that breathing guidance interventions could have implications for improving radiotherapy treatment planning and interfraction reproducibility.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

The Role of Sensitivity Analysis in the Building Performance Analysis: A Critical Review

A building system is highly nonlinear and commonly includes a variety of parameters ranging from the architectural design to the building mechanical and energy system. Serving as a powerful tool to understand the complicated building system, sensitivity analysis (SA) has been receiving increasing attention in the recent decade. This review paper focused on the application of SA in the building performance analysis (BPA). First, the existing review papers on the application of SA for BPA were briefly reviewed and summarized. Then, a large amount of recent SA case studies in BPA were reviewed. The critical information regarding the implementation of a SA, such as the sampling method, the SA method, etc., were extracted and summarized. Next, an extensive analysis was performed to evaluate the role of the SA in the BPA. This includes: 1) The typical selection of the input and output parameters for the SA were visualized; 2) The uncertainty level and sampling strategies for the input parameters were investigated; 3) The principles, benefits, and drawbacks of the SA methods were analyzed and summarized; and 4) The various tools used in the SA, including the simulation software, sampling tools, and SA tools were introduced to facilitate the practitioners. Lastly, several conclusions were summarized on the role of the SA in the BPA. Suggestions were also provided to offer practical solutions to the current challenges.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗