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All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

An experimental study of a supercritical trailing-edge flow

An experimental study has been conducted of a transonic, turbulent, high-Reynolds-number blunt trailing-edge flow. The model shape and the surface pressure distribution are characteristics of a modern supercritical airfoil under shock-free conditions. Reynolds number and pressure gradient scaling of the boundary layer are relevant to airfoil applications. The data set is exceptionally accurate and consistent, with the momentum balance accounting for the flux of momentum to within 1 percent, except in the immediate vicinity of the blunt trailing edge. The experimental flow exhibits strong viscous-inviscid interaction and higher-order boundary-layer effects including strong adverse streamwise pressure gradient, significant normal pressure gradients associated with surface and streamline curvature, and significant wake curvature. Navier-Stokes calculations with a two-equation K-epsilon turbulence model predict the correct pressure distribution which demonstrates the utility of these engineering tools. The experiment approaches separation at the strailing edge. However, in comparison to the experiment, the calculations predict too high skin friction and insufficient displacement thickness growth. An analysis of the turbulent and mean flow fields reveals the turbulence model defects are likely in modeling the dissipation source and sink terms, and in the eddy viscosity relation.

Brown, J. L.↗
NASA NTRSDate not supplied

Real Time Nitrogen Monitoring and Quality Control System for NASA Astromaterials Collection

The Nitrogen system is a vital utility supporting the curation office within NASA's Astromaterials Re-search and Exploration Science (ARES) Division at the Johnson Space center (JSC). Since the Apollo samples were returned in 1969. It has played an essential role in preserving NASA’s astromaterial collections (now nine collections) by maintaining contamination-free, controlled environments required for long term curation and advanced scientific research. To meet the stringent purity requirements for contamination control, high purity modified Grade C Liquid Nitrogen (LN2) is delivered weekly by an industrial gas vendor to a 15,000-gallon tank located outside at NASA JSC near the ARES facility. This nitrogen is vital for creating an inert atmosphere to store the collection in, ensuring they are continuously shielded from contaminants and alterations through a constant N2purge. For most of the past 65 years deliveries of LN2 have required a CoA (Certificate of Analysis) prior to delivery. If those were not available, then LN2 deliver were sent to third-party laboratories for verification, creating an operational bottleneck and quality gap. To address this challenge and maintain rigorous quality control, NASA JSC Infrastructure and Astromaterials Acquisition & Curation Office initiated the development of an on-site Analytical Gas Sampling (AGS) Laboratory. Designed to streamline quality verification if a CoA unavailable, the AGS lab was constructed by a subcontractor in Newton, NJ. After a successful factory acceptance test conducted by the NASA ARES Infrastructure team, the lab was trans-ported to NASA JSC, where it was anchored and integrated into the site’s nitrogen pressure system using stainless steel, oxygen-cleaned tubing. The ARES nitrogen system was modified to provide parallel flows to the AGS lab for quality control and to the astromaterials collection labs for maintaining an inert environment. The AGS lab features two operational modes: (1)Primary: Gaseous Nitrogen (GN2) Quality Monitoring –The AGS system continuously samples the site’s GN2 supply every 15 minutes to ensure compliance with required purity levels. (2) Secondary: LN2 Quality Verification when a comprehensive CoA is not available, a cryogenic vaporizer converts LN2 to GN2, which is then analyzed for impurities: H₂, Ar, O₂, CO, CO₂, H₂O, and total hydrocarbons (THC). By significantly enhancing on-site analytical capabilities, the AGS lab eliminates reliance on external testing, ensures uninterrupted quality monitoring of the nitrogen pressure system, and reinforces NASA’s commitment to preserving pristine astromaterials under the highest standards of curation and research integrity.

glove box↗
DOE OSTI2022

Robust Carbon Dioxide Plume Imaging Using Joint Tomographic Inversion of Seismic Onset Time and Distributed Pressure and Temperature Measurements (Final Report)

We develop and demonstrate rapid and cost-effective methodologies for spatiotemporal tracking of CO2 plumes during geologic sequestration using joint inversion of seismic data and distributed pressure and temperature measurements. Key elements of our methodology are: (a) a computationally efficient approach to pressure and temperature propagation, (b) analysis of time lapse seismic data using a novel ‘seismic onset time’ approach to detect fluid front propagation, and (c) data assimilation and uncertainty assessment via joint inversion of pressure, temperature and time lapse seismic data, and (d) validating the numerical tomographic inversion using a CO2 injection demonstration projects, specifically data collected from the from the Petra Nova Parish Holdings CCUS project in the West Ranch Field, Texas and the Chester-16 reef CO2 injection site in Northern Michigan which is part of the DOE Midwestern Carbon Sequestration Project. The research team is led by Texas A&M University and includes Battelle as a subcontractor with support from Shell, Anadarko, Chevron and JX Nippon. A carbon dioxide (CO2) water-alternating-gas (WAG) pilot was conducted to gain insights into tertiary oil recovery potential via CO2 flood in the West Ranch Field as part of the Petra Nova project, the world’s largest post-combustion CO2 capture and utilization initiative. With a fluvial formation geology and large contrasts in permeability, this is a challenging and novel application of CO2 enhanced oil recovery (EOR). We build a predictive dynamic model of the subsurface that incorporates the multiphase and compositional data acquired during the pilot operation. The calibrated model is used for the carbon dioxide plume imaging. The study began with an initialization of the pilot sector model extracted from a calibrated full-field model. The pilot model calibration follows a two-step hierarchical workflow. First, we performed a large-scale update of the permeability distribution by integrating available bottomhole pressure and multiphase production data. In the second step, local permeability field is fine-tuned using a streamline-based method to match CO2 breakthrough times at the producers. The predictive capability of the calibrated model was verified through two blind validation tests: (1) the model showed good agreement with saturation logs acquired at two observation wells; and (2) the model reproduced the CO2 recovery as a fraction of the injected CO2. The use of seismic onset times has shown great promise for integrating near-continuous seismic surveys for updating geologic models. In this study, we analyze the impact of seismic survey frequency on the onset time approach aiming to extend the application of onset time to infrequent seismic surveys. In addition, we quantitatively examine the nonlinearity of the onset time method and compare it to the commonly used amplitude inversion method. We carry out a sensitivity analysis of seismic survey frequency based on the complete seismic survey data (over 175 surveys) of steam injection in a heavy oil reservoir (Peace River Unit) in Canada. Our results show that an adequate onset time map can be obtained from the infrequent seismic surveys by interpolation between seismic surveys as long as there is no change in the dominant underlying physics between the successive surveys. The study also shows that nonlinearity of the onset time method can be -smaller than that of the amplitude inversion method by several orders of magnitude. Application to the Brugge benchmark case shows that the onset time method obtains comparable permeability update as the traditional seismic amplitude inversion method with faster computation and improved convergence characteristics. We extend the streamline-based data integration approach to incorporate distributed temperature sensor (DTS) data using the concept of thermal tracer travel time. Then, a hierarchical workflow composed of evolutionary and streamline methods is employed to jointly history match the DTS and pressure data. Finally, CO2 saturation and streamline maps are used to visualize the CO2 plume movement during the sequestration process. The hierarchical workflow is applied to a carbon sequestration project in a carbonate reef reservoir within the Northern Niagaran Pinnacle Reef Trend in Michigan, USA. The monitoring data set consists of distributed temperature sensing (DTS) data acquired at the injection well and a monitoring well, flowing bottom-hole pressure data at the injection well, and time-lapse pressure measurements at several locations along the monitoring well. The history matching results indicate that the CO2 movement is mostly restricted to the intended zones of injection which is consistent with an independent warm-back analysis of the temperature data. In addition to employing simulation models and inverse methods for CO2 plume imaging, we also initialized a data-driven technology for detecting inter-well connectivity based on production and pressure data. Our machine-learning framework is built on the statistical recurrent unit (SRU) model and interprets well-based injection/production data into inter-well connectivity without relying on a geologic model. We test it on synthetic and field-scale CO2 EOR projects utilizing the water-alternating-gas (WAG) process. The validation of the proposed data-driven inter-well connectivity assessment is performed using synthetic data from simulation models where inter-well connectivity can be easily measured using the streamline-based flux allocation. The SRU model is shown to offer excellent prediction performance on the synthetic case. Despite significant measurement noise and frequent well shut-ins imposed in the field-scale case, the SRU model offers good prediction accuracy, the overall relative error of the phase production rates at most producers ranges from 10% to 30%. It is shown that the dominant connections identified by the data-driven method and streamline method are in close agreement. Texas A&M University, the lead organization in the project, was primarily responsible for the development of tomographic approaches for CO2 plume mapping in conjunction with distributed pressure, temperature and seismic onset time data. Battelle, as a subcontractor, was primarily responsible for the development of analytical and empirical methods for analyzing transient injection rate and pressure data from point/line sources such as injection and monitoring wells. An additional area of emphasis for Battelle was the use of machine learning for such tasks as inferring reservoir connectivity information from injection-production data, and identifying variable importance for machine learning-based proxy models developed from full-physics simulations. The two organizations also collaborated on the application of the tomographic inversion methodology for a field data set.

02 PETROLEUM↗
DOE OSTI2015

Classification of Arnold-Beltrami flows and their hidden symmetries

In the context of mathematical hydrodynamics, we consider the group theory structure which underlies the so named ABC flows introduced by Beltrami, Arnold and Childress. Main reference points are Arnold’s theorem stating that, for flows taking place on compact three manifolds ℳ{sub 3}, the only velocity fields able to produce chaotic streamlines are those satisfying Beltrami equation and the modern topological conception of contact structures, each of which admits a representative contact one-form also satisfying Beltrami equation. We advocate that Beltrami equation is nothing else but the eigenstate equation for the first order Laplace-Beltrami operator ★{sub g }d, which can be solved by using time-honored harmonic analysis. Taking for ℳ{sub 3}, a torus T {sup 3} constructed as ℝ{sup 3}/Λ, where Λ is a crystallographic lattice, we present a general algorithm to construct solutions of the Beltrami equation which utilizes as main ingredient the orbits under the action of the point group B {sub A }of three-vectors in the momentum lattice *Λ. Inspired by the crystallographic construction of space groups, we introduce the new notion of a Universal Classifying Group GA{sub Λ} which contains all space groups as proper subgroups. We show that the ★{sub g }d eigenfunctions are naturally arranged into irreducible representations of GA{sub Λ} and by means of a systematic use of the branching rules with respect to various possible subgroups H{sub i}⊂GA{sub Λ} we search and find Beltrami fields with non trivial hidden symmetries. In the case of the cubic lattice the point group is the proper octahedral group O{sub 24} and the Universal Classifying Group GA{sub cubic} is a finite group G{sub 1536} of order |G{sub 1536}| = 1536 which we study in full detail deriving all of its 37 irreducible representations and the associated character table. We show that the O{sub 24} orbits in the cubic lattice are arranged into 48 equivalence classes, the parameters of the corresponding Beltrami vector fields filling all the 37 irreducible representations of G{sub 1536}. In this way we obtain an exhaustive classification of all generalized ABC-flows and of their hidden symmetries. We make several conceptual comments about the need of a field-theory yielding Beltrami equation as a field equation and/or an instanton equation and on the possible relation of Arnold-Beltrami flows with (supersymmetric) Chern-Simons gauge theories. We also suggest linear generalizations of Beltrami equation to higher odd-dimensions that are different from the non-linear one proposed by Arnold and possibly make contact with M-theory and the geometry of flux-compactifications.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Integration of the SSPM and STAGE with the MPACT Virtual Facility Distributed Test Bed.

The Material Protection Accounting and Control Technologies (MPACT) program within DOE NE is working toward a 2020 milestone to demonstrate a Virtual Facility Distributed Test Bed. The goal of the Virtual Test Bed is to link all MPACT modeling tools, technology development, and experimental work to create a Safeguards and Security by Design capability for fuel cycle facilities. The Separation and Safeguards Performance Model (SSPM) forms the core safeguards analysis tool, and the Scenario Toolkit and Generation Environment (STAGE) code forms the core physical security tool. These models are used to design and analyze safeguards and security systems and generate performance metrics. Work over the past year has focused on how these models will integrate with the other capabilities in the MPACT program and specific model changes to enable more streamlined integration in the future. This report describes the model changes and plans for how the models will be used more collaboratively. The Virtual Facility is not designed to integrate all capabilities into one master code, but rather to maintain stand-alone capabilities that communicate results between codes more effectively.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Fluoride-Cooled High-Temperature Pebble-Bed Reactor Reference Plant Model

In this report we present work performed in Fiscal Year 2022 that demonstrates the modeling and simulation of a fully coupled neutronics thermal hydraulics reference plant model for a fluoride-cooled high-temperature pebble-bed reactor. The multiphysics model is developed on the Nuclear Regulatory Commission’s Comprehensive Reactor Analysis Bundle (BlueCRAB) available on the Idaho National Laboratory’s high-performance computer, which natively and seamlessly couples Griffin, Pronghorn, and the BISON Multiphysics Object-Oriented Simulation Environment based applications. Griffin provides reactor physics capabilities, including depletion to the equilibrium core, k-eigenvalue, adjoint, and transient. The unique direct equilibrium core capability in Griffin is based on a streamline methodology to spatially deplete the pebbles into burnup groups. Pronghorn solves the porous medium equations for the fluid regions and conduction in the solid regions and incorporates a fluidic diode model to simulate the transition from forced to natural convection during accident scenarios. MOOSE modules solves thermal conduction problems for the pebbles and tristructural isotropic in the pebble-bed core, thus providing the fuel and moderator spatial fields for each pebble burnup group. The neutronics feedback relies primarily on fuel, moderator, and reflector temperatures as as well as the FLiBe salt density. Here, we present results for the uncoupled equilibrium core and perform comparisons to equivalent Monte Carlo models. The power distributions and kinetic parameters obtained with Griffin are consistent with those computed with Griffin. We demonstrate a noticeable improvement with the use of discrete ordinates method (SN) transport. The coupled steady-state equilibrium core provides the initial condition for two time-dependent problems: a control rod withdrawal event and an unprotected loss of flow event. In both cases, the reactor design is self-stabilizing and the solutions are consistent with the expected physics. Although this model is prototypical regarding BlueCRAB’s capabilities, its results are consistent with published work by Kairos Power and other research entities. Significant improvements to the model are planned in future work.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2017

Mass and Reliability Source (MaRS) Database

The Mass and Reliability Source (MaRS) Database consolidates components mass and reliability data for all Oribital Replacement Units (ORU) on the International Space Station (ISS) into a single database. It was created to help engineers develop a parametric model that relates hardware mass and reliability. MaRS supplies relevant failure data at the lowest possible component level while providing support for risk, reliability, and logistics analysis. Random-failure data is usually linked to the ORU assembly. MaRS uses this data to identify and display the lowest possible component failure level. As seen in Figure 1, the failure point is identified to the lowest level: Component 2.1. This is useful for efficient planning of spare supplies, supporting long duration crewed missions, allowing quicker trade studies, and streamlining diagnostic processes. MaRS is composed of information from various databases: MADS (operating hours), VMDB (indentured part lists), and ISS PART (failure data). This information is organized in Microsoft Excel and accessed through a program made in Microsoft Access (Figure 2). The focus of the Fall 2017 internship tour was to identify the components that were the root cause of failure from the given random-failure data, develop a taxonomy for the database, and attach material headings to the component list. Secondary objectives included verifying the integrity of the data in MaRS, eliminating any part discrepancies, and generating documentation for future reference. Due to the nature of the random-failure data, data mining had to be done manually without the assistance of an automated program to ensure positive identification.

Valdenegro, Wladimir↗
DOE OSTI2025

Projection Analysis for ATR Irradiation of the AFC-FAST Experiment

Analyses of the Advanced Fuels Campaign Fission Accelerated Steady-state Test (AFC-FAST) in the Advanced Test Reactor are presented. A detailed methodology was employed to better account for uncertainties in the planned power and duration of sequential reactor loading cycles. By performing coupled depletion analyses at multiple power levels and durations, the differences in experiment heating outputs can be found. The effects of these uncertainties upon multiple experiment configurations were assessed in an effort to streamline the process of planning for and documenting future irradiations. In conclusion, the data generated from this work have been used to help inform assumptions on subsequent projections to perform only a nominal case depletion.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Trajectory-based modeling of fluid transport in a medium with smoothly varying heterogeneity

Using an asymptotic methodology, valid in the presence of smoothly varying heterogeneity and prescribed boundaries, we derive a trajectory-based solution for tracer transport. The analysis produces a Hamilton-Jacobi partial differential equation for the phase of the propagating tracer front. The trajectories follow from the characteristic equations that are equivalent to the Hamilton-Jacobi equation. The paths are determined by the fluid velocity field, the total porosity, and the dispersion tensor. Due to their dependence upon the local hydrodynamic dispersion, they differ from conventional streamlines. This difference is borne out in numerical calculations for both uniform and dipole flow fields. In an application to the computational X-ray imaging of a saline tracer test, we illustrate that the trajectories may serve as the basis for a form of tracer tomography. In particular, we use the onset time of a change in attenuation for each volume element of the X-ray image as a measure of the arrival time of the saline tracer. In conclusion, the arrival times are used to image the spatial variation of the effective hydraulic conductivity within the laboratory sample.

58 GEOSCIENCES↗
DOE OSTI2025

Distribution Substation Planning Toolkit (dsp-toolkit) v1.0

The Distribution Substation Planning Toolkit (DSP Toolkit) is a software suite designed to streamline the planning and optimization of distribution substations. This toolkit offers a comprehensive set of tools and APIs for data curation, short-term electric load forecasting, and weather-sensitive load adjustment, making it an essential resource for utility companies, engineers, and researchers. Features • Data Preprocessing and Curation: Efficiently manage and preprocess large datasets to ensure high-quality input for analysis. • Short-Term Load Forecasting: Utilize data-driven models to predict short-term electric loads accurately. • Weather-Sensitive Modeling: Automatically adjust load forecasts based on weather data to predict future peak demands more precisely. Uses The DSP Toolkit is ideal for planning and optimizing distribution substations, providing a user-friendly interface and comprehensive documentation. It is suitable for both novice and experienced users, facilitating efficient and accurate planning processes. Advantages • Efficiency: Automates complex planning tasks, reducing manual effort and minimizing errors. • Scalability: Handles large datasets and complex models, making it suitable for large-scale projects. • Community and Support: Open-source with active community contributions, ensuring continuous improvement and support. • Extensibility: Easily extendable with custom modules and plugins, allowing users to tailor the toolkit to their specific needs. The DSP Toolkit stands out by offering a robust, flexible, and user-friendly solution for distribution substation planning. Public Abstract

Li, Han [Lawrence Berkeley National Laboratory (LB↗
DOE OSTI2026

CMIP7 data request: land and land ice priorities and opportunities

The Land and Land Ice Theme in the Coupled Model Intercomparison Project Phase 7 (CMIP7) represents the current understanding of physical processes in land surface ecosystems, hydrology, cryosphere, and their physical interactions with other Earth system components. Simulations from Earth system models (ESMs) could provide crucial information for assessing planetary safety, such as critical tipping elements, and be used to inform climate risks for improving climate impact assessments and policy decisions. This paper presents a collaborative effort to identify scientific opportunities in the Land and Land Ice Theme of the CMIP7 Data Request. The proposed opportunities build upon advances in ESMs, including new freshwater system and land ice processes being included in CMIP7, as well as the scientific community's demand for high-frequency and sub-grid-scale land surface outputs. In total, 25 variable groups that contain 716 variables have been identified to be potentially available to the broad scientific audience for performing analysis in land–atmosphere coupling, hydrological processes and freshwater systems, glacier and ice sheet mass balance and their influence on the sea levels, land use, and plant phenology. Key reflections from this data request effort include advocacy for closer engagement between the user community and modeling groups, reduction in the technical barriers to tracking existing parameters and defining new variables, and more streamlined variable management. These will be essential to enhance the usability and reliability of CMIP7 outputs for climate and Earth system research and applications to a broad audience that relies on the CMIP7 endeavor.

Li, Yue [Univ. of California, Los Angeles, CA (Uni↗
NASA NTRS2010

Adaptive Planning: Understanding Organizational Workload to Capability/ Capacity through Modeling and Simulation

In August 2003, the Secretary of Defense (SECDEF) established the Adaptive Planning (AP) initiative [1] with an objective of reducing the time necessary to develop and revise Combatant Commander (COCOM) contingency plans and increase SECDEF plan visibility. In addition to reducing the traditional plan development timeline from twenty-four months to less than twelve months (with a goal of six months)[2], AP increased plan visibility to Department of Defense (DoD) leadership through In-Progress Reviews (IPRs). The IPR process, as well as the increased number of campaign and contingency plans COCOMs had to develop, increased the workload while the number of planners remained fixed. Several efforts from collaborative planning tools to streamlined processes were initiated to compensate for the increased workload enabling COCOMS to better meet shorter planning timelines. This paper examines the Joint Strategic Capabilities Plan (JSCP) directed contingency planning and staffing requirements assigned to a combatant commander staff through the lens of modeling and simulation. The dynamics of developing a COCOM plan are captured with an ExtendSim [3] simulation. The resulting analysis provides a quantifiable means by which to measure a combatant commander staffs workload associated with development and staffing JSCP [4] directed contingency plans with COCOM capability/capacity. Modeling and simulation bring significant opportunities in measuring the sensitivity of key variables in the assessment of workload to capability/capacity analysis. Gaining an understanding of the relationship between plan complexity, number of plans, planning processes, and number of planners with time required for plan development provides valuable information to DoD leadership. Through modeling and simulation AP leadership can gain greater insight in making key decisions on knowing where to best allocate scarce resources in an effort to meet DoD planning objectives.

Hase, Chris↗
DOE OSTI2020

Machine Learning for Automated Extraction of Building Geometry

As data science comes to buildings, the promise of using machine learning and novel sources of data has received much attention. Advances in machine learning and computer vision algorithms, combined with increased access to unstructured data (e.g., images and text), have created an opportunity for automated extraction of building characteristics – cost-effectively, and at scale. Acquisition of features such as footprint are time consuming and costly to acquire with today’s manual methods, but can be streamlined through intelligent software-based solutions applied to satellite images. When combined with aerial RGB and thermal images, full 3D geometries and thermal maps can be constructed to determine additional characteristics such as window to wall ratio, height, number of stories and envelope thermal characteristics. In this paper we present three contributions to accelerate these high potential opportunities: (1) a methodical analysis of how these features can be integrated into today’s simulation and data driven software tools to enhance efficiency measure identification and owner/operator decision making; (2) development and accuracy testing of open source deep neural network methods to extract building footprints from satellite imagery, including the curation and application of openly available GIS datasets for training and continued development by others; and (3) an open framework for drone-based image capture and creation of 3D building geometries. This work represents an important bridge between high-level studies that span diverse application areas and those that detail point solutions yet cannot be easily replicated or extended.

Touzani, Samir↗
DOE OSTI2014

Conforming Morse-Smale Complexes

Morse-Smale (MS) complexes have been gaining popularity as a tool for feature-driven data analysis and visualization. However, the quality of their geometric embedding and the sole dependence on the input scalar field data can limit their applicability when expressing application-dependent features. In this paper we introduce a new combinatorial technique to compute an MS complex that conforms to both an input scalar field and an additional, prior segmentation of the domain. The segmentation constrains the MS complex computation guaranteeing that boundaries in the segmentation are captured as separatrices of the MS complex. We demonstrate the utility and versatility of our approach with two applications. First, we use streamline integration to determine numerically computed basins/mountains and use the resulting segmentation as an input to our algorithm. This strategy enables the incorporation of prior flow path knowledge, effectively resulting in an MS complex that is as geometrically accurate as the employed numerical integration. Our second use case is motivated by the observation that often the data itself does not explicitly contain features known to be present by a domain expert. We introduce edit operations for MS complexes so that a user can directly modify their features while maintaining all the advantages of a robust topology-based representation.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1986

PAN AIR analysis of the NASA/MCAIR 279-3: An advanced supersonic V/STOL fighter/attack aircraft

PAN AIR is a computer program for predicting subsonic or supersonic linear potential flow about arbitrary configurations. The program was applied to a highly complex single-engine-cruise V/STOL fighter/attack aircraft. Complexities include a close-coupled canard/wing, large inlets, and four exhaust nozzles mounted directly under the wing and against the fuselage. Modeling uncertainties involving canard wake location and flow-through approximation through the inlet and the exhaust nozzles were investigated. The recently added streamline capability of the program was utilized to evaluate visually the predicted flow over the model. PAN AIR results for Mach numbers of 0.6, 0.9, and angles of attack of 0, 5, and 10 deg. were compared with data obtained in the Ames 11- by 11-Foot Transonic Wind tunnel, at a Reynolds number of 3.69 x 10 to the 6th power based on c bar.

Madson, Michael D.↗
NASA NTRS2012

JPL Genesis and Rapid Intensification Processes (GRIP) Portal

Satellite observations can play a very important role in airborne field campaigns, since they provide a comprehensive description of the environment that is essential for the experiment design, flight planning, and post-experiment scientific data analysis. In the past, it has been difficult to fully utilize data from multiple NASA satellites due to the large data volume, the complexity of accessing NASA s data in near-real-time (NRT), as well as the lack of software tools to interact with multi-sensor information. The JPL GRIP Portal is a Web portal that serves a comprehensive set of NRT observation data sets from NASA and NOAA satellites describing the atmospheric and oceanic environments related to the genesis and intensification of the tropical storms in the North Atlantic Ocean. Together with the model forecast data from four major global atmospheric models, this portal provides a useful tool for the scientists and forecasters in planning and monitoring the NASA GRIP field campaign during the 2010 Atlantic Ocean hurricane season. This portal uses the Google Earth plug-in to visualize various types of data sets, such as 2D maps, wind vectors, streamlines, 3D data sets presented at series of vertical cross-sections or pointwise vertical profiles, and hurricane best tracks and forecast tracks. Additionally, it allows users to overlap multiple data sets, change the opacity of each image layer, generate animations on the fly with selected data sets, and compare the observation data with the model forecast using two independent calendars. The portal also provides the capability to identify the geographic location of any point of interest. In addition to supporting the airborne mission planning, the NRT data and portal will serve as a very rich source of information during the post-field campaign analysis stage of the airborne experiment. By including a diverse set of satellite observations and model forecasts, it provides a good spatial and temporal context for the high-resolution, but limited in space and time, airborne observations.

Knosp, Brian W.↗
DOE OSTI2019

Characteristic path analysis of confinement influence on steady two-dimensional detonation propagation

Steady detonation in multi-dimensional flow is controlled by the chemical energy release that occurs in a subsonic elliptic flow region known as the detonation driving zone (DDZ). It is the region encompassing the detonation shock and sonic flow locus (in the frame of the detonation shock). A detonation that is strongly confined by material surrounding the explosive has the shock and sonic locus separated at the material interface. Information about the material boundary is traditionally believed to influence the DDZ structure via the subsonic flow on the boundary ahead of the sonic locus. A detonation that is weakly confined has the detonation shock and sonic locus intersecting at the material boundary. The sonic nature of the flow at the intersection point on the boundary is believed to isolate the DDZ structure from the material properties of the confinement. We examine the paths of characteristics propagating information about the confinement through the supersonic hyperbolic flow region that exists beyond the sonic locus, and determine whether these paths may impinge on the sonic locus and consequently influence the DDZ structure. Our configuration consists of a solid wall boundary deflected through a specified angle on detonation shock arrival, so that the streamline turning angle of the wall at the explosive edge is unambiguously defined. By varying the wall deflection angle from small through large values, we can systematically capture the evolution of the DDZ structure and the characteristic flow regions that influence its structure for strongly to weakly confined detonations. In all strong and weak confinement cases examined, we find that a subset of characteristics from the supersonic flow regions always impinge on the sonic locus. Limiting characteristics are identified that define the boundary between characteristics that impinge on the sonic surface and those that propagate information downstream of the sonic surface. In combination with an oblique-shock polar analysis, we show that the effects on the DDZ of characteristic impingement can be significant.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Capability to Process and Characterize Uranium-Zirconium (U-Zr) and Uranium-Zirconium-Plutonium (U-Zr-Pu) Alloys

This work investigated co-reduction of anhydrous compounds of uranium, zirconium, and plutonium to produce uranium rich ternary nuclear fuel alloys. Metallothermic co-reduction is a novel method to produce all-metal nuclear fuels. Metal fuels offer thermal, fissility, compatibility, and security benefits over oxide fuels. Alloys of uranium–10% zirconium with plutonium contents of 0%, 2.5%, 5%, and 10% were produced, with yields of 60–85% of theoretical values in a traditional calciothermic bomb reduction apparatus. Microstructural analysis indicated transformation of uranium phase from gamma to beta and then alpha, in alternating lamellar plates typical of alpha phase uranium and delta phase uranium-zirconium, with zirconium and carbides at prior grain boundaries. Some of the analyses were inconclusive in their results and therefore require additional testing. Successful ternary co-reduction would simplify production of homogeneous feedstock and thereby streamline manufacture of homogeneous ternary metallic fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗