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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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At least 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Visual Orbits of Spectroscopic Binaries with the CHARA Array. I. HD 224355

We present the visual orbit of the double-lined spectroscopic binary HD 224355 from interferometric observations with the CHARA Array, as well as an updated spectroscopic analysis using echelle spectra from the Apache Point Observatory 3.5 m telescope. By combining the visual and spectroscopic orbital solutions, we find the binary components to have masses of M 1 = 1.626 ± 0.005M ⊙ and M 2 = 1.608 ± 0.005M ⊙ , and a distance of d = 63.98 ± 0.26 pc. Using the distance and the component angular diameters found by fitting spectrophotometry from the literature to spectral energy distribution models, we estimate the stellar radii to be R 1 = 2.65 ± 0.21R ⊙ and R 2 = 2.47 ± 0.23R ⊙ . We then compare these observed fundamental parameters to the predictions of stellar evolution models, finding that both components are evolved toward the end of the main sequence with an estimated age of 1.9 Gyr.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Visual Orbits of Spectroscopic Binaries with the CHARA Array. III. HD 8374 and HD 24546

We present the visual orbits of two long-period spectroscopic binary stars, HD 8374 and HD 24546, using interferometric observations acquired with the CHARA Array and the Palomar Testbed Interferometer. We also obtained new radial velocities from echelle spectra using the APO 3.5 m and Fairborn 2.0 m telescopes. By combining the visual and spectroscopic observations, we solve for the full, three-dimensional orbits and determine the stellar masses and distances to within 3% uncertainty. We then estimate the effective temperature and radius of each component star through Doppler tomography and spectral energy distribution analyses, in order to compare the observed stellar parameters to the predictions of stellar evolution models. For HD 8374, we find masses of M {sub 1} = 1.636 ± 0.050M {sub ⊙} and M {sub 2} = 1.587 ± 0.049M {sub ⊙}, radii of R {sub 1} = 1.84 ± 0.05R {sub ⊙} and R {sub 2} = 1.66 ± 0.12R {sub ⊙}, temperatures of T{sub eff1}=7280±110 K and T{sub eff2}=7280±120 K, and an estimated age of 1.0 Gyr. For HD 24546, we find masses of M {sub 1} = 1.434 ± 0.014M {sub ⊙} and M {sub 2} = 1.409 ± 0.014M {sub ⊙}, radii of R {sub 1} = 1.67 ± 0.06R {sub ⊙} and R {sub 2} = 1.60 ± 0.10R {sub ⊙}, temperatures of T{sub eff1}=6790±120 K and T{sub eff2}=6770±90 K, and an estimated age of 1.4 Gyr. HD 24546 is therefore too old to be a member of the Hyades cluster, despite its physical proximity to the group.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

The DESI Survey Validation: Results from Visual Inspection of the Quasar Survey Spectra

Abstract A key component of the Dark Energy Spectroscopic Instrument (DESI) survey validation (SV) is a detailed visual inspection (VI) of the optical spectroscopic data to quantify key survey metrics. In this paper we present results from VI of the quasar survey using deep coadded SV spectra. We show that the majority (≈70%) of the main-survey targets are spectroscopically confirmed as quasars, with ≈16% galaxies, ≈6% stars, and ≈8% low-quality spectra lacking reliable features. A nonnegligible fraction of the quasars are misidentified by the standard spectroscopic pipeline, but we show that the majority can be recovered using post-pipeline “afterburner” quasar-identification approaches. We combine these “afterburners” with our standard pipeline to create a modified pipeline to increase the overall quasar yield. At the depth of the main DESI survey, both pipelines achieve a good-redshift purity (reliable redshifts measured within 3000 km s −1 ) of ≈99%; however, the modified pipeline recovers ≈94% of the visually inspected quasars, as compared to ≈86% from the standard pipeline. We demonstrate that both pipelines achieve a median redshift precision and accuracy of ≈100 km s −1 and ≈70 km s −1 , respectively. We constructed composite spectra to investigate why some quasars are missed by the standard pipeline and find that they are more host-galaxy dominated (i.e., distant analogs of “Seyfert galaxies”) and/or more dust reddened than the standard-pipeline quasars. We also show example spectra to demonstrate the overall diversity of the DESI quasar sample and provide strong-lensing candidates where two targets contribute to a single spectrum.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Visualizing How the Structure of Large-Radius Jets Shapes Their Wakes

The ATLAS collaboration has introduced and implemented a strategy for selecting and analyzing large-radius jets composed of skinny $R=0.2$ subjets in heavy ion collisions at the LHC. We show how measurements of these jets teach us about the resolution length $L_{\rm res}$ of quark-gluon plasma (QGP) and can teach us how jet substructure shapes the wakes that jets excite in the QGP droplets through which they pass. We use Hybrid Model calculations to reproduce measurements of $R_{AA}$ for large-radius jets in PbPb collisions, and study their dependence on the angle between the two skinny subjets involved in the final reclustering step of an $R=1$ jet. We show how these observables can constrain the value of $L_{\rm res}$ and demonstrate that the ATLAS data rule out any picture in which an entire parton shower loses energy coherently as if it were a single entity. Determining the degree to which the QGP can resolve partons within a jet is central to the broader program of using jet quenching measurements to probe QGP. We make further use of this setup by analyzing the response of the medium to the passage of large-radius $R=2$ jets containing two skinny subjets in gamma-jet events. We introduce novel jet-shape observables that allow us to visualize the angular shape of the soft hadrons originating from the wakes that wide jets with two skinny subjets excite in a droplet of QGP, as a function of the angular separation between the subjets. We find that even when they are $\sim 0.8- 1$ radian apart, a single broad wake is produced. Only when the two subjets are even farther apart is the presence of two sub-wakes revealed. We show that the way in which jet structure shapes jet wakes can be visualized with similar clarity in experiments by using only those hadrons with low $p_T$. These observables thus offer a new and distinctive way of seeing jet wakes in heavy ion collision data.

FOS: Physical sciences↗
DOE OSTI2025

CERF Visualization: Projected locations of new natural gas combined cycle power plants (with recirculating cooling) in Wyoming, USA (2020-2050)

Visualization of CERF outputs for years 2030-2050 in 5-year time steps for a region in Wyoming, USA. This visualization was built using a custom CesiumJS application. The region of interest was zoomed into and then the app shows the layered application of natural gas combined cycle power plants (with recirculating cooling) suitability criteria, show the siting for each year in planform, simulates the selection of a site using Net Locational Cost, and then zooms into to show a single functional gas plant and simulates its connection to the grid.

CERF↗
DOE OSTI2015

Geographic Visualization of Power-Grid Dynamics

The visualization enables the simulation analyst to see changes in the frequency through time and space. With this technology, the analyst has a bird's eye view of the frequency at loads and generators as the simulated power system responds to the loss of a generator, spikes in load, and other contingencies. The significance of a contingency to the operation of an electrical power system depends critically on how the resulting tansients evolve in time and space. Consequently, these dynamic events can only be understood when seen in their proper geographic context. this understanding is indispensable to engineers working on the next generation of distributed sensing and control systems for the smart grid. By making possible a natural and intuitive presentation of dynamic behavior, our new visualization technology is a situational-awareness tool for power-system engineers.

Sukumar, Sreenivas R.↗
DOE OSTI2016

Visualization of the Eastern Renewable Generation Integration Study: Preprint

The Eastern Renewable Generation Integration Study (ERGIS), explores the operational impacts of the wide spread adoption of wind and solar photovoltaics (PV) resources in the U.S. Eastern Interconnection and Quebec Interconnection (collectively, EI). In order to understand some of the economic and reliability challenges of managing hundreds of gigawatts of wind and PV generation, we developed state of the art tools, data, and models for simulating power system operations using hourly unit commitment and 5-minute economic dispatch over an entire year. Using NREL's high-performance computing capabilities and new methodologies to model operations, we found that the EI, as simulated with evolutionary change in 2026, could balance the variability and uncertainty of wind and PV at a 5-minute level under a variety of conditions. A large-scale display and a combination of multiple coordinated views and small multiples were used to visually analyze the four large highly multivariate scenarios with high spatial and temporal resolutions. state of the art tools, data, and models for simulating power system operations using hourly unit commitment and 5-minute economic dispatch over an entire year. Using NRELs high-performance computing capabilities and new methodologies to model operations, we found that the EI, as simulated with evolutionary change in 2026, could balance the variability and uncertainty of wind and PV at a 5-minute level under a variety of conditions. A large-scale display and a combination of multiple coordinated views and small multiples were used to visually analyze the four large highly multivariate scenarios with high spatial and temporal resolutions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Falcon: A Temporal Visual Analysis System

Flexible visible exploration of long, high-resolution time series from multiple sensor streams is a challenge in several domains. Falcon is a visual analytics approach that helps researchers acquire a deep understanding of patterns in log and imagery data. Falcon allows users to interactively explore large, time-oriented data sets from multiple linked perspectives. Falcon provides overviews, detailed views, and unique segmented time series visualizations with multiple levels of detail. These capabilities are applicable to the analysis of any quantitative time series.

Steed, Chad A.↗
DOE OSTI2017

Flow visualization methods for field test verification of CFD analysis of an open gloveport

Anemometer readings alone cannot provide a complete picture of air flow patterns at an open gloveport. Having a means to visualize air flow for field tests in general provides greater insight by indicating direction in addition to the magnitude of the air flow velocities in the region of interest. Furthermore, flow visualization is essential for Computational Fluid Dynamics (CFD) verification, where important modeling assumptions play a significant role in analyzing the chaotic nature of low-velocity air flow. A good example is shown Figure 1, where an unexpected vortex pattern occurred during a field test that could not have been measured relying only on anemometer readings. Here by, observing and measuring the patterns of the smoke flowing into the gloveport allowed the CFD model to be appropriately updated to match the actual flow velocities in both magnitude and direction.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Visualization for Classification in Deep Neural Networks

Recently, the techniques based on Deep Neural Networks (DNNs) have achieved a great performance in classification tasks in a wide range of applications, such as image recognition and natural language processing. However, DNN developers face a lot of trial and error during the development process and spend their efforts in debugging their network model through analyzing and understanding the classification results. As such, tools are needed that help the developers not only understand the results, but also suggest the ways to improve their model. In this paper, we propose a visual analytics tool for visualizing the classification results during the iterative development pipeline of a DNN model. Our tool enables exploring the classification results from any type of neural network models, identifying misclassified samples, examining the predicted score distributions of samples, and showing how the outcomes progressively change during the training process.

Chae, Junghoon↗
DOE OSTI2019

Systems and methods of generating color saturated data marks in data visualizations

A method of displaying data visualizations includes retrieving a dataset from a multidimensional database, where the dataset includes a plurality of fields, including first and second fields, and the first field is a data hierarchy that includes multiple subfields. The method further includes displaying a GUI with a first region displaying the plurality of fields (with the first field in a collapsed state), a second region with a plurality of shelves, and a third region. In response to receiving a user action to display the first field in an expanded state, the method displays the first field and the multiple subfields in a hierarchical structure. The method receives additional user actions to: (i) associate a first subfield of the plurality with a first shelf, and (ii) associate the second field with a second shelf, and then displays, in accordance with the user actions, a data visualization in the third region.

Stolte, Chris↗
DOE OSTI2020

Scientific Visualization: New Techniques in Production Software

The field of visualization encompasses a wide range of techniques, from infographics to isosurfaces. An important subfield called "scientific visualization" is specifically dedicated to data sets with spatial components, i.e., (X, Y, Z) locations. Furthermore, this subfield's name is inspired by the fact that the data in question often come from the sciences, i.e., physics simulations or sensor networks.

Moreland, Kenneth D.↗
DOE OSTI2016

Using GIS for Processing, Analysis and Visualization of Hydrological Model Data - 16202

The Applied Research Center at Florida International University (ARC-FIU) is supporting the soil and groundwater remediation efforts of the U.S. Department of Energy's (DOE's) Savannah River Site (SRS) by developing a surface water model to simulate the hydrology and the fate and transport of contaminants and sediment in the Tims Branch watershed. Advances in ArcGIS software through the development of spatial GIS database (geo-database) technology, coupled with the development of data models such as ArcHydro which possesses a spatial relational database management system (RDMS) schema and relationship structure specific to hydrologic systems, provides modelers with tools and applications to assist in the processing, analysis and visualization of flow and contaminant transport data. In addition, the coupling of this type of geo-database structure with a numerical modeling package such as MIKE SHE/MIKE 11 can serve as an efficient tool that significantly reduces the time needed for data preparation. The MIKE modeling system has a geographic information systems (GIS) user interface built into its system that can directly use GIS data for model inputs. GIS-based hydrologic models can provide a spatial element that other hydrologic models lack. GIS is important for processing and analysis of large spatio-temporal datasets derived from multiple sources that are being used for setting up of models, model calibration and simulation of flow and contaminant fate and transport. GIS-based approaches in hydrological modeling can also provide the benefit of combining different layers of geographic data to create new integrated information which can be quite useful for creating dependent or independent hydrological variables. ARC-FIU has developed an ArcGIS geo-database to support the hydrological modeling work being conducted at SRS. The SRS geo-database was developed based on the ArcHydro and ArcGIS Base Map data models with modifications made for project specific input parameters. The significance of this approach was to ensure its replicability for potential application at other DOE sites. The SRS geo-database assists in the storage and management of GIS and time series data being used for hydrological model development at Savannah River Site. Other GIS tools such as ArcGIS Model Builder coupled with Python scripting have enabled the automation of many of the repetitive geo-processing tasks required for pre- and post-processing of the hydrological modeling data. Automation of many of the data processing tasks has facilitated faster and hence more complex analyses of field test data. The toolbox created is also a scalable and reusable application that can be implemented in other watersheds. This paper describes the use of ArcGIS tools for the pre-processing, spatial delineation and analysis of hydrological model data; for automation of repetitive geo-processing tasks; and for visualization of different hydrological components of the Tims Branch watershed. (authors)

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

A Prototype Dual Robot System to Perform Ultrasonic and Visual Inspection for the Bottom of Double-Shell Tanks - 18624

Up to this point, ultrasonic inspection-based condition data has only been available for double-shell tank (DST) sidewalls because direct inspection access to the primary tank bottom is limited to vent duct channels in an insulating refractory pad that the primary tank rests on. Probe access through the air slot would provide the opportunity to get information about the condition of the bottom of the primary tank, but it is a challenge to deploy a crawling robot that is capable of performing nondestructive ultrasonic and visual inspection through confined air slots. As such, a conceptual prototype of a deployable inspection robot system to enable ultrasonic and visual inspection for DST base through ventilation ducts was designed and fabricated. This prototype dual robot system consisting of the AnnulusBot and the MouseBot can be integrated with nondestructive evaluation (NDE) sensors to inspect and examine the physical properties of the underside of DSTs to enable status assessment. The AnnulusBot was designed to carry the MouseBot and to be deployed to the annulus space through a riser. To deploy the MouseBot to every ventilation channel in the annulus, the arm consisting of a boom and a forearm was used to place the MouseBot on the underside of the tank. The AnnulusBot used segmented wheels enable to traverse pipes and other potential obstacles. The cable management system utilized motorized wheels to feed the cable into the ventilation channel. This would reduce the amount of work that the MouseBot would have to do during inspection. This feeding mechanism would also be used to retrieve the MouseBot at the end of its inspection. Additionally, if the MouseBot fails, this mechanism would be used for retrieval. Once deployed, the MouseBot navigates to the center of the tank via the air ventilation channel beneath the inner shell (the primary tank) while inspecting the space. The MouseBot is then retrieved from the channel by a combination of its own drive power and the AnnulusBot retracting the attached umbilical cord. Compare with the AnnulusBot, the physical dimensional limitations of the MouseBot were a greater challenge. As the surface state of the concrete of the air channels could have variable texture, and may contain debris, it was decided not to travel along this surface. The ceiling of these channels is carbon steel and can be utilized throughout the channel. To use this travel surface, magnetic wheels were employed. A foreseeable problem with the use of magnets on this surface, is that they would preclude the use of eddy currents sensors. However, other technologies like ultrasonic technology sensors should be unaffected. Laboratory scale test was performed on a mock-up single wedge of the refractory pad to evaluate maneuverability of the MouseBot. The electronic components for the prototype would work in the ranges of 150-185 deg. F (65.6-85 deg. C). Both the AnnulusBot and MouseBot will be subject to constant radiation. All major printed circuit board (PCB) microcontroller components were designed to be situated outside of the annulus space and inside the main control panel to avoid radiation-induced failure. As future work, electronic components including the Arduinos that used Atmel commercial microcontrollers will be replaced with the high temperature rated Atmel microcontrollers so that the robots can be operated reliably at ambient temperatures up to 200 deg. F (93.3 deg. C). In addition, the robots will be service life tested to evaluate performance at elevated temperature and under gamma irradiation. (authors)

42 ENGINEERING↗
DOE OSTI2016

Using Python For 3D Visualizations of MCNP output

MCNP is ubiquitously used within industries, universities and national laboratories as a tool for accurately modeling radiation. With so much focus on the details of transport, attention is seldom given to the visualizations of these meticulously constructed outputs. Python is a programing language designed to promote code readability and has steadily grown in popularity since the 1990's. Python is also a heavily crowd-sourced programing language which generally means that the problems that you are trying to solve with computer codes are already solved; The user is often left with the now-simplified task of cobbling together a good and useful compilation of these tools and adapting them to solve the problem at hand. I have taken advantage of this situation and constructed some visualization tools in python that can be used to duplicate some of the 2D radiation fields that MCNP produces and also produce a meaningful 3D representation of a radiation field. (author)

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2024

Visualizing a Vulnerability: Its Connections to Hardware and Software

All Hazards Analysis (AHA) is a framework developed by Idaho National Laboratory that provides capabilities to collect, store, analyze, and visualize critical infrastructure information. A core function of AHA is its ability to simulate faults or outages in networks of infrastructure originating from a plethora of causes, ranging from natural disasters to cyberattacks. AHA utilizes Hardware and Software Bills of Material (HBOM and SBOM, respectively) along with Known Exploited Vulnerabilities (KEVs) to document the potential attack vectors for each piece of infrastructure. The objective of this contribution to AHA was to create a visualization tool that could capture the small details held in each individual artifact as well as preserve the large-scale connections that link them together to aid threat modeling.

58 GEOSCIENCES↗
DOE OSTI2026

Visualization of Two-phase Flow Maldistribution in Brazed Plate Heat Exchangers

Brazed plate heat exchangers (BPHEs) are widely used in refrigeration and HVAC applications, but are susceptible to two-phase flow maldistribution especially when operated as evaporators. Existing visualization approaches are either limited to idealized conditions or suffer from poor optical transparency. This paper presents a novel visualization method in which one edge of a BPHE, parallel to the refrigerant inlet or outlet port, is removed by wire electrical discharge machining and replaced with a flat, transparent plate. The planar geometry allows the use of optically and infrared (IR)-transparent materials, enabling both high-speed videography and IR thermography of the two-phase flow at the channel entrances and exits. Preliminary tests with R134a and R1234ze(Z) at saturation temperatures between 5 °C and 15 °C demonstrate that distinct two-phase flow patterns in the inlet header can be clearly identified and differentiated under realistic operating conditions. Potentials of optical flow analysis of high-speed videos are shown to provide objective, quantitative indicators for flow regime characterization and comparison. IR imaging of the outlet port reveals non-uniform temperature distributions at the channel exits, providing independent evidence of maldistribution across the channel stack. Limitations of IR temperature accuracy due to the spectral properties of the sapphire window are discussed, and directions for improvement are identified.

Hausherr, Carsten [Technical University of Berlin ↗
DOE OSTI2018

Challenges in Visual Analysis of Ensembles

Modeling physical phenomena through computational simulation increasingly relies on generating a collection of related runs, known as an ensemble. In this paper, we explore the challenges we face in developing analysis and visualization systems for large and complex ensemble data sets, which we seek to understand without having to view the results of every simulation run. Implementing approaches and ideas developed in response to this goal, we demonstrate the analysis of a 15K run material fracturing study using Slycat, our ensemble analysis system.

97 MATHEMATICS AND COMPUTING↗