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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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NASA NTRSDate not supplied

Assessing Engine Hot Fire Data for Human Spaceflight Applications

Development and certification of liquid engine systems for human spaceflight missions requires exhaustive analysis to meet the NASA’s requirements for engine health, reliability, and performance. The techniques used to assess requirement conformance and test-to-test engine health pose many unique challenges including the unusually large scale of data, complex component and system analysis, and rigorous engineering judgement standards. To address these challenges, NASA Marshall Space Flight Center’s Engine Systems branch has developed and maintained a robust software suite and operational processes that satisfy programmatic requirements levied on engines and the 7 Elements of Flight Rationale. Analysis at a systems level includes subsystem assessment of components such as turbomachinery and combustion devices as well as structural and fluid dynamics and transient and steady-state assessment at a systems level. Some of the most important tools to accomplish this analysis are automated script databases, creation of historical and statistical comparisons, and parameters calculated at the full data rate. These tools greatly simplify the crucial processes of anomaly investigation, limit monitoring, health assessment, and timely communication of key conclusions drawn from hot fire testing and flight data analysis.

Data Assessment↗

NASA NTRSDate not supplied

Assessing Engine Hot Fire Data for Human Spaceflight Applications

Data Assessment↗

DOE OSTI2015

Transport Energy Impact Analysis; NREL (National Renewable Energy Laboratory)

Presented at the Sustainable Transportation Energy Pathways Spring 2015 Symposium on May 13, 2015, this presentation by Jeff Gonder of the National Renewable Energy Laboratory (NREL) provides information about NREL's transportation energy impact analysis of connected and automated vehicles.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2016

Facility Improvements and Modifications to Extend the Operational Life of the Modular Caustic-Side Solvent Extraction Process - 16082

Savannah River Remediation, LLC (SRR) is working to remove, stabilize, and dispose of approximately 36.7 million gallons (138.9 million liters) of liquid radioactive waste currently stored in 43 underground waste tanks, and ultimately close waste tanks. In 2008, as an interim salt treatment system to remove cesium from high level waste salt solutions prior to the Salt Waste Processing Facility start up, the Modular Caustic-Side Solvent Extraction Unit (MCU) initiated the removal of cesium from liquid radioactive salt waste prior to disposal. The MCU was designed and built for an expected three-year operational life and five-year design life. The first MCU cold runs began in June 2007 and hot startup was completed in April 2008. MCU remains in hot operation to this day, aiding in multiple, high-level tank closures. In an effort to continue liquid waste disposition at the Savannah River Site (SRS), equipment upgrades and operational improvements have been made to extend the life of the MCU beyond the original three years. Several pieces of fixed equipment have been converted into removable equipment which reduces the downtime associated with equipment change-outs and thereby reduces the dose to workers and processing impacts. Multiple pumps and filters have been upgraded to more robust designs. Process monitoring and controls have been upgraded to improve process performance. Redundant centrifugal contactor vibration equipment has been installed on each contactor in order to better assess the reliability, processing performance, and lifetime of the contactors. A new Solvent Hold Tank (SHT) Sampler has been installed to minimize the organic cross-contamination within the sampler, dose to workers, and sample analysis time. To increase processing availability and aid in visually obtained data, camera port has been added to the Salt Solution Feed Tank (SSFT). In order to decrease the overall background dose to the workers, the Process Vessel Ventilation (PVV) duct work now has the capability to be flushed to remove contamination. The caustic wash addition system has been modified to be a once-through system to improve equipment reliability, decrease downtime, and decrease dose to workers. In addition, the solvent that MCU utilizes to extract Cesium out of salt waste has been upgraded to Next Generation Solvent (NGS) which is based on MaxCalix extractant instead of a BobCalix extractant. Further, these upgrades and improvements have allowed MCU to be able to process at higher flow rates (up to 8.5 GPM) and with increased throughput (as high as 1.3 million gallons in FY13 and 5.3 million gallons since hot operations initiated) that have allowed SRR to continue the disposition of nuclear salt waste. The continued operation of MCU ensures more curies are stabilized into a glass matrix at SRS's Defense Waste Processing Facility (DWPF) and less curies are retained within South Carolina at SRS's Saltstone Disposal Facility (SDF). Unique challenges associated with modifying and improving a demonstration plant that is in hot operations and was designed to be temporary with a limited plant footprint have been successfully overcome. Further, creative strategies for removing old equipment have been utilized given the limited decontamination agents available for use that will not interfere with the organic solvent. This paper presents and discusses the deployment of these upgrades and operational improvements to MCU in order to allow continued, increased salt waste processing beyond the initial design life. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2023

Merger identification through photometric bands, colours, and their errors

Aims. We present the application of a fully connected neural network (NN) for galaxy merger identification using exclusively photometric information. Our purpose is not only to test the method’s efficiency, but also to understand what merger properties the NN can learn and what their physical interpretation is. Methods. We created a class-balanced training dataset of 5860 galaxies split into mergers and non-mergers. The galaxy observations came from SDSS DR6 and were visually identified in Galaxy Zoo. The 2930 mergers were selected from known SDSS mergers and the respective non-mergers were the closest match in both redshift and r magnitude. The NN architecture was built by testing a different number of layers with different sizes and variations of the dropout rate. We compared input spaces constructed using: the five SDSS filters: u, g, r, i, and z; combinations of bands, colours, and their errors; six magnitude types; and variations of input normalization. Results. We find that the fibre magnitude errors contribute the most to the training accuracy. Studying the parameters from which they are calculated, we show that the input space built from the sky error background in the five SDSS bands alone leads to 92.64 ± 0.15% training accuracy. We also find that the input normalization, that is to say, how the data are presented to the NN, has a significant effect on the training performance. Conclusions. We conclude that, from all the SDSS photometric information, the sky error background is the most sensitive to merging processes. This finding is supported by an analysis of its five-band feature space by means of data visualization. Moreover, studying the plane of the g and r sky error bands shows that a decision boundary line is enough to achieve an accuracy of 91.59%.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Architecture for Web-Based Visualization of Large-Scale Energy Domains: Preprint

With the growing penetration of inverter-based distributed energy resources and increased loads through electrification, power systems analyses are becoming more important and more complex. Moreover, these analyses increasingly involve the combination of interconnected energy domains with data that are spatially and temporally increasing in scale by orders of magnitude, surpassing the capabilities of many existing analysis and decision-support systems. We present the architectural design, development, and application of a high-resolution web-based visualization environment capable of cross-domain analysis of tens of millions of energy assets, focusing on scalability and performance. Our system supports the exploration, navigation, and analysis of large data from diverse domains such as electrical transmission and distribution systems, mobility and electric vehicle charging networks, communications networks, cyber assets, and other supporting infrastructure. We evaluate this system across multiple use cases, describing the capabilities and limitations of a web-based approach for high-resolution energy system visualizations.

grid modernization↗

DOE OSTI2026

The LCLStream Ecosystem for Multi-Institutional Dataset Exploration

We describe a new end-to-end experimental data streaming framework designed from the ground up to support new types of applications – AI training, extremely high-rate X-ray time-of-flight analysis, crystal structure determination with distributed processing, and custom data science applications and visualizers yet to be created. Throughout, we use design choices merging cloud microservices with traditional HPC batch execution models for security and flexibility. This project makes a unique contribution to the DOE Integrated Research Infrastructure (IRI) landscape. By creating a flexible, API-driven data request service, we address a significant need for high-speed data streaming sources for the X-ray science data analysis community. With the combination of data request API, mutual authentication web security framework, job queue system, high-rate data buffer, and complementary nature to facility infrastructure, the LCLStreamer framework has prototyped and implemented several new paradigms critical for future generation experiments.

Rogers, David [ORNL] (ORCID:0000000251871768)↗

NASA NTRS1997

SimGraph: A Flight Simulation Data Visualization Workstation

Today's modern flight simulation research produces vast amounts of time sensitive data, making a qualitative analysis of the data difficult while it remains in a numerical representation. Therefore, a method of merging related data together and presenting it to the user in a more comprehensible format is necessary. Simulation Graphics (SimGraph) is an object-oriented data visualization software package that presents simulation data in animated graphical displays for easy interpretation. Data produced from a flight simulation is presented by SimGraph in several different formats, including: 3-Dimensional Views, Cockpit Control Views, Heads-Up Displays, Strip Charts, and Status Indicators. SimGraph can accommodate the addition of new graphical displays to allow the software to be customized to each user s particular environment. A new display can be developed and added to SimGraph without having to design a new application, allowing the graphics programmer to focus on the development of the graphical display. The SimGraph framework can be reused for a wide variety of visualization tasks. Although it was created for the flight simulation facilities at NASA Langley Research Center, SimGraph can be reconfigured to almost any data visualization environment. This paper describes the capabilities and operations of SimGraph.

Kaplan, Joseph A.↗

DOE OSTI2017

Skills and Knowledge for Data-Intensive Environmental Research

The scale and magnitude of complex and pressing environmental issues lend urgency to the need for integrative and reproducible analysis and synthesis, facilitated by data-intensive research approaches. However, the recent pace of technological change has been such that appropriate skills to accomplish data-intensive research are lacking among environmental scientists, who more than ever need greater access to training and mentorship in computational skills. Here, we provide a roadmap for raising data competencies of current and next-generation environmental researchers by describing the concepts and skills needed for effectively engaging with the heterogeneous, distributed, and rapidly growing volumes of available data. We articulate five key skills: (1) data management and processing, (2) analysis, (3) software skills for science, (4) visualization, and (5) communication methods for collaboration and dissemination. We provide an overview of the current suite of training initiatives available to environmental scientists and models for closing the skill-transfer gap.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1994

Feature isolation and quantification of evolving datasets

Identifying and isolating features is an important part of visualization and a crucial step for the analysis and understanding of large time-dependent data sets (either from observation or simulation). In this proposal, we address these concerns, namely the investigation and implementation of basic 2D and 3D feature based methods to enhance current visualization techniques and provide the building blocks for automatic feature recognition, tracking, and correlation. These methods incorporate ideas from scientific visualization, computer vision, image processing, and mathematical morphology. Our focus is in the area of fluid dynamics, and we show the applicability of these methods to the quantification and tracking of three-dimensional vortex and turbulence bursts.

Source record↗

NASA NTRS1974

Automated analysis of video data

A software/hardware system designed and developed to perform automated video imagery analysis is described. Major elements included in the analysis system are: (1) sampling oscilloscope; (2) programmable trigger unit; (3) central computer; and (4) software processing library. The function of the scope and trigger unit, in conjunction with the control computer, is to digitize the selected portion of the video image and store as amplitude and time data in computer memory. Evaluation of the video data, analogus to interpretation of a visual image, is accomplished by the processing software. It is indicated that this technique of video image analysis is applicable to a wide variety of nonaerospace applications involving video data and image analysis.

Hafner, D. J.↗

NASA NTRS1980

Study of the cerrado vegetation in the Federal District area from orbital data

The physiognomic units of cerrado in the area of Distrito Federal (DF) were studied through the visual and automatic analysis of products provided by Multispectral Scanning System (MSS) of LANDSAT. The visual analysis of the multispectral images in black and white, at the 1:250,000 scale, was made based on the texture and tonal patterns. The automatic analysis of the compatible computer tapes (CCT) was made by means of IMAGE-100 system. The following conclusions were obtained: (1) the delimitation of cerrado vegetation forms can be made by the visual and automatic analysis; (2) in the visual analysis, the principal parameter used to discriminate the cerrado forms was the tonal pattern, independently of the year's seasons, and the channel 5 gave better information; (3) in the automatic analysis, the data of the four channels of MSS can be used in the discrimination of the cerrado forms; and (4) in the automatic analysis, the four channels combination possibilities gave more information in the separation of cerrado units when soil types were considered.

Dejesusparada, N.↗

NASA NTRS2010

Terrestrial Hydrological Data from NASA's Hydrology Data and Information Services Center (HDISC): Products, Services, and Applications

Terrestrial hydrological variables are important in global hydrology, climate, and carbon cycle studies. The North American and Global Land Data Assimilation Systems (NLDAS and GLDAS, respectively) have been generating a series of land surface states (soil moisture, snow, and temperature) and fluxes (evapotranspiration, radiation, and heat flux) variables. These data, hosted at and available from NASA s Hydrology Data and Information Services Center (HDISC), include the NLDAS hourly 1/8 degree products and the GLDAS 3-hourly 0.25 and 1.0 degree products. HDISC provides easy access and visualization and analysis capabilities for these products, thus reducing the time and resources spent by scientists on data management and facilitating hydrological research. Users can perform spatial and parameter subsetting, data format transformation, and data analysis operations without needing to first download the data. HDISC is continually being developed as a data and services portal that supports weather and climate forecasts, and water and energy cycle research.

Fang, Hongliang↗

NASA NTRS2011

Engineering and Scientific Applications: Using MatLab(Registered Trademark) for Data Processing and Visualization

MatLab(R) (MATrix LABoratory) is a numerical computation and simulation tool that is used by thousands Scientists and Engineers in many cou ntries. MatLab does purely numerical calculations, which can be used as a glorified calculator or interpreter programming language; its re al strength is in matrix manipulations. Computer algebra functionalities are achieved within the MatLab environment using "symbolic" toolbo x. This feature is similar to computer algebra programs, provided by Maple or Mathematica to calculate with mathematical equations using s ymbolic operations. MatLab in its interpreter programming language fo rm (command interface) is similar with well known programming languag es such as C/C++, support data structures and cell arrays to define c lasses in object oriented programming. As such, MatLab is equipped with most ofthe essential constructs of a higher programming language. M atLab is packaged with an editor and debugging functionality useful t o perform analysis of large MatLab programs and find errors. We belie ve there are many ways to approach real-world problems; prescribed methods to ensure foregoing solutions are incorporated in design and ana lysis of data processing and visualization can benefit engineers and scientist in gaining wider insight in actual implementation of their perspective experiments. This presentation will focus on data processing and visualizations aspects of engineering and scientific applicati ons. Specifically, it will discuss methods and techniques to perform intermediate-level data processing covering engineering and scientifi c problems. MatLab programming techniques including reading various data files formats to produce customized publication-quality graphics, importing engineering and/or scientific data, organizing data in tabu lar format, exporting data to be used by other software programs such as Microsoft Excel, data presentation and visualization will be discussed. The presentation will emphasize creating practIcal scripts (pro grams) that extend the basic features of MatLab TOPICS mclude (1) Ma trix and vector analysis and manipulations (2) Mathematical functions (3) Symbolic calculations & functions (4) Import/export data files (5) Program lOgic and flow control (6) Writing function and passing parameters (7) Test application programs

Sen, Syamal K.↗

NASA NTRS2006

MHD Flow Visualization of Magnetopause and Polar Cusps Vortices

Detailed analysis of Wind, Geotail, and Cluster data shows how magnetopause boundary and polar cusps vortices associated with high speed streams can be a carrier of energy flux to the Earth s magnetosphere. For our analysis time interval, March 29 . - April 5 2002, the Interplanetary Magnetic Field (IMF) is primarily northward and MHD simulations of vortices along the flanks within nine hours of the time interval suggest that a Kelvin Helmholtz (KH) instability is likely present. Vortices were classified by solar wind input provided by the Wind satellite located 70-80 RE upstream from Earth. We present statistics for a total of 304 vortices found near the ecliptic plane on the magnetopause flanks, 273 with northward IMF and 31 with southward IMF. The vortices generated under northward IMF were more driven into the dawnside than into the duskside, being substantially more ordered on the duskside. Most of the vortices were large in scale, up to 10 RE, and with a rotation axis closely aligned with the ZGSE direction. They rotated preferentially clockwise on the dawnside, and. counter-clockwise on the duskside. Those generated under southward IMF were less ordered, fewer in number, and also smaller in diameter. Significant vortex activity occurred on the nightside region of the magnetosphere for these southward cases in contrast to the northward IMF cases on which most of the activity was driven onto the magnetopause flanks. Magnetopause crossings seen by the Geotail spacecraft for the time interval were analyzed and compared with the MHD simulation to validate our results. Vortices over the polar cusps are also being analyzed and the simulation results will be compared to the multi-point measurements of the four Cluster satellites.

Collado-Vega, Y. M.↗

NASA NTRS2007

MHD Flow Visualization of Magnetopause and Polar Cusps Vortices

Detailed analysis of Wind, Geotail, and Cluster data shows how magnetopause boundary and polar cusps vortices associated with high speed streams can be a carrier of energy flux to the Earth's magnetosphere. For our analysis time interval, March 29 . - April 5 2002, the Interplanetary Magnetic Field (IMF) is primarily northward and MHD simulations of vortices along the flanks within nine hours of the time interval suggest that a Kelvin Helmholtz (KH) instability is likely present. Vortices were classified by solar wind input provided by the Wind satellite located 70-80 RE upstream from Earth. We present statistics for a total of 304 vortices found near the ecliptic plane on the magnetopause flanks, 273 with northward IMF and 31 with southward IMF. The vortices generated under northward IMF were more driven into the dawnside than into the duskside, being substantially more ordered on the duskside. Most of the vortices were large in scale, up to 10 RE, and with a rotation axis closely aligned with the Z(sub GSE) direction. They rotated preferentially clockwise on the dawnside, and. counter-clockwise on the duskside. Those generated under southward IMF were less ordered, fewer in number, and also smaller in diameter. Significant vortex activity occurred on the nightside region of the magnetosphere for these southward cases in contrast to the northward IMF cases on which most of the activity was driven onto the magnetopause flanks. Magnetopause crossings seen by the Geotail spacecraft for the time interval were analyzed and compared with the MHD simulation to validate our results. Vortices over the polar cusps are also being analyzed and the simulation results will be compared to the multi-point measurements of the four Cluster satellites.

Collado-Vega, Y. M.↗

DOE OSTI2019

Computational Reproducibility of Scientific Workflows at Extreme Scales

We propose an approach for improved reproducibility that includes capturing and relating provenance characteristics and performance metrics, in a hybrid queriable system, the ProvEn server. The system capabilities are illustrated on two use cases: scientific reproducibility of results in the ACME climate simulations and performance reproducibility in molecular dynamics workflows on HPC computing platforms.

provenance, Reproducibility, Climate & Earth Syste↗

DOE OSTI2024

Discovering invariant spatial features in electron energy loss spectroscopy images on the mesoscopic and atomic levels

Over the last two decades, Electron Energy Loss Spectroscopy (EELS) imaging with a scanning transmission electron microscope has emerged as a technique of choice for visualizing complex chemical, electronic, plasmonic, and phononic phenomena in complex materials and structures. The availability of the EELS data necessitates the development of methods to analyze multidimensional data sets with complex spatial and energy structures. Traditionally, the analysis of these data sets has been based on analysis of individual spectra, one at a time, whereas the spatial structure and correlations between individual spatial pixels containing the relevant information of the physics of underpinning processes have generally been ignored and analyzed only via the visualization as 2D maps. Here, we develop a machine learning-based approach and workflows for the analysis of spatial structures in 3D EELS data sets using a combination of dimensionality reduction and multichannel rotationally invariant variational autoencoders. This approach is illustrated for the analysis of both the plasmonic phenomena in a system of nanowires and in the core excitations in functional oxides using low loss and core-loss EELS, respectively. The code developed in this manuscript is open sourced and freely available and provided as a Jupyter notebook for the interested reader.

36 MATERIALS SCIENCE↗