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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 505 records · Page 28

The Software Element of the NASA Portable Electronic Device Radiated Emissions Investigation

NASA Langley Research Center's (LaRC) High Intensity Radiated Fields Laboratory (HIRF Lab) recently conducted a series of electromagnetic radiated emissions tests under a cooperative agreement with Delta Airlines and an interagency agreement with the FAA. The frequency spectrum environment at a commercial airport was measured on location. The environment survey provides a comprehensive picture of the complex nature of the electromagnetic environment present in those areas outside the aircraft. In addition, radiated emissions tests were conducted on portable electronic devices (PEDs) that may be brought onboard aircraft. These tests were performed in both semi-anechoic and reverberation chambers located in the HIRF Lab. The PEDs included cell phones, laptop computers, electronic toys, and family radio systems. The data generated during the tests are intended to support the research on the effect of radiated emissions from wireless devices on aircraft systems. Both tests systems relied on customized control and data reduction software to provide test and instrument control, data acquisition, a user interface, real time data reduction, and data analysis. The software executed on PC's running MS Windows 98 and 2000, and used Agilent Pro Visual Engineering Environment (VEE) development software, Common Object Model (COM) technology, and MS Excel.

Koppen, Sandra V.↗

Short- and Long-Term Propagation of Spacecraft Orbits

The Planetary Observer Planning Software (POPS) comprises four computer programs for use in designing orbits of spacecraft about planets. These programs are the Planetary Observer High Precision Orbit Propagator (POHOP), the Planetary Observer Long-Term Orbit Predictor (POLOP), the Planetary Observer Post Processor (POPP), and the Planetary Observer Plotting (POPLOT) program. POHOP and POLOP integrate the equations of motion to propagate an initial set of classical orbit elements to a future epoch. POHOP models shortterm (one revolution) orbital motion; POLOP averages out the short-term behavior but requires far less processing time than do older programs that perform long-term orbit propagations. POPP postprocesses the spacecraft ephemeris created by POHOP or POLOP (or optionally can use a less accurate internal ephemeris) to search for trajectory-related geometric events including, for example, rising or setting of a spacecraft as observed from a ground site. For each such event, POPP puts out such user-specified data as the time, elevation, and azimuth. POPLOT is a graphics program that plots data generated by POPP. POPLOT can plot orbit ground tracks on a world map and can produce a variety of summaries and generic ordinate-vs.-abscissa plots of any POPP data.

Smith, John C., Jr.↗

Assistant for Analyzing Tropical-Rain-Mapping Radar Data

A document is defined that describes an approach for a Tropical Rain Mapping Radar Data System (TDS). TDS is composed of software and hardware elements incorporating a two-frequency spaceborne radar system for measuring tropical precipitation. The TDS would be used primarily in generating data products for scientific investigations. The most novel part of the TDS would be expert-system software to aid in the selection of algorithms for converting raw radar-return data into such primary observables as rain rate, path-integrated rain rate, and surface backscatter. The expert-system approach would address the issue that selection of algorithms for processing the data requires a significant amount of preprocessing, non-intuitive reasoning, and heuristic application, making it infeasible, in many cases, to select the proper algorithm in real time. In the TDS, tentative selections would be made to enable conversions in real time. The expert system would remove straightforwardly convertible data from further consideration, and would examine ambiguous data, performing analysis in depth to determine which algorithms to select. Conversions performed by these algorithms, presumed to be correct, would be compared with the corresponding real-time conversions. Incorrect real-time conversions would be updated using the correct conversions.

James, Mark↗

GeoNEX-ML: A Machine Learning System for Geostationary Satellite Imagery

Improved capabilities of earth monitoring satellites are enabling a wide range of studies on the environmental effects of climate change, often leveraging the recent advancements in machine learning. At the same time, the new capabilities, including higher spatial resolution and temporal frequency, are expanding the amount of data generated at exponential rates. Further, a large majority of archived datasets generated by scientific processing is never used. This motivates the development of an efficient machine learning system for end-to-end processing of multi-level satellite datasets, from level 1 top of atmosphere observations to user friendly environmental variables of interest. Using current generation geostationary satellites GOES-16/17 (NOAA/NASA), Himawari-8/9 (JAXA), and GK-2A (Korea), we present an interchangeable set of machine models to perform spectral adjustment, physical model emulation, LEO-GEO emulation, and optical flow in a high performance computing environment. We use these tools to generate consistent virtual observations across sensors, perform atmospheric correction and cloud detection, and estimate land surface temperature and atmospheric winds. This approach aims to improve the robustness of remotely sensed data processing by learning from diverse sets of observations while enabling near real-time and on-demand capabilities.

Geostationary satellites↗

GeoNEX-ML: A Machine Learning System for Earth Observations

Improved capabilities of earth monitoring satellites are enabling a wide range of studies on the environmental effects of climate change, often leveraging the recent advancements in machine learning. At the same time, the new capabilities, including higher spatial resolution and temporal frequency, are expanding the amount of data generated at exponential rates. At the NASA Earth eXchange (NEX), we build deep learning methods to learn from cross sensor satellite-based Earth observations for generating new datasets with efficient processing techniques. Using current generation geostationary satellites on NEX, we present an interchangeable set of machine models to perform spectral adjustment, physical model emulation, LEO-GEO emulation, and optical flow. These tools are used to generate consistent virtual observations across sensors, perform atmospheric correction and cloud detection, and estimate land surface temperature and atmospheric winds. This approach aims to improve the robustness of remotely sensed data processing by learning from diverse sets of observations while enabling near real-time and on-demand capabilities.

Geostationary↗

Atmospheric winds with deep optical flow

Improved capabilities of earth monitoring satellites are enabling a wide range of studies on the environmental effects of climate change, often leveraging the recent advancements in machine learning. At the same time, the new capabilities, including higher spatial resolution and temporal frequency, are expanding the amount of data generated at exponential rates. At the NASA Earth eXchange (NEX), we build deep learning methods to learn from cross sensor satellite-based Earth observations for generating new datasets with efficient processing techniques. Using current generation geostationary satellites on NEX, we present an interchangeable set of machine models to perform spectral adjustment, physical model emulation, LEO-GEO emulation, and optical flow. These tools are used to generate consistent virtual observations across sensors, perform atmospheric correction and cloud detection, and estimate land surface temperature and atmospheric winds. This approach aims to improve the robustness of remotely sensed data processing by learning from diverse sets of observations while enabling near real-time and on-demand capabilities.

Atmospheric winds↗

Direct Simulation of Flow over A Wall-Mounted Hump

Simulating separated flows at high Reynolds numbers using Reynolds Averaged Navier-Stokes (RANS) modeled equations remains a challenge in aeronautics. The main hindrance to progress stems from the lack of extended de- tailed data pertinent to the root cause of failure of RANS models, as well as the little progress in RANS modeling innovations in the past several decades. The goal of the current effort is to generate data for separated flow at a Reynolds numbers where conventional models are challenged. We use Direct Numerical Simulations to model turbulent flow over the wall-mounted hump configuration to investigate the physics of flow separation and boundary layer recovery, as well as provide data relevant to the modeling community. A chord-based Reynolds number of Re(sub c) = 47,500 is considered with a turbulent inflow profile of Re(sub θ) = 1,400 (θ /c = 3%). We use FDL3DI, a code that solves the compressible Navier-Stokes equations using high-order compact-difference scheme and filter, with the standard re- cycling/rescaling method of generating turbulent boundary layers as inflow to the computational domain. Two differ- ent configurations of the upper-wall are analyzed for two sets of boundary conditions (slip and no-slip). The results are compared with the available higher Re(sub c) (= 936,000, Re(sub θ) = 7,200, θ /c = 0.77%) experiment for major flow features. The simulated lower Rec allows for DNS-like mesh resolutions, and adequately wide spans. The results from these simulations show earlier separation and delayed reattachment compared to Re(sub c) = 936,000, and significantly higher skin friction in the forebody of the hump. We also find that the upper-wall shape and boundary condition influence pressure distribution over the hump, whereas skin friction is only influenced by the boundary condition.

Wall-Mounted↗

Overview of the NASA Earth Action Strategies Wildland Fire Initiative

As part of NASA’s new Earth Action strategy, the Wildland Fire initiative was established, which includes both the NASA Wildland Fire Program (WFP) and the FireSense project. NASA has over 50 years of experience generating data and technology to enhance fire science and operational management. The WFP’s mission is threefold: 1) assemble communities of practice through collaborative efforts with government, academia, and the private sector; 2) co-develop knowledge and applications with relevant partners and stakeholders in the wildfire community; and 3) improve wildland fire management through the transitioning of NASA data, technology, tools, and science to stakeholder organizations. The WFP is focusing on supporting proactive fire management, including situational awareness, preparedness, and risk mitigation. This will be accomplished through selected projects that identify management challenges, relevant to partners and end users, and the NASA data that will be utilized to deliver innovative solutions to enhance the management of wildland fires. Examples include: i) investigation of evaporative stress from OpenET to help predict the risk of wildfire occurrence in watersheds; ii) incorporation of space based LiDAR for the generation of 3-dimensional forest fuel metrics, used to improve wildfire risk and behavior models; iii) integration of global, multi-platform geostationary active-fire data in near-real-time into NASA’s Fire Information for Resource Management System (FIRMS); and iv) identification of post-fire ecohydrological conditions using thermal, multispectral, synthetic aperture radar (SAR), and hyperspectral remotely-sensed data to improve flood hazard forecast models. The FireSense project is a US-focused 5-year project that will focus on delivering NASA’s unique Earth science and technological capabilities to operational agencies, striving towards enhancing fire fighting and air quality management. The project will include airborne campaigns and new technology that will likely have global implications. Initial stakeholder engagement led FireSense to focus on four use-cases focused on the characterization and measurement of: (i) pre-fire fuels conditions, (ii) active fire-dynamics; (iii) post-fire impact and threats; and iv) air quality impacts and forecasting, each-developed with identified stakeholders.

Wildland Fire program↗

Unique strategies for technical information management at Johnson Space Center

In addition to the current NASA manned programs, the maturation of Space Station and the introduction of the Space Exploration programs are anticipated to add substantially to the number and variety of data and documentation at NASA Johnson Space Center (JSC). This growth in the next decade has been estimated at five to ten fold compared to the current numbers. There will be an increased requirement for the tracking and currency of space program data and documents with National pressures to realize economic benefits from the research and technological developments of space programs. From a global perspective the demand for NASA's technical data and documentation is anticipated to increase at local, national, and international levels. The primary users will be government, industry, and academia. In our present national strategy, NASA's research and technology will assume a great role in the revitalization of the economy and gaining international competitiveness. Thus, greater demand will be placed on NASA's data and documentation resources. In this paper the strategies and procedures developed by DDMS, Inc., to accommodate the present and future information utilization needs are presented. The DDMS, Inc., strategies and procedures rely on understanding user requirements, library management issues, and technological applications for acquiring, searching, storing, and retrieving specific information accurately and quickly. The proposed approach responds to changing customer requirements and product deliveries. The unique features of the proposed strategy include: (1) To establish customer driven data and documentation management through an innovative and unique methods to identify needs and requirements. (2) To implement a structured process which responds to user needs, aimed at minimizing costs and maximizing services, resulting in increased productivity. (3) To provide a process of standardization of services and procedures. This standardization is the central theme of the strategic approach. It will allow Division level Data and Documentation Libraries (DDL's) to function independently and optimize efficiency at the Directorate level. This process also facilitates interconnectivity between Division level DDL's and makes them transparent to the users. (4) To implement the process of 'cost savings', and at the same time the objective is to gain substantial improvement in the organization, categorization, and preservation of JSC-generated data and documentation, and (5) To find, locate, retrace, restore, and preserve the Center-generated crucial scientific and technical information that has been and is being provided by the engineers and scientists of JSC. This is important to the preservation of 'lessons learned'. Preliminary estimates of the possible cost savings which will result from the implementation of this process will also be discussed in this paper.

Krishen, Vijay↗

Harnessing on-machine metrology data for prints with a surrogate model for laser powder directed energy deposition

In this study, we leverage the massive amount of multi-modal on-machine metrology data generated from Laser Powder Directed Energy Deposition (LP-DED) to construct a comprehensive surrogate model of the 3D printing process. By employing Dynamic Mode Decomposition with Control (DMDc), a data-driven technique, we capture the complex physics inherent in this extensive dataset. This physics-based surrogate model emphasizes thermodynamically significant quantities, enabling us to accurately predict key process outcomes. The model ingests 21 process parameters, including laser power, scan rate, and position, while providing outputs such as melt pool temperature, melt pool size, and other essential observables. Furthermore, it incorporates uncertainty quantification to provide bounds on these predictions, enhancing reliability and confidence in the results. We then deploy the surrogate model on a new, unseen part and monitor the printing process as validation of the method. Our experimental results demonstrate that the predictions align with actual measurements with high accuracy, confirming the effectiveness of our approach. Furthermore, this methodology not only facilitates real-time predictions but also operates at process-relevant speeds, establishing a basis for implementing feedback control in LP-DED.

Digital twins↗

Microstructure and Mechanical Properties of Ni-based Alloys Fabricated by Laser Powder Bed Fusion

The Advanced Materials and Manufacturing Technologies (AMMT) program is aiming at the accelerated incorporation of new materials and manufacturing technologies into nuclear-related systems. Complex Ni-based components fabricated by laser powder bed fusion (LPBF) could enable operating temperatures at T > 700°C in aggressive environments such as molten salts or liquid metals. However, available mechanical properties data relevant to material qualification remains limited, in particular for Ni-based alloys routinely fabricated by LPBF such as IN718 (Ni- 19Cr-18Fe-5Nb-3Mo) and Haynes 282 (Ni-20Cr-10Co-8.5Mo-2.1Ti-1.5Al). Creep testing was conducted on LPBF 718 at 600°C and 650°C and on LPBF 282 at 750°C. finding that the creep strength of the two alloys was close to that of wrought counterparts. with lower ductility at rupture. Heat treatments were tailored to the LPBF-specific microstructure to achieve grain recrystallization and form strengthening γ' precipitates for LPBF 282 and γ' and γ" precipitates for LPBF 718. In-situ data generated during printing and ex-situ X-ray computed tomography (XCT) scans were used to correlate the creep properties of LPBF 282 to the material flaw distribution. In- situ data revealed that spatter particles are the potential causes for flaws formation in LPBF 282. with significant variation between rods based on their location on the build plate. XCT scans revealed the formation of a larger number of creep flaws after testing in the specimens with a higher initial flaw density. which led to a lower ductility for the specimen.

Dryepondt, Sebastien↗

Deep Learning System for Efficient Processing of Geostationary Satellite Imagery

Improved capabilities of Earth monitoring satellites are enabling a wide range of studies on the environmental effects of climate change, often leveraging the recent advancements in machine learning. At the same time, the new capabilities, including higher spatial resolution and temporal frequency, are expanding the amount of data generated at exponential rates. Further, a large majority of archived datasets generated by scientific processing is never used. This motivates the development of an efficient machine learning system for end-to-end processing of multi-level satellite datasets, from level 1 top of atmosphere observations to user friendly environmental variables of interest. Using current generation geostationary satellites GOES-16/17 (NOAA/NASA), and Himawari-8/9 (JAXA), we present an interchangeable set of machine models to perform spectral adjustment among sensors, physical model emulation, LEO-GEO emulation, and optical flow in a high performance computing environment. We use these tools on the NASA Earth eXchange (NEX) to generate consistent virtual observations across sensors, perform atmospheric correction and cloud detection, and estimate surface reflectance, surface temperature and atmospheric winds. This approach aims to improve the robustness of remotely sensed data processing by learning from diverse sets of observations while enabling near real-time and on-demand capabilities.

Thomas Vandal↗

Space Shuttle Plume Simulation Effect on Aerodynamics

Technology for simulating plumes in wind tunnel tests was not adequate to provide the required confidence in test data where plume induced aerodynamic effects might be significant. A broad research program was undertaken to correct the deficiency. Four tasks within the program are reported. Three of these tasks involve conducting experiments, related to three different aspects of the plume simulation problem: (1) base pressures; (2) lateral jet pressures; and (3) plume parameters. The fourth task involves collecting all of the base pressure test data generated during the program. Base pressures were measured on a classic cone ogive cylinder body as affected by the coaxial, high temperature exhaust plumes of a variety of solid propellant rockets. Valid data were obtained at supersonic freestream conditions but not at transonic. Pressure data related to lateral (separation) jets at M infinity = 4.5, for multiple clustered nozzles canted to the freestream and operating at high dynamic pressure ratios. All program goals were met although the model hardware was found to be large relative to the wind tunnel size so that operation was limited for some nozzle configurations.

Hair, L. M.↗

PCDS as a tool in teaching and research at the University of Michigan

The Space Physics Research Laboratory's (SPRL) use of the Pilot Climate Data System (PCDS) is discussed. For this purpose, a computer center was established to provide the hardware and software necessary to fully utilize existing data bases for research and teaching purposes. A schematic of the SPRL network is given. The core of the system consists of two VAX 11/750s and a VAX 8600, networked through ETHERNET to several LSI 11/23 microprocessors. Much of the system is used for external communications with major networks and data centers. A VAX 11/750 provides DECNET services through the SPAN network to the PCDS. A functional diagram of PCDS usage is given. The browsing capabilities of the PCDS are used to generate data files, which are later transferred to the SPRL center for further data manipulation and display. This mode of operation for classroom instruction will be used to effectively use terminals and to simplify usage of the data base. The Atmosphere Explorer data base has been used successfully in a similar manner in courses related to the thermosphere and ionosphere. The main motivation to access the PCDS was to complement research efforts related to the High Resolution Doppler Imager (HRDI), to be flown on the Upper Atmosphere Research Satellite (UARS).

Abreu, V.↗

Model Output Is Data, Too: And Other Futuristic Views

The NASA space science data environment has been undergoing significant changes during the past decade: Data has become significantly more voluminous and more varied. At the same time it became much more openly available to the scientific community. As a result a number of efforts have been made to document the data content at NSSDC/SPDF, PDS, the ISTP program and more recently as part of the newly developing Virtual Observatories. Concurrently, our need to access data has become much more immediate dictating a distributed environment where users can obtain their data directly from the production sites. But where does this change lead? And what more needs to be done to further enable scientific productivity? A view of our data system 5- years in the future will be offered that envisions distributed data processing services whereby the user can obtain the type of data that is needed not necessarily what is produced. Moreover, in an ideal system the means should exist to treat models as instruments allowing the ready mixing of their output with spacecraft generated data.

Szabo, A.↗

A Noise and Emissions Assessment of the N3-X Transport

Analytical predictions of certification noise and exhaust emissions for NASA's N3-X - a notional, hybrid wingbody airplane - are presented in this paper. The N3-X is a 300-passenger concept transport propelled by an array of fans distributed spanwise near the trailing edge of the wingbody. These fans are driven by electric motors deriving power from twin generators driven by turboshaft engines. Turboelectric distributed hybrid propulsion has the potential to dramatically increase the propulsive efficiency of aircraft. The noise and exhaust emission estimates presented here are generated using NASA's conceptual design systems analysis tools with several key modifications to accommodate this unconventional architecture. These tools predict certification noise and the emissions of oxides of nitrogen by leveraging data generated from a recent analysis of the N3-X propulsion system.

Berton, Jeffrey J.↗

Monte Carlo Tree Search Methods for the Earth-Observing Satellite Scheduling Problem

This work explores on-board planning for the single spacecraft, multiple ground station Earth-observing satellite scheduling problem through artificial neural network function approximation of state–action value estimates generated by Monte Carlo tree search (MCTS). An extensive hyperparameter search is conducted for MCTS on the basis of performance, safety, and downlink opportunity utilization to determine the best hyperparameter combination for data generation. A hyperparameter search is also conducted on neural network architectures. The learned behavior of each network is explored, and each network architecture’s robustness to orbits and epochs outside of the training distributions is investigated. Furthermore, each algorithm is compared with a genetic algorithm, which serves to provide a baseline for optimality. MCTS is shown to compute near-optimal solutions in comparison to the genetic algorithm. The state–action value networks are shown to match or exceed the performance of MCTS in six orders of magnitude less execution time, showing promise for execution on board spacecraft.

Adam P. Herrmann↗

Adsorptive denitrogenation of model aviation fuel using mesoporous silica in a packed bed adsorption system

This study aims to understand the effects of system process parameters such as flow rate, adsorbent particle size, and use of recycled adsorbent on denitrogenation performance of a model fuel using mesoporous silica gel. The goal is to reduce the nitrogen content of the model fuel from 1500 parts per million to single-digit ppm to meet ASTM specifications for drop-in fuels. This work was done with the intent of applying adsorptive denitrogenation to sustainable aviation fuel (SAF) product fractions produced via hydrothermal liquefaction (HTL). The adsorption performance of the silica is evaluated via packed column breakthrough data, with data generated from collecting from the column outlet and quantifying nitrogen content via gas chromatography. Select experiments use a significantly larger (2.5x column diameter and length) column to demonstrate linear scalability of the process. Thermogravimetric analysis data is collected to evaluate the effects of thermal calcination as a sorbent regeneration method. Effects of a more complex feed are also investigated using a known reference fuel with additional added nitrogen containing compounds. The results presented in this work successfully demonstrate up to 99.8 % removal of NCCs from a model fuel fraction at an original NCC concentration of approximately 1500 ppm to single-digit parts per million after treatment. We also examine calcination of sorbent materials to remove the adsorbed species to enable sorbent reuse and minimize waste generation and show that the calcined material can be reused up to 5 cycles with reduced adsorption capacity. Overall, this work indicates that adsorptive denitrogenation using silica gel is a viable solution to enable the integration of HTL-derived aviation fuels into existing fuel infrastructure.

Adsorption techniques↗