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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 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Finite Element Analysis and Test Correlation of a 10-Meter Inflation-Deployed Solar Sail

Under the direction of the NASA In-Space Propulsion Technology Office, the team of L Garde, NASA Jet Propulsion Laboratory, Ball Aerospace, and NASA Langley Research Center has been developing a scalable solar sail configuration to address NASA's future space propulsion needs. Prior to a flight experiment of a full-scale solar sail, a comprehensive phased test plan is currently being implemented to advance the technology readiness level of the solar sail design. These tests consist of solar sail component, subsystem, and sub-scale system ground tests that simulate the vacuum and thermal conditions of the space environment. Recently, two solar sail test articles, a 7.4-m beam assembly subsystem test article and a 10-m four-quadrant solar sail system test article, were tested in vacuum conditions with a gravity-offload system to mitigate the effects of gravity. This paper presents the structural analyses simulating the ground tests and the correlation of the analyses with the test results. For programmatic risk reduction, a two-prong analysis approach was undertaken in which two separate teams independently developed computational models of the solar sail test articles using the finite element analysis software packages: NEiNastran and ABAQUS. This paper compares the pre-test and post-test analysis predictions from both software packages with the test data including load-deflection curves from static load tests, and vibration frequencies and mode shapes from vibration tests. The analysis predictions were in reasonable agreement with the test data. Factors that precluded better correlation of the analyses and the tests were uncertainties in the material properties, test conditions, and modeling assumptions used in the analyses.

Sleight, David W.↗
NASA NTRS2005

Structural Analysis of an Inflation-Deployed Solar Sail With Experimental Validation

Under the direction of the NASA In-Space Propulsion Technology Office, the team of L Garde, NASA Jet Propulsion Laboratory, Ball Aerospace, and NASA Langley Research Center has been developing a scalable solar sail configuration to address NASA s future space propulsion needs. Prior to a flight experiment of a full-scale solar sail, a comprehensive phased test plan is currently being implemented to advance the technology readiness level of the solar sail design. These tests consist of solar sail component, subsystem, and sub-scale system ground tests that simulate the vacuum and thermal conditions of the space environment. Recently, two solar sail test articles, a 7.4-m beam assembly subsystem test article and a 10-m four-quadrant solar sail system test article, were tested in vacuum conditions with a gravity-offload system to mitigate the effects of gravity. This paper presents the structural analyses simulating the ground tests and the correlation of the analyses with the test results. For programmatic risk reduction, a two-prong analysis approach was undertaken in which two separate teams independently developed computational models of the solar sail test articles using the finite element analysis software packages: NEiNastran and ABAQUS. This paper compares the pre-test and post-test analysis predictions from both software packages with the test data including load-deflection curves from static load tests, and vibration frequencies and mode shapes from structural dynamics tests. The analysis predictions were in reasonable agreement with the test data. Factors that precluded better correlation of the analyses and the tests were uncertainties in the material properties, test conditions, and modeling assumptions used in the analyses.

Sleight, David W.↗
NASA NTRS2007

Airborne RF Measurement System (ARMS) and Analysis of Representative Flight RF Environment

Environmental radio frequency (RF) data over a broad band of frequencies (30 MHz to 1000 MHz) were obtained to evaluate the electromagnetic environment in airspace around several airports. An RF signal measurement system was designed utilizing a spectrum analyzer connected to the NASA Lancair Columbia 300 aircraft's VHF/UHF navigation antenna. This paper presents an overview of the RF measurement system and provides analysis of sample RF signal measurement data. This aircraft installation package and measurement system can be quickly returned to service if needed by future projects requiring measurement of an RF signal environment or exploration of suspected interference situations.

Koppen, Sandra V.↗
NASA NTRS2017

Atmospheric Correction for Hyperspectral Ocean Color Retrieval with Application to the Hyperspectral Imager for the Coastal Ocean (HICO)

The classical multi-spectral Atmospheric Correction (AC) algorithm is inadequate for the new generation of spaceborne hyperspectral sensors such as NASA's first hyperspectral Ocean Color Instrument (OCI) onboard the anticipated Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) satellite mission. The AC process must estimate and remove the atmospheric path radiance contribution due to the Rayleigh scattering by air molecules and scattering by aerosols from the measured top-of-atmosphere (TOA) radiance, compensate for the absorption by atmospheric gases, and correct for reflection and refraction of the air-sea interface. In this work, we present and evaluate an improved AC for hyperspectral sensors developed within NASA's Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Data Analysis System software package (SeaDAS). The improvement is based on combining the classical AC approach of multi-spectral capabilities to correct for the atmospheric path radiance, extended to hyperspectral, with a gas correction algorithm to compensate for absorbing gases in the atmosphere, including water vapor. The SeaDAS-hyperspectral version is capable of operationally processing the AC of any hyperspectral airborne or spaceborne sensor. The new algorithm development was evaluated and assessed using the Hyperspectral Imager for Coastal Ocean (HICO) scenes collected at the Marine Optical BuoY (MOBY) site, and other SeaWiFS Bio-optical Archive and Storage System (SeaBASS) and AERosol Robotic NETwork - Ocean Color (AERONET-OC) coastal sites. A hyperspectral vicarious calibration was applied to HICO, showing the validity and consistency of HICO's ocean color products. The hyperspectral AC capability is currently available in SeaDAS to the scientific community at https://oceancolor.gsfc.nasa.gov/.

Ocean Color↗
NASA NTRS2018

Double Data Rate (DDR) Memory Devices

This presentation will include information about Double Data Rate (DDR) technology, NASA Electronic Parts and Packaging (NEPP) tasks and their purpose, collaborations, a roadmap, NEPP partners, results to date, and future plans.

NASA Electronic Parts and Packaging (NEPP) Program↗
NASA NTRSDate not supplied

Nancy Grace Roman Space Telescope Observatory Implementation and Challenges

NASA’s Nancy Grace Roman Space Telescope (Roman) is a deep space infrared observatory with a Hubble-sized telescope and wide field of regard with a boresight view greater than 200 times that of the Hubble Wide Field Camera 3infrared field of view, that will conduct a suite of science surveys to characterize dark energy and expand the census of exoplanets in our galaxy. Roman will also demonstrate exoplanet coronagraphy with active wavefront control technology and provide general investigator opportunities for the science community. Roman is finishing the critical design phase and is planning for launch in 2026. It will operate at the second Sun-Earth-Moon Lagrange for a five-year primary mission life. The Observatory features a telescope with an existing, repurposed 2.4m primary mirror, a Wide Field Instrument with a near-infrared detector focal plane array and optical elements for imaging and spectroscopy, as well as a Coronagraph instrument technology demonstration for direct imaging and spectroscopy of exoplanets. The telescope and instruments are mounted to an Instrument Carrier for optical metering and isolation from Spacecraft-induced disturbances. The Spacecraft includes a Bus, Solar Array Sunshield, Deployable Aperture Cover, Outer Barrel Assembly, and Star Tracker/Inertial Reference Unit Bench. When fully integrated, Roman will be the largest Observatory assembled and tested at NASA’s Goddard Space Flight Center. The development of scientific satellites is challenging and pushes engineering boundaries to broaden scientific knowledge. The Roman mission implementation is a prime example and expected challenges have been amplified by the foundational decision to use existing, repurposed telescope components. Other unique aspects of the Roman mission, including its survey nature, large data volume, and Observatory packaging, create constrained design spaces that drive competing requirements across Observatory subsystems. Given these challenges, systems engineering has been a critical discipline in balancing implementation decisions and will continue to play a key role in the development of the Roman mission. This paper will discuss details of the Roman Observatory configuration, systems engineering challenges and the decision-making process used to mature the Roman Space Telescope from preliminary design to implementation.

Lisa M L Bartusek↗
NASA NTRSDate not supplied

Beyond Gravity Single Launch Payload Accommodations Shock Testing

The Vulcan Centaur launch vehicle is purpose-built to meet all the U.S. government’s National Security Space Launch (NSSL) needs. A shock test for the Centaur V’s payload accommodations (PLA), single launch (SL) configuration was successfully conducted at NASA’s Marshall Space Flight Center (MSFC) in Huntsville, Alabama, in May 2021. This test was a joint effort between MSFC, Beyond Gravity and United Launch Alliance. The primary purpose of the shock test was to characterize the shock environment induced by the separation event on components attached to the PLA and its interfaces. Additional test requirements included: (1) verifying the payload fairing (PLF) did not contact the flight hardware during the mechanical separation of the PLF horizontal separation system (HSS) and (2) evaluating the performance of the HSS spring packages during jettison. The data acquired during the PLF SL shock test will be used to validate the shock predictions from pre-test analysis of the launch vehicle and the PLF separation analysis. This paper provides an overview of the PLA SL shock test planning and execution as well as the required catch system, instrumentation and results.

separation↗
NASA NTRSDate not supplied

Beyond Gravity Single Launch Payload Accommodations Shock Testing

The Vulcan Centaur launch vehicle is purpose-built to meet all the U.S. government’s National Security Space Launch (NSSL) needs. A shock test for the Centaur V’s payload accommodations (PLA), single launch (SL) configuration was successfully conducted at NASA’s Marshall Space Flight Center (MSFC) in Huntsville, Alabama, in May 2021. This test was a joint effort between MSFC, Beyond Gravity and United Launch Alliance. The primary purpose of the shock test was to characterize the shock environment induced by the separation event on components attached to the PLA and its interfaces. Additional test requirements included: (1) verifying the payload fairing (PLF) did not contact the flight hardware during the mechanical separation of the PLF horizontal separation system (HSS) and (2) evaluating the performance of the HSS spring packages during jettison. The data acquired during the PLF SL shock test will be used to validate the shock predictions from pre-test analysis of the launch vehicle and the PLF separation analysis. This paper provides an overview of the PLA SL shock test planning and execution as well as the required catch system, instrumentation and results.

separation↗
NASA NTRSDate not supplied

Beyond Gravity Single Launch Payload Accommodations Shock Testing

The Vulcan Centaur launch vehicle is purpose-built to meet all the U.S. government’s National Security Space Launch (NSSL) needs. A shock test for the Centaur V’s payload accommodations (PLA), single launch (SL) configuration was successfully conducted at NASA’s Marshall Space Flight Center (MSFC) in Huntsville, Alabama, in May 2021. This test was a joint effort between MSFC, Beyond Gravity and United Launch Alliance. The primary purpose of the shock test was to characterize the shock environment induced by the separation event on components attached to the PLA and its interfaces. Additional test requirements included: (1) verifying the payload fairing (PLF) did not contact the flight hardware during the mechanical separation of the PLF horizontal separation system (HSS) and (2) evaluating the performance of the HSS spring packages during jettison. The data acquired during the PLF SL shock test will be used to validate the shock predictions from pre-test analysis of the launch vehicle and the PLF separation analysis. This paper provides an overview of the PLA SL shock test planning and execution as well as the required catch system, instrumentation and results.

separation↗
NASA NTRS2024

Xstar Atomic Database: The PyXstar Package

We present a progress report on the development of PyXstar, a Python package to manage the data (input, output, intermediate, atomic database, and model-grids) associated with the XSTAR code for treating photoionized and collisionally ionized plasmas. The PyXstar modular structure and database retrieval scheme are described, and its functionality is illustrated with Python functions and classes for performing database searches. We briefly compare PyXstar with two other Python spectrum modeling tools: PyNeb and PyAtomDB.

Claudio Mendoza↗
DOE OSTI2021

Real-Time XFEL Data Analysis at SLAC and NERSC: a Trial Run of Nascent Exascale Experimental Data Analysis

X-ray scattering experiments using Free Electron Lasers (XFELs) are a powerful tool to determine the molecular structure and function of unknown samples (such as COVID-19 viral proteins). XFEL experiments are a challenge to computing in two ways: i) due to the high cost of running XFELs, a fast turnaround time from data acquisition to data analysis is essential to make informed decisions on experimental protocols; ii) data collection rates are growing exponentially, requiring new scalable algorithms. Here we report our experiences analyzing data from two experiments at the Linac Coherent Light Source (LCLS) during September 2020. Raw data were analyzed on NERSC's Cori XC40 system, using the Superfacility paradigm: our workflow automatically moves raw data between LCLS and NERSC, where it is analyzed using the software package CCTBX. We achieved real time data analysis with a turnaround time from data acquisition to full molecular reconstruction in as little as 10 min -- sufficient time for the experiment's operators to make informed decisions. By hosting the data analysis on Cori, and by automating LCLS-NERSC interoperability, we achieved a data analysis rate which matches the data acquisition rate. Furthermore, completing data analysis with 10 mins is a first for XFEL experiments and an important milestone if we are to keep up with data collection trends.

Blaschke, Johannes P.↗
DOE OSTI2022

Analysis of SCALE Criticality and Sensitivity Calculations for Reflected HEU Cylinders [Abstract]

The SCALE code package offers several nuclear data libraries to support Monte Carlo (MC) transport, as well as MC-based derivation of $\kappa$ eff sensitivity and uncertainty (S/U) data. The CSAS sequence using the KENO MC code can utilize continuous-energy (CE) cross sections, or pre-generated multigroup (MG) cross section libraries. The use of MG libraries introduces bias into calculations in exchange for faster transport solutions. The TSUNAMI-3D sequence also utilizes KENO MC calculations. TSUNAMI-3D has two CE calculational methods: the Iterated Fission Probability (IFP) method, and the Contribution-Linked eigenvalue sensitivity/Uncertainty estimation via Tracklength importance CHaracterization (CLUTCH) method. Previous work has shown poor agreement between CLUTCH and confirmatory direct perturbation calculations in specific applications, e.g., fissionable and polyethylene reflectors

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2019

The Dragonfly Entry and Descent System

Dragonfly is a proposed New Frontiers class mission that will send a nuclear powered octocopter to the surface of Titan for an extended science mission. This presentation will provide an overview of the Entry and Descent system that is under development to ensure the save delivery of this unique "relocatable lander" to Titan. Titan's dense atmosphere, large atmospheric scale height, and low gravity allows for a slow-paced entry and descent sequence that lasts more than 100 minutes, as opposed to the "7 minutes of terror" that is charac-teristic of landed Mars missions. This slow pace al-lows for sufficient temporal separation between critical events of the EDL sequence to minimize overall risk.The Dragonfly entry and descent system is composed of high-heritage components, minimizing overall risk. The aeroshell will be a scaled Genesis Sample Return capsule with a diameter of 3.75 meters, built by Lock-heed Martin. The thermal protection system (TPS) is made up of Phenolic Impregnated Carbon Ablator-Domestic (PICA-D) on the heatshield, SLA-561V on the backshell, and SLA-220M on the aft cover and low gain antenna. Each material has extensive heritage for the chosen application. The spacecraft will enter Titan at a velocity of 7.3 km/s, resulting in a predicted fully margined stagnation point heating environment of 254 W/cm2 heat rate and 13 kJ/cm2 heat load, well within the tested limits of the chosen materials. The aeroheat-ing environments, including the significant contribu-tion of shock layer radiation from CN on both the heatshield and backshell, are evaluated using state of the art models and codes that have been validated with appropriate ground testing.Once the deceleration pulse is complete, a disk-gap-band (DGB) drogue parachute will be deployed at ap-proximately Mach 1.5 to stabilize and further deceler-ate the spacecraft. Due to the dense atmosphere, the spacecraft will spend more than 80 minutes on this parachute, until reaching an appropriate altitude to de-ploy the subsonic main parachute. The lander is re-leased after approximately 17 minutes on the main chute before releasing and transitioning to powered flight in order to navigate to its first landing site. The release of the lander from the backshell effectively ends the entry and descent portion of the mission.The full presentation will provide additional details about the design of the EDL system hardware, engi-neering design, and overall con-ops. Preliminary aero-thermal and TPS sizing analyses will be presented, and the parachute system will be described in greater detail. In addition, the Dragonfly spacecraft will carry an En-gineering Science Investigation (ESI) package designed to obtain engineering data during EDL that will be used to validate the design methodology for future missions. An overview of the proposed ESI package will also be presented.

EDL↗
DOE OSTI2025

Electricity Baseline 2022 Background Data and Log File

The ElectricityLCI v2 Python package (https://github.com/USEPA/ElectricityLCI/tree/v2.0) was used to generate the 2022 electricity baseline: a regionalized life cycle inventory model of U.S. electricity generation, consumption, and distribution using standardized facility and generation data. ElectricityLCI implements a local data store for downloading and accessing public data on an individual's computer. The data store follows the folder definition provided by USEPA's esupy Python package (https://github.com/USEPA/esupy), which utilized the appdirs Python dependency (https://pypi.org/project/appdirs/). This submission includes the background data used to generate the 2022 electricity baseline inventory. Each zip archive stores the source files as found in their data stores. Sub-folders in each of the data stores are archived separately. For example, stewi.zip contains the JSON files, while stewi.facility.zip is the 'facility' sub-folder of stewi data store that stores the parquet files. To reproduce the data store, extract each zip file and drag-and-drop sub-folders in to their appropriate root folders to recreate the data stores, then copy the root folders to your data store folder (as returned by running the following on the command line: `python -c "import appdirs; print(appdirs.user_data_dir())"`). The main five data stores include: 'electricitylci', 'facilitymatcher', 'fedelemflowlist', 'stewi', and 'stewicombo'. The log file generated by the 2022 model run is also included, which contains the statements at the DEBUG level and above.

Electricity; LCA; data inventory↗
DOE OSTI2025

Electricity Baseline 2021 Background Data and Log File

The ElectricityLCI v2 Python package (https://github.com/USEPA/ElectricityLCI/tree/v2.0) was used to generate the 2021 electricity baseline: a regionalized life cycle inventory model of U.S. electricity generation, consumption, and distribution using standardized facility and generation data. ElectricityLCI implements a local data store for downloading and accessing public data on an individual's computer. The data store follows the folder definition provided by USEPA's esupy Python package (https://github.com/USEPA/esupy), which utilizes the appdirs Python dependency (https://pypi.org/project/appdirs/). An overview of the ElectricityLCI data stores may be found on the README (https://github.com/USEPA/ElectricityLCI/blob/v2.0/README.md#data-store). This submission includes the background data used to generate the 2021 electricity baseline inventory. Each zip archive stores the source files as found in their data stores. Sub-folders in each of the data stores are archived separately. For example, stewi.zip contains the JSON files, while stewi.facility.zip is the 'facility' sub-folder of stewi data store that stores the parquet files. To reproduce the data store, extract each zip file and drag-and-drop sub-folders in to their appropriate root folders to recreate the data stores, then copy the root folders to your data store folder (as returned by running the following on the command line: python -c "import appdirs; print(appdirs.user_data_dir())"). The main five data stores include: 'electricitylci', 'facilitymatcher', 'fedelemflowlist', 'stewi', and 'stewicombo'. The log file generated by the 2021 model run is also included, which contains the statements at the DEBUG level and above.

Electricity; LCA; LCI; Life Cycle; data inventory↗
DOE OSTI2025

Electricity Baseline 2020 Background Data and Log File

The ElectricityLCI v2 Python package (https://github.com/USEPA/ElectricityLCI/tree/v2.0) was used to generate the 2020 electricity baseline: a regionalized life cycle inventory model of U.S. electricity generation, consumption, and distribution using standardized facility and generation data. ElectricityLCI implements a local data store for downloading and accessing public data on an individual's computer. The data store follows the folder definition provided by USEPA's esupy Python package (https://github.com/USEPA/esupy), which utilizes the appdirs Python dependency (https://pypi.org/project/appdirs/). An overview of the ElectricityLCI data stores may be found on the README (https://github.com/USEPA/ElectricityLCI/blob/v2.0/README.md#data-store). This submission includes the background data used to generate the 2020 electricity baseline inventory. Each zip archive stores the source files as found in their data stores. Sub-folders in each of the data stores are archived separately. For example, stewi.zip contains the JSON files, while stewi.facility.zip is the 'facility' sub-folder of stewi data store that stores the parquet files. To reproduce the data store, extract each zip file and drag-and-drop sub-folders in to their appropriate root folders to recreate the data stores, then copy the root folders to your data store folder (as returned by running the following on the command line: python -c "import appdirs; print(appdirs.user_data_dir())"). The main five data stores include: 'electricitylci', 'facilitymatcher', 'fedelemflowlist', 'stewi', and 'stewicombo'. The log file generated by the 2020 model run is also included, which contains the statements at the DEBUG level and above.

Electricity; LCA; LCI; Life Cycle; data inventory↗
NASA NTRS1990

Managing Mobile/Satellite Propagation Data

"Data Management System for Mobile Satellite Propagation" software package collection of FORTRAN programs and UNIX shell scripts designed to handle huge amounts of data resulting from mobile/satellite radio-propagation experiments. Data from experiments converted into standard and more useful forms. Software package contains program to convert binary format of data into standard ASCII format suitable for use with wide variety of computing-machine architectures. Written in either FORTRAN 77 or UNIX shell scripts.

Kantak, Anil V.↗
DOE OSTI2024

Deeplynx Airflow Provider Package

The DeepLynx Airflow Provider Package is a python package used to interact with the data warehouse DeepLynx when using the workflow orchestration tool Apache Airflow. This python package is packaged together using the airflow package standard so that it can be easily installed and used in any Apache Airflow environment. This package is meant to encapsulate the DeepLynx API for use in Airflow so that any interactions with DeepLynx that a user may want to use in their Airflow workflow can be easily accomplished using this provider package. This allows us to develop, implement, and test our DeepLynx-Airflow interactions in one provider package repository, and then easily install and use this package in any airflow instance. This DeepLynx Airflow Provider Package will be used extensively by the DeepLynx DAG repository.

Cavaluzzi, JackM↗