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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 235 records · Page 13
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NASA NTRSDate not supplied

Comparison of Exploration Portable Life Support Subsystem (xPLSS) Thermal Modeling to Thermal Vacuum Testing

To support NASA’s goal to return to the Moon through the Artemis mission, the development of an exploration portable life support system (xPLSS) has been conducted at Johnson Space Center (JSC). As part of this development process, a large system level thermal/fluid model of the xPLSS was developed using Thermal Desktop and an in-house human model (METMAN). The xPLSS model was used throughout the design process to predict the performance and temperature of nearly all components within the xPLSS. In the fall of 2023, the design, verification, and testing (DVT) unit of the xPLSS was tested in a thermal vacuum (TVAC) chamber at JSC. This testing consisted of combining the xPLSS with an upper torso of the exploration pressure garment system (xPGS) and simulating five extravehicular activities (EVAs) in extreme thermal conditions (two cold EVAs and three hot EVAs). The data generated in this test series provided system level data of the xPLSS operating in vacuum and at flight-like environmental temperatures for the first time. This data was compared to results output by the xPLSS system model to assess the accuracy of previous analyses and improve the fidelity and accuracy of the xPLSS system model. The comparison between model and test hardware provides valuable insight that will help improve the design and fidelity of next generation space suits. In general, comparison between test data and model data generally showed slightly un-conservative values (model predicting colder temperatures than test in hot environments, and hotter temperatures than test in cold environments). Model assumptions and test assumptions were assessed to understand potential causes of some of these sources in error. Recommendations to improve the fidelity of the xPLSS model were also made based on the results presented in this paper.

xPLSS↗
NASA NTRSDate not supplied

Comparison of Exploration Portable Life Support Subsystem (xPLSS) Thermal Modeling to Thermal Vacuum Testing

To support NASA’s goal to return to the Moon through the Artemis Mission, the development of an Exploration Portable Life Support Subsystem (xPLSS) has been conducted at Johnson Space Center (JSC). As part of this development process, a large system level thermal/fluid model of the xPLSS was developed using Thermal Desktop and an in-house human model (METMAN). The xPLSS model was used throughout the design process to predict the performance and temperature of nearly all components within the xPLSS. In the fall of 2023, the Design, Verification, and Testing (DVT) unit of the xPLSS was tested in a thermal vacuum (TVAC) chamber at JSC. This testing consisted of combining the xPLSS with an upper torso of the Exploration Pressure Garment System (xPGS) and simulating five Extravehicular Activities (EVAs) in extreme thermal conditions (two cold EVAs and three hot EVAs). The data generated in this test series provided system level data of the xPLSS operating in vacuum and at flight-like environmental temperatures for the first time. These data were compared to results output by the xPLSS system model to assess the accuracy of previous analyses and improve the fidelity and accuracy of the xPLSS system model. The comparison between model and test hardware provides valuable insight that will help improve the design and fidelity of next generation space suits. In general, comparison between test data and model data generally showed slightly un-conservative values (model predicting colder temperatures than test in hot environments, and hotter temperatures than test in cold environments). Model assumptions and test assumptions were assessed to understand potential causes of some of these sources in error. Recommendations to improve the fidelity of the xPLSS model were also made based on the results presented in this paper.

xPLSS↗
NASA NTRSDate not supplied

NASA Space Launch System Artemis I & II Post Flight Ascent Aerothermal Environments Overview

Since 2011 the Aerosciences Branch/EV33 at NASA Marshall Space Flight Center has been involved with the development of ascent external aerothermal environments for the NASA Space Launch System (SLS) Block 1 launch vehicle for the purposes of supporting thermal analysis and the design of thermal protection systems. The SLS Block 1 Artemis I and II launch vehicles successfully launched from Pad39B at NASA Kennedy Space Center on November 16th, 2022 and April 1st, 2026, respectively. Over 70 aerothermal islands, consisting of over 265 operational instruments captured aerodynamic heating and plume induced environments throughout the launch vehicles. Gauges consisted of calorimeters, radiometers, gas temperature probes, pressure transducers, bi-directional pressure probes and thermocouples. Prior to launch, aerothermal design environment models were generated to predict ascent aerodynamic heating and plume induced environments over a design space that covered a range of vehicle trajectories that varied atmospheric, vehicle performance, and off-nominal, engine-out conditions. Post flight reconstruction models were developed for each flight island using the Day-of-Launch (DOL) Best Equivalent Trajectory (BET) that provided freestream conditions and propulsion system boundary conditions. This paper discusses a summary of the ascent aerothermal environments observed during the flights and the respective modelling approaches and the performance of them through comparisons of flight data and predictions.

aerothermodynamics↗
NASA NTRS2018

The Habitability of Proxima Centauri b: Environmental States and Observational Discriminants

Proxima Centauri b provides an unprecedented opportunity to understand the evolution and nature of terrestrial planets orbiting M dwarfs. Although Proxima Cen b orbits within its star’s habitable zone, multiple plausible evolutionary paths could have generated different environments that may or may not be habitable. Here, we use 1-D coupled climate-photochemical models to generate self-consistent atmospheres for several evolutionary scenarios, including high-O2, high-CO2, and more Earth-like atmospheres, with both oxic and anoxic compositions. We show that these modeled environments can be habitable or uninhabitable at Proxima Cen b's position in the habitable zone. We use radiative transfer models to generate synthetic spectra and thermal phase curves for these simulated environments, and use instrument models to explore our ability to discriminate between possible planetary states. These results are applicable not only to Proxima Cen b but to other terrestrial planets orbiting M dwarfs. Thermal phase curves may provide the first constraint on the existence of an atmosphere. We find that James Webb Space Telescope ( JWST) observations longward of 10 mm could characterize atmospheric heat transport and molecular composition. Detection of ocean glint is unlikely with JWST but may be within the reach of larger-aperture telescopes. Direct imaging spectra may detect O4 absorption, which is diagnostic of massive water loss and O2 retention, rather than a photosynthetic biosphere. Similarly, strong CO2 and CO bands at wavelengths shortward of 2.5 mm would indicate a CO2-dominated atmosphere. If the planet is habitable and volatile-rich, direct imaging will be the best means of detecting habitability. Earth-like planets with microbial biospheres may be identified by the presence of CH4-which has a longer atmospheric lifetime under Proxima Centauri's incident UV-and either photosynthetically produced O2 or a hydrocarbon haze layer.

Meadows, Victoria S.↗
NASA NTRS1991

A rapid method of calculating the orbital radiation environment

This paper describes the process of integrating available environment models into a single package that calculates the radiation environment for any earth orbit quickly and accurately with the only input being initial orbit parameters, launch date and length of mission, and units of output. The radiation dose is calculated for particles penetrating varying aluminum shielding thicknesses and incident upon several materials inside. Included also are modifications that have been made to the codes that account for the decrease of the magnetic field with time, which allows the use of data taken in the past to accurately predict a future environment. The complete package has relatively short run times, 20 minutes per mission on a Micro VAX II, allowing multiple iterations for application to mission design and planning.

Gates, Michele M.↗
NASA NTRS2005

Radiation Belt and Plasma Model Requirements

Contents include the following: Radiation belt and plasma model environment. Environment hazards for systems and humans. Need for new models. How models are used. Model requirements. How can space weather community help?

Barth, Janet L.↗
NASA NTRS2012

Assimilating Remote Sensing Observations of Leaf Area Index and Soil Moisture for Wheat Yield Estimates: An Observing System Simulation Experiment

Observing system simulation experiments were used to investigate ensemble Bayesian state updating data assimilation of observations of leaf area index (LAI) and soil moisture (theta) for the purpose of improving single-season wheat yield estimates with the Decision Support System for Agrotechnology Transfer (DSSAT) CropSim-Ceres model. Assimilation was conducted in an energy-limited environment and a water-limited environment. Modeling uncertainty was prescribed to weather inputs, soil parameters and initial conditions, and cultivar parameters and through perturbations to model state transition equations. The ensemble Kalman filter and the sequential importance resampling filter were tested for the ability to attenuate effects of these types of uncertainty on yield estimates. LAI and theta observations were synthesized according to characteristics of existing remote sensing data, and effects of observation error were tested. Results indicate that the potential for assimilation to improve end-of-season yield estimates is low. Limitations are due to a lack of root zone soil moisture information, error in LAI observations, and a lack of correlation between leaf and grain growth.

Nearing, Grey S.↗
NASA NTRS2015

Integrated Vehicle and Trajectory Design of Small Spacecraft with Electric Propulsion for Earth and Interplanetary Missions

This paper investigates the feasibility of Earth-transfer and interplanetary mission architectures for miniaturized spacecraft using emerging small solar electric propulsion technologies. Emerging small SEP thrusters offer significant advantages relative to existing technologies and will enable U-class systems to perform trajectory maneuvers with significant Delta V requirements. The approach in this paper is unique because it integrates trajectory design with vehicle sizing and accounts for the system and operational constraints of small U-class missions. The modeling framework includes integrated propulsion, orbit, energy, and external environment dynamics and systems-level power, energy, mass, and volume constraints. The trajectory simulation environment models orbit boosts in Earth orbit and flyby and capture trajectories to interplanetary destinations. A family of small spacecraft mission architectures are studied, including altitude and inclination transfers in Earth orbit and trajectories that escape Earth orbit and travel to interplanetary destinations such as Mercury, Venus, and Mars. Results are presented visually to show the trade-offs between competing performance objectives such as maximizing available mass and volume for payloads and minimizing transfer time. The results demonstrate the feasibility of using small spacecraft to perform significant Earth and interplanetary orbit transfers in less than one year with reasonable U-class mass, power, volume, and mission durations.

Spangelo, Sara↗
NASA NTRS2021

Harmonized Emissions Component (HEMCO) 3.0 as a Versatile Emissions Component for Atmospheric Models: Application in the GEOS-Chem, NASA GEOS, WRF-GC, CESM2, NOAA GEFS-Aerosol, and NOAA UFS Models

Emissions are a central component of atmospheric chemistry models. The Harmonized Emissions Component (HEMCO) is a software component for computing emissions from a user-selected ensemble of emission inventories and algorithms. It allows users to re-grid, combine, overwrite, subset, and scale emissions from different inventories through a configuration file and with no change to the model source code. The configuration file also maps emissions to model species with appropriate units. HEMCO can operate in offline stand-alone mode, but more importantly it provides an online facility for models to compute emissions at runtime. HEMCO complies with the Earth System Modeling Framework (ESMF) for portability across models. We present a new version here, HEMCO 3.0, that features an improved three-layer architecture to facilitate implementation into any atmospheric model and improved capability for calculating emissions at any model resolution including multiscale and unstructured grids. The three-layer architecture of HEMCO 3.0 includes (1) the Data Input Layer that reads the configuration file and accesses the HEMCO library of emission inventories and other environmental data, (2) the HEMCO Core that computes emissions on the user-selected HEMCO grid, and (3) the Model Interface Layer that re-grids (if needed) and serves the data to the atmospheric model and also serves model data to the HEMCO Core for computing emissions dependent on model state (such as from dust or vegetation). The HEMCO Core is common to the implementation in all models, while the Data Input Layer and the Model Interface Layer are adaptable to the model environment. Default versions of the Data Input Layer and Model Interface Layer enable straightforward implementation of HEMCO in any simple model architecture, and options are available to disable features such as re-gridding that may be done by independent couplers in more complex architectures. The HEMCO library of emission inventories and algorithms is continuously enriched through user contributions so that new inventories can be immediately shared across models. HEMCO can also serve as a general data broker for models to process input data not only for emissions but for any gridded environmental datasets. We describe existing implementations of HEMCO 3.0 in (1) the GEOS-Chem “Classic” chemical transport model with shared-memory infrastructure, (2) the high-performance GEOS-Chem (GCHP) model with distributed-memory architecture, (3) the NASA GEOS Earth System Model (GEOS ESM), (4) the Weather Research and Forecasting model with GEOS-Chem (WRF-GC), (5) the Community Earth System Model Version 2 (CESM2), and (6) the NOAA Global Ensemble Forecast System – Aerosols (GEFS-Aerosols), as well as the planned implementation in the NOAA Unified Forecast System (UFS). Implementation of HEMCO in CESM2 contributes to the Multi-Scale Infrastructure for Chemistry and Aerosols (MUSICA) by providing a common emissions infrastructure to support different simulations of atmospheric chemistry across scales.

Haipeng Lin↗
NASA NTRS2014

Comparisons Between Model Predictions and Spectral Measurements of Charged and Neutral Particles on the Martian Surface

Detailed measurements of the energetic particle radiation environment on the surface of Mars have been made by the Radiation Assessment Detector (RAD) on the Curiosity rover since August 2012. RAD is a particle detector that measures the energy spectrum of charged particles (10 to approx. 200 MeV/u) and high energy neutrons (approx 8 to 200 MeV). The data obtained on the surface of Mars for 300 sols are compared to the simulation results using the Badhwar-O'Neill galactic cosmic ray (GCR) environment model and the high-charge and energy transport (HZETRN) code. For the nuclear interactions of primary GCR through Mars atmosphere and Curiosity rover, the quantum multiple scattering theory of nuclear fragmentation (QMSFRG) is used. For describing the daily column depth of atmosphere, daily atmospheric pressure measurements at Gale Crater by the MSL Rover Environmental Monitoring Station (REMS) are implemented into transport calculations. Particle flux at RAD after traversing varying depths of atmosphere depends on the slant angles, and the model accounts for shielding of the RAD "E" dosimetry detector by the rest of the instrument. Detailed comparisons between model predictions and spectral data of various particle types provide the validation of radiation transport models, and suggest that future radiation environments on Mars can be predicted accurately. These contributions lend support to the understanding of radiation health risks to astronauts for the planning of various mission scenarios

Kim, Myung-Hee Y.↗
NASA NTRS2007

Method and program product for determining a radiance field in an optical environment

A hybrid method is presented by which Monte Carlo techniques are combined with iterative relaxation techniques to solve the Radiative Transfer Equation in arbitrary one-, two- or three-dimensional optical environments. The optical environments are first divided into contiguous regions, or elements, with Monte Carlo techniques then being employed to determine the optical response function of each type of element. The elements are combined, and the iterative relaxation techniques are used to determine simultaneously the radiance field on the boundary and throughout the interior of the modeled environment. This hybrid model is capable of providing estimates of the under-water light field needed to expedite inspection of ship hulls and port facilities. It is also capable of providing estimates of the subaerial light field for structured, absorbing or non-absorbing environments such as shadows of mountain ranges within and without absorption spectral bands such as water vapor or CO.sub.2 bands.

Reinersman, Phillip N.↗
NASA NTRS2016

High Fidelity Surface Charging and Magnetic Noise Analysis of the Juno Magnetometer

During Earth flyby of NASA’s Juno spacecraft, unexpected noise was observed in magnetometer data. The noise is attributed to surface currents sourced from ionospheric plasma and directed through the magnetometer boom structure by a vxB electric field. Approximate hand calculations under-predicted the severity of the noise by an order of magnitude. In response, a high fidelity analysis was performed to assess confidence in our model and risk to magnetometer science at Jupiter. Combining NASCAP2k with commercial FEA software, and using detailed inputs from a variety of environment models and CAD tools, the observed effect at Earth was replicated with agreement to a factor of 2. Extending the model to the Jovian environment, we predict a signal-to-noise ratio that is more favourable than at Earth and acceptable to magnetometer science.

Chinn, James↗
NASA NTRS2020

Ellicott City Disasters II: Enhancing a Statistical Flood Risk Model to Continue Improving Early Warning Systems and Public Safety in Ellicott City, Maryland

As flooding events in the United States grow in frequency and intensity, the use of technological advancements and applied science are increasingly necessary for effective flood monitoring and warning systems. The NASA DEVELOP Ellicott City Disasters II project investigated the use of machine learning for applications in flood risk detection to support the improvement of early warning systems. To strengthen the efforts of the Howard County Office of Emergency Management (OEM) in building a more robust flood monitoring system, the project improved the original statistical flood risk model, FLuME (Flood Learning Model Environment), programmed by the first DEVELOP term. The enhancements incorporated an additional six years of precipitation and soil moisture data from the North American Land Data Assimilation System (NLDAS), modeled using Aqua Advanced Microwave Scanning Radiometer for EOS and Tropical Rainfall Measuring Mission (TRMM) Microwave Imager. These Earth observations were supplemented by stream gauge data from the OEM and the US Geological Survey. The resultant flood risk model FLASH (Flood Learning Environment and Severity Assessment Hub) was trained to evaluate input variables and predict stage height in Ellicott City in real time. The addition of an advanced deep learning framework known as long short-term memory improved the model’s ability to capture relationships between variables. To assess the effectiveness of the new model, FLASH produced a model efficiency metric of 0.99, a significant improvement over the 0.85 value produced by the previous model. The project assisted the OEM in pursuing the integration of open data and NASA Earth observations into a threat matrix capable of informing near real-time decision making.

Disasters↗
NASA NTRS2020

Ellicott City Disasters II: Enhancing a Statistical Flood Risk Model to Continue Improving Early Warning Systems and Public Safety in Ellicott City, Maryland

As flooding events in the United States grow in frequency and intensity, the use of technological advancements and applied science are increasingly necessary for effective flood monitoring and warning systems. The NASA DEVELOP Ellicott City Disasters II project investigated the use of machine learning for applications in flood risk detection to support the improvement of early warning systems. To strengthen the efforts of the Howard County Office of Emergency Management (OEM) in building a more robust flood monitoring system, the project improved the original statistical flood risk model, FLuME (Flood Learning Model Environment), programmed by the first DEVELOP term The enhancements incorporated an additional six years of precipitation and soil moisture data from the North American Land Data Assimilation System (NLDAS), modeled using Aqua Advanced Microwave Scanning Radiometer for EOS and Tropical Rainfall Measuring Mission TRMM Microwave Imager. These Earth observations were supplemented by stream gauge data from the OEM and the US Geological Survey. The resultant flood risk model FLASH (Flood Learning Environment and Severity Assessment Hub) was trained to evaluate input variables and predict stage height in Ellicott City in real time. The addition of an advanced deep learning framework known as long short-term memory improved the model’s ability to capture relationships between variables. To assess the effectiveness of the new model, FLASH produced a model efficiency metric of 0.99, a significant improvement over the 0.85 value produced by the previous model. The project assisted the OEM in pursuing the integration of open data and NASA Earth observations into a threat matrix capable of informing near real-time decision making.

Disasters↗
NASA NTRS2010

Development of Supersonic Retro-Propulsion for Future Mars Entry, Descent, and Landing Systems

Recent studies have concluded that Viking-era entry system technologies are reaching their practical limits and must be succeeded by new methods capable of delivering large payloads (greater than 10 metric tons) required for human exploration of Mars. One such technology, termed Supersonic Retro-Propulsion, has been proposed as an enabling deceleration technique. However, in order to be considered for future NASA flight projects, this technology will require significant maturation beyond its current state. This paper proposes a roadmap for advancing the component technologies to a point where Supersonic Retro-Propulsion can be reliably used on future Mars missions to land much larger payloads than are currently possible using Viking-based systems. The development roadmap includes technology gates that are achieved through testing and/or analysis, culminating with subscale flight tests in Earth atmosphere that demonstrate stable and controlled flight. The component technologies requiring advancement include large engines capable of throttling, computational models for entry vehicle aerodynamic/propulsive force and moment interactions, aerothermodynamic environments modeling, entry vehicle stability and control methods, integrated systems engineering and analyses, and high-fidelity six degree-of-freedom trajectory simulations. Quantifiable metrics are also proposed as a means to gage the technical progress of Supersonic Retro-Propulsion. Finally, an aggressive schedule is proposed for advancing the technology through sub-scale flight tests at Earth by 2016.

Edquist, Karl T.↗
NASA NTRS2013

Determine ISS Soyuz Orbital Module Ballistic Limits for Steel Projectiles Hypervelocity Impact Testing

A new orbital debris environment model (ORDEM 3.0) defines the density distribution of the debris environment in terms of the fraction of debris that are low-density (plastic), medium-density (aluminum) or high-density (steel) particles. This hypervelocity impact (HVI) program focused on assessing ballistic limits (BLs) for steel projectiles impacting the enhanced Soyuz Orbital Module (OM) micrometeoroid and orbital debris (MMOD) shield configuration. The ballistic limit was defined as the projectile size on the threshold of failure of the OM pressure shell as a function of impact speeds and angle. The enhanced OM shield configuration was first introduced with Soyuz 30S (launched in May 2012) to improve the MMOD protection of Soyuz vehicles docked to the International Space Station (ISS). This test program provides HVI data on U.S. materials similar in composition and density to the Russian materials for the enhanced Soyuz OM shield configuration of the vehicle. Data from this test program was used to update ballistic limit equations used in Soyuz OM penetration risk assessments. The objective of this hypervelocity impact test program was to determine the ballistic limit particle size for 440C stainless steel spherical projectiles on the Soyuz OM shielding at several impact conditions (velocity and angle combinations). This test report was prepared by NASA-JSC/ HVIT, upon completion of tests.

Lyons, Frankel↗
NASA NTRS2015

Using the Shuttle In Situ Window and Radiator Data for Meteoroid Measurements

Every time NASA's Space Shuttle flew in orbit, it was exposed to the natural meteoroid and artificial debris environment. NASA Johnson Space Center maintains a database of impact cratering data of 60 Shuttle missions flown since the mid‐1990's that were inspected after flight. These represent a total net exposure time to the space environment of 2 years. Impact damage was recorded on the windows and radiators, and in many cases information on the impactor material was determined by later analysis of the crater residue. This information was used to segregate damage caused by natural meteoroids and artificial space debris. The windows represent a total area of 3.565 sq m, and were capable of resolving craters down to about 10 micrometers in size. The radiators represent a total area of 119.26 sq m, and saw damage from objects up to approximately 1 mm in diameter. These data were used extensively in the development of NASA's ORDEM 3.0 Orbital Debris Environment Model, and gives a continuous picture of the orbital debris environment in material type and size ranging from about 10 micrometers to 1 mm. However, the meteoroid data from the Shuttles have never been fully analyzed. For the orbital debris work, special "as flown" files were created that tracked the pointing of the surface elements and their shadowing by structure (such as the ISS during docking). Unfortunately, such files for the meteoroid environment have not yet been created. This talk will introduce these unique impact data and describe how they were used for orbital debris measurements. We will then discuss some simple first‐order analyses of the meteoroid data, and point the way for future analyses.

Matney, Mark↗
NASA NTRS2017

The MSFC Solar Activity Future Estimation (MSAFE) Model

The MSAFE model provides forecasts for the solar indices SSN, F10.7, and Ap. These solar indices are used as inputs to space environment models used in orbital spacecraft operations and space mission analysis. Forecasts from the MSAFE model are provided on the MSFC Natural Environments Branch's solar web page and are updated as new monthly observations become available. The MSAFE prediction routine employs a statistical technique that calculates deviations of past solar cycles from the mean cycle and performs a regression analysis to calculate the deviation from the mean cycle of the solar index at the next future time interval. The forecasts are initiated for a given cycle after about 8 to 9 monthly observations from the start of the cycle are collected. A forecast made at the beginning of cycle 24 using the MSAFE program captured the cycle fairly well with some difficulty in discerning the double peak that occurred at solar cycle maximum.

Suggs, Ron↗