The Scintillation Prediction Observations Research Task (SPORT): an International Science Mission Using a CubeSat
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Spann, James↗
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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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Space station contamination study: Assessment of contaminant spectral brightness
The assessment of spectral brightness resulting from the ambient-contaminant interaction requires a knowledge of the details of cross sections and excitation mechanisms. The approach adopted was to utilize the spectral brightness measurements made on Spacelab 1 and on the S3-4 spacecraft to identify source mechanisms, key cross sections and hence, the abundance of contaminant species. These inferred abundances were then used to update the composition comprising the total column concentrations predicted by the Science and Engineering Associates' configuration contamination model for the Space Station and to scale the irradiances to four altitudes: 300, 350, 400, and 463 km. The concentration irradiances are compared with zodiacal natural background levels. The results demonstrate that emissive contamination is significantly more severe than anticipated. It is shown that spectral emissions can become competitive with the zodiacal background up to altitudes as high as 400 km for the vacuum ultraviolet and visible emissions.
Torr, D. G.↗
Microgravity Emissions Laboratory Facility and Testing Results
The goal of this presentation is to provide information about the testing support for simulation and verification of the Space Station microgravity: environment component and rack surveys for ISS; essential for ground SEA/FEM analytical correlation; and essential to predicting interface and science levels on orbit.
McNelis, Anne↗
Integrated Modeling Approach for the Terrestrial Planet Finder Mission
Because of the complexity of the Terrestrial Planet Finder (TPF) design concepts, the project will rely heavily on the use of engineering and science simulations to predict on-orbit performance. Furthermore, current understanding of these missions indicates that the 3m to 8m class optical systems need to be as stable as picometers in wavefront and sub-milli arcsec in pointing. These extremely small requirements impose on the models a level of predictive accuracy heretofore never achieved, especially in the area of microgravity effects, material property accuracy, thermal solution convergence, and all other second order modeling effects typically ignored. New modeling tools and analysis paradigms are developed which emphasize computational accuracy and fully integrated analytical simulations. The process is demonstrated on sample problems using the TPF Coronagraph design concept. The TPF project is also planning a suite of testbeds through which various aspects of the models and simulations will be verified.
terrestrial planet finder↗
Soil Moisture Initialization Error and Subgrid Variability of Precipitation in Seasonal Streamflow Forecasting
Offline simulations over the conterminous United States (CONUS) with a land surface model are used to address two issues relevant to the forecasting of large-scale seasonal streamflow: (i) the extent to which errors in soil moisture initialization degrade streamflow forecasts, and (ii) the extent to which a realistic increase in the spatial resolution of forecasted precipitation would improve streamflow forecasts. The addition of error to a soil moisture initialization field is found to lead to a nearly proportional reduction in streamflow forecast skill. The linearity of the response allows the determination of a lower bound for the increase in streamflow forecast skill achievable through improved soil moisture estimation, e.g., through satellite-based soil moisture measurements. An increase in the resolution of precipitation is found to have an impact on large-scale streamflow forecasts only when evaporation variance is significant relative to the precipitation variance. This condition is met only in the western half of the CONUS domain. Taken together, the two studies demonstrate the utility of a continental-scale land surface modeling system as a tool for addressing the science of hydrological prediction.
Streamflow Prediction↗
Interim Report of the Astronomy Spacelab Payloads Study: Ultraviolet and Optical Astronomy - Volume 2
The Space Shuttle will comprise NASA's primary transportation system into near-earth orbit during the 1980s. The Shuttle will provide the astronomical community with a major new capability to send a wide variety of instrumentation into orbit, to utilize it there under manned or automatic control for periods from seven to thirty days, and to return it to the ground. To this end the European Space Research Organization (ESRO) is developing Spacelab, an array of interchangeable components -pressurized manned modules, unpressurized pallets and related support systems - to be mounted in the Shuttle payload bay. Spacelab will offer important opportunities to carry out astronomical research with instruments optimized for specific objectives. With a high flight frequency and with the ability to modify or interchange telescopes and instruments between flights, one will not need to make rigid long-term commitments to specific and compromised telescope/instrument/ detector combinations as is the case for automated satellites. Observational techniques demanding the physical return of data and equipment - in particular the use of photographic film, instruments requiring tight calibration controls, cryogens, high-risk detectors and degradeable optical coatings -will open research areas not readily addressed by automated satellites. Although Shuttle flight duration will be limited to periods from seven to thirty days, substantial data can be obtained with a single instrument on short missions, if targets are carefully selected and prioritized, and a large number of instruments can be accommodated on a single flight. Important astronomical data are regularly obtained on sounding rocket flights of five minutes duration. Spacelab will provide far longer observing periods for large and small telescopes, with resources greatly exceeding those of sounding rockets, while retaining much of the sounding rocket philosophy in terms of instrument flexibility, simplicity, reliability assurance and development costs. The Ultraviolet and Optical Astronomy Program on Spacelab is being planned to provide optical astronomers with relatively simple and regular access to the extended wavelength coverage, the superior image quality and the darkness of the night sky available above the earth's atmosphere. In a rapidly evolving science one cannot predict what problems will be timely in the 1980s. Extrapolating from the current epoch, however, one can envision a continuing interest in such areas as the structure, composition and phenomenology of planetary surfaces and atmospheres; the composition and physical nature of the interstellar medium; the composition, structure and life history of stars, especially those in advanced stages of evolution; the stellar population of other galaxies; such enigmatic phenomena as X-ray binary black holes, pulsars, active galactic nuclei and quasars; large scale interactions between galaxies and the nature of the intergalactic medium; precise calibration of the Hubble law for the expansion of the universe; the average density of the universe; and the existence of extraterrestrial life.
Source record↗
Mars 2020 Reconstructed Aerothermal Environments and Design Margins
The Mars 2020 aeroshell's thermal protection system was nearly identical to the Mars Science Laboratory system that successfully completed its mission for the Curiosity rover's landing in 2012. It was predicted that, like Mars Science Laboratory, the Mars 2020 heatshield would experience boundary layer transition and that the thermal protection system would provide sufficient material thickness margins against the aerothermal environments, even after adding radiative heating that was not included for Mars Science Laboratory. The Mars 2020 flight instrumentation suite included heatshield sensors similar to Mars Science Laboratory and new backshell measurements. A full set of surface pressure and in-depth temperature data were collected during atmospheric entry. This paper provides an initial analysis of the flight data and focuses on the reconstructed total surface heat flux inferred from the measured temperatures. Turbulent boundary layer conditions again were observed on the Mars 2020 heatshield, and the temperatures at all eleven heatshield and six backshell thermocouple in-depth sensor locations were well within system capabilities due to favorable entry conditions and conservative uncertainties. New computational fluid dynamics results on the reconstructed entry trajectory are compared to the measured surface pressures and reconstructed total heat fluxes. The predicted heatshield surface pressures at six locations match the data qualitatively and quantitatively well, as expected. Smooth-wall laminar heating predictions prior to boundary layer transition fall above the reconstructed heating on the heatshield. After the observed boundary layer transition time, total heat flux based on algebraic turbulence model calculations generally match the heat flux trends relative to one another. The convective heat flux was predicted to constitute the majority of the total heating. On the backshell, smooth-wall laminar total heat flux predictions generally exceed the reconstructed total heating at six locations. At each of these locations, it is estimated that radiative heating provided almost all of the total heating. The Mars 2020 as-flown aerothermal environments were well below the design levels for all measurement locations due to conservative design assumptions and a stressing design trajectory.
Mars 2020↗
Mars 2020 Reconstructed Aerothermal Environments and Design Margins
The Mars 2020 aeroshell's thermal protection system was nearly identical to the Mars Science Laboratory system that successfully completed its mission for the Curiosity rover's landing in 2012. It was predicted that, like Mars Science Laboratory, the Mars 2020 heatshield would experience boundary layer transition and that the thermal protection system would provide sufficient material thickness margins against the aerothermal environments, even after adding radiative heating that was not included for Mars Science Laboratory. The Mars 2020 flight instrumentation suite included heatshield sensors similar to Mars Science Laboratory and new backshell measurements. A full set of surface pressure and in-depth temperature data were collected during atmospheric entry. This paper provides an initial analysis of the flight data and focuses on the reconstructed total surface heat flux inferred from the measured temperatures. Turbulent boundary layer conditions again were observed on the Mars 2020 heatshield, and the temperatures at all eleven heatshield and six backshell thermocouple in-depth sensor locations were well within system capabilities due to favorable entry conditions and conservative uncertainties. New computational fluid dynamics results on the reconstructed entry trajectory are compared to the measured surface pressures and reconstructed total heat fluxes. The predicted heatshield surface pressures at six locations match the data qualitatively and quantitatively well, as expected. Smooth-wall laminar heating predictions prior to boundary layer transition fall above the reconstructed heating on the heatshield. After the observed boundary layer transition time, total heat flux based on algebraic turbulence model calculations generally match the heat flux trends relative to one another. The convective heat flux was predicted to constitute the majority of the total heating. On the backshell, smooth-wall laminar total heat flux predictions generally exceed the reconstructed total heating at six locations. At each of these locations, it is estimated that radiative heating provided almost all of the total heating. The Mars 2020 as-flown aerothermal environments were well below the design levels for all measurement locations due to conservative design assumptions and a stressing design trajectory.
Mars 2020↗
The Updated Solar Activity Prediction during the MAVEN Mission, but Should We Believe It?
Mars atmospheric processes are very dependent not only on the absolute level of the solar irradiance but also the changes in solar irradiance. Correlated with many of these irradiance changes, especially during solar flares, are large particle events called coronal mass ejections that themselves significantly drive processes in the Martian atmosphere. The NOAA Space Weather Prediction Center has issued a consensus solar cycle activity prediction for the upcoming solar cycle 24 maximum, and this maximum period of solar activity will be during the prime MAVEN science mission. This 'consensus' prediction calls for lower activity than the previous solar cycle maximum that occurred during the years 2001-2002, but looking at the wide spread of peer-reviewed predictions there is little faith that can be taken in any one prediction. This drives the importance of real-time measurements from the LPW/EUV diodes and the measurement and modeling results that will be improved upon using results from the Solar Dynamics Observatory (SDO).
Chamberlin, Philip↗
Enhancing Dataset Discovery With Knowledge Graph Link Prediction Techniques
● In the evolving landscape of open science, the ability to navigate and discover pertinent datasets is increasingly significant. This primarily hinges on the presence of detailed metadata, delineating the dataset’s content, and potential spheres of application. ● The GES DISC datasets are characterized by science keywords to enable dataset discovery in web search interfaces. ● A problem may arise where a dataset lacks a science keyword that it otherwise should have. ● Machine learning techniques such as link prediction can be used to detect these missing science keywords by estimating the probability of new links forming between dataset and keyword nodes.
machine learning↗
LUVOIR-ECLIPS Closed-Loop Adaptive Optics Performance and Contrast Predictions
One of the primary science goals of the Large UV/Optical/Infrared Surveyor (LUVOIR) mission concept is to detect and characterize Earth-like exoplanets orbiting nearby stars with direct imaging. The success of its coronagraph instrument ECLIPS (Extreme Coronagraph for Living Planetary Systems) depends on the ability to stabilize the wavefront from a large segmented mirror such that optical path differences are limited to tens of picometers RMS during an exposure time of a few hours. In order to relax the constraints on the mechanical stability, ECLIPS will be equipped with a wavefront sensing and control (WS\&C) architecture to correct wavefront errors up to temporal frequencies $\gtrsim$1 Hz. These errors may be dominated by spacecraft structural dynamics exciting vibrations at the segmented primary mirror. In this work, we present detailed simulations of the WS\&C system within the ECLIPS instrument and the resulting contrast performance. This study assumes wavefront aberrations based on a finite element model of a simulated telescope with spacecraft structural dynamics. Wavefront residuals are then computed according to a model of the adaptive optics system that includes numerical propagation to simulate a realistic wavefront sensor and an analytical model of the temporal performance. An end-to-end numerical propagation model of ECLIPS is then used to estimate the residual starlight intensity distribution at the science detector. We show that the contrast performance depends strongly on the target star magnitude and the spatio-temporal distribution of wavefront errors from the telescope. In cases with significant vibration, we advocate for the use of laser metrology to mitigate high temporal frequency wavefront errors and increase the mission yield.
Sirbu, Dan↗
Game-Changing Science with SmallSats and Hosted Payloads
This talk outlines the opportunities using space-based remote sensing to collect the basic climate research data that will serve as the foundation of our science, our models, and our predictive capabilities. With SmallSats and hosted payloads to supplement data from our traditional large spacecraft, and with constellations of SmallSats and with hosted payloads, the Science Mission Directorate is able to make new types of observations, such as synchronic temporal and spatial measurements of the same events. Our data enables science-based decision making. Our models and predictions inform and educate our decision makers at every level.
remote sensing↗
Introduction to the Prediction Of Worldwide Energy Resources (POWER) Project: NASA Applied Sciences Week 2021
Explore the source record for details and available documents.
Energy↗
Comparison of Multivariate Time Series Prediction Techniques for Emulating Noah-LSM Soil Moisture Outputs
Land surface models are crucial tools for many earth science applications including numerical weather prediction, water resource and crop monitoring, and climatological analysis. Given a set of atmospheric forcings, seasonal data, and static parameters, models like Noah-LSM solve for land surface quantities including skin temperature, sensible heat flux, and soil moisture. While these calculations are theoretically robust, they are often computationally expensive. Since artificial neural networks (ANNs) are universal function approximators, they can learn to emulate the output of a deterministic numerical model given a time series of input forcings, with the learned ANN having substantially shorter execution time. The ANN could efficiently parameterize other models, generate ensembles, and provide first-guess inputs for retrievals. As such, with the goal of developing a model that efficiently mimics the output of Noah-LSM given NLDAS2 forcings on a region covering much of the central US, we examine and compare several neural network architectures for the multi-horizon multivariate time series forecasting problem. Recent literature includes a diverse set of approaches including autoregressive architectures like LSTM and GRU, parametric and non-parametric statistical predictors (ForecastNet and MQRNN), self-attention (LSTM-attention-LSTM), and temporal convovlution (DeepTCN). We implement several of these models for the Noah-LSM prediction task, highlighting the features and challenges for each and providing practical insight on the training process.
Mitchell Dodson↗
The Swift Gamma-ray Burst Explorer: Early views into Black-hole Creation
Swift has exceeded every pre-launch predicted advance in GRB science. It has discovered the farthest GRB ever seen and identified new GRBs at a rate of 100/year. It has also explored a brand new time interval in GRB light curves by revealing unpredicted phenomena of GRB flares and rapid x-ray afterglow declines. Swift has conducted 20,00o successful slews to sources and is predicted to stay in orbit until 2022.
Hill, Joe↗
PolarMERRA: A Polar-Focused Global Reanalysis Project for Scientific and Stakeholder Needs
The adequate modeling of physical processes in the Arctic and Antarctic is vital for developing prediction capabilities and for obtaining an understanding of rapidly evolving polar conditions, including their potential global impacts. These processes are often poorly represented in global models and reanalyses, owing to a legacy modeling focus on midlatitude processes, as well as a scarcity of observations needed for model development in polar regions. The polarMERRA initiative, a joint effort between NASA’s Cryospheric Sciences and Modeling and Prediction programs, seeks to improve the representation of cryospheric and polar atmospheric processes and to develop an open-source framework for a quantitively evaluation of polar-relevant variables against current and future satellite and in-situ observations, models, and reanalyses. Here, we evaluate the impacts of spatial resolution and modifications to sea ice, ice sheet, and atmospheric parameterizations on the representation of high latitude conditions by using a quantitative scorecard approach that leverages NASA’s extensive satellite record. Investigations are conducted using the NASA Goddard Earth Observing System model (GEOS) and its data assimilation system (GEOS DAS). Through a quantitative identification of process deficiencies, bias reductions in key surface variables, including temperature and precipitation over cryospheric surfaces, may be achieved. The polarMERRA project additionally seeks to identify additional data sources for use in the GEOS DAS, and to incorporate data and parameterization improvements into future model and reanalysis products for scientific and stakeholder use.
Lauren C Andrews↗
Towards a flexible framework for community-wide ensemble forecasting tailored for major space environment impacts
To build continuously improving space weather predictive capabilities based on science and enable assessments and rapid implementations of advances in research into source-to-impact modelling systems we need: to assemble parts of the puzzle by solving problems focused on specific physical domains; to identify essential space environment quantities (ESEQs) passed between domains and linked to impacts; evaluate modeling capabilities for each ESEQ; connect all validated solutions from space weather origins on the sun to impacts on humans and critical infrastructure; to design displays for ensemble predictions tailored for major space weather user groups; to build a collaborative environment for efficient sharing of information and capabilities (models/data/expertise) and collaborative development. The presentation will overview existing community-wide space weather forecasting frameworks and research-to-operations pipelines and discuss opportunities to build a collaborative plug-and-play platform for interconnecting predictive capabilities developed under different space weather programs.
space weather↗