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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 217 records · Page 12

An Overview of the Design and Development of the GOES R-Series Space Segment

The first of the National Oceanic and Atmospheric Administration (NOAA) Geostationary Operational Environmental Satellite R-series (GOES-R) satellites was launched in November 2016. GOES-R has been developed by NOAA in partnership with the National Aeronautics and Space Administration (NASA). The satellite represents a quantum leap in the state of the art for geostationary weather satellites by providing data from a suite of six new instruments. All instruments were developed expressly for this mission, and include two Earth-observing instruments (the Advanced Baseline Imager (ABI) and Geostationary Lightning Mapper (GLM)), two solar-viewing instruments (Solar Ultraviolet Imager (SUVI) and Extreme ultraviolet and X-ray Irradiance Sensors (EXIS)) and two in situ instruments (Space Environment In-Situ Suite (SEISS) and a magnetometer pair). In addition to hosting the instruments, GOES-R also accommodates several communication packages designed to collect and relay data for weather forecasting and emergency management. Accommodating the six instruments and four communication payloads imposed challenging and competing constraints on the satellite, including requirements for extremely stable earth and solar pointing, high-speed and nearly error-free instrument data transmission, and a very quiet electromagnetic background. To meet mission needs, GOES-R employed several technological innovations, including low-thrust rocket engines that allow instrument observations to continue during maneuvers, and the first civilian use of Global Positioning System-based orbit determination in geostationary orbit. This paper will provide a brief overview of the GOES-R satellite and its instruments as well as the developmental challenges involved in accommodating the instruments and communications payloads.

GOES-16↗

NASA System Wide Safety Project Safety Metrics Research

This is a short set of PPT slides that we will use when we visit several US airlines to provide an introduction to a data collection task supporting the System Wide Safety Project. The goal is to gain an understanding of what airline dispatchers and other airline personnel see as hazards affecting the safety of flight. We want to list the hazards and how they are evaluated as safety metrics. This may eventually lead to an ability to monitor safety metrics in the National Airspace System and identify and predict possible unsafe situations.

Aviation safety↗

The Pheno-Evo Model: Evolution of Microbial Phenotypic Diversity in 2D Space

Biologists appreciate microbes for their simplicity and predictability: we assume that a population of genetically identical cells in a uniform environment will all behave the same way. While this assumption is often useful, it is also often wrong. Not only might microbes in a clonal population act differently from one another, the differences may be categorical (growing v. non-growing; toxin-sensitive v. tolerant), and this diversity might be an evolved trait conferring increased fitness on the population. How does such phenotypic heterogeneity evolve? And how does a population find the optimal distribution of phenotypes for a given environment? Efforts at modeling microbial phenotypic heterogeneity often focus on populations with two discrete phenotypic types; phenotypes in continuous distributions remain poorly explored. To address this gap and to explore the role of spatial relationships, we use agent-based modeling to simulate a phenotypically diverse population of microbial cells evolving in the presence of periodic toxic stress. Cells on patches in a 2D grid may degrade toxin, suffer damage from toxin, switch phenotype, and reproduce. An individual's phenotype its toxin degradation rate-- for which there is a tradeoff with reproduction-- and the genotype encodes the distribution of phenotypic values in the population. The rate of toxin diffusion determines how individuals influence their neighbors' environments. We examine the effects of toxin concentration, diffusion rate, and environmental predictability on the survival success of populations with different phenotype distributions, and populations' evolutionary trajectories when phenotype distribution is allowed to evolve. We conduct all simulations on the platform NetLogo, which provides a friendly interface allowing users of any experience level to tweak parameters and run their own simulations. We have also created custom tools in R for analyzing and visualizing the results of multiple runs.

microbial evolution↗

Near real-time air quality forecasts using the NASA GEOS model

NASA's Global Modeling and Assimilation Office (GMAO) produces high-resolution global forecasts for weather, aerosols, and air quality. The NASA Global Earth Observing System (GEOS) model has been expanded to provide global near-real-time5-day forecasts of atmospheric composition at unprecedented horizontal resolution of 0.25 degrees (~25 km). This composition forecast system (GEOS-CF) combines the operational GEOS weather forecasting model with the state-of-the-science GEOS-Chem chemistry module (version 12) to provide detailed analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5). Satellite observations are assimilated into the system for improved representation of weather and smoke. The assimilation system is being expanded to include chemically reactive trace gases. We discuss current capabilities of the GEOS Constituent Data Assimilation System (CoDAS) to improve atmospheric composition modeling and possible future directions, notably incorporating new observations (TROPOMI, geostationary satellites) and machine learning techniques. We show how machine learning techniques can be used to correct for sub-grid-scale variability, which further improves model estimates at a given observation site.

Air Quality Forecast↗

Evaluation of the GEOS-Chem UCX Stratosphere in the GEOS Composition Forecast System

The NASA GEOS Composition Forecast (GEOS-CF) system provides 3-dimensional atmospheric composition analyses and forecasts to the public in near-real time at the high spatial resolution of 25 km. While the main focus of this new product is on tropospheric air quality information, the GEOS-Chem chemistry model (v12) used in this system includes the UCX stratospheric chemistry mechanism. Here, we describe the GEOS-CF system and provide comparisons against remote-sensed observations for stratospheric composition, including measurements of HCl, ClO, NO2, and O3. The GEOS-CF nudges the stratospheric ozone towards the GEOS Forward Processing (GEOS FP) assimilated ozone product; as a result the stratospheric ozone analysis in theGEOS-CF agrees well with observations. Additionally, with the inclusion of the GEOS-Chem UCX stratospheric chemistry mechanism in GEOS-CF, 5-day forecasts, especially during the abnormal 2020 NH polar spring, capture the chemical and dynamical changes missed by the GEOS FP system, which tends towards climatology. The GEOS-CF is a new tool for the research community providing near-real time 3-dimensional gridded information on atmospheric composition throughout the troposphere and stratosphere.

Stratosphere↗

Cassini distributed instrument operations – what we’ve learned since Saturn orbit insertion

The Cassini mission to Saturn is complex with 12 science teams conducting distributed operations across the United States and Europe. Each Team includes scientists from around the world who actively participate in operations, including observation design, instrument commanding, downlink processing, and archiving. This represents a change in how JPL complex deep-space missions have been operated. Since Saturn Orbit Insertion (SOI), the Cassini Project has spent 17 months conducting science operations and has gained realworld experience that has tested the assumptions and rationale for this approach. We have learned that many of the expected benefits have been realized, but there were numerous unexpected challenges as well. This paper will discuss the lessons learned from the Cassini Tour experience to date. It will revisit the assumptions and rationale behind the distributed instrument operations design and will describe the results, good and bad, of implementing this method of operations. We will describe how Instrument Teams are structured, their roles and responsibilities, what challenges they faced going into orbital operations (the “tour”) and what creative solutions were proposed when funding limitations and schedule milestones prevented optimum solutions. We will also discuss the problems that have been encountered both on the ground and with the instruments, how these problems and anomalies were overcome, and what was learned along the way about the characteristics of distributed instrument operations.

Woncik, Pam↗

(abstract) Navigating through the Venus Atmosphere

This paper presents the problems and challenges of the Magellan Navigation Team. The challenges are: 1) to predict the periapsis time to an accuracy of less than 100 seconds, 2) to accurately predict the dynamic pressure incurred by the spacecraft, 3) to model and to generate this prediction in a timely manner, 4) to provide navigation support 7 days per week for 70 days with 3 navigators and one graphic specialist to generate a daily package for presentation and display. The problems encountered by the Navigation Team in order to meet the above challenges are: 1) the uncertainty in the Venus atmosphere model, 2) the uncertainty in the Venus gravity model, 3) the uncertainty in predicting the attitude control thruster firing, 4) the sparse amount of radiometric tracking data, 5) the radiometric data editing is complicated by the effects of the Venus atmosphere fluctuations.

Venus↗

KELT-9 b's Asymmetric TESS Transit Caused by Rapid Stellar Rotation and Spin-Orbit Misalignment

KELT-9 b is an ultra-hot Jupiter transiting a rapidly rotating, oblate early-A-type star in a polar orbit. We model the effect of rapid stellar rotation on KELT-9 b’s transit light curve using photometry from the Transiting Exoplanet Survey Satellite to constrain the planet’s true spin–orbit angle and to explore how KELT-9 b may be influenced by stellar gravity darkening. We constrain the host star’s equatorial radius to be 1.089±0.017 times as large as its polar radius and its local surface brightness to vary by∼38% between its hot poles and cooler equator. We model the stellar oblateness and surface brightness gradient and find that it causes the transit light curve to lack the usual symmetry around the time of minimum light. We take advantage of the light-curve asymmetry to constrain KELT-9b’s true spin–orbit angle (87degree+ -10degrees/-11degrees), agreeing with Gaudi et al. that KELT-9 b is in a nearly polar orbit. We also apply a gravity-darkening correction to the spectral energy distribution model from Gaudi et al. and find that accounting for rapid rotation gives a better fit to available spectroscopy and yields a more reliable estimate for the star’s polar effective temperature.

Exoplanets↗

NASA-ISRO Synthetic Aperture Radar (NISAR) Mission

NISAR is a multi-disciplinary Earth-observing radar mission that makes global measurements of land surface changes that will greatly improve Earth system models. NISAR data will clarify spatially and temporally complex phenomena, including ecosystem disturbances, ice sheet collapse, and natural hazards including earthquakes, tsunamis, volcanoes, and landslides. It provides societally relevant data that will enable better protection of life and property. The mission, a NASA-ISRO partnership, uses two fully polarimetric SARs, one at L-band (L-SAR) and one at S-band (S-SAR), in exact repeating orbits every 12 days that allows interferometric combination of data on repeated passes. NASA provides the L SAR; a shared deployable reflector; an engineering payload that supports mission-specific data handling, navigation and communication functions; science observation planning and L SAR data processing. ISRO provides the S-SAR, spacecraft, launch vehicle, satellite operations, and S-SAR data processing. The mission will be launched from the Satish Dhawan Space Centre, Sriharikota, India. Mission development has addressed many unique challenges and incorporates many “firsts” for a jointly-developed free-flyer radar science mission.

Sarma, C V H S↗

TOI-257b (HD 19916b): a warm sub-saturn orbiting an evolved F-type star

We report the discovery of a warm sub-Saturn, TOI-257b (HD 19916b), based on data from NASA’s Transiting Exoplanet Survey Satellite (TESS). The transit signal was detected by TESS and confirmed to be of planetary origin based on radial velocity observations. An analysis of the TESS photometry, the MINERVA-Australis, FEROS, and HARPS radial velocities, and the asteroseismic data of the stellar oscillations reveals that TOI-257b has a mass of M(P) = 0.138 ± 0.023 M(J) (43.9 ± 7.3 Mꚛ), a radius of R(P) = 0.639 ± 0.013 R(J) (7.16 ± 0.15 Rꚛ⁠), bulk density of 0.65 (+0.12,−0.11) (cgs), and period 18.38818 (+0.00085,−0.00084) days⁠. TOI-257b orbits a bright (V = 7.612 mag) somewhat evolved late F-type star with M⁎ = 1.390 ± 0.046 M(sun)⁠, R⁎ = 1.888 ± 0.033 R(sun)⁠, T(eff) = 6075 ± 90 K⁠, and 𝜈sin 𝑖 = 11.3 ± 0.5 km/s. Additionally, we find hints for a second non-transiting sub-Saturn mass planet on a ∼71 day orbit using the radial velocity data. This system joins the ranks of a small number of exoplanet host stars (∼100) that have been characterized with asteroseismology. Warm sub-Saturns are rare in the known sample of exoplanets, and thus the discovery of TOI-257b is important in the context of future work studying the formation and migration history of similar planetary systems.

asteroseismology↗

A Status Update for the FLASHFlux Working Group

This presentation provides an overview of the progress made by the FLASHFlux working group within the CERES Science Team. FLASHFlux is maintaining operations, continuing validation, migration production code for future production systems, and evaluating new inputs for their impacts on the current radiative flux data products. FLASHFlux data products continue to be served to the community and comprise the low latency solar and thermal infrared data products provided to the energy and agricultural communities at relatively low latency for global gridded data fluxes. (< 7days).

surface radiative flux↗