1. Simulating Air Taxi Safety Near the Ground<\/strong><\/h2>\nWith the development of urban air mobility (UAM) vehicles, in the near future people might be hailing rides in air taxis. Researchers studying the aerodynamics performance of multiple UAM designs are focusing this year on simulations to analyze how these vehicles perform close to the ground. Many of the agency\u2019s UAM aircraft concepts have rotors, just like helicopters. Supercomputers at the NASA Advanced Supercomputing (NAS) facility at NASA\u2019s Ames Research Center in California\u2019s Silicon Valley run complex, high-fidelity computational fluid dynamics simulations that capture in detail the interaction between rotors, other vehicle components, and the ground surface. These simulations enable scientists to better understand the vehicle aerodynamics and the rotor-induced flow around the vehicles to detect potentially dangerous areas with high winds and gusts. Simulation data allows the team to predict changes in how UAMs handle close to the ground and to provide guidelines for safe crew and passenger movement near the vehicles.<\/p>\n
\n\n\n![\"\"](\"https:\/\/spaceweekly.com\/wp-content\/uploads\/2023\/11\/06-ventura-p-sc23-uam-ground-1.png\")
<\/figure>\nNASA\u2019s six-passenger air taxi quadcopter in hover (out of ground effect). Q-criterion \u2014 a measure of the amount of vorticity in the aerodynamic flow \u2014 isosurfaces colored with the vorticity magnitude show the vortex wake, where blue is low and magenta is high. In the background, the pressure coefficient is shown, where black is low and white is high. Understanding the complex flow and aerodynamic interactions of multi-rotor vehicles is key to design the future air taxis.<\/div>\nNASA\/Patricia Ventura Diaz<\/div>\n<\/figcaption><\/div>\n<\/div>\n<\/div>\n2. Predicting the Strongest Storms within a Global Computer Model<\/strong><\/h2>\nThe common fuel for severe thunderstorms, tornadoes, and hurricanes is convection \u2013 vigorous up-and-down motions of the atmosphere that vertically transport heat and moisture. Operational weather forecasting centers typically predict convective-scale weather using regional, limited-area computer models because global models at convection resolving resolution need too much computing power. Researchers at NASA\u2019s Goddard Space Flight Center in Greenbelt, Maryland, have adapted their global Goddard Earth Observing System (GEOS) model to apply finer grid resolutions of 2 to 4 kilometers (about 1.25 to 2.5 miles) over the continental United States. GEOS forecasts running on the NASA Center for Climate Simulation\u2019s (NCCS\u2019s) Discover supercomputer and NAS\u2019s Aitken supercomputer are extending the predictability of the strongest storms beyond two days while better representing local impacts from intense precipitation, winds, and heat. Ongoing simulations accurately tracked extreme weather events of 2023 including hurricanes Idalia and Lee and tropical storm Ophelia.<\/p>\n
\n\n\n![\"\"](\"https:\/\/spaceweekly.com\/wp-content\/uploads\/2023\/11\/23-putman-w-sc23-geos-img1-no-title.png\")
<\/figure>\nHurricane Idalia made landfall along Florida\u2019s northern Gulf Coast on August 30, 2023. Radar reflectivity from observations (left) and simulations by the Goddard Earth Observing System (GEOS) model at 4-kilometer (2.5-mile) (center) and 12-kilometer (7.5-mile) (right) resolution visualize Idalia\u2019s internal structure. While both GEOS forecasts captured Idalia\u2019s landfall within miles of the actual landfall days in advance, the 4- kilometer forecast improved representations of central pressure values, near-surface wind speeds, a very compact eye, and banding convection spiraling inwards from the southeast.<\/div>\nNASA\/William Putman<\/div>\n<\/figcaption><\/div>\n<\/div>\n<\/div>\n3. Protecting Space Capsules During Planetary Entry, Descent, and Landing<\/strong><\/h2>\nNASA space capsules are designed to survive entering planetary atmospheres at hypersonic speeds and protect their payloads \u2013 or their crew \u2013 from the extreme temperatures that occur during entry. In addition to heat, the spacecraft can also encounter dynamic instabilities as they are slowed down by aerodynamic drag during descent. To quantify and understand this additional hazard, researchers at NASA Ames used the agency\u2019s Pleiades and Electra supercomputers to simulate the free-flight conditions of capsules during the full trajectory of planetary entry. These complex simulations are used to analyze capsule flight dynamics and identify any risks the instabilities may pose during the later stage of the flight trajectory. The resulting analyses help engineers design entry vehicles for planetary exploration, helping ensure the success of NASA programs including Artemis and the upcoming Dragonfly mission to Saturn\u2019s largest moon, Titan.\u00a0<\/p>\n
\n\n\n![\"\"](\"https:\/\/spaceweekly.com\/wp-content\/uploads\/2023\/11\/16-thompson-k-sc23-4-adept-turbulence-v0.png\")
<\/figure>\nFree-flight simulation of the Adaptable Deployable Entry and Placement Technology vehicle showing Q-criterion, which is a measure of the amount of vorticity in the aerodynamic flow. The iso-contours indicate vortex structure, indicating lower vorticity in blue and higher vorticity in red.<\/div>\nNASA\/Joseph Brock<\/div>\n<\/figcaption><\/div>\n<\/div>\n<\/div>\n4. Transforming and Depicting Earth Science Data<\/strong><\/h2>\nFrom the agency\u2019s founding in 1958, NASA has been tasked with widely disseminating information about its activities and results. One new NASA public communication effort is the Earth Information Center<\/a> (EIC), which presents visualizations of raw observational and model data across a set of dashboards arranged like a NASA Mission Control Center for our planet. The EIC installation at NASA Headquarters in Washington includes a multi-panel hyperwall for displaying large-format animations surrounded by smaller portals depicting a number of \u201cvital signs\u201d of the Earth. The diverse data sources include simulations run on the NCCS Discover supercomputer and observations from satellites and ground instruments maintained by NASA and partners. Since opening in late June 2023, the EIC has drawn a great variety of visitors, from dignitaries to elementary school students. In addition, EIC information is aiding policy makers, scientists, and NASA data users such as farmers, business owners, and researchers.<\/p>\n\n\n\n![\"\"](\"https:\/\/spaceweekly.com\/wp-content\/uploads\/2023\/11\/35-lopez-chyatte-sc23-04-eic-multiple-data-points.png\")
<\/figure>\nThe Earth Information Center (EIC) dashboards include (left) visualizations generated by simulations run on the NASA Center for Climate Simulation\u2019s Discover supercomputer and (right) an \u201cImage of the Day\u201d and \u201cVital Signs\u201d of the planet compiled from NASA and partner agency observations. <\/div>\nNASA\/Brenda Lopez Silva, Michael Chyatte<\/div>\n<\/figcaption><\/div>\n<\/div>\n<\/div>\n5. Using Autonomous Onboard Science Agents for Planetary Exploration<\/strong><\/h2>\nResearchers in NASA Goddard\u2019s Distributed Systems Missions initiative are working to enable deep-space missions that are adaptable and can autonomously interpret and respond to newly-collected science data using an onboard software \u201cagent\u201d rather than waiting for new instructions from Earth at each phase of the mission. To test this new, autonomous mission design, they chose Enceladus, an icy ocean moon of Saturn and one of the most promising targets to search for life in our solar system. In a simulated mission scenario, the scientists modeled various trajectories and orbits of eight small spacecraft to produce what would be the first stable constellation around Enceladus to provide global coverage of the moon for collecting science observations. The team deployed their\u00a0 autonomous onboard science agent to analyze simulated data in \u201creal-time.\u201d The agent uses multiple machine learning models to process and interpret the relative amounts of various compounds detected in Europa\u2019s icy plumes \u2013 indicators of the possibility of life \u2013 autonomously interprets those data, then makes decisions impacting follow-on analysis or prioritized data transmission based on pre-programmed mission goals.\u00a0\u00a0\u00a0<\/p>\n
\n\n\n<\/figure>\nWith its steady plume of subsurface liquid water jetting out into space, Saturn\u2019s moon Enceladus is a likely candidate for an astrobiology study on a future NASA mission using autonomous spacecraft. In this visualization of that mission, the onboard system (science agent) tracks all eight spacecraft in the constellation (top center window). When the ground track lights up (shows white), the animation in the left window shows a close-up view of the position of that spacecraft. The spacecraft field of view is shown by a green cone (representing a volume of space) and corresponding green rectangle (on the surface). These spacecraft positions could be altered if strongly recommended by the science data results, and these changes can be safely executed autonomously.<\/div>\nNASA\/Pavel Galchenko, NASA\u2019s Scientific Visualization Studio<\/div>\n<\/figcaption><\/div>\n<\/div>\n<\/div>\nFor more information about supercomputers run by NASA High-End Computing, visit: <\/p>\n
https:\/\/hec.nasa.gov\/<\/a><\/p>\n\nFor news media:<\/strong><\/p>\nMembers of the news media interested in covering this topic should reach out to the NASA Ames newsroom<\/a>.<\/p>\n\n
<\/figure>2. Predicting the Strongest Storms within a Global Computer Model<\/strong><\/h2>\nThe common fuel for severe thunderstorms, tornadoes, and hurricanes is convection \u2013 vigorous up-and-down motions of the atmosphere that vertically transport heat and moisture. Operational weather forecasting centers typically predict convective-scale weather using regional, limited-area computer models because global models at convection resolving resolution need too much computing power. Researchers at NASA\u2019s Goddard Space Flight Center in Greenbelt, Maryland, have adapted their global Goddard Earth Observing System (GEOS) model to apply finer grid resolutions of 2 to 4 kilometers (about 1.25 to 2.5 miles) over the continental United States. GEOS forecasts running on the NASA Center for Climate Simulation\u2019s (NCCS\u2019s) Discover supercomputer and NAS\u2019s Aitken supercomputer are extending the predictability of the strongest storms beyond two days while better representing local impacts from intense precipitation, winds, and heat. Ongoing simulations accurately tracked extreme weather events of 2023 including hurricanes Idalia and Lee and tropical storm Ophelia.<\/p>\n
\n\n\n<\/figure>\nHurricane Idalia made landfall along Florida\u2019s northern Gulf Coast on August 30, 2023. Radar reflectivity from observations (left) and simulations by the Goddard Earth Observing System (GEOS) model at 4-kilometer (2.5-mile) (center) and 12-kilometer (7.5-mile) (right) resolution visualize Idalia\u2019s internal structure. While both GEOS forecasts captured Idalia\u2019s landfall within miles of the actual landfall days in advance, the 4- kilometer forecast improved representations of central pressure values, near-surface wind speeds, a very compact eye, and banding convection spiraling inwards from the southeast.<\/div>\nNASA\/William Putman<\/div>\n<\/figcaption><\/div>\n<\/div>\n<\/div>\n3. Protecting Space Capsules During Planetary Entry, Descent, and Landing<\/strong><\/h2>\nNASA space capsules are designed to survive entering planetary atmospheres at hypersonic speeds and protect their payloads \u2013 or their crew \u2013 from the extreme temperatures that occur during entry. In addition to heat, the spacecraft can also encounter dynamic instabilities as they are slowed down by aerodynamic drag during descent. To quantify and understand this additional hazard, researchers at NASA Ames used the agency\u2019s Pleiades and Electra supercomputers to simulate the free-flight conditions of capsules during the full trajectory of planetary entry. These complex simulations are used to analyze capsule flight dynamics and identify any risks the instabilities may pose during the later stage of the flight trajectory. The resulting analyses help engineers design entry vehicles for planetary exploration, helping ensure the success of NASA programs including Artemis and the upcoming Dragonfly mission to Saturn\u2019s largest moon, Titan.\u00a0<\/p>\n
\n\n\n<\/figure>\nFree-flight simulation of the Adaptable Deployable Entry and Placement Technology vehicle showing Q-criterion, which is a measure of the amount of vorticity in the aerodynamic flow. The iso-contours indicate vortex structure, indicating lower vorticity in blue and higher vorticity in red.<\/div>\nNASA\/Joseph Brock<\/div>\n<\/figcaption><\/div>\n<\/div>\n<\/div>\n4. Transforming and Depicting Earth Science Data<\/strong><\/h2>\nFrom the agency\u2019s founding in 1958, NASA has been tasked with widely disseminating information about its activities and results. One new NASA public communication effort is the Earth Information Center<\/a> (EIC), which presents visualizations of raw observational and model data across a set of dashboards arranged like a NASA Mission Control Center for our planet. The EIC installation at NASA Headquarters in Washington includes a multi-panel hyperwall for displaying large-format animations surrounded by smaller portals depicting a number of \u201cvital signs\u201d of the Earth. The diverse data sources include simulations run on the NCCS Discover supercomputer and observations from satellites and ground instruments maintained by NASA and partners. Since opening in late June 2023, the EIC has drawn a great variety of visitors, from dignitaries to elementary school students. In addition, EIC information is aiding policy makers, scientists, and NASA data users such as farmers, business owners, and researchers.<\/p>\n\n\n\n<\/figure>\nThe Earth Information Center (EIC) dashboards include (left) visualizations generated by simulations run on the NASA Center for Climate Simulation\u2019s Discover supercomputer and (right) an \u201cImage of the Day\u201d and \u201cVital Signs\u201d of the planet compiled from NASA and partner agency observations. <\/div>\nNASA\/Brenda Lopez Silva, Michael Chyatte<\/div>\n<\/figcaption><\/div>\n<\/div>\n<\/div>\n5. Using Autonomous Onboard Science Agents for Planetary Exploration<\/strong><\/h2>\nResearchers in NASA Goddard\u2019s Distributed Systems Missions initiative are working to enable deep-space missions that are adaptable and can autonomously interpret and respond to newly-collected science data using an onboard software \u201cagent\u201d rather than waiting for new instructions from Earth at each phase of the mission. To test this new, autonomous mission design, they chose Enceladus, an icy ocean moon of Saturn and one of the most promising targets to search for life in our solar system. In a simulated mission scenario, the scientists modeled various trajectories and orbits of eight small spacecraft to produce what would be the first stable constellation around Enceladus to provide global coverage of the moon for collecting science observations. The team deployed their\u00a0 autonomous onboard science agent to analyze simulated data in \u201creal-time.\u201d The agent uses multiple machine learning models to process and interpret the relative amounts of various compounds detected in Europa\u2019s icy plumes \u2013 indicators of the possibility of life \u2013 autonomously interprets those data, then makes decisions impacting follow-on analysis or prioritized data transmission based on pre-programmed mission goals.\u00a0\u00a0\u00a0<\/p>\n
\n\n\n<\/figure>\nWith its steady plume of subsurface liquid water jetting out into space, Saturn\u2019s moon Enceladus is a likely candidate for an astrobiology study on a future NASA mission using autonomous spacecraft. In this visualization of that mission, the onboard system (science agent) tracks all eight spacecraft in the constellation (top center window). When the ground track lights up (shows white), the animation in the left window shows a close-up view of the position of that spacecraft. The spacecraft field of view is shown by a green cone (representing a volume of space) and corresponding green rectangle (on the surface). These spacecraft positions could be altered if strongly recommended by the science data results, and these changes can be safely executed autonomously.<\/div>\nNASA\/Pavel Galchenko, NASA\u2019s Scientific Visualization Studio<\/div>\n<\/figcaption><\/div>\n<\/div>\n<\/div>\nFor more information about supercomputers run by NASA High-End Computing, visit: <\/p>\n
https:\/\/hec.nasa.gov\/<\/a><\/p>\n\nFor news media:<\/strong><\/p>\nMembers of the news media interested in covering this topic should reach out to the NASA Ames newsroom<\/a>.<\/p>\n\n
<\/figure>3. Protecting Space Capsules During Planetary Entry, Descent, and Landing<\/strong><\/h2>\nNASA space capsules are designed to survive entering planetary atmospheres at hypersonic speeds and protect their payloads \u2013 or their crew \u2013 from the extreme temperatures that occur during entry. In addition to heat, the spacecraft can also encounter dynamic instabilities as they are slowed down by aerodynamic drag during descent. To quantify and understand this additional hazard, researchers at NASA Ames used the agency\u2019s Pleiades and Electra supercomputers to simulate the free-flight conditions of capsules during the full trajectory of planetary entry. These complex simulations are used to analyze capsule flight dynamics and identify any risks the instabilities may pose during the later stage of the flight trajectory. The resulting analyses help engineers design entry vehicles for planetary exploration, helping ensure the success of NASA programs including Artemis and the upcoming Dragonfly mission to Saturn\u2019s largest moon, Titan.\u00a0<\/p>\n
\n\n\n<\/figure>\nFree-flight simulation of the Adaptable Deployable Entry and Placement Technology vehicle showing Q-criterion, which is a measure of the amount of vorticity in the aerodynamic flow. The iso-contours indicate vortex structure, indicating lower vorticity in blue and higher vorticity in red.<\/div>\nNASA\/Joseph Brock<\/div>\n<\/figcaption><\/div>\n<\/div>\n<\/div>\n4. Transforming and Depicting Earth Science Data<\/strong><\/h2>\nFrom the agency\u2019s founding in 1958, NASA has been tasked with widely disseminating information about its activities and results. One new NASA public communication effort is the Earth Information Center<\/a> (EIC), which presents visualizations of raw observational and model data across a set of dashboards arranged like a NASA Mission Control Center for our planet. The EIC installation at NASA Headquarters in Washington includes a multi-panel hyperwall for displaying large-format animations surrounded by smaller portals depicting a number of \u201cvital signs\u201d of the Earth. The diverse data sources include simulations run on the NCCS Discover supercomputer and observations from satellites and ground instruments maintained by NASA and partners. Since opening in late June 2023, the EIC has drawn a great variety of visitors, from dignitaries to elementary school students. In addition, EIC information is aiding policy makers, scientists, and NASA data users such as farmers, business owners, and researchers.<\/p>\n\n\n\n<\/figure>\nThe Earth Information Center (EIC) dashboards include (left) visualizations generated by simulations run on the NASA Center for Climate Simulation\u2019s Discover supercomputer and (right) an \u201cImage of the Day\u201d and \u201cVital Signs\u201d of the planet compiled from NASA and partner agency observations. <\/div>\nNASA\/Brenda Lopez Silva, Michael Chyatte<\/div>\n<\/figcaption><\/div>\n<\/div>\n<\/div>\n5. Using Autonomous Onboard Science Agents for Planetary Exploration<\/strong><\/h2>\nResearchers in NASA Goddard\u2019s Distributed Systems Missions initiative are working to enable deep-space missions that are adaptable and can autonomously interpret and respond to newly-collected science data using an onboard software \u201cagent\u201d rather than waiting for new instructions from Earth at each phase of the mission. To test this new, autonomous mission design, they chose Enceladus, an icy ocean moon of Saturn and one of the most promising targets to search for life in our solar system. In a simulated mission scenario, the scientists modeled various trajectories and orbits of eight small spacecraft to produce what would be the first stable constellation around Enceladus to provide global coverage of the moon for collecting science observations. The team deployed their\u00a0 autonomous onboard science agent to analyze simulated data in \u201creal-time.\u201d The agent uses multiple machine learning models to process and interpret the relative amounts of various compounds detected in Europa\u2019s icy plumes \u2013 indicators of the possibility of life \u2013 autonomously interprets those data, then makes decisions impacting follow-on analysis or prioritized data transmission based on pre-programmed mission goals.\u00a0\u00a0\u00a0<\/p>\n
\n\n\n<\/figure>\nWith its steady plume of subsurface liquid water jetting out into space, Saturn\u2019s moon Enceladus is a likely candidate for an astrobiology study on a future NASA mission using autonomous spacecraft. In this visualization of that mission, the onboard system (science agent) tracks all eight spacecraft in the constellation (top center window). When the ground track lights up (shows white), the animation in the left window shows a close-up view of the position of that spacecraft. The spacecraft field of view is shown by a green cone (representing a volume of space) and corresponding green rectangle (on the surface). These spacecraft positions could be altered if strongly recommended by the science data results, and these changes can be safely executed autonomously.<\/div>\nNASA\/Pavel Galchenko, NASA\u2019s Scientific Visualization Studio<\/div>\n<\/figcaption><\/div>\n<\/div>\n<\/div>\nFor more information about supercomputers run by NASA High-End Computing, visit: <\/p>\n
https:\/\/hec.nasa.gov\/<\/a><\/p>\n\nFor news media:<\/strong><\/p>\nMembers of the news media interested in covering this topic should reach out to the NASA Ames newsroom<\/a>.<\/p>\n\n
<\/figure>4. Transforming and Depicting Earth Science Data<\/strong><\/h2>\nFrom the agency\u2019s founding in 1958, NASA has been tasked with widely disseminating information about its activities and results. One new NASA public communication effort is the Earth Information Center<\/a> (EIC), which presents visualizations of raw observational and model data across a set of dashboards arranged like a NASA Mission Control Center for our planet. The EIC installation at NASA Headquarters in Washington includes a multi-panel hyperwall for displaying large-format animations surrounded by smaller portals depicting a number of \u201cvital signs\u201d of the Earth. The diverse data sources include simulations run on the NCCS Discover supercomputer and observations from satellites and ground instruments maintained by NASA and partners. Since opening in late June 2023, the EIC has drawn a great variety of visitors, from dignitaries to elementary school students. In addition, EIC information is aiding policy makers, scientists, and NASA data users such as farmers, business owners, and researchers.<\/p>\n\n\n\n<\/figure>\nThe Earth Information Center (EIC) dashboards include (left) visualizations generated by simulations run on the NASA Center for Climate Simulation\u2019s Discover supercomputer and (right) an \u201cImage of the Day\u201d and \u201cVital Signs\u201d of the planet compiled from NASA and partner agency observations. <\/div>\nNASA\/Brenda Lopez Silva, Michael Chyatte<\/div>\n<\/figcaption><\/div>\n<\/div>\n<\/div>\n5. Using Autonomous Onboard Science Agents for Planetary Exploration<\/strong><\/h2>\nResearchers in NASA Goddard\u2019s Distributed Systems Missions initiative are working to enable deep-space missions that are adaptable and can autonomously interpret and respond to newly-collected science data using an onboard software \u201cagent\u201d rather than waiting for new instructions from Earth at each phase of the mission. To test this new, autonomous mission design, they chose Enceladus, an icy ocean moon of Saturn and one of the most promising targets to search for life in our solar system. In a simulated mission scenario, the scientists modeled various trajectories and orbits of eight small spacecraft to produce what would be the first stable constellation around Enceladus to provide global coverage of the moon for collecting science observations. The team deployed their\u00a0 autonomous onboard science agent to analyze simulated data in \u201creal-time.\u201d The agent uses multiple machine learning models to process and interpret the relative amounts of various compounds detected in Europa\u2019s icy plumes \u2013 indicators of the possibility of life \u2013 autonomously interprets those data, then makes decisions impacting follow-on analysis or prioritized data transmission based on pre-programmed mission goals.\u00a0\u00a0\u00a0<\/p>\n
\n\n\n<\/figure>\nWith its steady plume of subsurface liquid water jetting out into space, Saturn\u2019s moon Enceladus is a likely candidate for an astrobiology study on a future NASA mission using autonomous spacecraft. In this visualization of that mission, the onboard system (science agent) tracks all eight spacecraft in the constellation (top center window). When the ground track lights up (shows white), the animation in the left window shows a close-up view of the position of that spacecraft. The spacecraft field of view is shown by a green cone (representing a volume of space) and corresponding green rectangle (on the surface). These spacecraft positions could be altered if strongly recommended by the science data results, and these changes can be safely executed autonomously.<\/div>\nNASA\/Pavel Galchenko, NASA\u2019s Scientific Visualization Studio<\/div>\n<\/figcaption><\/div>\n<\/div>\n<\/div>\nFor more information about supercomputers run by NASA High-End Computing, visit: <\/p>\n
https:\/\/hec.nasa.gov\/<\/a><\/p>\n\nFor news media:<\/strong><\/p>\nMembers of the news media interested in covering this topic should reach out to the NASA Ames newsroom<\/a>.<\/p>\n\n
<\/figure>5. Using Autonomous Onboard Science Agents for Planetary Exploration<\/strong><\/h2>\nResearchers in NASA Goddard\u2019s Distributed Systems Missions initiative are working to enable deep-space missions that are adaptable and can autonomously interpret and respond to newly-collected science data using an onboard software \u201cagent\u201d rather than waiting for new instructions from Earth at each phase of the mission. To test this new, autonomous mission design, they chose Enceladus, an icy ocean moon of Saturn and one of the most promising targets to search for life in our solar system. In a simulated mission scenario, the scientists modeled various trajectories and orbits of eight small spacecraft to produce what would be the first stable constellation around Enceladus to provide global coverage of the moon for collecting science observations. The team deployed their\u00a0 autonomous onboard science agent to analyze simulated data in \u201creal-time.\u201d The agent uses multiple machine learning models to process and interpret the relative amounts of various compounds detected in Europa\u2019s icy plumes \u2013 indicators of the possibility of life \u2013 autonomously interprets those data, then makes decisions impacting follow-on analysis or prioritized data transmission based on pre-programmed mission goals.\u00a0\u00a0\u00a0<\/p>\n
\n\n\n<\/figure>\nWith its steady plume of subsurface liquid water jetting out into space, Saturn\u2019s moon Enceladus is a likely candidate for an astrobiology study on a future NASA mission using autonomous spacecraft. In this visualization of that mission, the onboard system (science agent) tracks all eight spacecraft in the constellation (top center window). When the ground track lights up (shows white), the animation in the left window shows a close-up view of the position of that spacecraft. The spacecraft field of view is shown by a green cone (representing a volume of space) and corresponding green rectangle (on the surface). These spacecraft positions could be altered if strongly recommended by the science data results, and these changes can be safely executed autonomously.<\/div>\nNASA\/Pavel Galchenko, NASA\u2019s Scientific Visualization Studio<\/div>\n<\/figcaption><\/div>\n<\/div>\n<\/div>\nFor more information about supercomputers run by NASA High-End Computing, visit: <\/p>\n
https:\/\/hec.nasa.gov\/<\/a><\/p>\n\nFor news media:<\/strong><\/p>\nMembers of the news media interested in covering this topic should reach out to the NASA Ames newsroom<\/a>.<\/p>\n\n
For more information about supercomputers run by NASA High-End Computing, visit: <\/p>\n
https:\/\/hec.nasa.gov\/<\/a><\/p>\n\n For news media:<\/strong><\/p>\n Members of the news media interested in covering this topic should reach out to the NASA Ames newsroom<\/a>.<\/p>\n\n