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Into the Eye of the Storm: NASA's Parker probe flying through the Sun’s Corona
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By European Space Agency
Lobster-eye satellite Einstein Probe captured the X-ray flash from a very elusive celestial pair. The discovery opens a new way to explore how massive stars interact and evolve, confirming the unique power of the mission to uncover fleeting X-ray sources in the sky.
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By NASA
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Preparations for Next Moonwalk Simulations Underway (and Underwater)
NASA’s X-59 lights up the night sky with its unique Mach diamonds, also known as shock diamonds, during maximum afterburner testing at Lockheed Martin Skunk Works in Palmdale, California. The test demonstrated the engine’s ability to generate the thrust required for supersonic flight, advancing NASA’s Quesst mission.Credit: Lockheed Martin/Gary Tice NASA’s X-59 quiet supersonic research aircraft took another successful step toward flight with the conclusion of a series of engine performance tests.
In preparation for the X-59’s planned first flight this year, NASA and Lockheed Martin successfully completed the aircraft’s engine run tests in January. The engine, a modified F414-GE-100 that powers the aircraft’s flight and integrated subsystems, performed to expectations during three increasingly complicated tests that ran from October through January at contractor Lockheed Martin’s Skunk Works facility in Palmdale, California.
“We have successfully progressed through our engine ground tests as we planned,” said Raymond Castner, X-59 propulsion lead at NASA’s Glenn Research Center in Cleveland. “We had no major showstoppers. We were getting smooth and steady airflow as predicted from wind tunnel testing. We didn’t have any structural or excessive vibration issues. And parts of the engine and aircraft that needed cooling were getting it.”
The tests began with seeing how the aircraft’s hydraulics, electrical, and environmental control systems performed when the engine was powered up but idling. The team then performed throttle checks, bringing the aircraft up to full power and firing its afterburner – an engine component that generates additional thrust – to maximum.
In preparation for the X-59’s planned first flight this year, NASA and Lockheed Martin successfully completed the aircraft’s engine run tests in January. Testing included electrical, hydraulics, and environmental control systems.
Credit: NASA/Lillianne Hammel A third test, throttle snaps, involved moving the throttle swiftly back and forth to validate that the engine responds instantly. The engine produces as much as 22,000 pounds of thrust to achieve a desired cruising speed of Mach 1.4 (925 miles per hour) at an altitude of approximately 55,000 feet.
The X-59’s engine, similar to those aboard the U.S. Navy’s F-18 Super Hornet, is mounted on top of the aircraft to reduce the level of noise reaching the ground. Many features of the X-59, including its 38-foot-long nose, are designed to lower the noise of a sonic boom to that of a mere “thump,” similar to the sound of a car door slamming nearby.
Next steps before first flight will include evaluating the X-59 for potential electromagnetic interference effects, as well as “aluminum bird” testing, during which data will be fed to the aircraft under both normal and failure conditions. A series of taxi tests and other preparations will also take place before the first flight.
The X-59 is the centerpiece of NASA’s Quesst mission, which seeks to solve one of the major barriers to commercial supersonic flight over land by making sonic booms quieter.
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By NASA
An image of a coastal marshland combines aerial and satellite views in a technique similar to hyperspectral imaging. Combining data from multiple sources gives scientists information that can support environmental management.John Moisan When it comes to making real-time decisions about unfamiliar data – say, choosing a path to hike up a mountain you’ve never scaled before – existing artificial intelligence and machine learning tech doesn’t come close to measuring up to human skill. That’s why NASA scientist John Moisan is developing an AI “eye.”
Oceanographer John MoisanNASA Moisan, an oceanographer at NASA’s Wallops Flight Facility near Chincoteague, Virginia, said AI will direct his A-Eye, a movable sensor. After analyzing images his AI would not just find known patterns in new data, but also steer the sensor to observe and discover new features or biological processes.
“A truly intelligent machine needs to be able to recognize when it is faced with something truly new and worthy of further observation,” Moisan said. “Most AI applications are mapping applications trained with familiar data to recognize patterns in new data. How do you teach a machine to recognize something it doesn’t understand, stop and say ‘What was that? Let’s take a closer look.’ That’s discovery.”
Finding and identifying new patterns in complex data is still the domain of human scientists, and how humans see plays a large part, said Goddard AI expert James MacKinnon. Scientists analyze large data sets by looking at visualizations that can help bring out relationships between different variables within the data.
Infrared images like this one from a marsh area on the Maryland/Virginia Eastern Shore coastal barrier and back bay regions reveal clues to scientists about plant health, photosynthesis, and other conditions that affect vegetation and ecosystems.John Moisan It’s another story to train a computer to look at large data streams in real time to see those connections, MacKinnon said. Especially when looking for correlations and inter-relationships in the data that the computer hasn’t been trained to identify.
Moisan intends first to set his A-Eye on interpreting images from Earth’s complex aquatic and coastal regions. He expects to reach that goal this year, training the AI using observations from prior flights over the Delmarva Peninsula. Follow-up funding would help him complete the optical pointing goal.
“How do you pick out things that matter in a scan?” Moisan asked. “I want to be able to quickly point the A-Eye at something swept up in the scan, so that from a remote area we can get whatever we need to understand the environmental scene.”
Moisan’s on-board AI would scan the collected data in real-time to search for significant features, then steer an optical sensor to collect more detailed data in infrared and other frequencies.
Thinking machines may be set to play a larger role in future exploration of our universe. Sophisticated computers taught to recognize chemical signatures that could indicate life processes, or landscape features like lava flows or craters, might offer to increase the value of science data returned from lunar or deep-space exploration.
Today’s state-of-the-art AI is not quite ready to make mission-critical decisions, MacKinnon said.
“You need some way to take a perception of a scene and turn that into a decision and that’s really hard,” he said. “The scary thing, to a scientist, is to throw away data that could be valuable. An AI might prioritize what data to send first or have an algorithm that can call attention to anomalies, but at the end of the day, it’s going to be a scientist looking at that data that results in discoveries.”
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Last Updated Feb 10, 2025 Related Terms
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By NASA
“I do evolutionary programming,” said NASA Goddard oceanographer Dr. John Moisan. “I see a lot of possibility in using evolutionary programming to solve many large problems we are trying to solve. How did life start and evolve? Can these processes be used to evolve intelligence or sentience?”Courtesy of John Moisan Name: John Moisan
Formal Job Classification: Research oceanographer
Organization: Ocean Ecology Laboratory, Hydrosphere, Biosphere, Geophysics (HBG), Earth Science Directorate (Code 616) – duty station at NASA’s Wallops Flight Facility on Virginia’s Eastern Shore
What do you do and what is most interesting about your role here at Goddard? How do you help support Goddard’s mission?
I develop ecosystem models and satellite algorithms to understand how the ocean’s ecology works. My work has evolved over time from when I coded ocean ecosystem models to the present where I now use artificial intelligence to evolve the ocean ecosystem models.
How did you become an oceanographer?
As a child, I watched a TV series called “Sea Hunt,” which involved looking for treasure in the ocean. It inspired me to want to spend my life scuba diving.
I got a Bachelor of Science in marine biology from the University of New England in Biddeford, Maine, and later got a Ph.D. from the Center for Coastal Physical Oceanography at Old Dominion University in Norfolk, Virginia.
Initially, I just wanted to do marine biology which to me meant doing lots of scuba diving, maybe living on a sailboat. Later, when I was starting my graduate schoolwork, I found a book about mathematical biology and a great professor who helped open my eyes to the world of numerical modeling. I found out that instead of scuba diving, I needed instead to spend my days behind a computer, learning how to craft ideas into equations and then code these into a computer to run simulations on ocean ecosystems.
I put myself through my initial education. I went to school fulltime, but I lived at home and hitchhiked to college on a daily basis. When I started my graduate school, I worked to support myself. I was in school during the normal work week, but from Friday evening through Sunday night, I worked 40 hours at a medical center cleaning and sterilizing the operating room instrument carts. This was during the height of the AIDS epidemic.
What was most exciting about your two field trips to the Antarctic?
In 1987, I joined a six-week research expedition to an Antarctic research station to explore how the ozone hole was impacting phytoplankton. These are single-celled algae that are responsible for making half the oxygen we breathe. Traveling to Antarctica is like visiting another planet. There are more types of blue than I’ve ever seen. It is an amazingly beautiful place to visit, with wild landscapes, glaciers, mountains, sea ice, and a wide range of wildlife. After my first trip I returned home and went back in a few months later as a biologist on a joint Polish–U.S. (National Oceanic and Atmospheric Administration) expedition to carry out a biological survey and measure how much fast the phytoplankton was growing in different areas of the Southern Ocean. We used nets to measure the amounts of fish and shrimp and took water samples to measure salinity, the amount of algae and their growth rates. We ate well, for example the Polish cook made up a large batch of smoked ice fish.
What other field work have you done?
While a graduate student, I helped do some benthic work in the Gulf of Maine. This study was focused on understanding the rates of respiration in the muds on the bottom of the ocean and on understanding how much biomass was in the muds. The project lowered a benthic grab device to the bottom where it would push a box core device into the sediments to return it to the surface. This process is sort of like doing a biopsy of the ocean bottom.
What is your goal as a research oceanographer at Goddard?
Ocean scientists measure the amount and variability of chlorophyll a, a pigment in algae, in the ocean because it is an analogue to the amount of algae or phytoplankton in the ocean. Chlorophyll a is used to capture solar energy to make sugars, which the algae use for growth. Generally, areas of the ocean that have more chlorophyll are also areas where growth or primary production is higher. So, by estimating how much chlorophyll is in the ocean we can study how these processes are changing with an aim in understanding why. NASA uses the color of the ocean using satellites to estimate chlorophyll a because chlorophyll absorbs sunlight and changes the color of the ocean. Algae have other kinds of pigments, each of which absorbs light at different wavelengths. Because different groups of algae have different levels of pigments, they are like fingerprints that can reveal the type of algae in the water. Some of my research aims at trying to use artificial intelligence and mathematical techniques to create new ways to measure these pigments from space to understand how ocean ecosystems change.
In 2024, NASA plans to launch the Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) satellite, which will measure the color of the ocean at many different wavelengths. The data from this satellite can be used with results from my work on genetic programs and inverse modeling to estimate concentrations of different pigments and possibly concentrations of different types of algae in the ocean.
You have been at Goddard over 22 years. What is most memorable to you?
I develop ecosystem models. But ecosystems do not have laws in the same way that physics has laws. Equations need to be created so that the ecosystem models represent what is observed in the real world. Satellites have been a great source for those observations, but without a lot of other types of observations that are collected in the field, the ocean, it is difficult to develop these equations. In my time at NASA, I have only been able to develop models because of the great but often tedious work that ocean scientists around the world have been doing when they go on ocean expeditions to measure various ocean features, be it simple temperature or the more complicated measurements of algal growth rates. My experience with their willingness to collaborate and share data is especially memorable. This experience is also what I enjoyed with numerous scientists at NASA who have always been willing to support new ideas and point me in the right direction. It has made working at NASA a phenomenal experience.
What are the philosophical implications of your work?
The human capacity to think rapidly, to test and change our opinions based on what we learn, is slow compared to that of a computer. Computers can help us adapt more quickly. I can put 1,000 students in a room developing ecosystem model models. But I know that this process of developing ecosystem models is slow when compared what a computer can do using an artificial intelligence approach called genetic programming, it is a much faster way to generate ecosystem model solutions.
Philosophically, there is no real ecosystem model that is the best. Life and ecosystems on Earth change and adapt at rates too fast for any present-day model to resolve, especially considering climate change. The only real ecosystem model is the reality itself. No computer model can perfectly simulate ecosystems. By utilizing the fast adaptability that evolutionary computer modeling techniques provide, simulating and ultimately predicting ecosystems can be improved greatly.
How does your work have implications for scientists in general?
I do evolutionary programming. I see a lot of possibility in using evolutionary programming to solve many large problems we are trying to solve. How did life start and evolve? Can these processes be used to evolve intelligence or sentience?
The artificial intelligence (AI) work answers questions, but you need to identify the questions. This is the greater problem when it comes to working with AI. You cannot answer the question of how to create a sentient life if you do not know how to define it. If I cannot measure life, how can I model it? I do not know how to write that equation. How does life evolve? How did the evolutionary process start? These are big questions I enjoy discussing with friends. It can be as frustrating as contemplating “nothing.”
Who inspires you?
Many of the scientists that I was fortunate to work with at various research institutes, such as Scripps Institution of Oceanography at the University of California, San Diego. These are groups of scientists are open to always willing to share their ideas. These are individuals who enjoy doing science. I will always be indebted to them for their kindness in sharing of ideas and data.
Do you still scuba dive?
Yes, I wish I could dive daily, it is a very calming experience. I’m trying to get my kids to join me.
What else do you do for fun?
My wife and I bike and travel. Our next big bike trip will hopefully be to Shangri-La City in China. I also enjoy sailing and trying to grow tropical plants. But, most of all, I enjoy helping raise my children to be resilient, empathic, and intelligent beings.
What are your words to live by?
Life. So much to see. So little time.
Conversations With Goddard is a collection of question and answer profiles highlighting the breadth and depth of NASA’s Goddard Space Flight Center’s talented and diverse workforce. The Conversations have been published twice a month on average since May 2011. Read past editions on Goddard’s “Our People” webpage. Conversations With Goddard is a collection of Q&A profiles highlighting the breadth and depth of NASA’s Goddard Space Flight Center’s talented and diverse workforce. The Conversations have been published twice a month on average since May 2011. Read past editions on Goddard’s “Our People” webpage.
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Last Updated Feb 10, 2025 EditorJessica EvansContactRob Garnerrob.garner@nasa.gov Related Terms
Goddard Space Flight Center Artificial Intelligence (AI) People of Goddard Wallops Flight Facility Keep Exploring Discover More Topics From NASA
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By NASA
“Data visualization has recently exploded as a communication tool,” said Mark SubbaRao, information technology specialist and lead for NASA’s Scientific Visualization Studio. “As data becomes bigger and more complex, visualization becomes an even more important tool for understanding that data.”Rachel Connolly / Courtesy of Mark SubbaRao Name: Mark SubbaRao
Title: Lead, Scientific Visualization Studio (SVS)
Formal Job Classification: Information Technology Specialist
Organization: SVS, Science Mission Directorate (Code 606.4)
What do you do and what is most interesting about your role here at Goddard? How do you help support Goddard’s mission?
I have an amazing job. I get to work with all the most interesting NASA science and make it visual to help people can understand it. The Scientific Visualization Studio, the SVS, supports all of NASA and is located at Goddard.
What is your educational background?
I have B.S. in engineering physics, minor in astronomy, from Lehigh University in Bethlehem, Pennsylvania. I have a Ph.D. in astrophysics from Johns Hopkins University.
What is data visualization? How is it different from animation?
Data visualization is the graphical representation of actual data (in our case usually scientific data). At its most basic it takes the forms of charts, graphs, and maps. In contrast, conceptual animation, such as the work of our colleagues in the CI Lab, is the graphical representation of ideas. Conceptual animation and data visualization are both needed to communicate the full scientific process.
How did your work for the University of Chicago develop your interest in visualization?
I worked on software for the Sloan Digital Sky Survey, a project to create the biggest 3D map of the universe. Our goal was to map 3D positions of a million galaxies, which we did. My role was to develop the software to determine the distance to galaxies. To see the result we needed a way to see how the galaxies were distributed in 3D, which led to my interest in visualization.
Viewing this map, I felt like we had revealed a new world which no one had yet seen altogether. The desire to share that with the public led me a position at the Adler Planetarium in Chicago.
“Astrographics,” a video piece Mark SubbaRao produced for the Adler Planetarium, being projected on the Merchandise Mart on the Chicago riverfront.Michael SubbaRao / Courtesy of Mark SubbaRao How did planetariums evolve during your 18 years of working for the Adler Planetarium?
I led their visualization efforts for their Space Visualization Laboratory, a laboratory that was on the museum floor and had multiple specialized displays. The local scientific community used our laboratory to present to the public including other scientists and students.
I also produced planetarium shows and designed exhibits. My last project, “Astrographics” for Art on the Mart, was a 2.6-acre, outdoor projection onto a building near the Chicago River. We believe that this is the largest, permanent outdoor digital projection in the world.
I began to see the power of the planetarium as a data visualization environment. Traditionally, a planetarium has been a place to project stars and tell stories about constellations. Planetariums have now evolved into a general-purpose visualization platform to communicate science.
I got more involved with the planetarium community, which led to me becoming president of the International Planetarium Society. A major focus of my presidency was promoting planetariums in Africa.
Why did you come to NASA’s SVS at Goddard?
I came to Goddard in December 2020. I always admired NASA’s SVS and had used their products. I consider the SVS the preeminent group using scientific visualization for public communication.
I wanted to work on visualizations for a broader variety of sciences, in particular, climate science. Our group created visualizations for the United Nations Climate Conference (COP26) in Glasgow, Scotland, the fall of 2021. In March 2022, I created a visualization called Climate Spiral, which went viral.
This visualization shows monthly global temperature anomalies (changes from an average) between the years 1880 and 2021. Whites and blues indicate cooler temperatures, while oranges and reds show warmer temperatures.
Credits: NASA’s Goddard Space Flight Center / NASA’s Scientific Visualization Studio
Download high-resolution video and images from NASA’s Scientific Visualization Studio As the lead, how do you hope to inspire your group?
Our group is very talented, experienced, and self-motivated. Data visualization has recently exploded as a communication tool. Our goal is to continue to stay on top of this rapidly evolving field. Coupled with this, there has been an explosion in scientific data from satellites and super computers. As data becomes bigger and more complex, visualization becomes an even more important tool for understanding that data.
Karen St. Germain, NASA’s Director of Earth Science, presenting an SVS visualization of carbon dioxide to the 2021 United Nations Climate Change Conference in Glasgow, Scotland.
Download high-resolution video and images from NASA’s Scientific Visualization Studio: https://svs.gsfc.nasa.gov/31168NASA’s Goddard Space Flight Center / NASA’s Scientific Visualization Studio Your work combines art and science. What are the benefits of combining art and science?
One huge benefit is that you can reach people through an artistic visual presentation of science who may not be interested in simply reading an article. You can go beyond teaching people, you can move them emotionally through a good, artistic presentation.
For example, in “Climate Spiral,” we did not want to just inform people that global average temperatures have increased, we wanted people to feel that the temperature has increased.
Also, our universe is just beautiful. Why not let the beauty of the universe create something artistic for you? I sometimes feel like I cheat by letting the universe do my design for me.
What do you do for fun?
Since moving to Maryland, and living near the Chesapeake Bay, I have taken up stand up paddleboarding. I like to cook too. My father is Indian, so I cook a lot of Indian food.
Who inspires you?
Arthur C. Clarke, the science fiction writer, also wrote a lot of popular science. He played a big part in my decision to become a scientist.
Conversations With Goddard is a collection of Q&A profiles highlighting the breadth and depth of NASA’s Goddard Space Flight Center’s talented and diverse workforce. The Conversations have been published twice a month on average since May 2011. Read past editions on Goddard’s “Our People” webpage.
By Elizabeth M. Jarrell
NASA’s Goddard Space Flight Center, Greenbelt, Md.
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Last Updated Feb 10, 2025 EditorJessica EvansContactRob Garnerrob.garner@nasa.gov Related Terms
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