Archivo de la etiqueta: Astronomy

NASA’s Roman Team Selects Survey to Map Our Galaxy’s Far Side

NASA’s Nancy Grace Roman Space Telescope team has announced plans for an unprecedented survey of the plane of our Milky Way galaxy. It will peer deeper into this region than any other survey, mapping more of our galaxy’s stars than all previous observations combined.

“There’s a really broad range of science we can explore with this type of survey, from star formation and evolution to dust in between stars and the dynamics of the heart of the galaxy,” said Catherine Zucker, an astrophysicist at the Center for Astrophysics | Harvard & Smithsonian in Cambridge, Massachusetts, who co-authored a white paper describing some of the benefits of such an observing program.

A galactic plane survey was the top-ranked submission following a 2021 call for Roman survey ideas. Now, the scientific community will work together to design the observational program ahead of Roman’s launch by May 2027.

“There will be lots of trade-offs since scientists will have to choose between, for example, how much area to cover and how completely to map it in all the different possible filters,” said paper co-author Robert Benjamin, an astronomer at the University of Wisconsin-Whitewater.

While the details of the survey remain to be determined, scientists say if it covered about 1,000 square degrees – a region of sky as large as 5,000 full moons – it could reveal well over 100 billion cosmic objects (mainly stars).

“That would be pretty close to a complete census of all the stars in our galaxy, and it would only take around a month,” said Roberta Paladini, a senior research scientist at Caltech/IPAC in Pasadena, California, and the white paper’s lead author. “It would take decades to observe such a large patch of the sky with the Hubble or James Webb space telescopes. Roman will be a survey machine!”

Milky Way Anatomy

Observatories with smaller views of space have provided exquisite images of other galaxies, revealing complex structures. But studying our own galaxy’s anatomy is surprisingly difficult. The plane of the Milky Way covers such a large area on the sky that studying it in detail can take a very long time. Astronomers also must peer through thick dust that obscures distant starlight.

While we’ve studied our solar system’s neighborhood well, Zucker says, “we have a very incomplete view of what the other half of that Milky Way looks like beyond the galactic center.”

Observatories like NASA’s retired Spitzer Space Telescope have conducted large-area surveys of the galactic plane in longer wavelengths of light and revealed some star-forming regions on the far side of the galaxy. But it couldn’t resolve fine details like Roman will do.

“Spitzer set up the questions that Roman will be able to solve,” Benjamin said.

Roman’s combination of a large field of view, crisp resolution, and the ability to peer through dust make it the ideal instrument to study the Milky Way. And seeing stars in different wavelengths of light – optical and infrared – will help astronomers learn things such as the stars’ temperatures. That one piece of information unlocks much more data, from the star’s evolutionary stage and composition to its luminosity and size.

“We can do very detailed studies of things like star formation and the structure of our own galaxy in a way that we can’t do for any other galaxy,” Paladini said.

Roman will offer new insights about the structure of the central region known as the bulge, the “bar” that stretches across it, and the spiral arms that extend from it.

“We’ll basically rewrite the 3D picture of the far side of the galaxy,” Zucker said.

Roman’s sharp vision will help astronomers see individual stars even in stellar nurseries on the far side of the galaxy. That will help Roman generate a huge new catalog of stars since it will be able to map 10 times farther than previous precision mapping by ESA’s (the European Space Agency’s) Gaia space mission. Gaia mapped over 1 billion stars in 3D largely within about 10,000 light-years. Roman could map up to 100 billion stars 100,000 light-years away or more (stretching out to the most distant edge of our galaxy and beyond).

The Galactic Plane Survey is Roman’s first announced general astrophysics survey – one of several observation programs Roman will do in addition to its three core community surveys and Coronagraph technology demonstration. At least 25% of Roman’s five-year primary mission will be allocated to general astrophysics surveys in order to pursue science that can’t be done with only the mission’s core community survey data. Astronomers from all over the world will have the opportunity to use Roman and propose cutting-edge research, enabling the astronomical community to utilize the full potential of Roman’s capabilities to conduct extraordinary science.

The Nancy Grace Roman Space Telescope is managed at NASA’s Goddard Space Flight Center in Greenbelt, Maryland, with participation by NASA’s Jet Propulsion Laboratory and Caltech/IPAC in Southern California, the Space Telescope Science Institute in Baltimore, and a science team comprising scientists from various research institutions. The primary industrial partners are BAE Systems in Boulder, Colorado; L3Harris Technologies in Melbourne, Florida; and Teledyne Scientific & Imaging in Thousand Oaks, California.

Download high-resolution video and images from NASA’s Scientific Visualization Studio

By Ashley Balzer
NASA’s Goddard Space Flight Center, Greenbelt, Md.

Media contact:

Claire Andreoli
NASA’s Goddard Space Flight Center, Greenbelt, Md.
claire.andreoli@nasa.gov
301-286-1940

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Ashley Balzer

Understanding Risk, Artificial Intelligence, and Improving Software Quality

The software discipline has broad involvement across each of the NASA Mission Directorates. Some recent discipline focus and development areas are highlighted below, along with a look at the Software Technical Discipline Team’s (TDT) approach to evolving discipline best practices toward the future.

Understanding Automation Risk

Software creates automation. Reliance on that automation is increasing the amount of software in NASA programs. This year, the software team examined historical software incidents in aerospace to characterize how, why, and where software or automation is mostly likely to fail. The goal is to better engineer software to minimize the risk of errors, improve software processes, and better architect software for resilience to errors (or improve fault-tolerance should errors occur).

Some key findings shown in the above charts, indicate that software more often does the wrong thing rather than just crash. Rebooting was found to be ineffective when software behaves erroneously. Unexpected behavior was mostly attributed to the code or logic itself, and about half of those instances were the result of missing software—software not present due to unanticipated situations or missing requirements. This may indicate that even fully tested software is exposed to this significant class of error. Data misconfiguration was a sizeable factor that continues to grow with the advent of more modern data-driven systems. A final subjective category assessed was “unknown unknowns”—things that could not have been reasonably anticipated. These accounted for 19% of software incidents studied.

The software team is using and sharing these findings to improve best practices. More emphasis is being placed on the importance of complete requirements, off-nominal test campaigns, and “test as you fly” using real hardware in the loop. When designing systems for fault tolerance, more consideration should be given to detecting and correcting for erroneous behavior versus just checking for a crash. Less confidence should be placed on rebooting as an effective recovery strategy. Backup strategies for automations should be employed for critical applications—considering the historic prevalence of absent software and unknown unknowns. More information can be found in NASA/TP-20230012154, Software Error Incident Categorizations in Aerospace.

Employing AI and Machine Learning Techniques

The rise of artificial intelligence (AI) and machine learning (ML) techniques has allowed NASA to examine data in new ways that were not previously possible. While NASA has been employing autonomy since its inception, AI/ML techniques provide teams the ability to expand the use of autonomy outside of previous bounds. The Agency has been working on AI ethics frameworks and examining standards, procedures, and practices, taking security implications into account. While AI/ML generally uses nondeterministic statistical algorithms that currently limit its use in safety-critical flight applications, it is used by NASA in more than 400 AI/ML projects aiding research and science. The Agency also uses AI/ML Communities of Practice for sharing knowledge across the centers. The TDT surveyed AI/ML work across the Agency and summarized it for trends and lessons.

Common usages of AI/ML include image recognition and identification. NASA Earth science missions use AI/ML to identify marine debris, measure cloud thickness, and identify wildfire smoke (examples are shown in the satellite images below). This reduces the workload on personnel. There are many applications of AI/ML being used to predict atmospheric physics. One example is hurricane track and intensity prediction. Another example is predicting planetary boundary layer thickness and comparing it against measurements, and those predictions are being fused with live data to improve the performance over previous boundary layer models.

The Code Analysis Pipeline: Static Analysis Tool for IV&V and Software Quality Improvement

The Code Analysis Pipeline (CAP) is an open-source tool architecture that supports software development and assurance activities, improving overall software quality. The Independent Verification and Validation (IV&V) Program is using CAP to support software assurance on the Human Landing System, Gateway, Exploration Ground Systems, Orion, and Roman. CAP supports the configuration and automated execution of multiple static code analysis tools to identify potential code defects, generate code metrics that indicate potential areas of quality concern (e.g., cyclomatic complexity), and execute any other tool that analyzes or processes source code. The TDT is focused on integrating Modified Condition/Decision Coverage analysis support for coverage testing. Results from tools are consolidated into a central database and presented in context through a user interface that supports review, query, reporting, and analysis of results as the code matures.

The tool architecture is based on an industry standard DevOps approach for continuous building of source code and running of tools. CAP integrates with GitHub for source code control, uses Jenkins to support automation of analysis builds, and leverages Docker to create standard and custom build environments that support unique mission needs and use cases.

Improving Software Process & Sharing Best Practices

The TDT has captured the best practice knowledge from across the centers in NPR 7150.2, NASA Software Engineering Requirements, and NASA-HDBK-2203, NASA Software Engineering and Assurance Handbook (https://swehb.nasa.gov.) Two APPEL training classes have been developed and shared with several organizations to give them the foundations in the NPR and software engineering management. The TDT established several subteams to help programs/projects as they tackle software architecture, project management, requirements, cybersecurity, testing and verification, and programmable logic controllers. Many of these teams have developed guidance and best practices, which are documented in NASA-HDBK-2203 and on the NASA Engineering Network.

NPR 7150.2 and the handbook outline best practices over the full lifecycle for all NASA software. This includes requirements development, architecture, design, implementation, and verification. Also covered, and equally important, are the supporting activities/functions that improve quality, including software assurance, safety configuration management, reuse, and software acquisition. Rationale and guidance for the requirements are addressed in the handbook that is internally and externally accessible and regularly updated as new information, tools, and techniques are found and used.

The Software TDT deputies train software engineers, systems engineers, chief engineers, and project managers on the NPR requirements and their role in ensuring these requirements are implemented across NASA centers. Additionally, the TDT deputies train software technical leads on many of the advanced management aspects of a software engineering effort, including planning, cost estimating, negotiating, and handling change management.

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Meagan Chappell

Splashdown! NASA’s SpaceX Crew-7 Finishes Mission, Returns to Earth

NASA’s SpaceX Crew-7 completed the agency’s seventh commercial crew rotation mission to the International Space Station on Tuesday after splashing down safely in a Dragon spacecraft off the coast of Pensacola, Florida. The international crew of four spent 199 days in orbit.

NASA astronaut Jasmin Moghbeli, ESA (European Space Agency) astronaut Andreas Mogensen, JAXA (Japan Aerospace Exploration Agency) astronaut Satoshi Furukawa, and Roscosmos cosmonaut Konstantin Borisov, returned to Earth splashing down at 5:47 a.m. EDT. Teams aboard SpaceX recovery vessels retrieved the spacecraft and its crew. After returning to shore, the crew will fly to NASA’s Johnson Space Center in Houston.

“After more than six months aboard the International Space Station, NASA’s SpaceX Crew-7 has safely returned home,” said NASA Administrator Bill Nelson. “This international crew showed that space unites us all. It’s clear that we can do more – we can learn more – when we work together. The science experiments conducted during their time in space will help prepare for NASA’s bold missions at the Moon, Mars, and beyond, all while benefitting humanity here on Earth.”

The Crew-7 mission lifted off at 3:27 a.m. Aug. 26, 2023, on a Falcon 9 rocket from NASA’s Kennedy Space Center in Florida. About 30 hours later, Dragon docked to the Harmony module’s space-facing port. Crew-7 undocked at 11:20 a.m. Monday, March 11, to begin the trip home.

Moghbeli, Mogensen, Furukawa, and Borisov traveled 84,434,094 miles during their mission, spent 197 days aboard the space station, and completed 3,184 orbits around Earth. The Crew-7 mission was the first spaceflight for Moghbeli and Borisov. Mogensen has logged 209 days in space over his two flights, and Furukawa has logged 366 days in space over his two flights.

Throughout their mission, the Crew-7 members contributed to a host of science and maintenance activities and technology demonstrations. Moghbeli conducted one spacewalk, joined by NASA astronaut Loral O’Hara, replacing one of the 12 trundle bearing assemblies on the port solar alpha rotary joint, which allows the arrays to track the Sun and generate electricity to power the station.

The crew contributed to hundreds of experiments and technology demonstrations, including the first study of human response to different spaceflight durations, and an experiment growing food on the space station.

This was the third flight of the Dragon spacecraft, named Endurance. It also previously supported the Crew-3 and Crew-5 missions. The spacecraft will return to Florida for inspection and processing at SpaceX’s refurbishing facility at Cape Canaveral Space Force Station, where teams will inspect the Dragon, analyze data on its performance, and process it for its next flight.

The Crew-7 flight is part of NASA’s Commercial Crew Program and its return to Earth follows on the heels of NASA’s SpaceX Crew-8 launch, which docked to the station March 5, beginning another science expedition.

The goal of NASA’s Commercial Crew Program is safe, reliable, and cost-effective transportation to and from the International Space Station and low Earth orbit. This already is providing additional research time and has increased the opportunity for discovery aboard humanity’s microgravity testbed for exploration, including helping NASA prepare for human exploration of the Moon and Mars.

Learn more about NASA’s Commercial Crew program at:

https://www.nasa.gov/commercialcrew

-end-

Joshua Finch
Headquarters, Washington
202-358-1100
joshua.a.finch@nasa.gov

Steve Siceloff
Kennedy Space Center, Florida
321-867-2468
steven.p.siceloff@nasa.gov

Leah Cheshier
Johnson Space Center, Houston
281-483-5111
leah.d.cheshier@nasa.gov

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Jennifer M. Dooren

The Next Accident: How Do We Prevent It? 

By Andrew Chaikin, Independent Space Historian and member of the NESC Human Factors Technical Discipline Team 

I recently watched NESC Deputy Director Mike Kirsch stand before a roomful of engineers at the Langley Research Center and tell them that with every passing day, NASA breaks a record: the longest stretch without a major accident in the nation’s human spaceflight program since the Space Shuttle Columbia disintegrated during reentry on February 1, 2003. NASA’s challenge, he told them, was to make sure the record keeps being broken.   

Mike’s sobering message set the perfect tone for my presentation of “Principles of Success in Spaceflight,” the class I created with Victoria Kohl on the human behavior elements of success and failure in spaceflight projects. With the NESC’s support, I have given it at every NASA center, and it’s always a rewarding experience. You can’t spend the day with a group of NASA engineers and not experience their keen intelligence, passion, and commitment to excellence. As I lead them through case studies of the Apollo 1 fire in 1967, the Challenger accident in 1986, and Columbia, I tell them that no matter how good we are at the “rocket science,” we invite failure if we don’t pay attention to the attitudes, beliefs, and assumptions we bring to the work—in short, our mindset.   

Before the Apollo fire, there was a widespread belief that because Mercury and Gemini had used pure oxygen with no fires, there wouldn’t be any in Apollo. And the Apollo spacecraft program manager missed opportunities to prevent the accident due to his belief that the fire hazard created by combining pure oxygen with exposed wiring and flammable materials was not a “real” problem, one that warranted slowing the train barreling down the tracks to meet John F. Kennedy’s end-of-the-decade deadline for a lunar landing.  

When I talk about the Challenger accident, I caution that it’s essential to pay attention to the stories we tell ourselves. NASA had promised itself and Congress that the Shuttle would make spaceflight routine and affordable, a goal that required unrealistically high flight rates. Mounting schedule pressure in the lead-up to Challenger skewed decision makers’ perceptions of the SRB field joint anomalies that had occurred intermittently on previous launches and were not well understood. In the Columbia discussion, I recount the shocking swiftness with which NASA lost the lessons of Challenger and paved the way for another accident with renewed schedule pressure and a belief that external tank foam shedding was “not a safety of flight issue.” Accidents jolt us into new awareness, but Columbia is a painful reminder that awareness has a shelf life.    

What will it take to keep breaking the record that Mike spoke about? I believe we must talk to each other regularly about the behaviors that either invite success or lead us down the slippery slope to failure. Are we in the grip of what I call the “reality distortion field,” created by cost, schedule, and/or political pressure, that clouds our perceptions of risk? Are we unconsciously indulging in hard-wired “us vs. them” tribal behaviors that cut us off from the diverse “spotlights of awareness” we must have to navigate the unforgiving demands of human spaceflight? Are we telling ourselves a story that, under clear-eyed scrutiny, doesn’t hold up? These are the questions we need to ask ourselves again and again. The answers are critical. 

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Meagan Chappell

Operational Modal Analysis of the Artemis I Dynamic Rollout Test

Operational modal analysis (OMA) techniques have been used to identify the modal characteristics of the Artemis I launch vehicle during the Dynamic Rollout Test (DRT) and Wet Dress Rehearsal (WDR) configuration prior to launch. Forces induced during rollout and on the launch pad are not directly measurable, thus necessitating a unique approach.

NASA is developing the SLS to support lunar and deep space exploration. SLS is integrated inside the Vehicle Assembly Building (VAB) on the mobile launcher (ML), which supports the integrated SLS launch vehicle during transport to the pad through lift-off. The ML also provides the fuel, power, and data umbilicals running to the SLS and Orion Multi-Purpose Crew Vehicle (MPCV), as well as crew access to the MPCV crew module. The ML weighs ~10.6 million pounds and is over 380 feet tall. In the spring of 2022, the SLS was transported on the ML from the VAB to Launch Pad 39B (Figure 1) using the NASA crawler transporter (CT) to make this 4.2 mile trek, which takes ~8 hours. The CT alone weighs ~6.3 million pounds.

Although the rollout environment produces relatively small launch vehicle structural loads in comparison to launch and ascent loads for most structures, the induced loads are fully representative of all loading across the entire vehicle, which is not feasible to replicate using localized shakers as was done in the Integrated Modal Test. As mentioned, forces induced during rollout and on the launch pad are not directly measurable, and OMA techniques were used to identify the modal characteristics of Artemis I in the DRT and WDR configurations. WDR, which typically includes vehicle fueling and other operations to demonstrate launch readiness, included several days of on-pad operations. Data collected for the WDR configuration, with partially filled core fuel tanks and without the CT under the ML, provided engineers another model configuration to check (Figure 2).

Acquisition and processing the data from over 300 accelerometers located on Artemis I, ML, and CT was accomplished by a cross-program team of engineers and technicians from across the Agency, including from SLS, Exploration Ground Systems, and the NESC. Using analytical techniques developed from previous rollout tests combined with new data-processing methodologies, the team processed data from preselected CT speed increments during rollout and on-pad during WDR. By making the necessary modifications to the integrated models to match both the DRT and WDR configurations, the team was able to use those results to help make sense of what was being seen in the test data. This proved to be required for OMA testing on this structure, given the type of complex excitation that was being observed.

For information, contact Dexter Johnson dexter.johnson@nasa.gov and Teresa Kinney teresa.l.kinney@nasa.gov.

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Meagan Chappell