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By NASA
2 min read
Preparations for Next Moonwalk Simulations Underway (and Underwater)
Rebecca Anderson, a junior enrolled at the Portage School of Leaders High School in South Bend, Indiana, spent time with NASA Glenn Research Center’s Daniel Sutliff, an acoustic engineer, on the campus of the University of Notre Dame on Nov. 7, 2024. Students witnessed the operation of the Advanced Noise Control Fan owned by NASA and on loan to the university for STEM experiences.Credit: Matt Cashore/University of Notre Dame High school students in Indiana are contributing to NASA’s groundbreaking research to develop quieter, more fuel-efficient aircraft engines.
Their learning experience is a collaboration between aircraft noise researchers from NASA’s Glenn Research Center in Cleveland and educators from the University of Notre Dame’s Turbomachinery Laboratory. The collaboration aims to encourage students’ interest in science, technology, engineering, and math (STEM) careers.
Recently, Notre Dame hosted students from The Portage School of Leaders High School and a team from NASA Glenn to see the Advanced Noise Control Fan operate in an outdoor setting. The fan is a NASA-owned test rig that has been configured to enable the study of a quieter aircraft engine technology. Known as the open rotor fan concept, the configuration involves an engine fan without a cover. Ground microphones were used during the test operated by Notre Dame to evaluate the radiated sound as the open rotor fan spun at various speeds.
NASA’s Advanced Noise Control Fan is on loan at the University of Notre Dame through a Space Act Agreement. It provides a hands-on learning laboratory for students in STEM.Credit: Matt Cashore/University of Notre Dame Students from the high school, which is part of the Career Academy Network of Public Schools, used 3D printers from the school’s facilities to fabricate parts for the open rotor test fan. The parts, known as stator blades, help direct and control airflow, ensuring smooth operation of the large, exposed fan blades that are the defining feature of an open fan engine design.
“It was beyond words,” said Rebecca Anderson, a junior from the high school. “The part I enjoyed most was when they got the fan running. It was really impressive to see how quiet it was. I feel like everyone involved in STEM would love to work for NASA, including me.”
NASA researcher Dr. Daniel Sutliff was part of the team from NASA Glenn to spend time mentoring the students.
“This is real-world, hands-on research for them,” Sutliff said. “If airlines are able to use technologies to make flight quieter and cleaner, passengers will have more enjoyable flights.”
The Advanced Noise Control Fan is on loan to Notre Dame from NASA through a Space Act Agreement. The fan research is supported by NASA’s Advanced Air Transport Technology project and its Efficient Quiet Integrated Propulsors technical challenge.
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By NASA
Download PDF: Statistical Analysis Using Random Forest Algorithm Provides Key Insights into Parachute Energy Modulator System
Energy modulators (EM), also known as energy absorbers, are safety-critical components that are used to control shocks and impulses in a load path. EMs are textile devices typically manufactured out of nylon, Kevlar® and other materials, and control loads by breaking rows of stitches that bind a strong base webbing together as shown in Figure 1. A familiar EM application is a fall-protection harness used by workers to prevent injury from shock loads when the harness arrests a fall. EMs are also widely used in parachute systems to control shock loads experienced during the various stages of parachute system deployment.
Random forest is an innovative algorithm for data classification used in statistics and machine learning. It is an easy to use and highly flexible ensemble learning method. The random forest algorithm is capable of modeling both categorical and continuous data and can handle large datasets, making it applicable in many situations. It also makes it easy to evaluate the relative importance of variables and maintains accuracy even when a dataset has missing values.
Random forests model the relationship between a response variable and a set of predictor or independent variables by creating a collection of decision trees. Each decision tree is built from a random sample of the data. The individual trees are then combined through methods such as averaging or voting to determine the final prediction (Figure 2). A decision tree is a non-parametric supervised learning algorithm that partitions the data using a series of branching binary decisions. Decision trees inherently identify key features of the data and provide a ranking of the contribution of each feature based on when it becomes relevant. This capability can be used to determine the relative importance of the input variables (Figure 3). Decision trees are useful for exploring relationships but can have poor accuracy unless they are combined into random forests or other tree-based models.
The performance of a random forest can be evaluated using out-of-bag error and cross-validation techniques. Random forests often use random sampling with replacement from the original dataset to create each decision tree. This is also known as bootstrap sampling and forms a bootstrap forest. The data included in the bootstrap sample are referred to as in-the-bag, while the data not selected are out-of-bag. Since the out-of-bag data were not used to generate the decision tree, they can be used as an internal measure of the accuracy of the model. Cross-validation can be used to assess how well the results of a random forest model will generalize to an independent dataset. In this approach, the data are split into a training dataset used to generate the decision trees and build the model and a validation dataset used to evaluate the model’s performance. Evaluating the model on the independent validation dataset provides an estimate of how accurately the model will perform in practice and helps avoid problems such as overfitting or sampling bias. A good model performs well on
both the training data and the validation data.
The complex nature of the EM system made it difficult for the team to identify how various parameters influenced EM behavior. A bootstrap forest analysis was applied to the test dataset and was able to identify five key variables associated with higher probability of damage and/or anomalous behavior. The identified key variables provided a basis for further testing and redesign of the EM system. These results also provided essential insight to the investigation and aided in development of flight rationale for future use cases.
For information, contact Dr. Sara R. Wilson. sara.r.wilson@nasa.gov
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By NASA
4 Min Read NASA Finds ‘Sideways’ Black Hole Using Legacy Data, New Techniques
Image showing the structure of galaxy NGC 5084, with data from the Chandra X-ray Observatory overlaid on a visible-light image of the galaxy. Chandra’s data, shown in purple, revealed four plumes of hot gas emanating from a supermassive black hole rotating “tipped over” at the galaxy’s core. Credits: X-ray: NASA/CXC, A. S. Borlaff, P. Marcum et al.; Optical full image: M. Pugh, B. Diaz; Image Processing: NASA/USRA/L. Proudfit NASA researchers have discovered a perplexing case of a black hole that appears to be “tipped over,” rotating in an unexpected direction relative to the galaxy surrounding it. That galaxy, called NGC 5084, has been known for years, but the sideways secret of its central black hole lay hidden in old data archives. The discovery was made possible by new image analysis techniques developed at NASA’s Ames Research Center in California’s Silicon Valley to take a fresh look at archival data from the agency’s Chandra X-ray Observatory.
Using the new methods, astronomers at Ames unexpectedly found four long plumes of plasma – hot, charged gas – emanating from NGC 5084. One pair of plumes extends above and below the plane of the galaxy. A surprising second pair, forming an “X” shape with the first, lies in the galaxy plane itself. Hot gas plumes are not often spotted in galaxies, and typically only one or two are present.
The method revealing such unexpected characteristics for galaxy NGC 5084 was developed by Ames research scientist Alejandro Serrano Borlaff and colleagues to detect low-brightness X-ray emissions in data from the world’s most powerful X-ray telescope. What they saw in the Chandra data seemed so strange that they immediately looked to confirm it, digging into the data archives of other telescopes and requesting new observations from two powerful ground-based observatories.
Hubble Space Telescope image of galaxy NGC 5084’s core. A dark, vertical line near the center shows the curve of a dusty disk orbiting the core, whose presence suggests a supermassive black hole within. The disk and black hole share the same orientation, fully tipped over from the horizontal orientation of the galaxy.NASA/STScI, M. A. Malkan, B. Boizelle, A.S. Borlaff. HST WFPC2, WFC3/IR/UVIS. The surprising second set of plumes was a strong clue this galaxy housed a supermassive black hole, but there could have been other explanations. Archived data from NASA’s Hubble Space Telescope and the Atacama Large Millimeter/submillimeter Array (ALMA) in Chile then revealed another quirk of NGC 5084: a small, dusty, inner disk turning about the center of the galaxy. This, too, suggested the presence of a black hole there, and, surprisingly, it rotates at a 90-degree angle to the rotation of the galaxy overall; the disk and black hole are, in a sense, lying on their sides.
The follow-up analyses of NGC 5084 allowed the researchers to examine the same galaxy using a broad swath of the electromagnetic spectrum – from visible light, seen by Hubble, to longer wavelengths observed by ALMA and the Expanded Very Large Array of the National Radio Astronomy Observatory near Socorro, New Mexico.
“It was like seeing a crime scene with multiple types of light,” said Borlaff, who is also the first author on the paper reporting the discovery. “Putting all the pictures together revealed that NGC 5084 has changed a lot in its recent past.”
It was like seeing a crime scene with multiple types of light.
Alejandro Serrano Borlaff
NASA Research Scientist
“Detecting two pairs of X-ray plumes in one galaxy is exceptional,” added Pamela Marcum, an astrophysicist at Ames and co-author on the discovery. “The combination of their unusual, cross-shaped structure and the ‘tipped-over,’ dusty disk gives us unique insights into this galaxy’s history.”
Typically, astronomers expect the X-ray energy emitted from large galaxies to be distributed evenly in a generally sphere-like shape. When it’s not, such as when concentrated into a set of X-ray plumes, they know a major event has, at some point, disturbed the galaxy.
Possible dramatic moments in its history that could explain NGC 5084’s toppled black hole and double set of plumes include a collision with another galaxy and the formation of a chimney of superheated gas breaking out of the top and bottom of the galactic plane.
More studies will be needed to determine what event or events led to the current strange structure of this galaxy. But it is already clear that the never-before-seen architecture of NGC 5084 was only discovered thanks to archival data – some almost three decades old – combined with novel analysis techniques.
The paper presenting this research was published Dec. 18 in The Astrophysical Journal. The image analysis method developed by the team – called Selective Amplification of Ultra Noisy Astronomical Signal, or SAUNAS – was described in The Astrophysical Journal in May 2024.
For news media:
Members of the news media interested in covering this topic should reach out to the NASA Ames newsroom.
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Last Updated Dec 18, 2024 Related Terms
Black Holes Ames Research Center Ames Research Center's Science Directorate Astrophysics Chandra X-Ray Observatory Galaxies Galaxies, Stars, & Black Holes Galaxies, Stars, & Black Holes Research General Hubble Space Telescope Marshall Astrophysics Marshall Science Research & Projects Marshall Space Flight Center Missions NASA Centers & Facilities Science & Research Supermassive Black Holes The Universe Explore More
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By NASA
Portrait, Elaine Ho, Thursday, Jan. 23, 2020, at NASA Headquarters in Washington. Photo Credit: (NASA/Aubrey Gemignani) NASA Administrator Bill Nelson announced Monday Elaine P. Ho will serve as the next associate administrator of NASA’s Office of STEM Engagement (OSTEM), where she will lead the agency’s efforts to inspire Artemis Generation students and educators in science, technology, engineering, and mathematics (STEM). The role, based out of the agency’s headquarters in Washington, is effective immediately.
Ho also will remain the associate administrator for the agency’s Office of Diversity and Equal Opportunity while a permanent replacement is sought. She will succeed Mike Kincaid, who retired from the agency in November after 37 years with NASA. Kris Brown, who has been serving as acting associate administrator for OSTEM, will return to her position as the office’s deputy associate administrator for strategy and integration.
“At NASA, we know STEM education is critical for building a strong and competent future workforce,” said Nelson. “Under Elaine’s leadership, we will continue to empower students, educators, and communities to reach for the stars and tackle the challenges of tomorrow.”
In her role as associate administrator for NASA’s Office of Diversity and Equal Opportunity, she played an instrumental part in fostering a NASA culture that values the unique backgrounds of our workforce to bolster innovation and drive mission success. Prior to that role, she served as NASA’s deputy associate administrator for OSTEM, responsible for leading and managing a wide-ranging portfolio of projects and initiatives that benefit students, universities, and educational institutions across the country.
Before joining NASA, Ho held several roles at the White House, including senior policy advisor for the Let Girls Learn initiative in the Office of the First Lady and chief of staff of the U.S. Digital Service. In 2021, she returned to the White House on a year-long detail, serving as deputy chief of staff for workforce in the Office of Science and Technology Policy and director of Space STEM Policy for the Vice President’s National Space Council.
Prior to her federal service career, Ho was a practicing attorney, specializing in employment law. She also served four years of active duty as a criminal prosecutor in the U.S. Air Force and continues her service as a colonel in the Air Force Reserves.
Ho holds a civil engineering degree from Duke University and a Juris Doctor from the University of Florida.
For information about NASA and agency programs, visit:
https://www.nasa.gov
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Abbey Donaldson
Headquarters, Washington
202-358-1600
abbey.a.donaldson@nasa.gov
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By USH
The mystery of unidentified drones remains unresolved, with government authorities offering little clarity. Officials have downplayed the incidents, asserting there is no threat to national security and attributing many sightings to aircraft such as planes or helicopters. However, the lack of transparency has only fueled public speculation and heightened concerns.
What people/experts say:
Some speculate that these drones are part of covert operations designed to detect dirty bombs or nuclear devices or theses drones are part of an advanced surveillance systems operated by certain agencies.
The Space Force could be conducting classified exercises, such as testing cutting-edge technology or performing communication lockdown drills to evaluate detection and evasion capabilities.
A former CIA officer has suggested that the drones may be part of government efforts to trial advanced technologies in urban environments.
Reports indicate these drones exhibit unusual traits, such as lacking heat signatures and evading detection. They might employ RF jamming or encrypted communications, potentially causing unintentional disruptions to civilian electronics, including power outages, while avoiding capture.
Intelligence analysts have compared the drones to Russian Orlan-10 or Iranian Shahed-136 models, raising suspicions of international espionage.
But, the most striking statement came from Elon Musk, who warned earlier this year about the arrival of epic drone wars. He said that drone swarm battles are coming that will boggle the mind. What does he know that we don’t?
A large drone flying at a slow speed, shooting out or launching multiple smaller drones at a relatively high speed.
DAHBOO77 video: Musk's statement on X (formerly Twitter) at approximately the 1:23 mark.View the full article
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