Members Can Post Anonymously On This Site
Lunar Vehicle Active Charge Control System (LVACCS) PICASSO Proposal Awarded
-
Similar Topics
-
By NASA
3 min read
Preparations for Next Moonwalk Simulations Underway (and Underwater)
Regolith Adherence Characterization, or RAC, is one of 10 science and technology instruments flying on NASA’s next Commercial Lunar Payload Services (CLPS) flight as part of the Blue Ghost Misison-1. Developed by Aegis Aerospace of Webster, Texas, RAC is designed to study how lunar dust reacts to more than a dozen different types of material samples, located on the payload’s wheels. Photo courtesy Firefly Aerospace The Moon may look like barren rock, but it’s actually covered in a layer of gravel, pebbles, and dust collectively known as “lunar regolith.” During the Apollo Moon missions, astronauts learned firsthand that the fine, powdery dust – electromagnetically charged due to constant bombardment by solar and cosmic particles – is extremely abrasive and clings to everything: gloves, boots, vehicles, and mechanical equipment. What challenges does that dust pose to future Artemis-era missions to establish long-term outposts on the lunar surface?
That’s the task of an innovative science instrument called RAC-1 (Regolith Adherence Characterization), one of 10 NASA payloads flying aboard the next delivery for the agency’s CLPS (Commercial Lunar Payload Services) initiative and set to be carried to the surface by Firefly Aerospace’s Blue Ghost 1 lunar lander.
Developed by Aegis Aerospace of Webster, Texas, RAC will expose 15 sample materials – fabrics, paint coatings, optical systems, sensors, solar cells, and more – to the lunar environment to determine how tenaciously the lunar dust sticks to each one. The instrument will measure accumulation rates during landing and subsequent routine lander operations, aiding identification of those materials which best repel or shed dust. The data will help NASA and its industry partners more effectively test, upgrade, and protect spacecraft, spacesuits, habitats, and equipment in preparation for continued exploration of the Moon under the Artemis campaign.
“Lunar regolith is a sticky challenge for long-duration expeditions to the surface,” said Dennis Harris, who manages the RAC payload for NASA’s CLPS initiative at the agency’s Marshall Space Flight Center in Huntsville, Alabama. “Dust gets into gears, sticks to spacesuits, and can block optical properties. RAC will help determine the best materials and fabrics with which to build, delivering more robust, durable hardware, products, and equipment.”
Under the CLPS model, NASA is investing in commercial delivery services to the Moon to enable industry growth and support long-term lunar exploration. As a primary customer for CLPS deliveries, NASA aims to be one of many customers on future flights. NASA’s Marshall Space Flight Center in Huntsville, Alabama, manages the development of seven of the 10 CLPS payloads carried on Firefly’s Blue Ghost lunar lander.
Learn more about. CLPS and Artemis at:
https://www.nasa.gov/clps
Alise Fisher
Headquarters, Washington
202-358-2546
Alise.m.fisher@nasa.gov
Headquarters, Washington
202-358-2546
Alise.m.fisher@nasa.gov
Corinne Beckinger
Marshall Space Flight Center, Huntsville, Ala.
256-544-0034
corinne.m.beckinger@nasa.gov
Share
Details
Last Updated Dec 20, 2024 EditorBeth RidgewayContactCorinne M. Beckingercorinne.m.beckinger@nasa.govLocationMarshall Space Flight Center Related Terms
Commercial Lunar Payload Services (CLPS) Artemis Marshall Space Flight Center Explore More
3 min read NASA Payload Aims to Probe Moon’s Depths to Study Heat Flow
Article 2 days ago 4 min read NASA Technology Helps Guard Against Lunar Dust
Article 8 months ago 4 min read NASA Collects First Surface Science in Decades via Commercial Moon Mission
Article 10 months ago Keep Exploring Discover Related Topics
Missions
Humans in Space
Climate Change
Solar System
View the full article
-
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
View the full article
-
By European Space Agency
A multi-orbit constellation of about 300 satellites that will deliver resilient, secure and fast communications for EU governments, European companies and citizens will be put in orbit after two contracts were confirmed today in Brussels.
View the full article
-
By NASA
Congratulations to the selected teams and their schools who will participate in the Lunar Autonomy Challenge! 31 teams were selected for the qualifying round, engaging 229 students from colleges and universities in 15 states. Teams will now move on to a Qualifying Round where they will virtually explore and map the lunar surface using a digital twin of NASA’s lunar mobility robot, the ISRU Pilot Excavator (IPEx). Teams will develop software that can perform set actions without human intervention, navigating the digital IPEx in the harsh, low-light conditions of the Moon. The Qualifying Round will extend to February 28, when the top-scoring teams will proceed to the Final Round, with the winners announced in May 2025.
The Lunar Autonomy Challenge is a collaboration between NASA, The Johns Hopkins University (JHU) Applied Physics Laboratory (APL), Caterpillar Inc., and Embodied AI.
Learn more: https://lunar-autonomy-challenge.jhuapl.edu/
SchoolCityStateAmerican Public University SystemCharles TownWest VirginiaArizona State UniversityTempeArizonaCalifornia Polytechnic Institute, Pomona (1)PomonaCaliforniaCalifornia Polytechnic Institute, Pomona (2)PomonaCaliforniaCarnegie Mellon UniversityPittsburghPennsylvaniaEmbry Riddle Aeronautical UniversityDaytona BeachFloridaEssex County CollegeNewarkNew JerseyGeorgia Institute of Technology & Arizona State UniversityAtlanta & TempeGeorgia & ArizonaHarvard UniversityAllstonMassachusettsJohns Hopkins University Whiting School of EngineeringBaltimoreMarylandMassachusetts Institute of TechnologyCambridgeMassachusettsNew York University Tandon School of EngineeringBrooklynNew YorkNorth Carolina State UniversityRaleighNorth CarolinaPenn State (1)University ParkPennsylvaniaPenn State (2)University ParkPennsylvaniaPurdue UniversityWest LafayetteIndianaRochester Institute of TechnologyRochester New YorkRose Hulman Institue of TechnologyTerre HauteIndianaStanford UniversityStanfordCalifornia Texas A&M UniversityCollege StationTexasUniversity of AlabamaTuscaloosaAlabamaUniversity of Buffalo, State University of New YorkBuffaloNew YorkUniversity of California, StanislausTurlockCaliforniaUniversity of Illinois Urbana Champaign (1)UrbanaIllinoisUniversity of Illinois Urbana Champaign (2)UrbanaIllinoisUniversity of MarylandCollege ParkMarylandUniversity of Pennsylvania (1)Philadelphia PennsylvaniaUniversity of Pennsylvania (2)Philadelphia PennsylvaniaUniversity of Southern California & Stanford UniversityLos Angeles & StanfordCaliforniaWest Virginia UniversityMorgantownWest VirginiaWorcester Polytechnic InstituteWorcesterMassachusetts Keep Exploring Discover More Topics From NASA
Space Technology Mission Directorate
NASA’s Lunar Surface Innovation Initiative
ISRU Pilot Excavator
Education & Opportunities
We are committed to providing educational opportunities for students interested in pursuing professional experiences in the life science disciplines. Our…
View the full article
-
By NASA
2 Min Read Turn Supermoon Hype into Lunar Learning
Caption: The Earth-Moon distance to scale. Credits:
NASA/JPL-Caltech Supermoons get lots of publicity from the media, but is there anything to them beyond the hype? If the term “supermoon” bothers you because it’s not an official astronomical term, don’t throw up your hands. You can turn supermoon lemons into lunar lemonade for your star party visitors by using it to illustrate astronomy concepts and engaging them with great telescopic views of its surface!
Many astronomers find the frequent supermoon news from the media misleading, if not a bit upsetting! Unlike the outrageously wrong “Mars is as big as the moon” pieces that appear like clockwork every two years during Mars’s close approach to Earth, news about a huge full moon is more of an overstatement. The fact is that while a supermoon will indeed appear somewhat bigger and brighter in the sky, it would be difficult to tell the difference between an average full moon and a supermoon with the naked eye.
A whiteboard illustration of Earth’s Moon at perigee, or closest position to Earth. Credit: NASA There are great bits of science to glean from supermoon discussion that can turn supermoon questions into teachable moments. For example, supermoons are a great gateway into discussing the shape of the moon’s orbit, especially the concepts of apogee and perigee. Many people may assume that the moon orbits Earth in a perfect circle, when in fact its orbit is elliptical! The moon’s distance from Earth constantly varies, and so during its orbit it reaches both apogee (when it’s farthest from Earth), as well as perigee (closest to Earth). A supermoon occurs when the moon is at both perigee and in its full phase. That’s not rare; a full moon at closest approach to Earth can happen multiple times a year, as you may have noticed.
This activity is related to a Teachable Moment from Nov. 15, 2017. See “What Is a Supermoon and Just How Super Is It?” Credit: NASA/JPL While a human observer won’t be able to tell the difference between the size of a supermoon and a regular full moon, comparison photos taken with a telephoto lens can reveal the size difference between full moons. NASA has a classroom activity called Measuring the Supermoon where students can measure the size of the full moon month to month and compare their results.
Comparison of the size of an average full moon, compared to the size of a supermoon. NASA/JPL-Caltech Students can use digital cameras (or smartphones) to measure the moon, or they can simply measure the moon using nothing more than a pencil and paper! Both methods work and can be used depending on the style of teaching and available resources.
/wp-content/plugins/nasa-blocks/assets/images/media/media-example-01.jpg This landscape of “mountains” and “valleys” speckled with glittering stars is actually the edge of a nearby, young, star-forming region called NGC 3324 in the Carina Nebula. Captured in infrared light by NASA’s new James Webb Space Telescope, this image reveals for the first time previously invisible areas of star birth. NASA, ESA, CSA, and STScI View the full article
-
-
Check out these Videos
Recommended Posts
Join the conversation
You can post now and register later. If you have an account, sign in now to post with your account.
Note: Your post will require moderator approval before it will be visible.