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By NASA
3 min read
Preparations for Next Moonwalk Simulations Underway (and Underwater)
NASA’s Stennis Space Center near Bay St. Louis, Mississippi, is helping the Artemis Generation learn how to power space dreams with an interactive exhibit at INFINITY Science Center.
The engine test simulator exhibit at the official visitor center of NASA Stennis provides the chance to experience the thrill of being a NASA test engineer by guiding an RS-25 engine through a simulated hot fire test.
“It is an exhilarating opportunity to feel what it is like to be a NASA engineer, responsible for making sure the engine is safely tested for launch,” said Chris Barnett-Woods, a NASA engineer that helped develop the software for the exhibit.
Sitting at a console mirroring the actual NASA Stennis Test Control Center, users are immersed in the complex process of engine testing. The exhibit uses cutting-edge software and visual displays to teach participants how to manage liquid oxygen and liquid hydrogen propellants, and other essential elements during a hot fire.
A pair of young visitors to INFINITY Science Center carry out the steps of a simulated RS-25 engine hot fire on Dec. 19. The updated engine test simulator exhibit provided by NASA’s Stennis Space Center takes users through the hot fire process just as real engineers do at NASA Stennis.NASA/Danny Nowlin INFINITY Science Center, the official visitor center for NASA’s Stennis Space Center, has unveiled a new interactive simulator exhibit that allows visitors to become the test conductor for an RS-25 engine hot fire. NASA/Danny Nowlin Users follow step-by-step instructions that include pressing buttons, managing propellant tanks, and even closing the flare stack, just as real engineers do at NASA Stennis. Once the test is complete, they are congratulated for successfully conducting their own rocket engine hot fire.
The interactive exhibit is not just about pushing buttons. It is packed with interesting facts about the RS-25 engine, which helps power NASA’s Artemis missions as the agency explores secrets of the universe for the benefit of all. Visitors also can view real hot fires conducted at NASA Stennis from multiple angles, deepening their understanding of rocket propulsion testing and NASA’s journey back to the Moon and beyond.
NASA is currently preparing for the Artemis II mission, the first crewed flight test of the agency’s powerful SLS (Space Launch System) rocket and the Orion spacecraft around the Moon.
The first four Artemis missions are using modified space shuttle main engines tested at NASA Stennis. The center also achieved a testing milestone last April for engines to power future Artemis missions. For each Artemis mission, four RS-25 engines, along with a pair of solid rocket boosters, power NASA’s SLS rocket, producing more than 8.8 million pounds of total combined thrust at liftoff.
The revitalized exhibit, previously used when the visitor center was located onsite, represents a collaborative effort. It started as an intern project in the summer of 2023 before evolving into a full-scale experience. Engineers built on the initial concept, integrating carpentry, audio, and video to create the seamless experience to educate and inspire.
The best part might be that visitors to INFINITY Science Center can repeat the simulation as many times as they like, gaining confidence and learning more with each attempt.
“This exhibit was a favorite in the past, and with its new upgrades, the engine test simulator is poised to capture the imaginations of the Artemis Generation at INFINITY Science Center,” said NASA Public Affairs Specialist Samone Wilson. “This is one exhibit you will not want to miss.” INFINITY Science Center is located at 1 Discovery Circle, Pearlington, Mississippi. For hours of operation and admission information, please visit www.visitinfinity.com.
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Last Updated Dec 20, 2024 EditorNASA Stennis CommunicationsContactC. Lacy Thompsoncalvin.l.thompson@nasa.gov / (228) 688-3333LocationStennis Space Center Related Terms
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By Space Force
The new squadron, which falls under Space Delta 11, marks a critical milestone in advancing the Space Force’s ability to test, train, and prepare for cyber threats in the contested space domain.
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By NASA
1 min read
Preparations for Next Moonwalk Simulations Underway (and Underwater)
NASA’s X-59 quiet supersonic research aircraft completed its first maximum afterburner test at Lockheed Martin’s Skunk Works facility in Palmdale, California. This full-power test, during which the engine generates additional thrust, validates the additional power needed for meeting the testing conditions of the aircraft. The X-59 is the centerpiece of NASA’s Quesst mission, which aims to overcome a major barrier to supersonic flight over land by reducing the noise of sonic booms.Lockheed Martin Corporation/Garry Tice NASA completed the first maximum afterburner engine run test on its X-59 quiet supersonic research aircraft on Dec. 12. The ground test, conducted at Lockheed Martin’s Skunk Works facility in Palmdale, California, marks a significant milestone as the X-59 team progresses toward flight.
An afterburner is a component of some jet engines that generates additional thrust. Running the engine, an F414-GE-100, with afterburner will allow the X-59 to meet its supersonic speed requirements. The test demonstrated the engine’s ability to operate within temperature limits and with adequate airflow for flight. It also showed the engine’s ability to operate in sync with the aircraft’s other subsystems.
The X-59 is the centerpiece of NASA’s Quesst mission, which seeks to solve one of the major barriers to supersonic flight over land by making sonic booms quieter. The X-59’s first flight is expected to occur in 2025.
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Last Updated Dec 20, 2024 EditorDede DiniusContactMatt Kamletmatthew.r.kamlet@nasa.gov Related Terms
Aeronautics Aeronautics Research Mission Directorate Armstrong Flight Research Center Commercial Supersonic Technology Integrated Aviation Systems Program Low Boom Flight Demonstrator Quesst (X-59) Supersonic Flight Explore More
2 min read NASA, Notre Dame Connect Students to Inspire STEM Careers
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By European Space Agency
Global warming is driving the rapid melting of the Greenland Ice Sheet, contributing to global sea level rise and disrupting weather patterns worldwide. Because of this, precise measurements of its changing shape are of critical importance for adapting to climate change.
Now, scientists have delivered the first measurements of the Greenland Ice Sheet’s changing shape using data from ESA's CryoSat and NASA's ICESat-2 ice missions.
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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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