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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
Preparations for Next Moonwalk Simulations Underway (and Underwater)
The Aerostar Thunderhead balloon carries the STRATO payload into the sky to reach the stratosphere for flight testing. The balloon appears deflated because it will expand as it rises to higher altitudes where pressures are lower.Credit: Colorado Division of Fire Prevention and Control Center of Excellence for Advanced Technology Aerial Firefighting/Austin Buttlar NASA is participating in a collaborative effort to use high-altitude balloons to improve real-time communications among firefighters battling wildland fires.
The rugged and often remote locations where wildland fires burn mean cell phone service is often limited, making communication between firefighters and command posts difficult.
The flight testing of the Strategic Tactical Radio and Tactical Overwatch (STRATO) technology brought together experts from NASA’s Ames Research Center in California’s Silicon Valley, the U.S. Forest Service, high-altitude balloon company Aerostar, and Motorola to provide cell service from above. The effort was funded by the NASA Science Mission Directorate’s Earth Science Division Airborne Science Program and the agency’s Space Technology Mission Directorate Flight Opportunities program.
“This project leverages NASA expertise to address real problems,” said Don Sullivan, principal investigator for STRATO at NASA Ames. “We do a lot of experimental, forward-thinking work, but this is something that is operational and can make an immediate impact.”
Flying High Above Wildland Fires
Soaring above Earth at altitudes of 50,000 feet or more, Aerostar’s Thunderhead high-altitude balloon systems can stay in operation for several months and can be directed to “station keep,” staying within a radius of few miles. Because wildland fires often burn in remote, rugged areas, firefighting takes place in areas where cell service is not ideal. Providing cellular communication from above, from a vehicle that can move as the fire changes, would improve firefighter safety and firefighting efficiency.
The STRATO project’s first test flight took place over the West Mountain Complex fires in Idaho in August and demonstrated significant opportunities to support future firefighting efforts. The balloon was fitted with a cellular LTE transmitter and visual and infrared cameras. To transmit between the balloon’s cell equipment and the wildland fire incident command post, the team used a SpaceX Starlink internet satellite device and Silvus broadband wireless system.
When tested, the onboard instruments provided cell coverage for a 20-mile radius. By placing the transmitter on a gimbal, that cell service coverage could be adjusted as ground crews moved through the region.
The onboard cameras gave fire managers and firefighters on the ground a bird’s-eye view of the fires as they spread and moved, opening the door to increased situational awareness and advanced tracking of firefighting crews. On the ground, teams use an app called Tactical Awareness Kit (TAK) to identify the locations of crew and equipment. Connecting the STRATO equipment to TAK provides real-time location information that can help crews pinpoint how the fire moves and where to direct resources while staying in constant communication.
Soaring Into the Future
The next steps for the STRATO team are to use the August flight test results to prepare for future fire seasons. The team plans to optimize balloon locations as a constellation to maximize coverage and anticipate airflow changes in the stratosphere where the balloons fly. By placing balloons in strategic locations along the airflow path, they can act as replacements to one another as they are carried by airflow streams. The team may also adapt the scientific equipment aboard the balloons to support other wildland fire initiatives at NASA.
As the team prepares for further testing next year, the goal is to keep firefighters informed and in constant communication with each other and their command posts to improve the safety and efficiency of fighting wildland fires.
“Firefighters work incredibly hard saving lives and property over long days of work,” said Sullivan. “I feel honored to be able to do what we can to make their jobs safer and better.”
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Last Updated Nov 14, 2024 Related Terms
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By NASA
Since its launch in 2014, the Physical Sciences Informatics (PSI) system has served as NASA’s online repository for physical science data. Now, the PSI system is live with new updates to further align with NASA’s open data policy.
With its first significant update in over five years, the data repository has been completely redesigned, featuring a new layout, improved structure, and enhanced search functionalities. This updated system was created with a focus on user experience, and more updates are anticipated as new features are introduced.
A key new feature of the system is, the PSI Submission Portal. This tool is designed to streamline the processes of collecting, curating, and publishing new data by enabling Principal Investigators and scientific teams to upload files directly to the system with the support of a data curator. The Portal also offers a dedicated workspace for data submitters, assigns a unique digital object identifier to each dataset, and standardizes the documentation and data structure for each investigation.
Both the updated PSI system and Submission Portal can be accessed at PSI.NASA.gov.
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By NASA
3 min read
NASA Develops Process to Create Very Accurate Eclipse Maps
New NASA research reveals a process to generate extremely accurate eclipse maps, which plot the predicted path of the Moon’s shadow as it crosses the face of Earth. Traditionally, eclipse calculations assume that all observers are at sea level on Earth and that the Moon is a smooth sphere that is perfectly symmetrical around its center of mass. As such, these calculations do not take into account different elevations on Earth or the Moon’s cratered, uneven surface.
For slightly more accurate maps, people can employ elevation tables and plots of the lunar limb — the edge of the visible surface of the Moon as seen from Earth. However, now eclipse calculations have gained even greater accuracy by incorporating lunar topography data from NASA’s LRO (Lunar Reconnaissance Orbiter) observations.
Using LRO elevation maps, NASA visualizer Ernie Wright at NASA’s Goddard Space Flight Center in Greenbelt, Maryland, created a continuously varying lunar limb profile as the Moon’s shadow passes over the Earth. The mountains and valleys along the edge of the Moon’s disk affect the timing and duration of totality by several seconds. Wright also used several NASA data sets to provide an elevation map of Earth so that eclipse observer locations were depicted at their true altitude.
The resulting visualizations show something never seen before: the true, time-varying shape of the Moon’s shadow, with the effects of both an accurate lunar limb and the Earth’s terrain.
“Beginning with the 2017 total solar eclipse, we’ve been publishing maps and movies of eclipses that show the true shape of the Moon’s central shadow — the umbra,” said Wright.
A map showing the umbra (the Moon’s central shadow) as it passes over Cleveland at 3:15 p.m. local time during the April 8, 2024, total solar eclipse. NASA SVS/Ernie Wright and Michaela Garrison “And people ask, why does it look like a potato instead of a smooth oval? The short answer is that the Moon isn’t a perfectly smooth sphere.”
The mountains and valleys around the edge of the Moon change the shape of the shadow. The valleys are also responsible for Baily’s beads and the diamond ring, the last bits of the Sun visible just before and the first just after totality.
A computer simulation of Baily’s beads during a total solar eclipse. Data from Lunar Reconnaissance Orbiter makes it possible to map the lunar valleys that create the bead effect. NASA SVS/Ernie Wright Wright is lead author of a paper published September 19 in The Astronomical Journal that reveals for the first time exactly how the Moon’s terrain creates the umbra shape. The valleys on the edge of the Moon act like pinholes projecting images of the Sun onto the Earth’s surface.
A visualization of Sun images being projected from lunar valleys that are acting like pinhole projectors. Light rays from the Sun converge on each valley, then spread out again on their way to the Earth. NASA SVS/Ernie Wright The umbra is the small hole in the middle of these projected Sun images, the place where none of the Sun images reach.
Viewed from behind the Moon, the Sun images projected by lunar valleys on the Moon’s edge fall on the Earth’s surface in a flower-like pattern with a hole in the middle, forming the umbra shape. NASA SVS/Ernie Wright The edges of the umbra are made up of small arcs from the edges of the projected Sun images.
This is just one of several surprising results that have emerged from the new eclipse mapping method described in the paper. Unlike the traditional method invented 200 years ago, the new way renders eclipse maps one pixel at a time, the same way 3D animation software creates images. It’s also similar to the way other complex phenomena, like weather, are modeled in the computer by breaking the problem into millions of tiny pieces, something computers are really good at, and something that was inconceivable 200 years ago.
For more about eclipses, refer to:
https://science.nasa.gov/eclipses
By Ernie Wright and Susannah Darling
NASA’s Goddard Space Flight Center, Greenbelt, Md.
Media Contact:
Nancy Neal-Jones
NASA’s Goddard Space Flight Center, Greenbelt, Md.
301-286-0039
nancy.n.jones@nasa.gov
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Last Updated Sep 19, 2024 Editor wasteigerwald Contact wasteigerwald william.a.steigerwald@nasa.gov Location NASA Goddard Space Flight Center Related Terms
Lunar Reconnaissance Orbiter (LRO) Solar Eclipses Uncategorized Explore More
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By NASA
Timothy Lang (ST11) is a co-author on an article titled “Effective Visualization of Radar Data for Users Impacted by Color Vision Deficiency”, which was recently accepted for publication in Bulletin of the American Meteorological Society. The article is led by Zachary Sherman of Argonne National Laboratory (ANL), and it is an outgrowth of a long-standing collaboration on open science between ANL, MSFC, and other institutions that predates NASA Science Policy Directive (SPD) 41a and the Transform to Open Science (TOPS) campaign. Color Vision Deficiency (CVD) affects up to 8% of genetic males and 0.5% of genetic females, and traditional color maps used in radar meteorology and other Earth sciences often lack perceptual accuracy and clarity when viewed by those affected by CVD. The article reviews new color maps that convey useful and clear scientific information whether viewed by those with normal color perception or those with CVD. These color maps are available in open-source repositories like cmweather (https://github.com/openradar/cmweather) and pyart (http://arm-doe.github.io/pyart/). The article and the open-source CVD-friendly color maps are excellent examples of the greater inclusivity fostered when open science is practiced.
Read the paper at: https://journals.ametsoc.org/view/journals/bams/aop/BAMS-D-23-0056.1/BAMS-D-23-0056.1.xml.
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