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By NASA
5 Min Read NASA’s Parker Solar Probe Makes History With Closest Pass to Sun
An artist’s concept showing Parker Solar Probe. Credits:
NASA/APL Operations teams have confirmed NASA’s mission to “touch” the Sun survived its record-breaking closest approach to the solar surface on Dec. 24, 2024.
Breaking its previous record by flying just 3.8 million miles above the surface of the Sun, NASA’s Parker Solar Probe hurtled through the solar atmosphere at a blazing 430,000 miles per hour — faster than any human-made object has ever moved. A beacon tone received late on Dec. 26 confirmed the spacecraft had made it through the encounter safely and is operating normally.
This pass, the first of more to come at this distance, allows the spacecraft to conduct unrivaled scientific measurements with the potential to change our understanding of the Sun.
Flying this close to the Sun is a historic moment in humanity’s first mission to a star.
Nicky fox
NASA Associate Administrator, Science Mission Directorate
“Flying this close to the Sun is a historic moment in humanity’s first mission to a star,” said Nicky Fox, who leads the Science Mission Directorate at NASA Headquarters in Washington. “By studying the Sun up close, we can better understand its impacts throughout our solar system, including on the technology we use daily on Earth and in space, as well as learn about the workings of stars across the universe to aid in our search for habitable worlds beyond our home planet.”
NASA’s Parker Solar Probe survived its record-breaking closest approach to the solar surface on Dec. 24, 2024. Breaking its previous record by flying just 3.8 million miles above the surface of the Sun, the spacecraft hurtled through the solar atmosphere at a blazing 430,000 miles per hour — faster than any human-made object has ever moved.
Credits: NASA This video can be freely shared and downloaded at https://svs.gsfc.nasa.gov/14741.
Parker Solar Probe has spent the last six years setting up for this moment. Launched in 2018, the spacecraft used seven flybys of Venus to gravitationally direct it ever closer to the Sun. With its last Venus flyby on Nov. 6, 2024, the spacecraft reached its optimal orbit. This oval-shaped orbit brings the spacecraft an ideal distance from the Sun every three months — close enough to study our Sun’s mysterious processes but not too close to become overwhelmed by the Sun’s heat and damaging radiation. The spacecraft will remain in this orbit for the remainder of its primary mission.
“Parker Solar Probe is braving one of the most extreme environments in space and exceeding all expectations,” said Nour Rawafi, the project scientist for Parker Solar Probe at the Johns Hopkins Applied Physics Laboratory (APL), which designed, built, and operates the spacecraft from its campus in Laurel, Maryland. “This mission is ushering a new golden era of space exploration, bringing us closer than ever to unlocking the Sun’s deepest and most enduring mysteries.”
Close to the Sun, the spacecraft relies on a carbon foam shield to protect it from the extreme heat in the upper solar atmosphere called the corona, which can exceed 1 million degrees Fahrenheit. The shield was designed to reach temperatures of 2,600 degrees Fahrenheit — hot enough to melt steel — while keeping the instruments behind it shaded at a comfortable room temperature. In the hot but low-density corona, the spacecraft’s shield is expected to warm to 1,800 degrees Fahrenheit.
The spacecraft’s record close distance of 3.8 million miles may sound far, but on cosmic scales it’s incredibly close. If the solar system was scaled down with the distance between the Sun and Earth the length of a football field, Parker Solar Probe would be just four yards from the end zone — close enough to pass within the tenuous outer atmosphere of the Sun known as the corona. NASA/APL “It’s monumental to be able to get a spacecraft this close to the Sun,” said John Wirzburger, the Parker Solar Probe mission systems engineer at APL. “This is a challenge the space science community has wanted to tackle since 1958 and had spent decades advancing the technology to make it possible.”
By flying through the solar corona, Parker Solar Probe can take measurements that help scientists better understand how the region gets so hot, trace the origin of the solar wind (a constant flow of material escaping the Sun), and discover how energetic particles are accelerated to half the speed of light.
“The data is so important for the science community because it gives us another vantage point,” said Kelly Korreck, a program scientist at NASA Headquarters and heliophysicist who worked on one of the mission’s instruments. “By getting firsthand accounts of what’s happening in the solar atmosphere, Parker Solar Probe has revolutionized our understanding of the Sun.”
Previous passes have already aided scientists’ understanding of the Sun. When the spacecraft first passed into the solar atmosphere in 2021, it found the outer boundary of the corona is wrinkled with spikes and valleys, contrary to what was expected. Parker Solar Probe also pinpointed the origin of important zig-zag-shaped structures in the solar wind, called switchbacks, at the visible surface of the Sun — the photosphere.
Since that initial pass into the Sun, the spacecraft has been spending more time in the corona, where most of the critical physical processes occur.
This conceptual image shows Parker Solar Probe about to enter the solar corona. NASA/Johns Hopkins APL/Ben Smith “We now understand the solar wind and its acceleration away from the Sun,” said Adam Szabo, the Parker Solar Probe mission scientist at NASA’s Goddard Space Flight Center in Greenbelt, Maryland. “This close approach will give us more data to understand how it’s accelerated closer in.”
Parker Solar Probe has also made discoveries across the inner solar system. Observations showed how giant solar explosions called coronal mass ejections vacuum up dust as they sweep across the solar system, and other observations revealed unexpected findings about solar energetic particles. Flybys of Venus have documented the planet’s natural radio emissions from its atmosphere, as well as the first complete image of its orbital dust ring.
So far, the spacecraft has only transmitted that it’s safe, but soon it will be in a location that will allow it to downlink the data it collected on this latest solar pass.
The data that will come down from the spacecraft will be fresh information about a place that we, as humanity, have never been.
Joe Westlake
Heliophysics Division Director, NASA Headquarters
“The data that will come down from the spacecraft will be fresh information about a place that we, as humanity, have never been,” said Joe Westlake, the director of the Heliophysics Division at NASA Headquarters. “It’s an amazing accomplishment.”
The spacecraft’s next planned close solar passes come on March 22, 2025, and June 19, 2025.
By Mara Johnson-Groh
NASA’s Goddard Space Flight Center, Greenbelt, Md.
Media Contact: Sarah Frazier
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Last Updated Dec 27, 2024 Editor Abbey Interrante Related Terms
Goddard Space Flight Center Heliophysics Heliophysics Division Parker Solar Probe (PSP) Science & Research Science Mission Directorate Solar Flares Solar Wind Space Weather The Sun The Sun & Solar Physics Explore More
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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 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.
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