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4 Min Read Space Station Research Advances NASA’s Plans to Explore the Moon, Mars The full moon is pictured as the International Space Station orbited 254 miles above the Pacific Ocean northeast of Guam. Credits: NASA

Space, the saying goes, is hard. And the farther humans go, the harder it can get.

Some of the challenges on missions to explore the Moon and Mars include preventing microbial contamination of these destinations, navigating there safely, protecting crew members and hardware from radiation, and maintaining and repairing equipment.

Research on the International Space Station is helping NASA scientists develop tools and processes to ensure success on these important missions. Here are highlights from some of the investigations making space a little easier.

Tracking Tiny Stowaways

Bacteria and fungi live in and on all humans and all around us on Earth. Most of these microorganisms are beneficial or harmless but introducing them to other celestial bodies could adversely affect our ability to study ecosystems on those other worlds.

Crew members will conduct a spacewalk to collect samples near space station life support system vents for ISS External Microorganisms, an investigation to assess whether the orbiting laboratory releases microorganisms into space. Results could provide insight into the potential for organisms to survive and reproduce in space and help researchers determine which microbes would most likely contaminate other planetary bodies visited by crewed missions.

NASA astronaut Victor Glover trains for the ISS External Microorganisms spacewalk in the Neutral Buoyancy Laboratory pool at NASA’s Johnson Space Center in Houston.NASA

A miniature, hand-held digital microscope designed to make in-flight medical diagnoses, the Moon Microscope, also can test water, food, and surfaces for contamination. The device images samples at high resolution and processes data on web-enabled devices such as phones or tablets. Multiple users can access the microscope simultaneously, and some applications run autonomously.

Getting There and Back

Spacecraft must have sophisticated high-tech systems for navigating. Sextant Navigation tests the function of sextants in microgravity as an emergency backup navigation technique for Artemis and other future exploration missions. These mechanical devices have guided navigators for centuries, and Gemini and Apollo missions demonstrated they were useful for astronauts.

Astronaut Alexander Gerst of ESA (European Space Agency) tests the Sextant Navigation device.NASA

Refining Radiation Detection

Missions beyond low Earth orbit increase exposure to radiation, which can pose a hazard to human health and interfere with equipment operation. As NASA prepares for future missions, providing adequate protection is vital.

The Hybrid Electronic Radiation Assessor, or HERA, was built to serve as a primary radiation detection system for the Orion spacecraft, which will carry crews into orbit around the Moon. The International Space Station Hybrid Electronic Radiation Assessor investigation modified the system to operate on the space station to provide researchers input for use on future exploration missions.

Artemis HERA on Space Station further modified the radiation detection system so researchers could continue to evaluate the hardware in the space radiation environment prior to Artemis II.

ESA (European Space Agency) astronaut Thomas Pesquet holds a mobile unit for the ESA-Active-Dosimeters experiment.NASA

Active-Dosimeters, an investigation led by ESA (European Space Agency), tested a wearable system to measure radiation exposure to crew members on the space station and how it changes with the station’s orbit and altitude. Data from the wearable dosimeter improved radiation risk assessments and could lead to better protection for astronauts, including the ability to quickly respond to changes in exposure throughout future exploration missions.

Robot Helpers

On future exploration missions, robotic technology can help crew members with basic tasks, monitor and maintain equipment, and conduct operations such as sample collection, reducing the need to expose astronauts to harsh environments. Integrated System for Autonomous and Adaptive Caretaking demonstrates using autonomous robots to transfer and unpack cargo and to track and respond to maintenance issues such as leaks and fires, which could protect valuable equipment and reduce costly repairs on future missions. The investigation uses the space station’s Astrobee and Robonaut robots.

NASA astronaut Chris Cassidy sets up a test with an Astrobee robotic assistant.NASA

Multi-Resolution Scanning uses the station’s Astrobees to test sensors and robotics to support automated 3D sensing, mapping, and situational awareness functions. On future Gateway and lunar surface missions, such systems could automatically detect defects and conduct remote maintenance and autonomous operation of vehicles such as rovers.

ESA (European Space Agency) astronaut Samantha Cristoforetti practices maneuvers for the Surface Avatar investigation.NASA

Surface Avatar evaluates crew operation of multiple autonomous robots in space. The investigation also assesses crew member responsiveness to feedback on the consoles used to operate robots remotely, which supports design of effective setups for operating robots on the ground from a spacecraft orbiting above. Results contribute to the development of other uses of robotic assistance such as returning samples from Mars and asteroids.

Melissa Gaskill
International Space Station Research Communications Team
NASA’s Johnson Space Center

Search this database of scientific experiments to learn more about those mentioned above.

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Details Last Updated May 30, 2024 Related Terms

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Rocket Lab will launch the second of two cubesats for NASA's PREFIRE climate change mission tonight (May 31), and you can watch the action live.

Astronomers have detected giant, magnetic stars outside the Milky Way for the first time. These infant stars in the Magellanic Clouds could reveal details of early stellar evolution.

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2 min read

Hubble Views the Lights of a Galactic Bar This Hubble Space Telescope image reveals details in the barred spiral galaxy NGC 4731. ESA/Hubble & NASA, D. Thilker

This new image from the NASA/ESA Hubble Space Telescope shows the broad and sweeping spiral galaxy NGC 4731. It lies in the constellation Virgo and is located 43 million light-years from Earth. This highly detailed image uses data collected from six different filters. The abundance of color illustrates the galaxy’s billowing clouds of gas, dark dust bands, bright pink star-forming regions and, most obviously, the long, glowing bar with trailing arms.

Barred spiral galaxies outnumber both regular spirals and elliptical galaxies put together, numbering around 60% of all galaxies. The visible bar structure is a result of orbits of stars and gas in the galaxy lining up, forming a dense region that individual stars move in and out of over time. This is the same process that maintains a galaxy’s spiral arms, but it is somewhat more mysterious for bars: spiral galaxies seem to form bars in their centers as they mature, which helps explain the large number of bars we see today, but they can also lose them if the accumulated mass along the bar grows unstable. The orbital patterns and the gravitational interactions within a galaxy that sustain the bar also transport matter and energy into it, fueling star formation. Indeed, the observing program studying NGC 4731 seeks to investigate this flow of matter in galaxies.

Beyond the bar, the spiral arms of NGC 4731 stretch out far past the confines of this close-in Hubble view. Astronomers think the galaxy’s elongated arms are the result of gravitational interactions with other, nearby galaxies in the Virgo cluster.

Text Credit: European Space Agency (ESA)

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Claire Andreoli
NASA’s Goddard Space Flight Center, Greenbelt, MD
claire.andreoli@nasa.gov

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May 31, 2024

Editor Andrea Gianopoulos Location NASA Goddard Space Flight Center

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2 min read

June’s Night Sky Notes: Constant Companions: Circumpolar Constellations, Part III

by Kat Troche of the Astronomical Society of the Pacific

In our final installment of the stars around the North Star, we look ahead to the summer months, where depending on your latitude, the items in these circumpolar constellations are nice and high. Today, we’ll discuss Cepheus, Draco, and Ursa Major. These objects can all be spotted with a medium to large-sized telescope under dark skies.

From left to right: Ursa Major, Draco, and Cepheus. Credit: Stellarium Web

Herschel’s Garnet Star: Mu Cephei is a deep-red hypergiant known as The Garnet Star, or Erakis. While the star is not part of the constellation pattern, it sits within the constellation boundary of Cepheus, and is more than 1,000 times the size of our Sun. Like its neighbor Delta Cephei, this star is variable, but is not a reliable Cepheid variable. Rather, its brightness can vary anywhere between 3.4 to 5.1 in visible magnitude, over the course of 2-12 years.

This composite of data from NASA’s Chandra X-ray Observatory and Hubble Space Telescope gives astronomers a new look for NGC 6543, better known as the Cat’s Eye nebula. This planetary nebula represents a phase of stellar evolution that our sun may well experience several billion years from now. Credit: X-ray: NASA/CXC/SAO; Optical: NASA/STScI

The Cat’s Eye Nebula: Labeled a planetary nebula, there are no planets to be found at the center of this object. Observations taken with NASA’s Chandra X-ray Observatory and Hubble Space Telescopes give astronomers a better understanding of this complex, potential binary star, and how its core ejected enough mass to produce the rings of dust. When searching for this object, look towards the ‘belly’ of Draco with a medium-sized telescope.

NASA’s Spitzer, Hubble, and Chandra space observatories teamed up to create this multi-wavelength view of the M82 galaxy. The lively portrait celebrates Hubble’s “sweet sixteen” birthday .X-ray data recorded by Chandra appears in blue; infrared light recorded by Spitzer appears in red; Hubble’s observations of hydrogen emission appear in orange, and the bluest visible light appears in yellow-green. Credit: NASA, ESA, CXC, and JPL-Caltech

Bode’s Galaxy and the Cigar Galaxy: Using the arrow on the star map, look diagonal from the star Dubhe in Ursa Major. There you will find Bode’s Galaxy (Messier 81) and the Cigar Galaxy (Messier 82). Sometimes referred to as Bode’s Nebula, these two galaxies can be spotted with a small to medium-sized telescope. Bode’s Galaxy is a classic spiral shape, similar to our own Milky Way galaxy and our neighbor, Andromeda. The Cigar Galaxy, however, is known as a starburst galaxy type, known to have a high star formation rate and incredible shapes. This image composite from 2006 combines the power of three great observatories: the Hubble Space Telescope imaged hydrogen in orange, and visible light in yellow green; Chandra X-Ray Observatory portrayed X-ray in blue; Spitzer Space Telescope captured infrared light in red.

Up next, we celebrate the solstice with our upcoming mid-month article on the Night Sky Network page through NASA’s website!

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Arcturus and Vega highlight the evening, The Big Dipper quickly pivots. And sorry, tell your friends and family who ask that no "dazzling Parade of Planets" is blazing across the sky. Who makes this stuff up??

The post This Week's Sky at a Glance, May 31 – June 9 appeared first on Sky & Telescope.

Image: Resembling a reddish jellyfish, the Mahajamba Bay in Madagascar is imaged by Copernicus Sentinel-2.

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How can machine learning help astronomers find Earth-like exoplanets? This is what a recently accepted study to Astronomy & Astrophysics hopes to address as a team of international researchers investigated how a novel neural network-based algorithm could be used to detect Earth-like exoplanets using data from the radial velocity (RV) detection method. This study holds the potential to help astronomers develop more efficient methods in detecting Earth-like exoplanets, which are traditionally difficult to identify within RV data due to intense stellar activity from the host star.

The study notes, “Machine learning is one of the most efficient and successful tools to handle large amounts of data in the scientific field. Many algorithms based on machine learning have been proposed to mitigate stellar activity to better detect low-mass and/or long period planets. These algorithms can be classified into two categories: supervised learning and unsupervised learning. The advantage of supervised learning is that the proposed model contains a large set of variables and has the ability to produce relatively accurate predictions based on the training data.”

For the study, the researchers applied their algorithm to three stars to ascertain its ability to identify exoplanets within the stellar activity data: our Sun, Alpha Centauri B (HD 128621), and Tau ceti (HD 10700), with Alpha Centauri B being located approximately 4.3 light-years from Earth and Tau ceti being located approximately 12 light-years from Earth. After inserting simulated planetary signals within the algorithm, the researchers found their algorithm successfully identified simulated exoplanets with potential orbital periods ranging between 10 to 550 days for our Sun, 10 to 300 days for Alpha Centauri B, and 10 to 350 days for Tau ceti. It’s important to note that Alpha Centauri B currently has had several potential exoplanet detections but non confirmed while Tau ceti currently has eight exoplanets listed as “unconfirmed” within its system.

Additionally, the algorithm identified these results correspond to Alpha Centauri B and Tau ceti potentially having exoplanets approximately 4 times the size of Earth and within the habitable zones of those stars, as well. After inserting more stellar activity data into the algorithm, the researchers discovered the algorithm successfully identified a simulated exoplanet approximately 2.2 times the size of the Earth while orbiting the same distance as the Earth from our Sun.

The study noted in its conclusions, “In this paper, we developed a neural network framework to efficiently mitigate stellar activity at the spectral level, to enhance the detection of low-mass planets on periods from a few days up to a few hundred days, corresponding to the habitable zone of solar-type stars.”

While the study focused on finding Earth-like exoplanets within RV data, the researchers note that additional data, including transit time, phase, and space-based photometry, could be used to identify Earth-like exoplanets. They emphasize the European Space Agency’s PLATO space telescope mission could accomplish this, which is currently being developed and slated for launch sometime in 2026. Upon launch, it will be stationed at the Sun-Earth L2 Lagrange point located on the opposite side of the Earth from the Sun where it scan up to one million stars searching for exoplanets using the transit method with an emphasis on terrestrial (rocky) exoplanets.

PLATO mission discussed around the 9:00 mark

This study comes as the number of confirmed exoplanets by NASA has reached 5,632 as of this writing, which is comprised of 201 terrestrial exoplanets, and also provides the upcoming PLATO mission ample opportunity to discover many more terrestrial exoplanets within our Milky Way Galaxy.

How will machine learning help astronomers detect Earth-like exoplanets in the coming years and decades? Only time will tell, and this is why we science!

As always, keep doing science & keep looking up!

The post A New Deep Learning Algorithm Can Find Earth 2.0 appeared first on Universe Today.