Cape Town – An astronomer from the South African Astronomical Observatory (SAAO) was part of an international team that worked on a way to deflect potentially catastrophic asteroids that may one day encounter Earth.
As part of a team of four, Dr Nicolas Erasmus from SAAO and his fellow team members worked together to create a machine-learning algorithm called the “Deflector Selector”, which could be used to study dangerous space debris like asteroids and then determine which technology has the best chance of deflecting them from Earth’s path.
Asteroids are basically mini-planets that orbit our sun but are too small to be classified as planets.
Earth is vulnerable to space debris, including asteroids, which occasionally come close to or impact the Earth.
For example, in April this year, an asteroid called 2018 GE3 passed just 192,316 kilometres away from Earth’s atmosphere, which was about half the distance between Earth and the moon, according to NASA’s Center for Near Earth Object Studies (CNEOS).
In February 2013, a meteor (a small rocky or metallic body) exploded over Russia’s Ural Mountains in Chelyabinsk. The meteor was estimated to be about 10 tons and entered Earth’s atmosphere at a hypersonic speed of about 53,108 km/hr. Despite it having shattered into pieces above the ground, it still managed to have injured over 1000 people, according to the Russian Academy of Sciences.
In July 2016 Dr Erasmus attended the Frontier Development Lab hosted by the National Aeronautics and Space Administration’s (NASA) Ames Research Center and the Search for Extraterrestrial Intelligence (SETI) in California. The six-week workshop brought together planetary scientists and machine-learning experts.
Dr Erasmus’ team addressed the question, “could mankind deflect a hazardous asteroid on a crash course with Earth and if so which method would give us the best chance?”.
“Developing every proposed technology is currently prohibitively expensive, so determining now which technologies are most likely to be effective would allow us to prioritise a subset of proposed deflection technologies for funding and development,” the research paper said.
The algorithm tested the effectiveness of nuclear explosives, kinetic impactors, and gravity tractors. Nuclear detonations release an explosive force that helps stop space debris, gravity tractors involve hovering a spacecraft near an asteroid, allowing its gravitational pull to nudge the asteroid in a different direction, and a kinetic impactor forces an object to change direction by crashing a spacecraft into it.
Dr Erasmus was a co-author of the paper titled, “The Deflector Selector: A Machine Learning Framework for Prioritizing Hazardous Object Deflection Technology Development”, published by the Acta Astronautica journal.
