Robotics & Machine Learning Daily News2024,Issue(MAY.24) :47-47.

Sichuan University Reports Findings in Machine Learning [Stat eto-state dynamics and machine learning predictions of inelastic and reactive O (3P) + CO(1 +) collisions relevant to hypersonic flows]

Robotics & Machine Learning Daily News2024,Issue(MAY.24) :47-47.

Sichuan University Reports Findings in Machine Learning [Stat eto-state dynamics and machine learning predictions of inelastic and reactive O (3P) + CO(1 +) collisions relevant to hypersonic flows]

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is th e subject of a report. According to news reporting originating from Chengdu, Peo ple’s Republic of China, by NewsRx correspondents, research stated, “The state-t o-state (STS) inelastic energy transfer and O-atom exchange reaction between O a nd CO(v), as two fundamental processes in non-equilibrium air flow around spacec raft entering Mars’ atmosphere, yield the same products and both make significan t contributions to the O + CO(v) -> O + CO(v’) collision s. The inelastic energy transfer competes with the O-atom exchange reaction.”

Key words

Chengdu/People’s Republic of China/Asi a/Cyborgs/Emerging Technologies/Machine Learning

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
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