Episode 633: How Will Humans Return to the Moon in 2024? Lunar Lander Options for Artemis
After almost 50 years since the Apollo Moon landing missions ended, NASA announced that they’re going to return to the surface of the Moon with their Artemis mission, ideally taking the first lunar footsteps in 2024.
NASA Administrator Jim Bridenstine asked for additional funding to achieve this goal, and the other branches of government haven’t been as enthusiastic about this plan. So don’t be surprised if the landing date slips to 2028 or even farther.
But NASA is moving forward on its architecture to return humans to the Moon, from its launch rocket to the entire method of getting astronauts down to the surface.
Exactly which rockets, modules and landing systems that will be used are still getting worked out, with different options still getting considered.
Our Book is out!
https://www.amazon.com/Universe-Today-Ultimate-Viewing-Cosmos/dp/1624145442/
Audio Podcast version:
ITunes: https://itunes.apple.com/us/podcast/universe-today-guide-to-space-audio/id794058155?mt=2
RSS: https://www.universetoday.com/audio
Weekly email newsletter:
https://www.universetoday.com/newsletter
Weekly Space Hangout:
https://www.youtube.com/channel/UC0-KklSGlCiJDwOPdR2EUcg/
Astronomy Cast:
https://www.youtube.com/channel/UCUHI67dh9jEO2rvK--MdCSg
Support us at https://www.patreon.com/universetoday
More stories at https://www.universetoday.com/
Twitch: https://twitch.tv/fcain
Twitter: https://twitter.com/universetoday
Facebook: https://www.facebook.com/universetoday
Instagram - https://instagram.com/universetoday
Team: Fraser Cain - @fcain / frasercain@gmail.com
Karla Thompson - @karlaii / https://www.youtube.com/channel/UCEItkORQYd4Wf0TpgYI_1fw
Chad Weber - weber.chad@gmail.com
References:
https://www.nasa.gov/mission_pages/apollo/missions/index.html
http://fiso.spiritastro.net/telecon/Kokan_1-29-20/Kokan_1-29-20.pdf
https://spacenews.com/nasa-issues-call-for-proposals-for-human-lunar-landers/
https://www.blueorigin.com/blue-moon
https://mars.nasa.gov/msl/spacecraft/rover/summary/
https://www.space.com/jeff-bezos-blue-origin-artemis-moon-lander-team.html
Available Results
Generated results are saved to your library for reuse and search.
Choose Template
Pick the result you want. You can review provider and model before generating.
A concise first-pass summary for understanding the episode quickly.
A comprehensive, source-grounded extraction of the reusable knowledge in an episode.
Technologies, AI models, technical methods, capabilities, limitations, and adoption implications.
Repeatable methods, frameworks, mental models, processes, and systems.
A dedicated analysis of warnings, limitations, trade-offs, weak evidence, and uncertainty.
A dedicated inventory of concrete resources named in the episode.
A concise first-pass summary for understanding the episode quickly.
A detailed readable summary organized by chapter or topic.
A navigable map of subjects, topic flow, and suggested chapters.
A comprehensive, source-grounded extraction of the reusable knowledge in an episode.
Reusable atomic knowledge units extracted from the episode.
A comprehensive extraction focused on health practices, protocols, claims, and safety caveats.
A comprehensive extraction focused on opportunities, strategy, markets, and company building.
Explicit actions, next steps, habits, recommendations, and things to avoid.
A dedicated inventory of concrete resources named in the episode.
A dedicated analysis of warnings, limitations, trade-offs, weak evidence, and uncertainty.
A concise first-pass summary for understanding the episode quickly.
A detailed readable summary organized by chapter or topic.
A navigable map of subjects, topic flow, and suggested chapters.
A comprehensive, source-grounded extraction of the reusable knowledge in an episode.
Reusable atomic knowledge units extracted from the episode.
A comprehensive extraction focused on health practices, protocols, claims, and safety caveats.
A comprehensive extraction focused on opportunities, strategy, markets, and company building.
Scientific findings, mechanisms, studies, hypotheses, and the limits of the evidence discussed.
Technologies, AI models, technical methods, capabilities, limitations, and adoption implications.
Investment theses, assets, catalysts, valuation reasoning, time horizons, and risks.
Chronologies, actors, causes, consequences, turning points, and competing historical interpretations.
Policies, proposals, stakeholders, arguments, implementation constraints, and predicted effects.
Career paths, skills, hiring signals, workplace decisions, transitions, and limitations of the advice.
Behavioral mechanisms, biases, motivation, habits, emotions, interventions, and evidence limitations.
Economic mechanisms, incentives, indicators, market structure, forecasts, and uncertainty.
Leadership principles, team systems, organizational design, culture, feedback, and failure modes.
Audience, positioning, messaging, acquisition, retention, experiments, metrics, and failed approaches.
Teaching methods, learning strategies, practice, feedback, assessment, and effectiveness evidence.
Theses, premises, arguments, objections, values, thought experiments, and unresolved questions.
Communication patterns, conflict, boundaries, expectations, repair methods, and contextual limitations.
Books, papers, authors, courses, and other learning resources mentioned in the episode.
Repeatable methods, frameworks, mental models, processes, and systems.
Explicit actions, next steps, habits, recommendations, and things to avoid.
Memorable statements and important claims with attribution and source context.
A dedicated inventory of concrete resources named in the episode.
A dedicated analysis of warnings, limitations, trade-offs, weak evidence, and uncertainty.