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Lunar construction: A state-of-the-art survey

2025· article· en· W4416895046 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueProgress in Aerospace Sciences · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsnot available
FundersUniversity of Toronto
KeywordsScientific instrumentWork (physics)Extraterrestrial lifeScalabilityIncentiveCritical infrastructureSustainability

Abstract

fetched live from OpenAlex

The renewed global interest in furthering human’s presence on the Moon has catalyzed efforts to establish a sustainable lunar base. The incentive is not only for scientific opportunities and prospects of deep-space exploration, but also for demonstrating technologies that will extend our reach throughout the Solar System. Central to such efforts is the development of robust and scalable lunar construction technologies. This survey presents a comprehensive review of the state-of-the-art in lunar construction, including environmental characterization, infrastructure development, construction methods and materials, and robotic systems. The unique challenges posed by the lunar environment are highlighted, such as extreme temperature variations, high radiation exposure, and micrometeorite impacts, with a particular emphasis on the abrasive, adhesive, and electrostatically charged lunar regolith, thus including strategies developed for lunar dust mitigation. The survey investigates the critical infrastructure that will need to be established, including habitats, power stations, communication stations, landing pads, blast berms, and more. A detailed analysis of the methods and materials that are being developed to create such infrastructure is presented, identifying which methods have demonstrated promise and garnered the most attention. A diversity of robotic technologies are required to enable the construction of the necessary infrastructure using these methods and systems, which are broken down into lunar cranes, mobile manipulators, 3D printers, and robot teams, with a particular focus on work being done to develop flight systems. The paper concludes by identifying critical research and technological gaps that must be addressed to support the next generation of lunar missions and long-term extraterrestrial habitation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.320

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.279
Teacher spread0.262 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it