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Record W4407015552 · doi:10.52202/078370-0032

META-LUNA: Disruptive ISRU for Building Future Solar Power Satellites

2024· article· en· W4407015552 on OpenAlexaff
Haroon B. Oqab, Andrew Wilson, George B. Dietrich, Nobuyuki Kaya, Massimiliano Vasile

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSpacecraft Design and Technology
Canadian institutionsCanadian Space Agency
Fundersnot available
KeywordsAstrobiologySolar powerAerospace engineeringPower (physics)Environmental scienceEngineeringPhysics

Abstract

fetched live from OpenAlex

In situ utilisation (ISRU) of space resources is increasingly becoming a central consideration for long-duration space missions. The efficient and sustainable use of these resources must play a prominent role in our discussion of space exploration and development. Regolith represents the most accessible and utilisable resource on the Lunar, Martian and Asteroidal surfaces. Regolith is an abundant and diverse resource, and multiple use cases have been proposed from water or oxygen generation to its use in structural materials. In response to this opportunity, Metasat presents a novel approach to development of power sources needed to employ Regolith by designing and building solar power satellites (SPS) utilizing these resources for construction based on the Multi-domain Operations using Rapidly-responsive PHased Energy Universally Synchronized (MORPHEUS) Solar Power Satellite architecture, a Sandwich Type SPS solution providing an alternative energy source for sustainable energy. The proposed solution leverages advancements in photovoltaic and wireless power transmission technologies, enabling the collection of solar energy in the sunlit regions of space without the constraints of atmospheric interference or nighttime limitations, to deliver clean, abundant, affordable and secure energy. Combined with the use of regolith a sustainable approach to space- based energy harvesting is provided, addressing the needs of in-space manufacturing, with the aim of continually reducing the reliance on Earth-launched resources, decrease launch costs, and minimizing the environmental impact associated with traditional space missions. This paper will update paths forward for the MORPHEUS SPS architecture and introduces leveraging ISRU for building future solar power satellites.

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.

How this classification was reachedexpand

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.934
Threshold uncertainty score0.594

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.248
Teacher spread0.228 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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