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Record W4407413699 · doi:10.2514/6.2025-1863

On The Development of an ISRU-Based Calcium Sulfo-Aluminate (CSA) Concrete for 3-D Printed and Cast Lunar Surface Infrastructure Applications

2025· article· en· W4407413699 on OpenAlexaff
Michael Fiske, Alex Ellery

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsCarleton University
Fundersnot available
KeywordsAluminateMaterials scienceMetallurgy3d printedCalciumCementEngineeringManufacturing engineering

Abstract

fetched live from OpenAlex

NASA’s Artemis program will see the return of man to the Moon to test various technologies that will be used to establish a sustained human presence on the Lunar surface. In addition, these missions will serve as precursors for subsequent expeditions to Mars. Given the remote, perilous, and unhospitable conditions in extraterrestrial environments, supporting infrastructures such as launching and landing pads (LLP), blast shields, research labs, habitats, roads, hangars, and radiation shielding for both humans and surface-based nuclear reactors are needed to protect astronauts working or living on the Lunar surface. Because of the estimated $1.2M/kg launch cost to place material from Earth on the Lunar surface, the Moon to Mars Planetary Autonomous Construction Technology (MMPACT) project at NASA/MSFC is focused on the development of these lunar ISRU-based surface infrastructure materials and construction processes. On Earth, full-scale additive construction is a promising large-scale robotic technique that has been used for realizing civil infrastructure. Compared to traditional construction which inherently relies on laborious manual efforts, additive construction offers an accelerated, automated, cost-effective, safe, and lean construction method for building structures with customized designs and without the need for formwork. Although additive construction was originally envisioned for terrestrial applications, it has a huge potential for space construction as well considering the safety concerns related to the harsh environmental conditions and the need for robotic construction methods. To this goal, a suitable printing material locally sourced on the Moon and Mars is desired to avoid the cost and payload constraints related to transporting materials from Earth. Portland cement concrete (PCC) is commonly used as the printing material for additive construction on Earth due to its relatively low cost and wide availability. However, beyond Earth, PCC can be difficult to obtain due to the scarcity of its ingredients and its energy-intensive manufacturing processes. Calcium Sulfo-Aluminate (CSA) concrete presents an ISRU-derived alternative that has shown good mechanical performance in terrestrial applications and during testing for possible planetary applications as well, especially as demonstrated in 3D printing processes. In this paper, we will identify the primary components of CSA cement, how they can all be separated and isolated from the lunar regolith, and how they can be re-formulated as a binder to mix with regolith and water to form a lunar concrete. We will also describe work performed to optimize a recipe for CSA concrete to maximize its use in planetary 3D printing as well as lunar pre-cast concrete applications and characterize mechanical and thermal properties of CSA concrete as a function of cure pressure. Lastly, we will recommend applications and constraints for the use of CSA concrete on planetary surfaces and recommended future work to address these constraints.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.015
GPT teacher head0.264
Teacher spread0.249 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations1
Published2025
Admission routes1
Has abstractyes

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