Experimental study on porosity-permeability regulation and strength enhancement of 3D-printed rock analogs: New insights from post-processing explorations
Why this work is in the frame
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Bibliographic record
Abstract
Sandy 3D printing is an emerging technique enabling fabrication of artificial rock analogs with designed structures and controllable physical properties, finding widespread application in rock mechanics and geosciences. However, the low strength, stiffness, and high porosity-permeability of sandy 3D-printed rock analogs (3D-PRA) limit their utility for simulating natural rocks across broader application scenarios. This study explores three modification infiltrates to quantitatively regulate 3D-PRA properties. We systematically evaluate their effects on the physical, mechanical, and hydraulic properties of modified specimens. Permeability-porosity relationships and strength enhancement are analyzed integrally, while compression tests assess mechanical properties and failure behavior. Notably, modification with the three infiltrates increases unconfined compressive strength by over tenfold, exceeding 50 MPa. Permeability is quantitatively regulated across orders of magnitude—from Darcy-scale (∼10D) to millidarcy levels (∼0.2mD). For aqueous nano-silica solution (ANSS), porosity and permeability vary systematically with infiltration parameters. Conversely, polyacrylic resin adhesive (PARA) and epoxy resin adhesive (EPRA) infiltrates significantly reduce permeability but exhibit no quantifiable parametric relationship; porosity trends similarly lack mathematical correlation. Microstructural evolution mechanisms are elucidated through micro-computed tomography (μ-CT) and scanning electron microscope (SEM) analysis. This work contributes a comparative analysis of infiltrate effects on 3D-PRA property regulation and proposes a precision-controlled ANSS-based process for simultaneous permeability-porosity management and strength enhancement, significantly expanding application potential.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it