An In-depth Analysis of Strength and Stiffness Variability in 3D-Printed Sandstones: Implications for Geomechanics
Bibliographic record
Abstract
Natural rocks are highly heterogeneous due to various geological processes that constantly alter their properties. The accumulation, deposition, and cementation of mineral and organic particles continuously modify the spatial characteristics of rock properties. Property variability or anisotropy is commonly observed in most rock types and influences strength, transport, and thermal conductivity behavior. This unpredictability presents a significant challenge for laboratory testing. Binder-jet additive manufacturing (3D printing) has emerged as a valuable technology for characterizing rock properties in geoscience and engineering. This study proposes a methodology to evaluate the variability and repeatability of mechanical properties of 3D-printed sandstones during binder-jet additive manufacturing. The mechanical properties were analyzed statistically for samples located in various parts of the 3D printer build volume. The results showed that the 3D-printed sandstones exhibited significant variations in their strength and stiffness properties when measured from samples produced within the same build volume during binder-jet additive manufacturing. The Uniaxial Compressive Strength (UCS) varied from 23 to 38 MPa, with an average value of 29 MPa. The Young's modulus, on the other hand, ranged from 1.5 to 4.05 GPa, with an average value of 2.33 GPa. The variability of the mechanical properties, quantified by the standard deviation, decreased when the entire population of 3D-printed sandstones was divided into smaller samples situated at different elevations of the build platform.
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How this classification was reachedexpand
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".