Comparative analysis of mold-cast and 3D-printed cement-based components: implications for standardization in additive construction
Bibliographic record
Abstract
The rapid growth of additive construction emphasizes the need for developing testing methodologies specific to cement-based 3D-printed components. This study performs a comprehensive comparative analysis of the physical, mechanical, and microstructural characteristics of specimens fabricated through 3D printing versus those created using traditional mold-casting techniques. This research aims to inform and support standardization efforts in the field of additive construction, both within Canada and globally. Additionally, the research provides insights into material characterization to inform the development of numerical modeling strategies tailored for 3D-printed structural elements. The digital image correlation (DIC) technique was employed to examine strain behavior and generate stress-strain curves. The results showed a significant strength reduction and strain concentration at the interlayer surfaces of the 3D-printed specimens. Concluding recommendations include the adoption of the oblique shear test for shear strength assessment and the four-point flexural strength for evaluating interlayer bond strength in cement-based 3D-printed members.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".