New SMA Short Fibers for Cement Composites Manufactured by Cold Drawing
Bibliographic record
Abstract
<p class="1Body">This study suggests new shape memory alloy reinforcing fibers manufactured by cold drawing method. This study prepares NiTi shape memory alloy (SMA) wires with diameter of 1.0 mm. Then, the wires are elongated by cold drawing and, thus, the diameters are reduced to 0.93 or 0.965 mm, respectively. This procedure introduces prestrain into the wires. When elongated SMA wires are heated, the shape memory effect is activated; this process recovers the deformed length as well as the reduced diameter due to Poisson’s effect. Cold drawn wires with diameters of 0.93 and 0.965 mm recover diameters of 0.018 and 0.024 mm, respectively, with heating. The bulging of the SMA fiber in the radial direction inside cement composites induces confining pressure around the fiber and increases bond strength. When an SMA fiber is heated at the both ends, the heated parts bulge and the fiber shape looks like a dog-bone. Such a dog-bone shaped fiber can provide a geometrical anchoring action that also increases the bond resistance of the fiber. This study conducts pullout tests of SMA fibers to understand their pullout behavior and assess bond stress. The heated fibers and dog-bone shaped fibers increase pullout force compared to those of as-received and cold-drawn fibers. When dog-bone shaped fibers are heated, they show twice the pullout force of dog-bone shaped fibers without heating because geometric anchoring action as well as additional frictional resistance due to confining pressure are activated.</p>
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".