Material Characterization of Locally Available Textile Fabrics for Structural Applications
Bibliographic record
Abstract
In the current era, rehabilitation and strengthening of reinforced concrete structures is a major need due to premature structural damage owing to various environmental effects, natural hazards and major modifications in the existing building use. Textile fabrics can be an economical and viable option in comparison to traditional strengthening techniques. Therefore, this study was planned to investigate the use of locally available textile fabrics for structural applications leading to economical and sustainable solutions. Sixteen fabrics were collected randomly from the local market and a series of tests including microscopic analysis, mass per unit area, ends and picks count, yarn number and uniaxial tensile strength were conducted to explore the most suitable textile fabric from strength and application aspects. Moreover, rectangular textile-reinforced mortar specimens were prepared incorporating those textile fabrics. Tested textile fabric specimens exhibited mass per unit area in the range of 117 to 1145 g/m2 depending on the fabric types. It was observed that tensile strength of the tested textile fabric depends on fiber composition, ends and picks count, yarn number and weave type. The greater the number of yarns in a fabric, the denser it will be and therefore it will be stronger in either direction (warp and weft). It was observed that the tensile strength in warp direction was higher than in weft direction due to the higher number of yarns in the warp direction. For instance, tested specimen TF16 showed ultimate tensile loads of 2890 and 2600 N in warp and weft directions, respectively. Furthermore, plain weave type fabric showed higher strength compared to that of the twill weave. It can also be argued that among the sixteen selected fabric specimens, plain weave fabric (i.e., glass) was found most suitable for textile-reinforced mortar applications due to adequate spacing and alternative movement of yarns, which leads to a stronger bond with the matrix and ultimately achieving higher tensile strength.
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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 | 0.000 | 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) | 0.002 | 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".