Glass as a Structural Material: Post-tensioned Glass T-Beam
Bibliographic record
Abstract
Glass, traditionally, is used in buildings as windows because its strength capacity in windows is not significant.However, there is more demand for usage of glass such as beams, columns and decks.Glass' brittle nature has hindered its use as a strength carrying member.Aesthetics, recyclability, and transparency are the main reasons of the interest for glass in structural field.Moreover, glass may show significantly more benefits for certain types of projects such as historic building preservation and aesthetic buildings and bridges, where envelopments with minimal visual interruption are needed.However, more research should be done to be able to meet the demands and benefit from the advantages of glass.This study aims to contribute to the literature of structural glass and enhance the use of glass as a structural material, so a T-shaped glass beam is studied to develop a proper and safe design.Since glass is a brittle material and has high compressive strength and lower tensile strength, a T-beam is posttensioned in order to increase its initial fracture capacity and obtain ductile post-fracture performance.Several material tests are conducted to confirm the theoretical mechanical properties of glass as a material under compression and bending (indirect tension).After obtaining mechanical properties of the glass to be used in research, Finite Element Models (FEMs) of the T-beams were generated and analytical hand calculations were done for the same types of glass beams.Tests of T-shaped annealed (float) glass beams with and without post-tensioning were conducted.The results of the experiments were compared with the analytical hand calculations and FEMs.In this study, a glass T-beam was post-tensioned and its initial fracture capacity was increased.This resulted in a more ductile post-fracture performance, which would avoid sudden collapse and provide a safer fracture performance.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".