The Effect of Steel Strapping Tensioning Technique and Fibre-Reinforced Polymer on the Performance of Cross-Laminated Timber Slabs Subjected to Blast Loads
Bibliographic record
Abstract
Engineered wood products (EWP) are becoming extremely popular and a viable material option for the construction of residential, commercial, and hybrid buildings. Cross-laminated timber (CLT) is among one of the many EWP available in North America, which can be utilized for many different applications such as: walls, floors, and roofs. Despite the available requirements in the Canadian blast design standard (CSA, 2012) with regard to the design of wood structures, there are currently no provisions on how to retrofit timber structures to improve their performance when subjected to blast loads. The current study is aimed at investigating the effect of different retrofitting alternatives in order to improve the overall behaviour of CLT when exposed to out-of-plane bending. The experimental program examined the behaviour of seventeen reinforced CLT slabs. Testing was conducted at the University of Ottawa by means of a shock tube capable of simulating high strain rates similar to those experienced during a blast event. The current study was divided into two phases. The first consisted of CLT slabs retrofitted with steel straps where strap spacing, location, and order of installation was investigated. The second phase focused on the development of dynamic properties of CLT panels when reinforced with GFRP. Lay-up configuration and fabric orientation were among the parameters explored. The results from the experimental program show that reinforcing the panels with steel straps had minimal effect on the ultimate strength, but significant levels of post peak resistance and ductility was achieved. The horizontal straps were able to restrict the failure to small regions and to promote flexural failure by preventing rolling shear failure. It also eliminated flying debris and enhanced the ultimate strength, stiffness as well as ductility. Applying GFRP layers enhanced the overall behaviour of the slab resulting in a significant increase in peak resistance, ductility, and stiffness when compared to the dynamic results of an unretrofitted panel. The post peak resistance was also greatly improved. In particular, applying stacked quadraxial lay-up configuration significantly improved the ductility and resulted in the greatest post peak resistance. The effect of steel straps on damaged and retrofitted was relatively minimal, and only partial recovery of the resistance and the stiffness was achieved. GFRP with full confinement yielded better performance compared to the unretrofitted and undamaged counterpart. More work is needed to quantify the benefits of using GFRP in these applications.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| 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".