Skip to main content

Research Repository

Advanced Search

Outputs (4)

Flexural behaviour of concrete thin sheets prestressed with basalt-textile reinforcement (2023)
Journal Article
Hutaibat, M., Ghiassi, B., & Tizani, W. (2023). Flexural behaviour of concrete thin sheets prestressed with basalt-textile reinforcement. Construction and Building Materials, 404, Article 133213. https://doi.org/10.1016/j.conbuildmat.2023.133213

While the recently emerged textile-reinforced concrete (TRC) composites offer a more durable alternative to conventional reinforced concrete, these composites are susceptible to cracking and high deformations under service loads, wh... Read More about Flexural behaviour of concrete thin sheets prestressed with basalt-textile reinforcement.

Bond behaviour of light and heavy carbon fibre TRM to masonry interfaces (2023)
Journal Article
Makashev, K., Triantafyllou, S. P., Thermou, G. E., & Tizani, W. (2023). Bond behaviour of light and heavy carbon fibre TRM to masonry interfaces. Construction and Building Materials, 400, Article 132508. https://doi.org/10.1016/j.conbuildmat.2023.132508

We present the results of an experimental campaign on the bond behaviour between carbon fibre textile reinforced mortars and masonry substrate. The campaign involved 54 single lap direct shear tests on masonry wallettes reinforced with a single TRM l... Read More about Bond behaviour of light and heavy carbon fibre TRM to masonry interfaces.

Fusion of experimental and synthetic data for reliable prediction of steel connection behaviour using machine learning (2023)
Journal Article
Cabrera, M., Ninic, J., & Tizani, W. (2023). Fusion of experimental and synthetic data for reliable prediction of steel connection behaviour using machine learning. Engineering with Computers, https://doi.org/10.1007/s00366-023-01864-1

The development of robust prediction tools based on machine learning (ML) techniques requires the availability of complete, consistent, accurate, and numerous datasets. The application of ML in structural engineering has been limited since, although... Read More about Fusion of experimental and synthetic data for reliable prediction of steel connection behaviour using machine learning.

Post-fire strength of austenitic stainless-steel T-stubs with four bolts per row (2023)
Journal Article
Mahmood, M., Tizani, W., & Salman, W. D. (2023). Post-fire strength of austenitic stainless-steel T-stubs with four bolts per row. Journal of Constructional Steel Research, 207, Article 107966. https://doi.org/10.1016/j.jcsr.2023.107966

For connections made with carbon-steel, the behaviour of the T-stub component is well understood and documented in the Eurocodes and is applied to T-stubs with two or four bolts per row. Researchers have investigated the application of the same Euroc... Read More about Post-fire strength of austenitic stainless-steel T-stubs with four bolts per row.