- Forecasting the compressive strength of GGBFS-based geopolymer concrete via ensemble predictive models. Dans: Construction and Building Materials, v. 405 (novembre 2023). (2023):
- Extreme Learning Machine for Estimation of the Engineering Properties of Self-Compacting Mortar with High-Volume Mineral Admixtures. Dans: Iranian Journal of Science and Technology, Transactions of Civil Engineering, v. 48, n. 1 (décembre 2023). (2023):
- Effect of fiber type, shape and volume fraction on mechanical and flexural properties of concrete. Dans: Journal of Sustainable Construction Materials and Technologies. :
- Effect of Fiber Type, Shape and Volume Fraction on Mechanical and Flexural Properties of Concrete. Dans: Journal of Sustainable Construction Materials and Technologies, v. 7, n. 3 (30 septembre 2022). (2022):
- Estimation of strengths of hybrid FR‐SCC by using deep‐learning and support vector regression models. Dans: Structural Concrete, v. 23, n. 5 (octobre 2022). (2022):
- Deep learning and machine learning‐based prediction of capillary water absorption of hybrid fiber reinforced self‐compacting concrete. Dans: Structural Concrete, v. 23, n. 5 (octobre 2022). (2022):
- Bond strength of reinforcing bars in hybrid fiber-reinforced SCC with binary, ternary and quaternary blends of steel and PVA fibers. Dans: Materials and Structures, v. 54, n. 4 (2 juillet 2021). (2021):
- Self-compacting concrete with blended short and long fibres: experimental investigation on the role of fibre blend proportion. Dans: European Journal of Environmental and Civil Engineering, v. 26, n. 3 (février 2020). (2020):
- Influence of Silica Fume and Class F Fly Ash on Mechanical and Rheological Properties and Freeze-Thaw Durability of Self-Compacting Mortars. Dans: Journal of Cold Regions Engineering, v. 32, n. 3 (septembre 2018). (2018):
- Use of binary and ternary cementitious blends of F-Class fly-ash and limestone powder to mitigate alkali-silica reaction risk. Dans: Construction and Building Materials, v. 151 (octobre 2017). (2017):