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HomeAcademic staffDr Vireen Limbachiya
Dr Vireen Limbachiya

Dr Vireen Limbachiya

limbachv@lsbu.ac.uk

Civil and Building Services Engineering

https://orcid.org/0000-0003-0835-8464

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I am the Head of Civil and Building Services Engineering and an Associate Professor in Civil Engineering in the School of Built Environment and Architecture. I am passionate about improving the sustainability of the materials used in the construction industry and the application of AI in Civil Engineering.

I started working for LSBU in 2016 and previously to that I completed my undergraduate degree in Civil Engineering, my MSc in Low Carbon Building Design and Modelling at Loughborough University and then went onto complete my PhD at Coventry University, where the research focused on improving the sustainability of concrete.

My research interests started with improving the sustainability of the concrete that we use in construction. This was done by using cementitious by-products and demolition waste to replace cement and aggregates, respectively. In the past couple of years, my interest has focused on how artificial intelligence can be used in understanding and predicting specific mechanical properties of the materials that we use.

Postgraduate Research Supervision
Current
Mr Robert KovacsDoctoral Research ProjectPhD
Mr Ka-Lok KanDoctoral Research ProjectPhD
FunderYear wonProjectRole
The Institution of Structural Engineers2022Improving the Durability and Sustainability of Reinforced Concrete using Carbonated aggregates and BFRP reinforcementCo-Investigator
RDG Engineering2022Test scaffold couplersPrincipal Investigator

Machine learning for optimal design of circular hollow section stainless steel stub columns: A comparative analysis with Eurocode 3 predictions
Abarkan, I, Rabi, M., Ferreira, F., Shamass, R., Limbachiya, V., Jweihan, Y. and Pinho Santos, L. (2024). Machine learning for optimal design of circular hollow section stainless steel stub columns: A comparative analysis with Eurocode 3 predictions. Engineering Applications of Artificial Intelligence. 132 (107952). https://doi.org/10.1016/j.engappai.2024.107952

Machine learning-driven web-post buckling resistance prediction for high-strength steel beams with elliptically-based web openings
Rabi, M, Jweihan, Y, Abarkan, I, Ferreira, F, Shamass, R, Limbachiya, V., Tsavaridis, K and Pinho Santos, L. (2024). Machine learning-driven web-post buckling resistance prediction for high-strength steel beams with elliptically-based web openings. Results in Engineering. 21, p. 101749. https://doi.org/10.1016/j.rineng.2024.101749

Web-post buckling resistance calculation of perforated high-strength steel beams with elliptically-based web openings for EC3
Ferreira, F., Shamass, R., Santos, L., Tsavdaridis, K. and Limbachiya, V. (2023). Web-post buckling resistance calculation of perforated high-strength steel beams with elliptically-based web openings for EC3. Structures. https://doi.org/10.1016/j.istruc.2023.05.139

Mechanical and GWP Assessment of Concrete Using Blast Furnace Slag, Silica Fume and Recycled Aggregate
Shamass, R., Rispoli, O., Limbachiya, V. and Kovacs, R. (2023). Mechanical and GWP Assessment of Concrete Using Blast Furnace Slag, Silica Fume and Recycled Aggregate. Case Studies in Construction Materials. 18. https://doi.org/10.1016/j.cscm.2023.e02164

Prediction of the cross-sectional capacity of cold-formed CHS using numerical modelling and machine learning
Musab,R., Ferreira, F., Abarkan, A., Limbachiya, V. and Shamass, R. (2023). Prediction of the cross-sectional capacity of cold-formed CHS using numerical modelling and machine learning. Results in Engineering. 17 (100902). https://doi.org/10.1016/j.rineng.2023.100902

A Numerical Study of Shape Memory Alloy (SMA) Reinforced Beam Subjected to Seismic Loading
Bloy, J., Shamass, R., Limbachiya, V. and El-Desoqi, M. (2022). A Numerical Study of Shape Memory Alloy (SMA) Reinforced Beam Subjected to Seismic Loading. 4th Conference on Sustainability in Civil Engineering (CSCE’22) . Department of Civil Engineering Capital University of Science and Technology, Islamabad Pakistan 31 - 31 Aug 2022

Mechanical Properties of Bamboo Core Sandwich Panels
Limbachiya, V., Shamass, R. and Perera, J (2022). Mechanical Properties of Bamboo Core Sandwich Panels. 4th Conference on Sustainability in Civil Engineering. Pakistan 31 - 31 Aug 2022

Web-Post Buckling Prediction Resistance of Steel Beams with Elliptically-Based Web Openings using Artificial Neural Networks (ANN)
Shamass, R., Ferreira, F., Limbachiya, V., Pinho Santos, L. and Tsavdaridis, K.D. (2022). Web-Post Buckling Prediction Resistance of Steel Beams with Elliptically-Based Web Openings using Artificial Neural Networks (ANN). Thin-Walled Structures. 180 (109959). https://doi.org/10.1016/j.tws.2022.109959

EC3 design of web-post buckling resistance for perforated steel beams with elliptically-based web openings
Ferreira, F., Shamass, R., Pinho Santos, L., Limbachiya, V. and Tsavdaridis, K. (2022). EC3 design of web-post buckling resistance for perforated steel beams with elliptically-based web openings. Thin-Walled Structures. 175, p. 109196. https://doi.org/10.1016/j.tws.2022.109196

Lateral–torsional buckling resistance prediction model for steel cellular beams generated by Artificial Neural Networks (ANN)
Ferreira, F., Shamass, R., Limbachiya, V., Tsavdarisdis, K. and Martins, C. (2021). Lateral–torsional buckling resistance prediction model for steel cellular beams generated by Artificial Neural Networks (ANN). Thin-Walled Structures. 170, p. 108592. https://doi.org/10.1016/j.tws.2021.108592

Predicting the Impact of Chemical and Physical Variability in Binary and Ternary Cementitious Blends
Limbachiya, V. and Shamass, R. (2021). Predicting the Impact of Chemical and Physical Variability in Binary and Ternary Cementitious Blends. 3rd Conference on Sustainability in Civil Engineering (CSCE’21). Capital University of Science & Technology, . Islamabad Expressway, Kahuta Road, Zone-V Islamabad 11 - 11 Aug 2021 Department of Civil Engineering at Capital University of Science and Technology.

Impact of chopped basalt fibres on the mechanical proper- ties of concrete
Shamass, R. and Limbachiya, V. (2021). Impact of chopped basalt fibres on the mechanical proper- ties of concrete. 3rd Conference on Sustainability in Civil Engineering (CSCE’21). Capital University of Science & Technology, . Islamabad Expressway, Kahuta Road, Zone-V Islamabad 11 - 11 Aug 2021 Department of Civil Engineering at Capital University of Science and Technology.

Application of Artificial Neural Networks for web-post shear resistance of cellular steel beams
Limbachiya, V. and Shamass, R. (2021). Application of Artificial Neural Networks for web-post shear resistance of cellular steel beams. Thin-Walled Structures. 161, pp. 107414-107414. https://doi.org/10.1016/j.tws.2020.107414

Experimental Investigation on the Behaviour of Recycled Aggregate Concrete
Kovacs, R, Shamass, R, Limbachiya, V and Datoo, M (2019). Experimental Investigation on the Behaviour of Recycled Aggregate Concrete. 5th International Conference on Sustainable Construction Materials & Technologies. Surrey 14 - 17 Jul 2019

Strength, durability and leaching properties of concrete paving blocks incorporating GGBS and SF
Limbachiya, V (2016). Strength, durability and leaching properties of concrete paving blocks incorporating GGBS and SF. Construction and Building Materials. 113, pp. 273-279. https://doi.org/10.1016/j.conbuildmat.2016.02.152

The impact of variation in chemical and physical properties of PFA and BPD semi-dry cement paste on strength properties
Limbachiya, V, Ganjian, E and Claisse, P (2015). The impact of variation in chemical and physical properties of PFA and BPD semi-dry cement paste on strength properties. Construction and Building Materials. 96, pp. 248-255. https://doi.org/10.1016/j.conbuildmat.2015.08.002

The impact of variation in chemical and physical properties of PFA and BPD semi dry cement paste on strength properties
Limbachiya, V (2015). The impact of variation in chemical and physical properties of PFA and BPD semi dry cement paste on strength properties. Construction and Building Materials. 96, pp. 248-255. https://doi.org/10.1016/j.conbuildmat.2015.08.002