The impact of variation in chemical and physical properties of PFA and BPD semi-dry cement paste on strength properties

Journal article


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
AuthorsLimbachiya, V, Ganjian, E and Claisse, P
Abstract

The effect of Pulverised Fuel Ash (PFA) and By-Pass-Dust (BPD) in ternary semi-dry cement pastes was reported. As well as this, the variability over 6 months in chemical composition and particle distribution was reviewed to determine impact on strength. The addition of BPD in ternary pastes resulted in a reduced strength when combined with PFA. PFA and BPD samples obtained over a 6 month period showed variability in both chemical composition and particle distribution. For PFA, it was reported that at 14 days the particle size distribution had greatest impact on strength and at 28 days the SiO2 content had greatest impact. The high variability in BPD particle size distribution resulted in finer particles achieving the greatest strength.

Keywords0905 Civil Engineering; 1202 Building; Building & Construction
Year2015
JournalConstruction and Building Materials
Journal citation96, pp. 248-255
PublisherElsevier
ISSN0950-0618
Digital Object Identifier (DOI)https://doi.org/10.1016/j.conbuildmat.2015.08.002
Publication dates
Print15 Oct 2015
Publication process dates
Deposited08 Dec 2017
Accepted15 Oct 2015
Accepted author manuscript
License
Permalink -

https://openresearch.lsbu.ac.uk/item/875x4

  • 98
    total views
  • 85
    total downloads
  • 7
    views this month
  • 0
    downloads this month

Export as

Related outputs

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
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
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
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 (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