Mix design of fly ash based alkali activated concrete

Gunasekara, Chamila and Lokuge, Weena ORCID: https://orcid.org/0000-0003-1370-1976 and Law, David W. and Setunge, Sujeeva (2021) Mix design of fly ash based alkali activated concrete. In: Handbook of Advances in Alkali-activated Concrete. Woodhead Publishing Series in Civil and Structural Engineering. Woodhead Publishing Limited, United Kingdom, pp. 41-65. ISBN 9780323854696


Despite the widespread availability of research on fly ash alkali activated concrete and several proposed methodologies to calculate mix proportions, a universally applicable mix design process for the same is still predominantly reliant on the trial and error method. To address this deficit Artificial Neural Network (ANN) and Multivariate Adaptive Regression Spline (MARS) techniques have been utilized to compare the 28-day compressive strength predictions against the actual values. Prepared database was divided into training and testing in order to evaluate model performance. It is evident that MARS model performed more accurately than ANN model, predicting estimated compressive strength similar to the actual compressive strength values obtained through laboratory experiments. Contour plots were developed to represent the correlation between four key parameters and compressive strength. Expected compressive strengths at 28 days varied from 30 to 55 MPa were obtained, using the proposed mix design methodology. Hence, this mix design tool has the ability to deliver a novel approach for the design of fly ash alkali activated concrete mixes in order to obtain the expected compressive strength applicable to the requirement of the construction application.

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Item Type: Book Chapter (Commonwealth Reporting Category B)
Refereed: Yes
Item Status: Live Archive
Faculty/School / Institute/Centre: Historic - Faculty of Health, Engineering and Sciences - School of Civil Engineering and Surveying (1 Jul 2013 - 31 Dec 2021)
Faculty/School / Institute/Centre: Current - Institute for Advanced Engineering and Space Sciences - Centre for Future Materials (1 Jan 2017 -)
Date Deposited: 11 Mar 2022 04:17
Last Modified: 16 Mar 2022 06:19
Uncontrolled Keywords: Fly ash alkali activated concrete; machine learning methods; mix design; compressive strength; sustainability
Fields of Research (2008): 09 Engineering > 0905 Civil Engineering > 090503 Construction Materials
09 Engineering > 0905 Civil Engineering > 090506 Structural Engineering
09 Engineering > 0912 Materials Engineering > 091202 Composite and Hybrid Materials
Fields of Research (2020): 40 ENGINEERING > 4005 Civil engineering > 400510 Structural engineering
40 ENGINEERING > 4016 Materials engineering > 401602 Composite and hybrid materials
40 ENGINEERING > 4005 Civil engineering > 400505 Construction materials
Socio-Economic Objectives (2008): E Expanding Knowledge > 97 Expanding Knowledge > 970109 Expanding Knowledge in Engineering
Socio-Economic Objectives (2020): 28 EXPANDING KNOWLEDGE > 2801 Expanding knowledge > 280110 Expanding knowledge in engineering
12 CONSTRUCTION > 1203 Construction materials performance and processes > 120301 Cement and concrete materials
URI: http://eprints.usq.edu.au/id/eprint/45662

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