Mechanical properties prediction of blast furnace slag and fly ash-based alkali-activated concrete by machine learning methods

SUN, Beibei; DING, Luchuan; Ye, G.; De SCHUTTER, Geert

doi:10.1016/j.conbuildmat.2023.133933

Mechanical properties prediction of blast furnace slag and fly ash-based alkali-activated concrete by machine learning methods

Title

Mechanical properties prediction of blast furnace slag and fly ash-based alkali-activated concrete by machine learning methods

Author

SUN, Beibei (Universiteit Gent)
DING, Luchuan (Tongji University)
Ye, G. (TU Delft Materials and Environment; Universiteit Gent)
De SCHUTTER, Geert (Universiteit Gent)

Date

2023

Abstract

In this paper, 871 data were collected from literature and trained by the 4 representative machine learning methods, in order to build a robust compressive strength predictive model for slag and fly ash based alkali activated concretes. The optimum models of each machine learning method were verified by 4 validation metrics and further compared with an empirical formula and experimental results. Besides, a literature study was carried out to investigate the connection between compressive strength and other mechanical characteristics. As a result, the gradient boosting regression trees model and several predictive formulas were eventually proposed for the prediction of the mechanical behavior including compressive strength, elastic modulus, splitting tensile strength, flexural strength, and Poisson's ratio of BFS/FA-AACs. The importance index of each parameter on the strength of BFS/FA-AACs was elaborated as well.

Subject

Elastic modulus
Machine learning
Poisson's ratio
Prediction
Slag and fly ash-based alkali-activated concrete
Strength

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http://resolver.tudelft.nl/uuid:4cddec3c-bf35-4c45-b0a0-19f7c49c7659

DOI

https://doi.org/10.1016/j.conbuildmat.2023.133933

Embargo date

2024-04-27

ISSN

0950-0618

Source

Construction and Building Materials, 409

Bibliographical note

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Part of collection

Institutional Repository

Document type

journal article

Rights

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