Machine learning in concrete science: applications, challenges, and best practices

Z Li, J Yoon, R Zhang, F Rajabipour… - npj computational …, 2022 - nature.com
Concrete, as the most widely used construction material, is inextricably connected with
human development. Despite conceptual and methodological progress in concrete science …

Research into the properties of concrete modified with natural zeolite addition

D Nagrockiene, G Girskas - Construction and Building Materials, 2016 - Elsevier
Concrete mixture used for the tests consisted of cement CEM I 42.5 R, natural zeolite
(clinoptilolite), 0/4 fr. sand as fine aggregate, and 4/16 fr. gravel as coarse aggregate. Active …

Modelling of the mechanical properties of concrete with cement ratio partially replaced by aluminium waste and sawdust ash using artificial neural network

U Alaneme George, M Mbadike Elvis - SN Applied Sciences, 2019 - Springer
The use of aluminium waste (AW) and sawdust ash (SDA) in concrete was evaluated in this
study where the cement ratio was partially replaced by fractions of AW and SDA introduced …

[HTML][HTML] Prediction of concrete compressive strength due to long term sulfate attack using neural network

AM Diab, HE Elyamany, M Abd Elmoaty… - Alexandria Engineering …, 2014 - Elsevier
This work was divided into two phases. Phase one included the validation of neural network
to predict mortar and concrete properties due to sulfate attack. These properties were …

[PDF][PDF] Characterization of Bambara nut shell ash (BNSA) in concrete production

AG Uwadiegwu, ME Michael - Jurnal Kejuruteraan, 2021 - ukm.my
The goal of achieving concrete with adequate durability properties in terms of reduced
susceptibility to alkali-silica and mechanical-strength behaviour has led to several high …

Experimental investigation of Bambara nut shell ash in the production of concrete and mortar

GU Alaneme, EM Mbadike - Innovative Infrastructure Solutions, 2021 - Springer
The goal of producing concrete that provides long-term durability with regard to
characteristics like strength and reduced susceptibility to alkali–silica has led to the …

Applicability of Artificial Neural Networks to Predict Mechanical and Permeability Properties of Volcanic Scoria‐Based Concrete

AM al-Swaidani, WT Khwies - Advances in civil engineering, 2018 - Wiley Online Library
Numerous volcanic scoria (VS) cones are found in many places worldwide. Many of them
have not yet been investigated, although few of which have been used as a supplementary …

A practical hybrid NNGA system for predicting the compressive strength of concrete containing natural pozzolan using an evolutionary structure

R Rebouh, B Boukhatem, M Ghrici… - … and Building Materials, 2017 - Elsevier
Many researchers are interested in predicting the concrete compressive strength, resulting
in quite a few linear and nonlinear regression equations. Alternatively, other models have …

[HTML][HTML] Analysis of sulfate resistance in concrete based on artificial neural networks and USBR4908-modeling

O Hodhod, GA Salama - Ain shams engineering journal, 2013 - Elsevier
One of the available tests that can be used to evaluate concrete sulfate resistance is
USBR4908. However, there are deficiencies in this test method. This study focuses on the …

[HTML][HTML] Effect of lithium-slag in the performance of slag cement mortar based on least-squares support vector machine prediction

J Lu, Z Yu, Y Zhu, S Huang, Q Luo, S Zhang - Materials, 2019 - mdpi.com
There is a universally accepted view that environmental pollution should be controlled while
improving cement mortar natural abilities. The purpose of this study is to develop a green …