Prediction of geopolymer pumpability and setting time for well zonal isolation - Using machine learning and statistical based models-Reference-Cited by-同舟云学术

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Prediction of geopolymer pumpability and setting time for well zonal isolation - Using machine learning and statistical based models

Published:2023-07 Issue:7 Volume:9 Page:e17925
ISSN:2405-8440
Container-title:Heliyon
language:en
Short-container-title:Heliyon

Author:

Hoayek Anis,Khalifeh Mahmoud^ORCID,Hamie Hassan,El-Ghoul Bassam^ORCID,Zgheib Rania

Publisher

Elsevier BV

Subject

Multidisciplinary

Reference32 articles.

1. Geopolymer concrete: a review of some recent developments;Singh;Construct. Build. Mater.,2015

2. Effect of GGBFS on setting, workability and early strength properties of fly ash geopolymer concrete cured in ambient condition;Nath;Construct. Build. Mater.,2014

3. Engineered geopolymer composites: a state-of-the-art review;Zhong;Cement Concr. Compos.,2023

4. Artificial neural network model to predict the compressive strength of eco-friendly geopolymer concrete incorporating silica fume and natural zeolite;Shahmansouri;J. Clean. Prod.,2021

5. Artificial intelligence approaches for prediction of compressive strength of geopolymer concrete;van Dao;Materials,2019

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1. Effect of raw materials on the performance of 3D printing geopolymer: A review;Journal of Building Engineering;2024-05

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