Prediction of concrete and FRC properties at high temperature using machine and deep learning: a review of recent advances and future perspectives

NF Alkayem, L Shen, A Mayya, PG Asteris, R Fu… - Journal of Building …, 2024 - Elsevier
Concrete structures when exposed to elevated temperature significantly decline their
original properties. High temperatures substantially affect the concrete physical and …

Performance of geopolymer concrete at elevated temperature− A critical review

T Manzoor, JA Bhat, AH Shah - Construction and Building Materials, 2024 - Elsevier
Concrete, renowned for its strength and durability, stands as the primary material in
infrastructure construction. Despite its extensive use over millennia, its response to fire …

Investigation of machine learning models in predicting compressive strength for ultra-high-performance geopolymer concrete: A comparative study

M Abdellatief, YM Hassan, MT Elnabwy… - … and Building Materials, 2024 - Elsevier
Ultra-high-performance geopolymer concrete (UHPGC) is a new category of traditional
UHPC developed to meet the desire for ultra-high-strength and green building materials. In …

Artificial-intelligence-led revolution of construction materials: From molecules to Industry 4.0

XQ Wang, P Chen, CL Chow, D Lau - Matter, 2023 - cell.com
Industry 4.0 promotes the transformation of manufacturing industry to intelligence, which
demands advances in materials, devices, and systems of the construction industry …

[HTML][HTML] Eco-friendly mix design of slag-ash-based geopolymer concrete using explainable deep learning

RSS Ranasinghe, W Kulasooriya, US Perera… - Results in …, 2024 - Elsevier
Geopolymer concrete is a sustainable and eco-friendly substitute for traditional OPC
(Ordinary Portland Cement) based concrete, as it reduces greenhouse gas emissions. With …

Comparative analysis of various machine learning algorithms to predict strength properties of sustainable green concrete containing waste foundry sand

MF Javed, M Khan, M Fawad, H Alabduljabbar… - Scientific Reports, 2024 - nature.com
The use of waste foundry sand (WFS) in concrete production has gained attention as an eco-
friendly approach to waste reduction and enhancing cementitious materials. However …

Efficient machine learning algorithm with enhanced cat swarm optimization for prediction of compressive strength of GGBS-based geopolymer concrete at elevated …

PK Dash, SK Parhi, SK Patro, R Panigrahi - Construction and Building …, 2023 - Elsevier
In order to assess building damage and develop fire safety applications, it is crucial to
examine the mechanical behavior of concrete after exposure to high temperatures …

[HTML][HTML] A hybrid strategy of AutoML and SHAP for automated and explainable concrete strength prediction

B Sun, W Cui, G Liu, B Zhou, W Zhao - Case Studies in Construction …, 2023 - Elsevier
The precise prediction of concrete compressive strength is essential for ensuring safe and
reliable infrastructure design and construction. However, traditional empirical models often …

A comparative study of environmental and economic assessment of vegetation-based slope stabilization with conventional methods

F Yazdani, P AliPanahi, H Sadeghi - Journal of Environmental …, 2024 - Elsevier
The heavy rainfall induced by global warming has increased the risk of landslides. Eco-
friendly approaches, such as employing vegetation, prove effective in satisfying the …

Proposition of geopolymers obtained through the acid activation of iron ore tailings with phosphoric acid

AR de Carvalho, BR da Silva Calderón-Morales… - … and Building Materials, 2023 - Elsevier
This study aims to develop a geopolymer using iron ore tailings (IOT) as a geopolymer
precursor and phosphoric acid (H 3 PO 4) as an activating agent. IOT was characterized …