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 …

Fresh and mechanical performances of recycled plastic aggregate geopolymer concrete modified with Nano-silica: Experimental and computational investigation

HU Ahmed, AS Mohammed, AA Mohammed - Construction and Building …, 2023 - Elsevier
Concerning environmental concerns, it has become crucial to invent and develop alternative
construction materials that can replace ordinary Portland cement and use waste materials …

Machine-learning methods for estimating compressive strength of high-performance alkali-activated concrete

T Shafighfard, F Kazemi, N Asgarkhani… - Engineering Applications of …, 2024 - Elsevier
High-performance alkali-activated concrete (HP-AAC) is acknowledged as a cementless
and environmentally friendly material. It has recently received a substantial amount of …

[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 …

A systematic literature review of AI-based prediction methods for self-compacting, geopolymer, and other eco-friendly concrete types: Advancing sustainable concrete

T Ali, MH El Ouni, MZ Qureshi, ABMS Islam… - … and Building Materials, 2024 - Elsevier
The construction industry's growing emphasis on sustainability has driven the development
of eco-friendly concrete alternatives, such as self-compacting concrete (SCC) and …

Production, characterization and performance of green geopolymer modified with industrial by-products

R Abbas, MA Abdelzaher, N Shehata, MA Tantawy - Scientific Reports, 2024 - nature.com
Industrial by-products; have received a lot of attention as a possible precursor for cement
and/or concrete production for a more environmentally and economically sound use of raw …

Artificial intelligence-based prediction of strengths of slag-ash-based geopolymer concrete using deep neural networks

S Oyebisi, T Alomayri - Construction and Building Materials, 2023 - Elsevier
The construction and building industry, one of the greatest emitters of greenhouse gases, is
under tremendous pressure because of the growing concern about global climate change …

A soft-computing-based modeling approach for predicting acid resistance of waste-derived cementitious composites

Q Cao, X Yuan, MN Amin, W Ahmad, F Althoey… - … and Building Materials, 2023 - Elsevier
This research aimed to build estimation models for the compressive strength (CS) of cement
mortar containing eggshell and glass powder after the acid attack using machine learning …

Modelling soil compaction parameters using an enhanced hybrid intelligence paradigm of ANFIS and improved grey wolf optimiser

A Bardhan, RK Singh, S Ghani, G Konstantakatos… - Mathematics, 2023 - mdpi.com
The criteria for measuring soil compaction parameters, such as optimum moisture content
and maximum dry density, play an important role in construction projects. On construction …

Development of machine learning models for forecasting the strength of resilient modulus of subgrade soil: genetic and artificial neural network approaches

L Khawaja, U Asif, K Onyelowe, AF Al Asmari… - Scientific Reports, 2024 - nature.com
Accurately predicting the Modulus of Resilience (MR) of subgrade soils, which exhibit non-
linear stress–strain behaviors, is crucial for effective soil assessment. Traditional laboratory …