High-performance self-compacting concrete with recycled coarse aggregate: Soft-computing analysis of compressive strength

A Alyaseen, A Poddar, N Kumar, S Tajjour… - Journal of Building …, 2023 - Elsevier
The growth of cities and industrialization has led to an increase in demand for concrete,
resulting in resource depletion and environmental issues. Sustainable alternatives such as …

Use of operational research techniques for concrete mix design: A systematic review

AC Rosa, AWA Hammad, D Boer, A Haddad - Heliyon, 2023 - cell.com
Traditional methods for designing concrete mixtures provide good results; however, they do
not guarantee the optimum composition. Consequently, applying operational research …

Estimation of the compressive strength of green concretes containing rice husk ash: a comparison of different machine learning approaches

A Tavana Amlashi… - European Journal of …, 2023 - Taylor & Francis
To mitigate the environmental issues related to the utilisation of ordinary portland cement
(OPC) in concrete mixtures, attempts have been carried out to find alternative binders such …

Introduction of a novel evolutionary neural network for evaluating the compressive strength of concretes: A case of Rice Husk Ash concrete

P Hamidian, P Alidoust, EM Golafshani… - Journal of Building …, 2022 - Elsevier
The construction industry is facing challenges from the hazardous nature of Ordinary
Portland Cement (OPC) production as one of the main contributors to global warming and …

[HTML][HTML] Hybrid data-driven approaches to predicting the compressive strength of ultra-high-performance concrete using SHAP and PDP analyses

A Kashem, R Karim, SC Malo, P Das, SD Datta… - Case Studies in …, 2024 - Elsevier
Ultra-high-performance concrete (UHPC) is a cutting-edge and advanced construction
material known for its exceptional mechanical properties and durability. Recently, machine …

Optimized prediction modeling of micropollutant removal efficiency in forward osmosis membrane systems using explainable machine learning algorithms

A Aldrees, MF Javed, M Khan, B Siddiq - Journal of Water Process …, 2024 - Elsevier
This study investigated the feasibility of using machine learning (ML)-based models to
simulate the behavior of micropollutants (MPs) in the forward osmosis (FO) membrane water …

Prediction of the shear modulus of municipal solid waste (MSW): An application of machine learning techniques

P Alidoust, M Keramati, P Hamidian, AT Amlashi… - Journal of Cleaner …, 2021 - Elsevier
The dynamic properties of Municipal Solid Waste (MSW) are site-specific and need to be
evaluated separately in different regions. The laboratory-based evaluation of MSW has …

Machine learning techniques for evaluating concrete strength with waste marble powder

N Sharma, MS Thakur, P Sihag, MA Malik, R Kumar… - Materials, 2022 - mdpi.com
The purpose of the research is to predict the compressive and flexural strengths of the
concrete mix by using waste marble powder as a partial replacement of cement and sand …

Hygro–thermo–magnetically induced vibration of nanobeams with simultaneous axial and spinning motions based on nonlocal strain gradient theory

Y Bai, M Suhatril, Y Cao, A Forooghi… - Engineering with …, 2022 - Springer
In this paper, based on the nonlocal strain gradient theory (NSGT), the coupled vibrations of
nanobeams with axial and spinning motions under complex environmental changes are …

Computational prediction of workability and mechanical properties of bentonite plastic concrete using multi-expression programming

M Khan, M Ali, T Najeh, Y Gamil - Scientific Reports, 2024 - nature.com
Bentonite plastic concrete (BPC) demonstrated promising potential for remedial cut-off wall
construction to mitigate dam seepage, as it fulfills essential criteria for strength, stiffness, and …