[HTML][HTML] Analysis of models to predict mechanical properties of high-performance and ultra-high-performance concrete using machine learning

M Hematibahar, M Kharun, AN Beskopylny… - Journal of Composites …, 2024 - mdpi.com
High-Performance Concrete (HPC) and Ultra-High-Performance Concrete (UHPC) have
many applications in civil engineering industries. These two types of concrete have as many …

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 …

Soft computing models for prediction of bentonite plastic concrete strength

WB Inqiad, MF Javed, K Onyelowe, MS Siddique… - Scientific Reports, 2024 - nature.com
Bentonite plastic concrete (BPC) is extensively used in the construction of water-tight
structures like cut-off walls in dams, etc., because it offers high plasticity, improved …

Performance evaluation of indented macro synthetic polypropylene fibers in high strength self-compacting concrete (SCC)

C Yaqin, SU Haq, S Iqbal, I Khan, S Room, SA Khan - Scientific Reports, 2024 - nature.com
Concrete is used worldwide as a construction material in many projects. It exhibits a brittle
nature, and fibers' addition to it improves its mechanical properties. Polypropylene (PP) …

High-strength self-compacting concrete production incorporating supplementary cementitious materials: Experimental evaluations and machine learning modelling

MHR Sobuz, FS Aditto, SD Datta, MKI Kabbo… - International Journal of …, 2024 - Springer
This study investigates mechanical properties, durability performance, non-destructive
testing (NDT) characteristics, environmental impact evaluation, and advanced machine …

Multi-performance optimization of low-carbon geopolymer considering mechanical, cost, and CO2 emission based on experiment and interpretable learning

S Wang, K Chen, J Liu, P Xia, L Xu, B Chen… - … and Building Materials, 2024 - Elsevier
This study proposed a procedure to optimize the mixture proportion of geopolymer using
machine learning (ML) and multi-objective optimization (MOO) model, which enhances the …

[HTML][HTML] Deploying UAV-based detection of bridge structural deterioration with pilgrimage walk optimization-lite for computer vision

JS Chou, CY Liu, PJ Guo - Case Studies in Construction Materials, 2024 - Elsevier
Bridges are crucial components of national infrastructure, requiring rigorous maintenance
and inspections to ensure their safety and functionality. Inspections are incredibly …

[HTML][HTML] Predicting residual strength of hybrid fibre-reinforced Self-compacting concrete (HFR-SCC) exposed to elevated temperatures using machine learning

MS Khan, L Ma, WB Inqiad, M Khan, NM Khan… - Case Studies in …, 2025 - Elsevier
Hybrid fibre-reinforced Self-compacting concrete (HFR-SCC) offers significant advantages
over conventional concrete like increased ductility, crack resistance, and eliminating the …

[HTML][HTML] NSGA-II based short-term building energy management using optimal LSTM-MLP forecasts

M Cordeiro-Costas, H Labandeira-Pérez… - International Journal of …, 2024 - Elsevier
To conduct analysis on the field of electricity management in buildings is crucial to contribute
to the clean energy promotion, energy efficiency, and resilience against climate change …

[HTML][HTML] Utilization of Industrial, Agricultural, and Construction Waste in Cementitious Composites: A Comprehensive Review of their Impact on Concrete Properties …

F Alsharari - Materials Today Sustainability, 2025 - Elsevier
The escalating global demand for concrete, coupled with the environmental impact of
cement production, necessitates the exploration of sustainable alternatives. This paper aims …