Prediction of concrete and FRC properties at high temperature using machine and deep learning: a review of recent advances and future perspectives
Concrete structures when exposed to elevated temperature significantly decline their
original properties. High temperatures substantially affect the concrete physical and …
original properties. High temperatures substantially affect the concrete physical and …
[HTML][HTML] Intelligent predicting and monitoring of ultra-high-performance fiber reinforced concrete composites− A review
Ultra-high-performance fiber reinforced concrete (UHPFRC) is an advanced composite
known for its exceptional mechanical properties and durability, playing a vital role in modern …
known for its exceptional mechanical properties and durability, playing a vital role in modern …
[HTML][HTML] Machine learning-driven predictive models for compressive strength of steel fiber reinforced concrete subjected to high temperatures
Steel-fiber-reinforced concrete (SFRC) has emerged as a viable and efficient substitute for
traditional concrete in the construction industry. By incorporating steel fibers into the …
traditional concrete in the construction industry. By incorporating steel fibers into the …
[HTML][HTML] Metaheuristic optimization algorithms-based prediction modeling for titanium dioxide-Assisted photocatalytic degradation of air contaminants
Airborne contaminants pose significant environmental and health challenges. Titanium
dioxide (TiO 2) has emerged as a leading photocatalyst in the degradation of air …
dioxide (TiO 2) has emerged as a leading photocatalyst in the degradation of air …
[HTML][HTML] Forecasting the strength characteristics of concrete incorporating waste foundry sand using advance machine algorithms including deep learning
The incorporation of waste foundry sand (WFS) into concrete has been recognized as a
sustainable approach to improve the strength properties of waste foundry sand concrete …
sustainable approach to improve the strength properties of waste foundry sand concrete …
[HTML][HTML] Hybrid machine learning approach to prediction of the compressive and flexural strengths of UHPC and parametric analysis with shapley additive …
Ultra-high-performance concrete (UHPC) is a sustainable construction material; it can be
applied as a substitute for cement concrete. Artificial intelligence methods have been used …
applied as a substitute for cement concrete. Artificial intelligence methods have been used …
Towards sustainable construction: Machine learning based predictive models for strength and durability characteristics of blended cement concrete
Supplementary cementitious materials (SCMs) are widely utilized in concrete mixtures,
either substituting a part of the cement content or replacing a portion of clinker in cement …
either substituting a part of the cement content or replacing a portion of clinker in cement …
[HTML][HTML] Application of metaheuristic optimization algorithms in predicting the compressive strength of 3D-printed fiber-reinforced concrete
In recent years, the construction industry has been striving to make production faster and
handle more complex architectural designs. Waste reduction, geometric freedom, lower …
handle more complex architectural designs. Waste reduction, geometric freedom, lower …
Development of machine learning models for forecasting the strength of resilient modulus of subgrade soil: genetic and artificial neural network approaches
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 …
linear stress–strain behaviors, is crucial for effective soil assessment. Traditional laboratory …
AI-driven design for the compressive strength of ultra-high performance geopolymer concrete (UHPGC): From explainable ensemble models to the graphical user …
Ultra-high performance geopolymer concrete (UHPGC) has become of interest in recent
years as a more economical and sustainable alternative while offering similar mechanical …
years as a more economical and sustainable alternative while offering similar mechanical …