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 …
Buckling resistance prediction of high-strength steel columns using metaheuristic-trained artificial neural networks
The buckling behavior of columns, as the most influential members regarding the stability of
structures, has been a long-standing field of interest. Moreover, due to the conservative …
structures, has been a long-standing field of interest. Moreover, due to the conservative …
Advancements and challenges in the application of artificial intelligence in civil engineering: a comprehensive review
SM Harle - Asian Journal of Civil Engineering, 2024 - Springer
Artificial Intelligence (AI) has become a powerful tool in many fields, and its ability to change
the practice of urban architecture is increasingly recognized. This article provides a …
the practice of urban architecture is increasingly recognized. This article provides a …
[HTML][HTML] Synergistic effects of supplementary cementitious materials and compressive strength prediction of concrete using machine learning algorithms with SHAP …
In order to reduce the CO 2 associated with cement production, this study explored the
potential of rice husk ash (RHA) and fly ash (FA) as supplementary cementitios materials for …
potential of rice husk ash (RHA) and fly ash (FA) as supplementary cementitios materials for …
Alkali–silica reaction expansion prediction in concrete using hybrid metaheuristic optimized machine learning algorithms
SK Parhi, SK Panigrahi - Asian Journal of Civil Engineering, 2024 - Springer
Alkali–silica reaction (ASR) expansion prediction in concrete is crucial for assessing the
long-term durability and structural performance of concrete infrastructure. This study …
long-term durability and structural performance of concrete infrastructure. This study …
Evolutionary optimization of machine learning algorithm hyperparameters for strength prediction of high-performance concrete
High-performance concrete (HPC) is designed to be more efficient and shows a higher
value of flowability, strength, and durability in comparison to conventional concrete. The …
value of flowability, strength, and durability in comparison to conventional concrete. The …
Exploring the potential of neural network in assessing mechanical properties of geopolymer concrete incorporating fly ash and phosphogypsum in pavement …
The purpose of this research study is twofold:(1) to investigate the factors that influence the
mechanical properties of Geopolymer Concrete (GPC) made from fly ash (FA) and …
mechanical properties of Geopolymer Concrete (GPC) made from fly ash (FA) and …
Compressive strength prediction of high-strength concrete using hybrid machine learning approaches by incorporating SHAP analysis
Concrete is the most extensively used construction material, and cement is its main
component. Hybrid machine learning models attract researchers in building materials due to …
component. Hybrid machine learning models attract researchers in building materials due to …
Mechanical and durability analysis of geopolymer concrete incorporating bauxite residue, phosphogypsum, and ground granulated blast slag
One cementitious material is geopolymer concrete (GPC), which is produced by activating
industrial by-products with alkaline activators. This study evaluates the mechanical and …
industrial by-products with alkaline activators. This study evaluates the mechanical and …
Prediction of the compressive strength of Flyash and GGBS incorporated geopolymer concrete using artificial neural network
Many numerical computation methods have been devised and put to use in a variety of
science and technology disciplines in the twenty-first century. Artificial neural networks …
science and technology disciplines in the twenty-first century. Artificial neural networks …