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 …
Machine learning in concrete science: applications, challenges, and best practices
Concrete, as the most widely used construction material, is inextricably connected with
human development. Despite conceptual and methodological progress in concrete science …
human development. Despite conceptual and methodological progress in concrete science …
Artificial intelligence algorithms for prediction and sensitivity analysis of mechanical properties of recycled aggregate concrete: A review
Using recycled aggregates generated from demolition waste for concrete production is a
promissory option to reduce the environmental footprint of the built environment. However …
promissory option to reduce the environmental footprint of the built environment. However …
High-performance self-compacting concrete with recycled coarse aggregate: Soft-computing analysis of compressive strength
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 …
resulting in resource depletion and environmental issues. Sustainable alternatives such as …
[HTML][HTML] Assessing the compressive and splitting tensile strength of self-compacting recycled coarse aggregate concrete using machine learning and statistical …
The construction industry is adopting high-performance materials due to technological and
environmental advances. Researchers worldwide are studying the use of recycled coarse …
environmental advances. Researchers worldwide are studying the use of recycled coarse …
Tailoring 3D printed concrete through explainable artificial intelligence
Advances on the construction front continue to rise as the next industrial revolution
(Construction 4.0) nears. One promising front revolves around additively fabricated or simply …
(Construction 4.0) nears. One promising front revolves around additively fabricated or simply …
[HTML][HTML] Assessing water quality of an ecologically critical urban canal incorporating machine learning approaches
This study assessed water quality (WQ) in Tongi Canal, an ecologically critical and
economically important urban canal in Bangladesh. The researchers employed the Root …
economically important urban canal in Bangladesh. The researchers employed the Root …
[HTML][HTML] Utilizing graphene oxide in cementitious composites: A systematic review
Graphene oxide (GO) is a 2D nanoparticle with dimensions less than 100 nm and acts as
nano reinforcement in cementitious composites as a filling, crack-arresting agent, and nuclei …
nano reinforcement in cementitious composites as a filling, crack-arresting agent, and nuclei …
Assessment of convolutional neural network pre-trained models for detection and orientation of cracks
Failure due to cracks is a major structural safety issue for engineering constructions. Human
examination is the most common method for detecting crack failure, although it is subjective …
examination is the most common method for detecting crack failure, although it is subjective …
Data-driven ensemble learning approach for optimal design of cantilever soldier pile retaining walls
Cantilever soldier pile retaining walls are used to ensure the stability of excavations. This
paper deploys ensemble machine learning algorithms towards achieving optimum design of …
paper deploys ensemble machine learning algorithms towards achieving optimum design of …