A novel data-driven machine learning techniques to predict compressive strength of fly ash and recycled coarse aggregates based self-compacting concrete
S Aggarwal, R Singh, A Rathore, K Kapoor… - Materials Today …, 2024 - Elsevier
Compressive strength (CS) of concrete is one of the most important factors in the
construction industry and various time and effort-consuming tasks are required to measure it …
construction industry and various time and effort-consuming tasks are required to measure it …
Innovative machine learning approaches to predict the compressive strength of recycled plastic aggregate self-compacting concrete incorporating different waste …
Rapid urbanization and industrialization have spurred an increase in concrete
manufacturing, contributing to resource depletion and environmental damage. However, this …
manufacturing, contributing to resource depletion and environmental damage. However, this …
[HTML][HTML] Enhancing compressive strength prediction in self-compacting concrete using machine learning and deep learning techniques with incorporation of rice husk …
Focusing on sustainable development, the demand for alternative materials in concrete,
especially for Self-Compacting Concrete (SCC), has risen due to excessive cement usage …
especially for Self-Compacting Concrete (SCC), has risen due to excessive cement usage …
Machine learning approach for investigating compressive strength of self-compacting concrete containing supplementary cementitious materials and recycled …
P Huang, K Dai, X Yu - Journal of Building Engineering, 2023 - Elsevier
Supplementary cementitious materials (SCMs) and recycled coarse aggregate (RCA) have
the potential for sustainable development and resource utilization and have been widely …
the potential for sustainable development and resource utilization and have been widely …
[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 …
[HTML][HTML] Design automation of sustainable self-compacting concrete containing fly ash via data driven performance prediction
T Cui, S Kulasegaram, H Li - Journal of Building Engineering, 2024 - Elsevier
Self-compacting concrete (SCC) is a highly flowable and segregation-resistant material,
effectively facilitating proper filling and ensuring exceptional structural performance in …
effectively facilitating proper filling and ensuring exceptional structural performance in …
Machine Learning Models for the Prediction of the Compressive Strength of Self-Compacting Concrete Incorporating Incinerated Bio-Medical Waste Ash
N Chakravarthy HG, KM Seenappa, SR Naganna… - Sustainability, 2023 - mdpi.com
Self-compacting concrete (SCC) is a special form of high-performance concrete that is highly
efficient in its filling, flowing, and passing abilities. In this study, an attempt has been made to …
efficient in its filling, flowing, and passing abilities. In this study, an attempt has been made to …
Prediction of splitting tensile strength of self-compacting recycled aggregate concrete using novel deep learning methods
The composition of self-compacting concrete (SCC) contains 60–70% coarse and fine
aggregates, which are replaced by construction waste, such as recycled aggregates (RA) …
aggregates, which are replaced by construction waste, such as recycled aggregates (RA) …
Prediction on compressive strength of recycled aggregate self-compacting concrete by machine learning method
S Yang, J Sun, X Zhifeng - Journal of Building Engineering, 2024 - Elsevier
The compressive strength is generally a crucial mechanical indicator for evaluating the
quality of recycled aggregate self-compacting concrete (RASCC). To obtain a reliable …
quality of recycled aggregate self-compacting concrete (RASCC). To obtain a reliable …
[PDF][PDF] Comparative analysis of various machine learning algorithms to predict 28-day compressive strength of Self-compacting concrete
WB Inqiad, MS Siddique, SS Alarifi, MJ Butt, T Najeh… - Heliyon, 2023 - cell.com
Construction industry is indirectly the largest source of CO 2 emissions in the atmosphere,
due to the use of cement in concrete. These emissions can be reduced by using industrial …
due to the use of cement in concrete. These emissions can be reduced by using industrial …