Embodied carbon analysis and benchmarking emissions of high and ultra-high strength concrete using machine learning algorithms
Abstract High strength concrete (HSC)(50–100 MPa) and ultra-high strength concrete
(UHSC)(> 100 MPa) have been increasingly used in the construction industry due to its …
(UHSC)(> 100 MPa) have been increasingly used in the construction industry due to its …
Designing sustainable concrete mixture by developing a new machine learning technique
H Naseri, H Jahanbakhsh, P Hosseini… - Journal of Cleaner …, 2020 - Elsevier
Concrete is the most used materials in the construction industry known as an environmental
pollutant, posing enormous challenges for sustainability regarding resource depletion …
pollutant, posing enormous challenges for sustainability regarding resource depletion …
Machine learning prediction of carbonation depth in recycled aggregate concrete incorporating SCMs
I Nunez, ML Nehdi - Construction and Building Materials, 2021 - Elsevier
While recycled aggregates and supplementary cementitious materials have often been
hailed for enhancing concrete sustainability, their effects on the resistance of concrete to …
hailed for enhancing concrete sustainability, their effects on the resistance of concrete to …
Life cycle assessment of sustainable concrete with recycled aggregate and supplementary cementitious materials
Massive emissions and energy consumption during concrete production, together with the
demand for concrete, continuously threaten sustainable development and human health. To …
demand for concrete, continuously threaten sustainable development and human health. To …
Predicting carbonation depth of concrete using a hybrid ensemble model
Z Huo, L Wang, Y Huang - Journal of Building Engineering, 2023 - Elsevier
This study aims to develop a robust and accurate machine learning-based model to improve
the prediction accuracy of carbonation depth in complex concrete structures. Two hybrid …
the prediction accuracy of carbonation depth in complex concrete structures. Two hybrid …
A comprehensive approach to mitigation of embodied carbon in reinforced concrete buildings
The building sector represents nearly one third of the global greenhouse gas (GHG)
emissions, in which the embodied carbon of reinforced concrete is recognized as a …
emissions, in which the embodied carbon of reinforced concrete is recognized as a …
[HTML][HTML] Machine learning predictions for optimal cement content in sustainable concrete constructions
The designated concrete compressive strength at 28 days plays an important role in
determining the quantity of cement (water to cement ratio) needed in concrete mix designs …
determining the quantity of cement (water to cement ratio) needed in concrete mix designs …
[HTML][HTML] Development of prediction model to predict the compressive strength of eco-friendly concrete using multivariate polynomial regression combined with …
Concrete is the most widely used building material, but it is also a recognized pollutant,
causing significant issues for sustainability in terms of resource depletion, energy use, and …
causing significant issues for sustainability in terms of resource depletion, energy use, and …
A hybrid intelligent system for designing optimal proportions of recycled aggregate concrete
The replacement of natural coarse aggregate (NCA) with recycled coarse aggregate (RCA)
in concrete mixtures offers various advantages, including conservation of natural resources …
in concrete mixtures offers various advantages, including conservation of natural resources …
Reducing embodied carbon in concrete materials: A state-of-the-art review
The construction sector is responsible for about 40% of energy-related emissions worldwide.
Utilizing low-carbon concrete materials (LCCMs) has been recognized as an efficient way to …
Utilizing low-carbon concrete materials (LCCMs) has been recognized as an efficient way to …