Machine learning for durability and service-life assessment of reinforced concrete structures: Recent advances and future directions
WZ Taffese, E Sistonen - Automation in Construction, 2017 - Elsevier
Accurate service-life prediction of structures is vital for taking appropriate measures in a time-
and cost-effective manner. However, the conventional prediction models rely on simplified …
and cost-effective manner. However, the conventional prediction models rely on simplified …
Prediction of compressive strength of partially saturated concrete using machine learning methods
MDE Candelaria, SH Kee, KS Lee - Materials, 2022 - mdpi.com
The aim of this research is to recommend a set of criteria for estimating the compressive
strength of concrete under marine environment with various saturation and salinity …
strength of concrete under marine environment with various saturation and salinity …
Predicting resilient modulus of cementitiously stabilized subgrade soils using neural network, support vector machine, and Gaussian process regression
X Hu, P Solanki - International Journal of Geomechanics, 2021 - ascelibrary.org
Artificial neural network (ANN), support vector machine (SVM), and Gaussian process
regression (GPR) were developed in this study for predicting resilient modulus (Mr) values of …
regression (GPR) were developed in this study for predicting resilient modulus (Mr) values of …
[HTML][HTML] Computational modelling for predicting rheological properties of composite modified asphalt binders
The complicated viscoelastic characteristics of asphalt binders make it a challenging task to
precisely predict their rheological behavior. This study aims to investigate and compare the …
precisely predict their rheological behavior. This study aims to investigate and compare the …
Modelling the unsaturated hydraulic conductivity of a sandy loam soil using Gaussian process regression
NMN Al-Dosary, MA Al-Sulaiman, AM Aboukarima - Water SA, 2019 - journals.co.za
Unsaturated soil hydraulic conductivity is a main parameter in agricultural and
environmental studies, necessary for predicting and managing water and solute transport in …
environmental studies, necessary for predicting and managing water and solute transport in …
Future Prospects and Recent Advancements in Machine Learning for Assessing the Service Life and Durability of Reinforced Concrete Buildings
For necessary action to be taken in a timely and economical way, accurate service-life
forecast of buildings is essential. But the oversimplified assumptions of the traditional …
forecast of buildings is essential. But the oversimplified assumptions of the traditional …
[PDF][PDF] Case Studies in Construction Materials
AM Al-Sabaeei, H Alhussian, SJ Abdulkadir, A Milad… - researchgate.net
The complicated viscoelastic characteristics of asphalt binders make it a challenging task to
precisely predict their rheological behavior. This study aims to investigate and compare the …
precisely predict their rheological behavior. This study aims to investigate and compare the …