Evaluating bonding strength in UHPC-NC composite: A comprehensive review of direct and indirect characterization methods
L Zhao, Q Luo - Construction and Building Materials, 2024 - Elsevier
The bonding behavior between ultra-high performance concrete (UHPC) and normal
concrete (NC) is crucial for enhancing the durability and performance of reparation and …
concrete (NC) is crucial for enhancing the durability and performance of reparation and …
Machine learning prediction of concrete compressive strength using rebound hammer test
Abstract Machine learning has become a key branch in artificial intelligence by providing
unique predictive modeling solutions. Predicting the compressive strength of concrete …
unique predictive modeling solutions. Predicting the compressive strength of concrete …
Pore structure and splitting tensile strength of hybrid Basalt–Polypropylene fiber reinforced concrete subjected to carbonation
Y Li, Y Su, KH Tan, X Zheng, J Sheng - Construction and Building Materials, 2021 - Elsevier
To investigate effect of carbonization on pore structure and splitting tensile strength, splitting
tensile tests were subjected to normal concrete and basalt-polypropylene fiber hybrid …
tensile tests were subjected to normal concrete and basalt-polypropylene fiber hybrid …
Evaluation of water quality indexes with novel machine learning and SHapley Additive ExPlanation (SHAP) approaches
Water quality indexes (WQI) are pivotal in assessing aquatic systems. Conventional
modeling approaches rely on extensive datasets with numerous unspecified inputs, leading …
modeling approaches rely on extensive datasets with numerous unspecified inputs, leading …
A machine learning framework for intelligent development of Ultra-High performance concrete (UHPC): From dataset cleaning to performance predicting
L Xu, D Fan, K Liu, W Xu, R Yu - Expert Systems with Applications, 2024 - Elsevier
This study proposes a new machine learning (ML) framework, which mainly includes dataset
cleaning processing as well as performance predicting, for property prediction of ultra-high …
cleaning processing as well as performance predicting, for property prediction of ultra-high …
Freeze-thaw durability estimation for concrete through the Gaussian process regression with kernel convolution
BH Woo, JS Ryou, JY Kim, B Lee, HG Kim… - Construction and Building …, 2023 - Elsevier
This study aimed to improve the performance of Gaussian process regression (GPR)
estimation through kernel convolution for relative dynamic modulus (RDM) of the freeze …
estimation through kernel convolution for relative dynamic modulus (RDM) of the freeze …
The relative roles of different land-use types in bike-sharing demand: A machine learning-based multiple interpolation fusion method
C Sun, J Lu - Information Fusion, 2023 - Elsevier
Land use plays a crucial role in promoting the bike-sharing demand. Traditionally, studies
on bike-sharing demand (BSD) are mainly focused on its prediction through regression …
on bike-sharing demand (BSD) are mainly focused on its prediction through regression …
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 …
Multi-performance optimization of low-carbon geopolymer considering mechanical, cost, and CO2 emission based on experiment and interpretable learning
S Wang, K Chen, J Liu, P Xia, L Xu, B Chen… - … and Building Materials, 2024 - Elsevier
This study proposed a procedure to optimize the mixture proportion of geopolymer using
machine learning (ML) and multi-objective optimization (MOO) model, which enhances the …
machine learning (ML) and multi-objective optimization (MOO) model, which enhances the …
Influence of sustained compressive load on the carbonation of concrete containing blast furnace slag
Z Liu, P Van den Heede, C Zhang, X Shi… - … and Building Materials, 2022 - Elsevier
Carbonation of concrete, in which 0%, 50% and 70% of cement was replaced by blast
furnace slag (BFS), under different levels of sustained compressive load (0, 0.25, 0.5 and …
furnace slag (BFS), under different levels of sustained compressive load (0, 0.25, 0.5 and …