Infrastructure damage assessment via machine learning approaches: a systematic review
Monitoring civil infrastructures to detect early damage and extract the data required for urban
management can prevent sudden infrastructure collapse, increase infrastructure …
management can prevent sudden infrastructure collapse, increase infrastructure …
Development of autogenous shrinkage prediction model of alkali-activated slag-fly ash geopolymer based on machine learning
J Shen, Y Li, H Lin, Y Li - Journal of Building Engineering, 2023 - Elsevier
This paper developed an autogenous shrinkage prediction tool with high accuracy through
machine learning for alkali-activated slag-fly ash geopolymer. The influencing factors of …
machine learning for alkali-activated slag-fly ash geopolymer. The influencing factors of …
Prediction and uncertainty quantification of ultimate bond strength between UHPC and reinforcing steel bar using a hybrid machine learning approach
The composite action of the reinforcing bars in the UHPC involves complex and nonlinear
mechanisms. Inadequate knowledge of their interaction may lead to insufficient bond …
mechanisms. Inadequate knowledge of their interaction may lead to insufficient bond …
Prediction of high-temperature creep in concrete using supervised machine learning algorithms
In this paper, supervised machine learning techniques were employed to develop a
prediction model for concrete creep at elevated temperatures. Several algorithms were …
prediction model for concrete creep at elevated temperatures. Several algorithms were …
A transfer learning-based approach to fatigue life prediction of corroded bimetallic steel bars using small samples
L **ao, X Xue, N Wang, Q Ren, J Hua… - Construction and Building …, 2023 - Elsevier
The low-cycle fatigue life of reinforced steel bars is usually determined by time-consuming
tests. To investigate the fatigue behaviour of corroded steel bars, corrosion tests need to be …
tests. To investigate the fatigue behaviour of corroded steel bars, corrosion tests need to be …
Prediction of long-term prestress loss for prestressed concrete cylinder structures using machine learning
H Zhang, QQ Guo, LY Xu - Engineering Structures, 2023 - Elsevier
The long-term prestress loss caused by shrinkage and creep of concrete and stress
relaxation of prestressed tendons has significant effects on the sealability and safety of …
relaxation of prestressed tendons has significant effects on the sealability and safety of …
Hygro-thermal–mechanical coupling analysis for early shrinkage of cast in situ concrete slabs of composite beams: Theory and experiment
The steel girder of the steel–concrete composite bridge restricts the deformation induced by
variations in the temperature and relative humidity of the concrete. Thus, concrete …
variations in the temperature and relative humidity of the concrete. Thus, concrete …
[HTML][HTML] Using artificial intelligence methods to predict the compressive strength of concrete containing sugarcane bagasse ash
Sugarcane bagasse ash is an agricultural and industrial waste material produced in millions
of tonnes annually. While traditionally used as a fertilizer or buried underground …
of tonnes annually. While traditionally used as a fertilizer or buried underground …
Early shrinkage experiment of concrete and the development law of its temperature and humidity field in natural environment
Concrete shrinkage is one of the main causes of structural deterioration, and clear
understanding of the development law of temperature and humidity field is a key to …
understanding of the development law of temperature and humidity field is a key to …
Identification of mechanical properties of thin-film elastoplastic materials by machine learning
Nanoindentation can effectively evaluate the mechanical properties of materials in the form
of bulk and coating. However, the relationship between the indentation response and the …
of bulk and coating. However, the relationship between the indentation response and the …