Probabilistic estimation of flexural loading capacity of existing RC structures based on observational corrosion-induced crack width distribution using machine learning

M Zhang, M Akiyama, M Shintani, J Xin, DM Frangopol - Structural Safety, 2021 - Elsevier
Corrosion-induced crack width can provide effective information on the deterioration level of
in situ corroded reinforced concrete (RC) structures. However, the uncertainty associated …

Ensemble machine learning model for corrosion initiation time estimation of embedded steel reinforced self-compacting concrete

BA Salami, SM Rahman, TA Oyehan, M Maslehuddin… - Measurement, 2020 - Elsevier
Corrosion initiation time of embedded steel is an important service life parameter, which
depends on concrete material make-up, exposure environment, and duration of exposure …

Machine learning-based multiscale framework for mechanical behavior of nano-crystalline structures

AR Khoei, MR Seddighian, AR Sameti - International Journal of …, 2024 - Elsevier
In this paper, a computational atomistic-continuum multiscale framework is developed based
on the machine learning (ML) architecture to capture the nonlinear behavior of nano …

A machine learning-based atomistic-continuum multiscale technique for modeling the mechanical behavior of Ni3Al

AR Khoei, M Kianezhad - International Journal of Mechanical Sciences, 2023 - Elsevier
In this paper, a machine learning-based atomistic-continuum multiscale method is
developed to model the mechanical behavior of Ni-based superalloys. The kinematic and …

Triaxial mechanical properties and microstructure visualization of BFRC

F Chen, B Xu, H Jiao, X Chen, Y Shi, J Wang… - Construction and Building …, 2021 - Elsevier
The addition of basalt fiber can effectively improve the macroscopic performance of
concrete. At present, there are few studies on the micro-action mechanism of basalt fiber. In …

Structure genome based machine learning method for woven lattice structures

C Zhang, B Wang, H Zhu, H Fan - International Journal of Mechanical …, 2023 - Elsevier
As a type of lightweight composite material, three-dimensional (3D) woven lattice structure
(WLS) has been extensively applied in various fields. It is extremely significant to investigate …

Phase field to fracture analysis on engineered cementitious composites under complex stress states

Y Yu, B Dong, A Liu, J Fu, W Gao - International Journal of Mechanical …, 2024 - Elsevier
By developing multiple fine cracks before fracture failure, engineered cementitious
composites (ECC) exhibit “metal-like” tensile behaviour, overcoming the inherent brittleness …

[HTML][HTML] Electro-chemo-physical analysis for long-term reinforcement corrosion within the reactive system of concrete

B Dong, Y Yu, W Gao, C Gunasekara, G Zhao… - Cement and Concrete …, 2025 - Elsevier
This paper presents an electro-chemo-physical model for analyzing long-term chloride-
induced reinforcement corrosion in concrete structures. The integration of electrochemical …

Stacking ensemble tree models to predict energy performance in residential buildings

AS Mohammed, PG Asteris, M Koopialipoor… - Sustainability, 2021 - mdpi.com
In this research, a new machine-learning approach was proposed to evaluate the effects of
eight input parameters (surface area, relative compactness, wall area, overall height, roof …

Machine learning–assisted drift capacity prediction models for reinforced concrete columns with shape memory alloy bars

CS Lee, S Mangalathu, JS Jeon - Computer‐Aided Civil and …, 2024 - Wiley Online Library
Despite notable progress made in predicting the drift capacity of reinforced columns with
steel bars, these techniques and methods are proven inapplicable for accurately predicting …