State-of-the-art AI-based computational analysis in civil engineering

C Wang, L Song, Z Yuan, J Fan - Journal of Industrial Information …, 2023 - Elsevier
With the informatization of the building and infrastructure industry, conventional analysis
methods are gradually proving inadequate in meeting the demands of the new era, such as …

Hybrid machine learning model and Shapley additive explanations for compressive strength of sustainable concrete

Y Wu, Y Zhou - Construction and Building Materials, 2022 - Elsevier
The application of the traditional support vector regression (SVR) model to predict the
compressive strength of concrete faces the challenge of parameter tuning. To this end, a …

Artificial intelligence techniques in advanced concrete technology: A comprehensive survey on 10 years research trend

R Kazemi - Engineering Reports, 2023 - Wiley Online Library
Advanced concrete technology is the science of efficient, cost‐effective, and safe design in
civil engineering projects. Engineers and concrete designers are generally faced with the …

Compressive strength prediction of lightweight concrete: Machine learning models

A Kumar, HC Arora, NR Kapoor, MA Mohammed… - Sustainability, 2022 - mdpi.com
Concrete is the most commonly used construction material. The physical properties of
concrete vary with the type of concrete, such as high and ultra-high-strength concrete, fibre …

[HTML][HTML] Interpretable machine learning-based analysis of hydration and carbonation of carbonated reactive magnesia cement mixes

Y Peng, C Unluer - Journal of Cleaner Production, 2024 - Elsevier
This study explored the influence of different input variables on the hydration and
carbonation degree of carbonated reactive magnesia cement (RMC) system by employing …

Buckling and ultimate load prediction models for perforated steel beams using machine learning algorithms

VV Degtyarev, KD Tsavdaridis - Journal of Building Engineering, 2022 - Elsevier
Large web openings introduce complex structural behaviors and additional failure modes of
steel cellular beams, which must be considered in the design using laborious calculations …

[HTML][HTML] ANN-based rapid seismic fragility analysis for multi-span concrete bridges

Z Liu, A Sextos, A Guo, W Zhao - Structures, 2022 - Elsevier
Rapid seismic fragility analysis of regular bridges is necessary for the increasingly utilized
regional seismic risk assessment, which is usually difficult using numerical methods owing …

Physics-supervised ensemble learning model for predicting failure modes of reinforced concrete columns

B Yu, H Cheng, Z Yu, B Li, Q Zhang - Engineering Structures, 2023 - Elsevier
In order to overcome the limitation that traditional prediction models lack of learning ability of
physical laws and with low generalization performance, a novel physics-supervised …

Comprehensive functional resilience assessment methodology for bridge networks using data-driven fragility models

Z Liu, S Li, A Guo, H Li - Soil Dynamics and Earthquake Engineering, 2022 - Elsevier
This paper proposes a probabilistic seismic resilience assessment methodology for bridge
networks subjected to spatially correlated earthquakes. The proposed method integrates the …

Integrated method for intelligent structural design of steel frames based on optimization and machine learning algorithm

W Shan, J Liu, J Zhou - Engineering Structures, 2023 - Elsevier
Optimization methods using metaheuristic algorithms have been widely used in steel frame
design to improve the inefficient traditional design method due to repeated model tuning and …