Prediction of concrete and FRC properties at high temperature using machine and deep learning: a review of recent advances and future perspectives
Concrete structures when exposed to elevated temperature significantly decline their
original properties. High temperatures substantially affect the concrete physical and …
original properties. High temperatures substantially affect the concrete physical and …
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 …
methods are gradually proving inadequate in meeting the demands of the new era, such as …
Tailoring 3D printed concrete through explainable artificial intelligence
Advances on the construction front continue to rise as the next industrial revolution
(Construction 4.0) nears. One promising front revolves around additively fabricated or simply …
(Construction 4.0) nears. One promising front revolves around additively fabricated or simply …
Data-driven prediction and optimization of axial compressive strength for FRP-reinforced CFST columns using synthetic data augmentation
Fiber-reinforced polymer (FRP) sheets can be used as additional confinement to improve
the load-bearing capacity and durability of concrete-filled steel tubular (CFST) columns. This …
the load-bearing capacity and durability of concrete-filled steel tubular (CFST) columns. This …
Potential role and challenges of ChatGPT and similar generative artificial intelligence in architectural engineering
N Rane - Available at SSRN 4607767, 2023 - papers.ssrn.com
The incorporation of generative artificial intelligence (AI) systems, such as ChatGPT, holds
great potential in reshaping diverse facets of architectural engineering. This research …
great potential in reshaping diverse facets of architectural engineering. This research …
Multi-objective seismic design optimization of structures: a review
Optimal seismic design of structures is a branch of structural optimization being developed
by many researchers. Many optimization problems and solution methods have been …
by many researchers. Many optimization problems and solution methods have been …
[HTML][HTML] Machine learning for all! Benchmarking automated, explainable, and coding-free platforms on civil and environmental engineering problems
MZ Naser - Journal of Infrastructure Intelligence and Resilience, 2023 - Elsevier
One of the key challenges in fully embracing machine learning (ML) in civil and
environmental engineering revolves around the need for coding (or programming) …
environmental engineering revolves around the need for coding (or programming) …
Data-driven moment-carrying capacity prediction of hybrid beams consisting of UHPC-NSC using machine learning-based models
This paper presents, for the first time in the literature, a study on the development of data-
driven machine learning (ML) models to predict the moment-carrying capacity of ultra-high …
driven machine learning (ML) models to predict the moment-carrying capacity of ultra-high …
ANN model for predicting the elastic critical buckling coefficients of prismatic tapered steel web plates under stress gradients
Tapered steel plate girders are commonly used in large span industrial structures and
composite bridges. The tapered thin steel web plates under stress gradients in such …
composite bridges. The tapered thin steel web plates under stress gradients in such …
Unleashing the power of AI: a systematic review of cutting-edge techniques in AI-enhanced scientometrics, webometrics and bibliometrics
Purpose The study aims to analyze the synergy of artificial intelligence (AI), with
scientometrics, webometrics and bibliometrics to unlock and to emphasize the potential of …
scientometrics, webometrics and bibliometrics to unlock and to emphasize the potential of …