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Applications of machine learning to wind engineering
Advances of the analytical, numerical, experimental and field-measurement approaches in
wind engineering offers unprecedented volume of data that, together with rapidly evolving …
wind engineering offers unprecedented volume of data that, together with rapidly evolving …
[HTML][HTML] Machine learning for bridge wind engineering
Z Zhang, S Li, H Feng, X Zhou, N Xu, H Li… - Advances in Wind …, 2024 - Elsevier
Modeling and control are primary domains in bridge wind engineering. The natural wind
field characteristics (eg, non-stationary, non-uniform, spatial-temporal changing …
field characteristics (eg, non-stationary, non-uniform, spatial-temporal changing …
Enhancing wind performance of tall buildings using corner aerodynamic optimization
Wind-induced loads and motions of tall buildings usually govern the design of the lateral
load resisting systems. The outer shape of the building is one of the many parameters that …
load resisting systems. The outer shape of the building is one of the many parameters that …
Data-driven prediction of critical flutter velocity of long-span suspension bridges using a probabilistic machine learning approach
S Tinmitondé, X He, L Yan, AH Hounye - Computers & Structures, 2023 - Elsevier
Among the consequences of wind-induced excitation on long-span cable-supported
bridges, flutter instability is the most dangerous and can collapse bridge structures. Until …
bridges, flutter instability is the most dangerous and can collapse bridge structures. Until …
Prediction of aeroelastic response of bridge decks using artificial neural networks
The assessment of wind-induced vibrations is considered vital for the design of long-span
bridges. The aim of this research is to develop a methodological framework for robust and …
bridges. The aim of this research is to develop a methodological framework for robust and …
Optimizing lift-up design to maximize pedestrian wind and thermal comfort in 'hot-calm'and 'cold-windy'climates
A novel building design—the lift-up design—has shown promise in removing obstacles and
facilitating wind circulation at lower heights in built-up areas, yet little is understood about …
facilitating wind circulation at lower heights in built-up areas, yet little is understood about …
Machine learning strategy for predicting flutter performance of streamlined box girders
Engineers often heavily rely on wind tunnel tests or computational fluid dynamics (CFD) to
evaluate the flutter performance of bridges in their preliminary design, which is costly and …
evaluate the flutter performance of bridges in their preliminary design, which is costly and …
Prediction of solitary wave forces on coastal bridge decks using artificial neural networks
This study proposes an alternative and competitive methodology for predicting solitary wave
forces on coastal bridge decks using artificial neural networks (ANNs). It is imperative to …
forces on coastal bridge decks using artificial neural networks (ANNs). It is imperative to …
[HTML][HTML] A Gaussian Process-Based emulator for modeling pedestrian-level wind field
Wind tunnel tests and computational fluid dynamics (CFD) simulations remain the main
modeling techniques in wind engineering despite being expensive, time-consuming, and …
modeling techniques in wind engineering despite being expensive, time-consuming, and …
Simulation of unsteady flow around bluff bodies using knowledge-enhanced convolutional neural network
The unsteady flow with massive separation poses challenges to accurately and efficiently
simulate wind effects on civil structures, especially in the search for optimal aerodynamic …
simulate wind effects on civil structures, especially in the search for optimal aerodynamic …