Is the proper orthogonal decomposition suitable to validate simulation of turbulent wake? DOI
Tomáš Hlavatý, Martin Isoz, Marek Belda

et al.

Journal of Wind Engineering and Industrial Aerodynamics, Journal Year: 2024, Volume and Issue: 255, P. 105953 - 105953

Published: Nov. 21, 2024

Language: Английский

Spatially resolved air quality index prediction in megacities with a CNN-Bi-LSTM hybrid framework DOI

Reza Rabie,

Milad Asghari, Hossein Nosrati

et al.

Sustainable Cities and Society, Journal Year: 2024, Volume and Issue: 109, P. 105537 - 105537

Published: May 18, 2024

Language: Английский

Citations

20
Artificial neural network an innovative approach in air pollutant prediction for environmental applications: A review DOI Creative Commons

Vibha Yadav,

Amit Kumar Yadav, Vedant Singh

et al.

Results in Engineering, Journal Year: 2024, Volume and Issue: 22, P. 102305 - 102305

Published: May 22, 2024

Air pollution in the environment is growing daily as a result of urbanization and population growth, which causes numerous health issues. Information about air quality environmental risks provided by pollutant data crucial for management. The use artificial neural network (ANN) approaches predicting pollutants reviewed this research. These methods are based on several forecast intervals, including hourly, daily, monthly ones. This study shows that ANN techniques contaminants more precisely than traditional methods. It has been discovered input parameters architecture-type algorithms used affect accuracy prediction models. therefore accurate reliable other empirical models because they can handle wide range meteorological parameters. Finally, research gap networks identified. review may inspire researchers to certain extent promote development intelligence prediction.

Language: Английский

Citations

18
Effect of characteristic parameters of air-bleeding/blowing interface on tunnel pressure waves in streamlined regions of high-speed trains: A numerical simulation study DOI
Kailong Jin, Lin Zhang, Xinzhe Li

et al.

Sustainable Cities and Society, Journal Year: 2024, Volume and Issue: 102, P. 105222 - 105222

Published: Jan. 18, 2024

Language: Английский

Citations

13
Numerical and machine learning based evaluation of ethylene glycol based hybrid nano-structured (TiO2-SWCNTs) fluid flow DOI Creative Commons
Hijaz Ahmad,

Kamel Guedri,

Sohail Ahmad

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Feb. 19, 2025

A better mechanical resistance and improved thermal conductivity, as compared to mono nano-liquids, can be attained by the ethylene glycol-based hybrid nanofluids. These fluids have substantial uses in several engineering systems. The main focus, recent work, is assess dynamics of nano-structured fluid via computational (CFD) machine learning (ML) approaches. nano-composition single-walled carbon nanotubes (SWCNTs) titanium dioxide (TiO2) glycol causes mixture SWCNTs-TiO2/EG. CFD model, for simulation procedure, developed incorporating similarity coordinates governing partial differential equations. This model comprises a dimensionless system having prime parameters problem. numerical results are appraised means comparison between present existing results. levenberg marquardt (LM) technique powerful tool predict flow properties. complex correlations input properties interpreted with help well LM neural network. this work might provide basis design development high-performance heat exchangers management

Language: Английский

Citations

1
Machine Learning to speed up Computational Fluid Dynamics engineering simulations for built environments: A review DOI Creative Commons
Clément Caron,

Philippe Lauret,

Alain Bastide

et al.

Building and Environment, Journal Year: 2024, Volume and Issue: 267, P. 112229 - 112229

Published: Nov. 8, 2024

Language: Английский

Citations

5
Accelerating urban street canyon wind flow predictions with deep learning method DOI

Wai-Chi Cheng,

Tzung‐May Fu

Building Simulation, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 12, 2025

Language: Английский

Citations

0
Development of Machine Learning-Aided Rapid CFD Prediction for Optimal Urban Wind Environment Design DOI
Aiymzhan Baitureyeva, Tong Yang, Hua Sheng Wang

et al.

Sustainable Cities and Society, Journal Year: 2025, Volume and Issue: 121, P. 106208 - 106208

Published: Feb. 16, 2025

Language: Английский

Citations

0
Numerical investigation of building gap effects on traffic pollutant dispersion in urban networks with intersecting streets DOI
Yiqi Wang, Ke Zhong, Jin Cheng

et al.

Atmospheric Pollution Research, Journal Year: 2025, Volume and Issue: unknown, P. 102475 - 102475

Published: Feb. 1, 2025

Language: Английский

Citations

0
Research on the Impact of Urban Built Environments on PM2.5 Pollution Based on Machine Learning Methods DOI
Xiaoxia Wang, Zhihai Fan,

Yue X

et al.

Atmospheric Pollution Research, Journal Year: 2025, Volume and Issue: unknown, P. 102503 - 102503

Published: March 1, 2025

Language: Английский

Citations

0
A prediction of urban boundary layer using Recurrent Neural Network and reduced order modeling DOI
Yedam Lee, Sang Lee

Building and Environment, Journal Year: 2025, Volume and Issue: unknown, P. 112804 - 112804

Published: March 1, 2025

Language: Английский

Citations

0