Abstract
jiahui Tang, P. W. Chan, Jiachen Su, Xin Zeng
Abstract
Authors
Institutions
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Computational fluid dynamics for urban physics: importance, scales, possibilities, limitations and ten tips and tricks towards accurate and reliable simulations
10.1016/j.buildenv.2015.02.015 · 2015
Pedestrian-level wind conditions around buildings: review of wind-tunnel and CFD techniques and their accuracy for wind comfort assessment
10.1016/j.buildenv.2016.02.004 · 2016
Modeling the dynamics of PDE systems with physics-constrained deep auto-regressive networks
10.1016/j.jcp.2019.109056 · 2020
Generative adversarial networks
10.1145/3422622 · 2020
Aerodynamic properties of urban areas derived from analysis of surface form
1999
Super-resolution reconstruction of WorldView-3 multispectral satellite images based on generative adversarial networks
10.1016/j.engappai.2025.111706 · 2025
The influence of building height variability on pollutant dispersion and pedestrian ventilation in idealized high-rise urban areas
10.1016/j.buildenv.2012.03.023 · 2012
Image-to-image translation with conditional adversarial networks
2017
Neutralizing the impact of atmospheric turbulence on complex scene imaging via deep learning
Provenance
crossref
Confidence 100%
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openalex
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datacite
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10.1038/s42256-021-00392-1 · 2021
Review of urban computing in air quality management as smart city services: an integrated review
2021
A GAN-based surrogate model for instantaneous urban wind flow prediction
10.1016/j.buildenv.2023.110384 · 2023
Fourier neural operator for parametric partial differential equations
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Implementation of a fast fluid dynamics model in OpenFOAM for simulating indoor airflow
10.1080/10407782.2015.1090780 · 2016
EAF-WGAN: enhanced alignment fusion–Wasserstein generative adversarial network for turbulent image restoration
10.1109/tcsvt.2023.3262685 · 2023
Least squares generative adversarial networks
2017
Artificial Internet of Things, sensor-based digital twin and smart sustainable cities: a systematic review
10.3390/su16166749 · 2024
Turbulence-aware UAV path planning in urban environments
2024
Skilful precipitation nowcasting using deep generative models of radar
10.1038/s41586-021-03854-z · 2021
Adapting a deep convolutional RNN model with imbalanced regression loss for improved spatio-temporal forecasting of extreme wind speed events in the short to medium range
10.5194/gmd-16-251-2023 · 2023
A fast and stable framework for generative adversarial imitation learning
10.1016/j.engappai.2025.112460 · 2025
Advancements and future outlook of artificial intelligence in energy and climate change modeling
10.1016/j.adapen.2025.100211 · 2025
Influence of building-height variability on urban ventilation and pollutant dispersion characteristics
10.3390/atmos16050614 · 2025
Algorithmic urban planning for smart and sustainable development: systematic review of the literature
10.1016/j.scs.2023.104562 · 2023
Pedestrian level winds and outdoor human comfort
10.1016/j.jweia.2006.06.011 · 2006
Entropy-infused deep learning loss function for capturing extreme values in wind power forecasting
2024
Drag distribution in idealized heterogeneous urban environments
10.1007/s10546-020-00567-0 · 2021
Observations of tall-building wakes using a scanning Doppler lidar
10.5194/amt-18-1355-2025 · 2025
AIJ guidelines for practical applications of CFD to pedestrian wind environment around buildings
10.1016/j.jweia.2008.02.058 · 2008
CFD simulation of near-field pollutant dispersion in the urban environment: a review of current modeling techniques
10.1016/j.atmosenv.2013.07.028 · 2013
ESRGAN: enhanced super-resolution generative adversarial networks
2018
An analysis of wind field estimation and exploitation for quadrotor flight in the urban canopy layer
2016
A reduced order model for turbulent flows in the urban environment using machine learning
10.1016/j.buildenv.2018.10.035 · 2019
tempoGAN: a temporally coherent, volumetric GAN for super-resolution fluid flow
2018
Spatial characteristics of turbulent organized structures within the roughness sublayer over idealized urban surface with obstacle-height variability
10.1007/s10652-020-09764-4 · 2021
Differentiable augmentation for data-efficient GAN training
2020
Spatial characteristics of turbulent organized structures within the roughness sublayer over idealized urban surface with obstacle-height variability
10.1007/s10652-020-09764-4 · doi-reference
A reduced order model for turbulent flows in the urban environment using machine learning
10.1016/j.buildenv.2018.10.035 · doi-reference
CFD simulation of near-field pollutant dispersion in the urban environment: a review of current modeling techniques
10.1016/j.atmosenv.2013.07.028 · doi-reference
AIJ guidelines for practical applications of CFD to pedestrian wind environment around buildings
10.1016/j.jweia.2008.02.058 · doi-reference
Observations of tall-building wakes using a scanning Doppler lidar
10.5194/amt-18-1355-2025 · doi-reference
Drag distribution in idealized heterogeneous urban environments
10.1007/s10546-020-00567-0 · doi-reference
Pedestrian level winds and outdoor human comfort
10.1016/j.jweia.2006.06.011 · doi-reference
Algorithmic urban planning for smart and sustainable development: systematic review of the literature
10.1016/j.scs.2023.104562 · doi-reference
Influence of building-height variability on urban ventilation and pollutant dispersion characteristics
10.3390/atmos16050614 · doi-reference
Advancements and future outlook of artificial intelligence in energy and climate change modeling
10.1016/j.adapen.2025.100211 · doi-reference
A fast and stable framework for generative adversarial imitation learning
10.1016/j.engappai.2025.112460 · doi-reference
Adapting a deep convolutional RNN model with imbalanced regression loss for improved spatio-temporal forecasting of extreme wind speed events in the short to medium range
10.5194/gmd-16-251-2023 · doi-reference
Skilful precipitation nowcasting using deep generative models of radar
10.1038/s41586-021-03854-z · doi-reference
Artificial Internet of Things, sensor-based digital twin and smart sustainable cities: a systematic review
10.3390/su16166749 · doi-reference
EAF-WGAN: enhanced alignment fusion–Wasserstein generative adversarial network for turbulent image restoration
10.1109/tcsvt.2023.3262685 · doi-reference
Implementation of a fast fluid dynamics model in OpenFOAM for simulating indoor airflow
10.1080/10407782.2015.1090780 · doi-reference
A GAN-based surrogate model for instantaneous urban wind flow prediction
10.1016/j.buildenv.2023.110384 · doi-reference
Neutralizing the impact of atmospheric turbulence on complex scene imaging via deep learning
10.1038/s42256-021-00392-1 · doi-reference
The influence of building height variability on pollutant dispersion and pedestrian ventilation in idealized high-rise urban areas
10.1016/j.buildenv.2012.03.023 · doi-reference
Super-resolution reconstruction of WorldView-3 multispectral satellite images based on generative adversarial networks
10.1016/j.engappai.2025.111706 · doi-reference
Generative adversarial networks
10.1145/3422622 · doi-reference
Modeling the dynamics of PDE systems with physics-constrained deep auto-regressive networks
10.1016/j.jcp.2019.109056 · doi-reference
Pedestrian-level wind conditions around buildings: review of wind-tunnel and CFD techniques and their accuracy for wind comfort assessment
10.1016/j.buildenv.2016.02.004 · doi-reference
Computational fluid dynamics for urban physics: importance, scales, possibilities, limitations and ten tips and tricks towards accurate and reliable simulations
10.1016/j.buildenv.2015.02.015 · doi-reference