Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
4.6
2.5
Journals
Atmosphere
Special Issues
Advances in Computational Wind Engineering and Wind Energy
share announcement

Advances in Computational Wind Engineering and Wind Energy

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Meteorology".

Deadline for manuscript submissions: closed (15 July 2023) | Viewed by 28553

Special Issue Editors

Dr. Bowen Yan

E-Mail Website
Guest Editor
School of Civil Engineering, Chongqing University, Chongqing 400045, China
Interests: structural wind engineering; wind energy
Dr. Jinhui Yan

E-Mail Website
Guest Editor
Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, Champaign, IL 61801, USA
Interests: high-fidelity computational methods for fluid-structure interaction; multi-phase flows, and their application to real-world engineering problems in renewable energy and additive manufacturing
Dr. Chao Li

E-Mail Website
Guest Editor
School of Civil and Environmental Engineering, Harbin Institute of Technology, Shenzhen 518055, China
Interests: wind engineering; numerical wind tunnel; floating wind turbine; urban wind environment
Dr. Chaorong Zheng

E-Mail Website
Guest Editor
School of Civil Engineering, Harbin Institute of Technology, Harbin 150096, China
Interests: structural wind engineering; building aerodynamic; aerodynamic control; wind veering; pedestrian wind environment; AI in wind engineering
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Xiao Li

E-Mail
Guest Editor
School of Civil Engineering, Chongqing University, Chongqing 400044, China
Interests: extreme winds; wind-induced structural responses; wind hazards
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Computational wind engineering (CWE) is the application of computational methods to wind engineering problems. Computational fluid dynamics (CFD) has constituted the major part of CWE, which is widely used in the research concerned with fluid flow in civil engineering. CWE has increasingly become an essential branch in the field of wind engineering.

The fluid problems encountered in CWE mainly feature complex geometry, high-Reynolds number and strong flow seperations, which make the application of CFD in wind engineering quite challenging and problematic. With the rapid development of CFD techniques and increasing availability of substantial computing power, CWE covers wind climate analysis, wind loadings on buildings and structures, bridge aerodynamics, pedestrian-level wind environment, wind-driven rain/snow/fire, etc. Nowadays, the emerging trend is the application of optimization in CWE and the AI (artificial intelligence)-driven CWE, suggesting the promising areas for future research.

In this Special Issue, we invite the researchers to publish original research and review papers on the advances in CWE, including, but are not limited to:

  • atmospheric and pollutant dispersion;
  • big data application to wind engineering;
  • bluff body aerodynamics;
  • bridge aerodynamics;
  • computational methods for wind-related experiments;
  • micro and meso-scale meteorology model development;
  • model quality assurance;
  • wind energy and applications;
  • wind environment;
  • wind hazard assessments;
  • wind loading;
  • wind-induced human comfort;
  • wind-related disaster assessment;
  • wind-structure interactions

Dr. Bowen Yan
Dr. Jinhui Yan
Dr. Chao Li
Dr. Chaorong Zheng
Dr. Xiao Li
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Atmosphere is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • atmospheric and pollutant dispersion
  • big data application to wind engineering
  • bluff body aerodynamics
  • bridge aerodynamics
  • computational methods for wind-related experiments
  • micro and meso-scale meteorology model development
  • model quality assurance
  • wind energy and applications
  • wind environment
  • wind hazard assessments
  • wind loading
  • wind-induced human comfort
  • wind-related disaster assessment
  • wind-structure interactions

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (15 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

20 pages, 741 KiB  
Article
An XAI Framework for Predicting Wind Turbine Power under Rainy Conditions Developed Using CFD Simulations
by Ijaz Fazil Syed Ahmed Kabir, Mohan Kumar Gajendran, Prajna Manggala Putra Taslim, Sethu Raman Boopathy, Eddie Yin-Kwee Ng and Amirfarhang Mehdizadeh
Atmosphere 2024, 15(8), 929; https://doi.org/10.3390/atmos15080929 - 3 Aug 2024
Viewed by 892
Abstract
Renewable energy sources are essential to address climate change, fossil fuel depletion, and stringent environmental regulations in the subsequent decades. Horizontal-axis wind turbines (HAWTs) are particularly suited to meet this demand. However, their efficiency is affected by environmental factors because they operate in [...] Read more.
Renewable energy sources are essential to address climate change, fossil fuel depletion, and stringent environmental regulations in the subsequent decades. Horizontal-axis wind turbines (HAWTs) are particularly suited to meet this demand. However, their efficiency is affected by environmental factors because they operate in open areas. Adverse weather conditions like rain reduce their aerodynamic performance. This study investigates wind turbine power prediction under rainy conditions by integrating Blade Element Momentum (BEM) theory with explainable artificial intelligence (XAI). The S809 airfoil’s aerodynamic characteristics, used in NREL wind turbines, were analyzed using ANSYS FLUENT and symbolic regression under varying rain intensities. Simulations at a Reynolds number (Re) of 1 × 106 were performed using the Discrete Phase Model (DPM) and k–ω SST turbulence model, with liquid water content (LWC) values of 0 (dry), 10, 25, and 39 g/m3. The lift and drag coefficients were calculated at various angles of attack for all the conditions. The results indicated that rain led to reduced lift and increased drag. The innovative aspect of this research is the development of machine learning models predicting changes in the airfoil coefficients under rain with an R2 value of 0.97. The proposed XAI framework models rain effects at a lower computational time, enabling efficient wind farm performance assessment in rainy conditions compared to conventional CFD simulations. It was found that a heavy rain LWC of 39 g/m3 could reduce power output by 5.7% to 7%. These findings highlight the impact of rain on aerodynamic performance and the importance of advanced predictive models for optimizing renewable energy generation. Full article
(This article belongs to the Special Issue Advances in Computational Wind Engineering and Wind Energy)
►▼ Show Figures

Figure 1

19 pages, 9156 KiB  
Article
Numerical Simulation on Wind Speed Amplification of High-Rise Buildings with Openings
by Ziqi Gu, Fubin Chen, Yuzhe Zhu, Yu Mei, Zhanli Wang, Linfeng Xu and Yi Li
Atmosphere 2023, 14(11), 1687; https://doi.org/10.3390/atmos14111687 - 14 Nov 2023
Viewed by 1341
Abstract
To explore the influence of openings on wind loads and wind speeds in high-rise buildings, the wind flow around three-dimensional (3D) square cylinders with a breadth/height aspect ratio of 1:6 was numerically simulated using the large eddy simulation (LES) method via the Fluent [...] Read more.
To explore the influence of openings on wind loads and wind speeds in high-rise buildings, the wind flow around three-dimensional (3D) square cylinders with a breadth/height aspect ratio of 1:6 was numerically simulated using the large eddy simulation (LES) method via the Fluent 15.0 platform. The opening measures in the X-direction, Y-direction and both directions were all taken into consideration. Firstly, the inflow turbulence synthesis method and parameter settings for LES were verified by comparing the simulation results of standard square cylinders with those of wind tunnel experiments, and the optimal boundary conditions were determined. Then, the wind speed was extracted and compared with the mean wind speed of incoming flow at the same height to analyze the influence of different opening measures on the wind speed of incoming flow by setting monitoring points in the open holes. Finally, the mechanism underlying the effect of the opening form on wind loads and wind speeds was analyzed from the perspective of time-averaged and transient flow field. The results show that the X-direction openings affect the magnitude and distribution of the surface wind pressures by changing the flow separation and flow reattachment. The narrow tube effect can significantly increase the wind speed, while the Y-direction openings have no obvious improvement effect on the surface wind pressures of the structure. The wind speeds in the open holes are greatly reduced due to the shielding effect, and the wind pressures are also reduced for the Y-direction openings. In the X-direction opening holes, the wind speed at the monitoring point increases, while it decreases in the crosswind open holes. In general, the measure of openings in the X-direction can greatly improve the wind load of the structure compared to openings in the Y-direction, and it can provide a good reference for wind power generation in high-rise buildings. Full article
(This article belongs to the Special Issue Advances in Computational Wind Engineering and Wind Energy)
►▼ Show Figures

Figure 1

27 pages, 7064 KiB  
Article
Intelligent Identification and Verification of Flutter Derivatives and Critical Velocity of Closed-Box Girders Using Gradient Boosting Decision Tree
by Neyu Chen, Yaojun Ge and Claudio Borri
Atmosphere 2023, 14(7), 1165; https://doi.org/10.3390/atmos14071165 - 18 Jul 2023
Cited by 3 | Viewed by 1566
Abstract
Flutter derivatives (FDs) of the bridge deck are basic aerodynamic parameters by which flutter analysis determines critical flutter velocity (CFV), and they are traditionally identified by sectional model wind tunnel tests or computational fluid dynamics (CFD) numerical simulation. Based on some wind tunnel [...] Read more.
Flutter derivatives (FDs) of the bridge deck are basic aerodynamic parameters by which flutter analysis determines critical flutter velocity (CFV), and they are traditionally identified by sectional model wind tunnel tests or computational fluid dynamics (CFD) numerical simulation. Based on some wind tunnel testing results and numerical simulation data, the machine learning models for identifying FDs of closed-box girders are trained and developed via a gradient boosting decision tree in this study. The models can explore the underlying input–output transfer relationship of datasets and realize rapid intelligent identification of FDs without wind tunnel tests or numerical simulation. This method also provides a convenient and feasible option for expanding datasets of FDs, and the distribution of FDs can be analyzed through the post-interpretation of trained models. Combined with FD sensitivity analysis, the models can be verified by the calculation error of CFV. In addition, the proposed method can help determine the appropriate shape of the box girder cross-section in the preliminary design stage of long-span bridges and provide the necessary reference for aerodynamic shape optimization by modifying the local geometric features of the cross-section. Full article
(This article belongs to the Special Issue Advances in Computational Wind Engineering and Wind Energy)
►▼ Show Figures

Figure 1

19 pages, 8046 KiB  
Article
Semiempirical Models of Speedup Effect for Downburst Wind Field over 3-D Hills
by Bowen Yan, Yini He, Chenyan Ma and Xu Cheng
Atmosphere 2023, 14(4), 694; https://doi.org/10.3390/atmos14040694 - 7 Apr 2023
Cited by 3 | Viewed by 1312
Abstract
Downbursts occur frequently in mountainous regions, such as the southwest of China, and causing extensive damage to engineering structures. While some researchers have developed semiempirical models for the speedup effect, most are based on the wind field in the boundary layer over the [...] Read more.
Downbursts occur frequently in mountainous regions, such as the southwest of China, and causing extensive damage to engineering structures. While some researchers have developed semiempirical models for the speedup effect, most are based on the wind field in the boundary layer over the hill, and there is a lack of semiempirical models for the downburst wind field over the hill. This study employs three RANS (Reynolds Average Navier-Stokes) turbulence models to numerically simulate the downburst wind field over a quadratic curved hill. The realizable k-ε model is selected as the optimal model for the subsequent numerical simulations based on comparison with wind tunnel test results. Then, a semiempirical model of the speedup effect of the downburst wind field over the hill is constructed by numerically simulating the downburst wind field over the hill with different radial locations and different slopes. Finally, the constructed semiempirical model is validated and demonstrates good accuracy. Full article
(This article belongs to the Special Issue Advances in Computational Wind Engineering and Wind Energy)
►▼ Show Figures

Figure 1

12 pages, 2979 KiB  
Article
Bayesian Analysis of Spatial Model for Frequency of Tornadoes
by Haitao Zheng, Yi Zhang, Qiaoju Chen, Qingshan Yang, Guoqing Huang, Dahai Wang and Ruili Liu
Atmosphere 2023, 14(3), 472; https://doi.org/10.3390/atmos14030472 - 27 Feb 2023
Viewed by 1387
Abstract
Frequency analysis of tornadoes is very important for risk analysis and disaster control. In this paper, the annual frequency of tornadoes that occurred in the United States from 1967 to 2016 is analyzed. The simple analysis shows that frequencies of tornadoes of different [...] Read more.
Frequency analysis of tornadoes is very important for risk analysis and disaster control. In this paper, the annual frequency of tornadoes that occurred in the United States from 1967 to 2016 is analyzed. The simple analysis shows that frequencies of tornadoes of different sites are spatially correlated and over-dispersed. To explain the two characteristics of the data, the Bayesian hierarchical model is proposed. For comparison purposes, the Bayesian model with negative binomial distribution, Poisson distribution, Polya distribution, and first-order, non-negative, integer-valued autoregressive model with Bell innovations(BL-INAR(1)) are considered to fit the frequency of tornado. The distribution parameters of all sites are assumed to be spatially correlated, and the corresponding Bayesian hierarchical models were established. MCMC (Markov Chain Monte Carlo) method is applied to parameter estimations and relative statistical inference. By comparison of the analysis results, the negative binomial distribution is recommended to analyze the overdispersion and spatial correlation among the sites of the data. The comparison between the simulated frequencies based on the proposed model and the actual frequencies also verifies that the proposed method is a better model for the data. Full article
(This article belongs to the Special Issue Advances in Computational Wind Engineering and Wind Energy)
►▼ Show Figures

Figure 1

27 pages, 9690 KiB  
Article
Two-Stage Decomposition Multi-Scale Nonlinear Ensemble Model with Error-Correction-Coupled Gaussian Process for Wind Speed Forecast
by Jujie Wang, Maolin He and Shiyao Qiu
Atmosphere 2023, 14(2), 395; https://doi.org/10.3390/atmos14020395 - 17 Feb 2023
Cited by 3 | Viewed by 1619
Abstract
Wind power has great potential in the fields of electricity generation, heating, et cetera, and the precise forecasting of wind speed has become the key task in an effort to improve the efficiency of wind energy development. Nowadays, many existing studies have investigated [...] Read more.
Wind power has great potential in the fields of electricity generation, heating, et cetera, and the precise forecasting of wind speed has become the key task in an effort to improve the efficiency of wind energy development. Nowadays, many existing studies have investigated wind speed prediction, but they often simply preprocess raw data and also ignore the nonlinear features in the residual part, which should be given special treatment for more accurate forecasting. Meanwhile, the mainstream in this field is point prediction which cannot show the potential uncertainty of predicted values. Therefore, this paper develops a two-stage decomposition ensemble interval prediction model. The original wind speed series is firstly decomposed using a complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and the decomposed subseries with the highest approximate entropy is secondly decomposed through singular-spectrum analysis (SSA) to further reduce the complexity of the data. After two-stage decomposition, auto-encoder dimensionality reduction is employed to alleviate the accumulated error problem. Then, each reconstructed subsequence will generate an independent prediction result using an elastic neural network. Extreme gradient boosting (Xgboost) is utilized to integrate the separate predicted values and also carry out the error correction. Finally, the Gaussian process (GP) will generate the interval prediction result. The case study shows the best performance of the proposed models, not only in point prediction but also in interval prediction. Full article
(This article belongs to the Special Issue Advances in Computational Wind Engineering and Wind Energy)
►▼ Show Figures

Figure 1

13 pages, 4778 KiB  
Article
Study on the Peak Factor of the Wind-Induced Response of Super-High-Rise Buildings
by Jun-Bo Wang, Yu Wang, Lei Wang and Shu-Guo Liang
Atmosphere 2023, 14(2), 379; https://doi.org/10.3390/atmos14020379 - 15 Feb 2023
Cited by 2 | Viewed by 2022
Abstract
The wind-induced responses of tall buildings are stochastic processes, and the peak factor is an important parameter to evaluate the extreme value of the wind-induced response in wind-resistant design. The existing research on the peak factor mainly focuses on the wind pressure on [...] Read more.
The wind-induced responses of tall buildings are stochastic processes, and the peak factor is an important parameter to evaluate the extreme value of the wind-induced response in wind-resistant design. The existing research on the peak factor mainly focuses on the wind pressure on the building surface, but rarely concerns the wind-induced response peak factor of the structures. In view of this, the peak factor of the wind-induced response of super-high-rise buildings was studied in this paper. Firstly, a series of wind tunnel tests of the multi-degree-of-freedom aero-elastic models (MDOF) were carried out, wherein the along-wind and cross-wind responses were measured. Thereafter, the peak factor of wind-induced response was calculated using the peak factor method, classical extreme value theory, and the improved peak factor method. It was found that the peak factor calculated by the improved peak factor method is in good agreement with classical extreme value theory, which indicates that the improved peak factor method is applicable to calculate the peak factor of the wind-induced response of high-rise buildings. The results calculated using the improved peak factor method show that the peak factor of cross-wind response varies significantly with the wind speed, varying from about 2.5 to 5.5. The peak factor of cross-wind response first increases and then decreases with the increase in the wind speed, reaches the minimum near the critical wind speed of vortex-induced vibration (VIV), and increases again when the wind speed is larger than the VIV wind speed. Finally, an empirical formula for the cross-wind response peak factor was proposed as a function of the reduced wind speed, aspect ratio, and damping ratio of the structure. Full article
(This article belongs to the Special Issue Advances in Computational Wind Engineering and Wind Energy)
►▼ Show Figures

Figure 1

20 pages, 14195 KiB  
Article
Spatial Distribution and Trends of Wind Energy at Various Time Scales over the South China Sea
by Shuqin Zhang, Xiaoqi Yang, Hanwei Weng, Tianyu Zhang, Ruoying Tang, Hao Wang and Jinglei Su
Atmosphere 2023, 14(2), 362; https://doi.org/10.3390/atmos14020362 - 12 Feb 2023
Cited by 4 | Viewed by 2362
Abstract
In this study, the spatial distribution and trends of wind energy (as measured by wind and wind power density) were investigated from 1979 to 2021 across various time scales over the South China Sea (SCS)by utilizing ERA5 reanalysis data. The results indicate that [...] Read more.
In this study, the spatial distribution and trends of wind energy (as measured by wind and wind power density) were investigated from 1979 to 2021 across various time scales over the South China Sea (SCS)by utilizing ERA5 reanalysis data. The results indicate that the SCS possesses abundant wind energy. In addition, due to the fact that the East Asian monsoon dominates the SCS, the wind energy exhibits obvious seasonal changes. It is in winter and autumn that the winter monsoon (i.e., the northeast wind) prevails over the SCS. Here, the wind energy is abundant and reaches its maximum in December. In summer, the summer monsoon (i.e., the southwest wind) prevails over the SCS. Here, the wind energy is abundant over the southwestern SCS. In spring, however, the wind energy is poor. The annual mean wind energy shows a decreasing trend along the northern coast and an increasing trend over the central SCS. The trends of seasonal mean wind energy in winter, spring, and summer demonstrate a similar pattern to the annual mean wind energy. With respect to the intensity of the trends, they are strongest in winter, followed by spring and autumn, and weakest in summer. The trend of wind energy in autumn almost demonstrates the opposite pattern in comparison with the other seasons, i.e., both decreasing and increasing trends over the northern and southern SCS, respectively. The decreasing trend of wind energy along the northern coast of the SCS occurs in February, April, July, September, and November, whereas the increasing trend over the central SCS appears from the period of December to June. The spatial distribution and trends of wind energy over the SCS can help with issuing a more informed recommendation with respect to offshore wind energy planning. Full article
(This article belongs to the Special Issue Advances in Computational Wind Engineering and Wind Energy)
►▼ Show Figures

Figure 1

18 pages, 6385 KiB  
Article
Numerical Simulation of Wind Characteristics in Complex Mountains with Focus on Terrain Boundary Transition Curve
by Jiawei He, Hongfu Zhang and Lei Zhou
Atmosphere 2023, 14(2), 230; https://doi.org/10.3390/atmos14020230 - 23 Jan 2023
Cited by 4 | Viewed by 1949
Abstract
In recent years, an increasing number of projects have been developed in complex mountainous areas. The wind environment in mountainous areas, extremely complex due to the undulating terrain and diverse landscapes, is a key factor threatening the structural safety of buildings and their [...] Read more.
In recent years, an increasing number of projects have been developed in complex mountainous areas. The wind environment in mountainous areas, extremely complex due to the undulating terrain and diverse landscapes, is a key factor threatening the structural safety of buildings and their appurtenances in mountainous areas. Therefore, it is important to study the wind environment in complex terrain to clarify the wind resistance of structures in mountainous areas. Computational fluid dynamics (CFD) approaches are commonly used to examine wind fields in complex terrain; however, due to the limited range of terrain considered, direct modeling using terrain elevation data can result in truncated elevation differences, affecting the accuracy of numerical simulations. To address the problem of truncated elevation differences at terrain boundaries, the parameters of the wind tunnel contraction curve are optimized regarding the wind tunnel contraction section design principle. Moreover, several transition curves are analyzed and evaluated by numerical simulation methods, and a transition curve applicable to the terrain boundary transition form is proposed. The proposed terrain transition curves are applied to model the terrain of complex mountainous ski resort areas to be used in CFD numerical simulations. Furthermore, the accuracy of the numerical simulation is verified through a comparison with the field-measured data. Results indicate that the proposed method can accurately and effectively reflect the wind environment characteristics of a ski resort area. The proposed terrain transition curve provides a theoretical basis and case support for designing the terrain model boundary transition section, which can be used as a reference for wind tunnel and numerical simulation studies in complex mountainous areas. Full article
(This article belongs to the Special Issue Advances in Computational Wind Engineering and Wind Energy)
►▼ Show Figures

Figure 1

48 pages, 11256 KiB  
Article
Analysis of Flow Structures and Global Parameters across a Heated Square Cylinder in Forced and Mixed Convection
by Rashid Ali and Nadeem Hasan
Atmosphere 2023, 14(1), 22; https://doi.org/10.3390/atmos14010022 - 23 Dec 2022
Viewed by 1782
Abstract
In the present study, numerical simulations are performed to identify the role of Reynolds number (Re), Richardson number (Ri) and free-stream orientations (α) on flow structures, aerodynamic parameters and heat transfer characteristics for the conditions (20 ≤ Re ≤ 120, 0° ≤ α [...] Read more.
In the present study, numerical simulations are performed to identify the role of Reynolds number (Re), Richardson number (Ri) and free-stream orientations (α) on flow structures, aerodynamic parameters and heat transfer characteristics for the conditions (20 ≤ Re ≤ 120, 0° ≤ α ≤ 90° and 0 ≤ Ri ≤ 1.6). Prandtl number (Pr) and cylinder orientation (ϕ) are kept fixed at 0.71 and 0°. The Oberbeck–Boussinesq approximation is used to account for buoyancy effects. The governing equations of continuity, momentum and energy are discretized on a colocated body-fitted grid by employing a finite difference method. A viscous implicit pressure correction scheme is employed to advance the discrete solution in time. Contour maps of mean/steady drag coefficient and Nusselt number on (α-Ri) plane are plotted for 20 ≤ Re ≤ 120. From these contour maps, it is possible to identify the ranges of parameters (α, Ri) that can yield a relatively high mean/steady heat transfer rate accompanied by relatively low values of mean/steady drag coefficient. For [70° ≤ α ≤ 90°, 0 ≤ Ri ≤ 1.6], such a scenario is possible for any Re ∈ [20, 120]. The Strouhal number is observed to be maximum for Re = 120 at α = 45° and Ri = 1.2. Mean or steady coefficient of lift for any free-stream orientation (α ≠ 0°) is found to be highest at Re = 20 and Ri = 1.6. Sensitivity of (CD)Ri = 0.0 to α is observed to be minimum for Re = 20 and maximum for Re = 120. Sensitivity of the ratio CD(Ri,α)/CD(0,α) to Re is observed to be lower for unsteady flows than for steady flows, and it decreases with an increase in Re at a fixed value of Ri. Mean Nusselt number (Nu) in the forced flow regime increases significantly with an increase in Re at a fixed α. The Nusselt number is observed to be more sensitive to Ri for steady flows than for unsteady flows. The percentage increase in the ratio Nu(Ri,α)/Nu(0,α) for the entire range of Re is found to be 14.07%, 14.13%, 11.74% and 10.62% at α = 30°, 45°, 60° and 90°. At a fixed Ri, the Nusselt number ratio is found to decrease with an increase in Re for the entire range of α except for α = 90°. It is observed that the rate of heat transfer from the faces of the cylinder increases with an increase in Re for the entire ranges of α and Ri. Full article
(This article belongs to the Special Issue Advances in Computational Wind Engineering and Wind Energy)
►▼ Show Figures

Figure 1

19 pages, 12933 KiB  
Article
Numerical Simulation of Atmospheric Boundary Layer Turbulence in a Wind Tunnel Based on a Hybrid Method
by Zhaoqing Chen, Chao Wei, Zhuozhuo Chen, Shuang Wang and Lixiang Tang
Atmosphere 2022, 13(12), 2044; https://doi.org/10.3390/atmos13122044 - 6 Dec 2022
Cited by 4 | Viewed by 2466
Abstract
In the Computational Fluid Dynamics (CFD) simulation for building structures, it is important to generate a stable atmospheric boundary layer (ABL) flow field that meets the standards. In this paper, the wind profile, turbulence intensity, and wind velocity power spectrum in the target [...] Read more.
In the Computational Fluid Dynamics (CFD) simulation for building structures, it is important to generate a stable atmospheric boundary layer (ABL) flow field that meets the standards. In this paper, the wind profile, turbulence intensity, and wind velocity power spectrum in the target region of a numerical wind tunnel were accurately simulated by a hybrid method. With the numerical simulation software FLUENT, the hybrid simulation method was implemented. In the hybrid simulation method, the wind field was simulated by setting the roughness element in the upstream of the model, adding random disturbance, and setting the circulation surface. The influences of simulation parameters (such as roughness element and random number parameters) and FLUENT solution methods on the flow field results were studied. The results show that the influence range of the roughness element on turbulence intensity is approximately 6 times its physical height. The turbulence intensity is positively correlated with the standard deviation of random numbers and negatively correlated with the assignment height. Finally, the wind fields for different terrains satisfying the standards were obtained in numerical wind tunnels. A simulation of the wind pressure on an inflatable membrane structure was illustrated. The comparison between numerical and experimental results shows a good accordance, which indicates a desirable potential in practical application. Full article
(This article belongs to the Special Issue Advances in Computational Wind Engineering and Wind Energy)
►▼ Show Figures

Figure 1

13 pages, 4066 KiB  
Article
Simulation of Piston Effects on Platform Screen Doors Considering Air Leakage
by Jian Zhang, Jianyao Wang, Qingshan Yang and Qiusheng Li
Atmosphere 2022, 13(12), 1967; https://doi.org/10.3390/atmos13121967 - 25 Nov 2022
Viewed by 2220
Abstract
The complex wind effects around platform screen doors (PSDs) caused by train-induced piston wind effect and positive micropressure waves in subway station platforms are investigated. Numerical modeling of the wind field around full-scale PSDs with real gaps under different inflow conditions is developed [...] Read more.
The complex wind effects around platform screen doors (PSDs) caused by train-induced piston wind effect and positive micropressure waves in subway station platforms are investigated. Numerical modeling of the wind field around full-scale PSDs with real gaps under different inflow conditions is developed to analyze the pressure distributions on and around the PSDs and the corresponding recirculation regions in the frontal and rear PSD areas with computational fluid dynamics (CFD) method. An equivalent porous media model is developed to obtain the relationship between the pressure difference and wind velocity based on Darcy–Forchheimer’s Law. It includes a viscosity loss term and an inertial loss term in the simulation of the air leakage flow generated from the PSD gap. The coefficients of these two terms are estimated from the CFD results from the full-scale models. The complicated flow field originated from the gaps is the main cause of the large wind pressure on the PSD, and the flow velocity on the platform may significantly affect the comfort of pedestrians and of the safety design of the PSD system. Full article
(This article belongs to the Special Issue Advances in Computational Wind Engineering and Wind Energy)
►▼ Show Figures

Figure 1

14 pages, 6541 KiB  
Article
Forecasting and Optimization of Wind Speed over the Gobi Grassland Wind Farm in Western Inner Mongolia
by Jinyuan Xin, Daen Bao, Yining Ma, Yongjing Ma, Chongshui Gong, Shuai Qiao, Yunyan Jiang, Xinbing Ren, Tao Pang and Pengcheng Yan
Atmosphere 2022, 13(12), 1943; https://doi.org/10.3390/atmos13121943 - 22 Nov 2022
Cited by 4 | Viewed by 2182
Abstract
Wind power, as one of the primary clean energies, is an important way to achieve the goals of carbon peak and carbon neutrality. Therefore, high-resolution measurement and accurate forecasting of wind speed are very important in the organization and dispatching of the wind [...] Read more.
Wind power, as one of the primary clean energies, is an important way to achieve the goals of carbon peak and carbon neutrality. Therefore, high-resolution measurement and accurate forecasting of wind speed are very important in the organization and dispatching of the wind farm. In this study, several methodologies, including the mesoscale WRF (Weather Research and Forecasting(WRF) model, mathematical statistics algorithms, and machine learning algorithms, were adopted to systematically explore the predictability and optimization of wind speed of a Gobi grassland wind farm located in western Inner Mongolia. Results show that the rear-row turbines were significantly affected by upwind turbine wakes. The output power of upwind-group turbines was 591 KW with an average wind speed of 7.66 m/s, followed by 532 KW and 7.02 m/s in the middle group and 519 KW and 6.92 m/s in the downwind group. The higher the wind speed was, the more significantly the wake effect was presented. Intercomparison between observations and WRF simulations showed an average deviation of 3.73 m/s. Two postprocessing methods of bilinear interpolation and nearest replacement could effectively reduce the errors by 34.85% and 36.19%, respectively, with average deviations of 2.43 m/s and 2.38 m/s. A cycle correction algorithm named Average Variance–Trend (AVT) can further optimize the errors to 2.14 m/s and 2.13 m/s. In another aspect, the categorical boosting (CatBoost) artificial intelligence algorithm also showed a great performance in improving the accuracy of WRF outputs, and the four-day average deviation of 26–29 September decreased from 3.21 m/s to around 2.50 m/s. However, because of the influence of large-scale circulations, there still exist large errors in the results of various correction algorithms. It is therefore suggested through the investigation that data assimilation of the northwest and Mongolian plateau, boundary layer parameterization scheme optimization, and embedding of high-resolution topographic data could have great potential for obtaining more accurate forecasting products. Full article
(This article belongs to the Special Issue Advances in Computational Wind Engineering and Wind Energy)
►▼ Show Figures

Figure 1

12 pages, 3482 KiB  
Article
Accurate Stall Prediction for Thick Airfoil by Delayed Detached-Eddy Simulations
by Zhenye Sun, Rongkun Shi, Weijun Zhu, Xiaochuan Li and Junwei Yang
Atmosphere 2022, 13(11), 1804; https://doi.org/10.3390/atmos13111804 - 31 Oct 2022
Cited by 2 | Viewed by 1946
Abstract
The continuous increase in wind turbine blade length raises a serious question about how to effectively reduce the blade mass. As one of the solutions, recently, some wind turbine manufacturers are moving towards longer blades with thicker airfoils. As most of the numerical [...] Read more.
The continuous increase in wind turbine blade length raises a serious question about how to effectively reduce the blade mass. As one of the solutions, recently, some wind turbine manufacturers are moving towards longer blades with thicker airfoils. As most of the numerical simulation experiences are based on thin airfoils, the present paper focused on airfoils with thickness to chord ratios of 30% and specifically focused on the influence of spanwise length on the numerical results. Airfoils with a spanwise length of 0.1 to 5 chords were simulated utilizing the Delayed Detached-Eddy Simulations (DDES) approach. One of the important objectives was to identify the necessary grid resolution and configuration while still maintaining accuracy under a deep stall situation. It was found that the spanwise length of the computational domain had a crucial influence on the prediction of lift and drag. At a stall angle of attack, the aerodynamic force could not be accurately predicted when the airfoil span was reduced to 0.3 chords, even with a high grid density. The periodicity of the spanwise flow was clearly visible when the airfoil span was extended to 5 chords. Full article
(This article belongs to the Special Issue Advances in Computational Wind Engineering and Wind Energy)
►▼ Show Figures

Figure 1

20 pages, 8895 KiB  
Article
Aerodynamic Shape Optimization of a Square Cylinder with Multi-Parameter Corner Recession Modifications
by Zhaoyong Wang, Chaorong Zheng, Joshua Adriel Mulyanto and Yue Wu
Atmosphere 2022, 13(11), 1782; https://doi.org/10.3390/atmos13111782 - 28 Oct 2022
Cited by 4 | Viewed by 1956
Abstract
Corner modifications can reduce wind loads acting on supertall buildings and modify the corresponding flow structures. The present study investigated the aerodynamic shape optimization of the corner recession square cylinders with multiple geometric parameters in a large design space via the GA-GRNN surrogate [...] Read more.
Corner modifications can reduce wind loads acting on supertall buildings and modify the corresponding flow structures. The present study investigated the aerodynamic shape optimization of the corner recession square cylinders with multiple geometric parameters in a large design space via the GA-GRNN surrogate model updating-based multi-objective optimization framework. Six typical optimal aerodynamic shape sections M1~M6 were selected from the Pareto optimal front, and the effects of multiple geometric parameters of these sections on the aerodynamic performance and flow field were analyzed. The results showed that the present multi-objective optimization framework can significantly reduce the computational load and time cost, and significantly improve the optimization efficiency in solving complex engineering problems. The optimal corner recession sections can obviously reduce the mean drag coefficient CD and root mean square lift coefficient CσL while significantly increasing the Strouhal number St of the square cylinder, and it is concluded that the aerodynamic shape optimization can significantly improve the aerodynamic performance of square-sectional supertall buildings. When compared with the benchmark section, the CD and CσL of the optimal section M1 can be reduced up to 45.7% and 84.5%, respectively. Based on the analysis of the flow structures around the optimal sections, the flow mechanism can be attributed to the fact that the corner recession modifications postpone the flow separation, and deflect the separated shear layer towards the side surfaces and suppress the development of vortex shedding in the wake, which leads to significant elongation of the wake length and reduction of the width of the recirculation region. The proposed multi-objective optimization framework in this study can provide an important reference for the aerodynamic shape optimization of building structures and relevant studies. Full article
(This article belongs to the Special Issue Advances in Computational Wind Engineering and Wind Energy)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-15
Back to TopTop