Abstract
Since the 1970s, winglet devices have been widely utilized to ameliorate the aerodynamic performance of aircraft
by increasing L/D of the wing configuration. Modern designs can change cant angle during the flight in order to maximize their
benefits to all flight states, which is limited to on-design points in passive/fixed designs. This paper discusses the effects of
atmospheric and operating parameters on the aeroacoustics of a double-swept wing configuration facilitated with a rotary
winglet device. To do so, the turbulent flow is simulated via 3D RANS formulation and k-ω SST turbulence model. Then,
machine learning tools, consisting of Multi-layer Perceptron (MLP) neural networks and supervised classification methods are
used to generate scaler regression models based upon numerical aeroacoustic datasets. Moreover, deep Convolutional Neural
Network (CNN) is used to estimate the aeroacoustic field. The results depicted that changing the cant angle significantly affects
the aerodynamic noise of the wing configuration regardless of operating conditions. Secondly, artificial intelligence is a practical
modeling tool for acoustic parameters with reasonable accuracy and cost compared with RANS simulations.
Abstract
The NIST-UWO database has pressure coefficient time-history data, encompassing various roof slopes, eave
heights, terrain exposures, and wind angles. Utilizing SAP2000 to obtain the influence coefficients (IC) for eave and ridge
moments and displacements, corresponding critical moment and displacement coefficients were computed for three different
gable roof pitch (1/4:12,1:12, and 3:12) models each having three different eave heights of 7.32 m, 9.75 m, and 12.19 m, in two
terrain types – open country and suburban. The study utilized Decision Tree (DT), Random Forest (RF), and Extreme Gradient
Boosting (XGBoost) to predict these load effect coefficients for potential missing wind angles. Additionally, the study compared
these machine learning models' performance in handling exposure categories as numerical values (roughness length) and
categorical variables (represented via one-hot encoding). The results showed that all models performed consistently well,
regardless of exposure category representation, with XGBoost demonstrating better performance compared to RF and DT.
Key Words
machine learning; NIST-UWO aerodynamic database; wind load effects
Address
Manoj Adhikari:Department of Civil and Environmental Engineering, Rensselaer Polytechnic Institute, Troy, NY, U.S.A.
Christopher W. Letchford:Department of Civil and Environmental Engineering, Rensselaer Polytechnic Institute, Troy, NY, U.S.A.
Abstract
Super-large cooling tower is a kind of typical high-rise, large-span and wind-sensitive structure. The interaction
between the lower foundation structure of the tower and soil mass influences wind-induced vibration performances of the tower
body significantly. Nevertheless, the structure-pile foundation-soil coupling effect of the cooling tower is ignored in existing
norms. The value of wind-induced vibration coefficient cannot accurately reflect the wind-induced vibration performances of the
structure under wind load. Three different models of structure-pile foundation-soil finite element coupling effects were built for a
systematic quantitative study of influences of tower structure-soil coupling modeling techniques on the dynamic characteristics
and wind-induced vibration responses of the cooling tower. These three models are direct solidification between the herringbone
columns and soil mass (Model I), coupling effect of herringbone columns, circumferential base (beam element) and pile
foundation (soil spring) (Model II), and coupling effect of herringbone columns, circumferential base (solid element), pile
foundation (base element) and soil mass (Model III). A comparative analysis on displacement of tower body and responses to
internal force under wind loads was carried out. The value standard of wind-induced vibration coefficient under different target
responses was discussed. Results demonstrate that the structural fundamental frequency of Model I is 0.884Hz, while the
fundamental frequencies of Model II and Model III are decreased by 7.89% and 18.8%. For the maximum displacement of
cooling tower under dead load and static wind load, Model I <Model II<Model III.The maximum error of response extremum of
three cooling tower models to the meridian axial force under pulsation wind load is only 2.65%. The maximum means of radial
displacement and circumferential bending moment are Model I<Model II< Model III.The Model I shows the lowest wind
induced vibration coefficient under the response goals of radial displacement and circumferential bending moment, followed by
Model II and Model III successively. On this basis, a value standard of two-dimensional interval wind-induced vibration
coefficient for super-large cooling tower considering structure-pile foundation-soil coupling effect was established, which could
provide scientific reference for wind-resistant design of similar structures.
Abstract
Surface roughness reflects the obstructive effect of surface features on atmospheric turbulence, and is a key factor
influencing the characterization of the near-surface wind field. In this study, the method for measuring roughness in the
atmospheric boundary layer was introduced to investigate the effect of surface roughness on the wind profile shape and
turbulence characteristics of downbursts. Different roughness landforms in nature were simulated by arranging roughness
elements with various sizes and distribution densities. Subsequently, wind field experiments of the downburst outflow section
were carried out. The results show that roughness has a strong decay effect on streamwise wind speed; as the surface roughness
increases, the vertical height corresponding to the maximum wind speed increases. Meanwhile, the turbulence intensity in the
inner layer of the wall jet increases significantly, but the turbulence intensity in the outer layer decreases gradually. To address
the problem that the existing empirical models of vertical wind profiles for horizontal wind speeds of downburst are unsuitable
for all rough landforms, equations for fitting vertical wind profiles for different rough landforms are proposed. In addition, the
surface roughness significantly affects the Reynolds stress in the inner layer of the wall jet. The analysis reveals that the wall jet
still follows a dimensionless law in high Reynolds number tests with different surface roughness. The study further provides
some references for downburst wind loads considering roughness.
Key Words
surface roughness; wall jet; wind field characteristic; wind profile; wind tunnel test
Address
Yongli Zhong:School of Civil and Hydraulic Engineering, Chongqing University of Science and Technology, Chongqing 401331, China
Yichen Liu:School of Civil and Hydraulic Engineering, Chongqing University of Science and Technology, Chongqing 401331, China
Bowei Liu:School of Civil and Hydraulic Engineering, Chongqing University of Science and Technology, Chongqing 401331, China
Xiangjun Tan:School of Civil and Hydraulic Engineering, Chongqing University of Science and Technology, Chongqing 401331, China
Zhitao Yan:1)School of Civil and Hydraulic Engineering, Chongqing University of Science and Technology, Chongqing 401331, China 2)School of Civil Engineering, Chongqing University, Chongqing 400045, China
Xiaogang Yang:School of Civil and Hydraulic Engineering, Chongqing University of Science and Technology, Chongqing 401331, China
Abstract
Wind loads on tall buildings equipped with innovative Porous Double-Skin Facade (PDSF) systems of various
porosities were experimentally studied on a small-scale building model. The focus was on integral aerodynamic loads of a tall
building equipped with PDSF systems of the 25%, 50% and 65% porosity. This structural design is highly relevant for
engineering practice as it encompasses the range of the PDSF porosities that may occur in practice. The building model
characterized by a smooth surface was assessed as a reference case. The analysis was performed for suburban wind conditions as
a representative of atmospheric conditions characteristic of tall buildings. Wind conditions were studied at the 0° <<a < 45° flow
incidence angles. Aerodynamic loads on the building model were analyzed using a high-frequency force balance. Pressure
distribution on the inner (non-porous) facade was studied based on pressure measurements. The results obtained in these unique
configurations reveal some important findings relevant both for design practice and scholarly research. The most notable results
indicate that the maximum mean across-wind moment and its respective maximum standard deviation are lower for all studied
PDSF systems compared to the smooth building model. The effect of the PDSF systems on the mean along-wind moment and
the respective standard deviation of the building models is negligible. This indicates that the PDSF systems on tall buildings of
the studied (bluff body) type do not yield any adverse aerodynamic effects regarding both major aerodynamic moments. On the
contrary, the aerodynamic effects observed are favorable, thus a clear benefit for engineering design of tall buildings. In addition
to the exhibited integral aerodynamic effects, there are also some important local features to be noted. There is the effect of the
PDSF porosity on surface pressure distribution on the inner building model surface, where the less porous outer facade yields a
decrease in the mean pressure on the windward inner facade, as much as 20%. In general, there are no adverse effects of the
PDSF systems on the overall wind loads on tall buildings, while they may even benefit from the PDSF systems regarding their
aerodynamic characteristics.
