Parametric uncertainty quantification of SST turbulence model for a shock train and pseudo-shock phenomenon

Zeng, Fangfang; Li, Jinping; Wang, Yu; Sun, Meng; Yan, Chao

doi:10.1016/j.actaastro.2022.05.002

Cited by 16 publications

(6 citation statements)

References 37 publications

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“…In this study, these computations were used to solve the incompressible Reynoldsaveraged Navier-Stokes equations and shear-stress transport (SST) k-ω turbulence model to obtain accurate results. The model has been proven to perform well in simulations of the attached flow to the structure [32]. In this study, the SST k-ω turbulence model was used in the wall boundary layer.…”

Section: Numerical Calculation Methods and Boundary Conditionsmentioning

confidence: 99%

Analysis of the Influence of Antenna Arrangement Parameters on the Aerodynamic Performance of Telecommunication Towers

Jia,

Huang,

Liu

et al. 2024

Applied Sciences

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With the widespread adoption of 5G telecommunication networks, to reduce construction costs, it has become necessary to add new equipment or antennas to existing 4G and 3G telecommunication towers. This significantly changes the original aerodynamic shape of the towers, leading to a substantial increase in the wind load, which may exceed the original structure’s bearing capacity and pose a threat to the structure’s safety. This study employed three-dimensional numerical simulation methods to systematically investigate the impact of various antenna arrangement parameters, such as the arrangement number, arrangement form, and arrangement layers, on the wind load characteristics of telecommunication towers. The findings revealed that the antenna arrangement form significantly affects the sensitivity of the telecommunication tower’s wind load to the wind direction, with more uniform antenna arrangements resulting in less sensitivity. Compared to the drag coefficient and the windward base overturning moment coefficient, the tower’s lateral force coefficient and the crosswind base overturning moment coefficient are more sensitive to changes in the wind direction. The change patterns in the tower’s overturning force coefficient and overturning moment coefficient with the antenna arrangement number are essentially the same. However, as the antenna arrangement number increases, the growth rate of the tower’s overturning moment coefficient is about twice that of the overturning force coefficient. The tower’s overturning force coefficient increases approximately linearly with the increase in antenna arrangement layers, while the tower’s overturning moment coefficient exhibits a nonlinear increase with the increase in antenna arrangement layers. The rate of increase in the wind load with the antenna arrangement layers is significantly greater than that with the antenna arrangement number. Thus, to reduce wind load, it is advisable in practical engineering applications to increase the antenna arrangement number per layer, thereby reducing the antenna arrangement layers. The study also summarized a calculation method for the structural wind load of telecommunication towers, taking into account the influence of antenna arrangement parameters, providing a reliable basis for the structural design and safety assessment of telecommunication towers in practical engineering.

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Section: Numerical Calculation Methods and Boundary Conditionsmentioning

confidence: 99%

Analysis of the Influence of Antenna Arrangement Parameters on the Aerodynamic Performance of Telecommunication Towers

Jia,

Huang,

Liu

et al. 2024

Applied Sciences

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“…where T represents the temperature with a unit of k; λ is the heat transfer coefficient of the fluid; c p denotes the specific heat capacity, and S T is the source term. SST κ-ω turbulence model is widely used in the research of turbomachinery, which combines the advantages of the standard κ-ε turbulence model in simulating the nearwall flow and the standard κ-ω turbulence model in simulating the flow outside the boundary layer [26]. The SST κ-ω turbulence model was more suitable for simulating the complex vortex flows in compressors from the perspectives of computation accuracy and consumption.…”

Section: Numerical Simulation Methodsmentioning

confidence: 99%

Numerical Simulation on the Influence of Inlet Flow Characteristics on the Performance of a Centrifugal Compressor

Huang

Chen

et al. 2023

Energies

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Although inlet bent pipes are usually adopted due to limited installation space, the influences of different bend pipes on the inlet flow characteristics and performance of centrifugal compressors are still unclear. The numerical simulation of a centrifugal compressor is established and validated by experimental results with the case of a straight inlet pipe. Then, the internal flow characteristics of the centrifugal compressor with a 90-degree bent pipe (p90) and Z-shaped bent pipe (pz) are simulated and discussed. The results show that the adoption of two inlet bent pipes reduces the performance of the centrifugal compressor to a certain extent, which reduces more greatly with pz, with a maximum reduction of 6.82% in pressure ratio and 14.83% in efficiency, respectively. The pressure ratio and efficiency reduction of the centrifugal compressor both increase with the increment of distortion degree, which maintains the increasing trend as the flow rate increases, and the maximum distortion degree of p90 and pz reaches 0.0351 and 0.0479, respectively. The reduction degree of the pressure ratio shows a power–law relationship with the distortion degree, while the reduction degree of efficiency shows an exponential relationship with it. The flow characteristics at the outlet section of the inlet pipe affect the flow field distribution at the inlet of the impeller, and the distortion area ranges of the total pressure and axial velocity at the inlet of the impeller are near 72°–144° in the circumferential direction for p90, while those of pz are close to 108°–180° and 288°–360°. When the flow with a high distortion degree enters the impeller, a large area with high turbulent kinetic energy is formed in the downstream flow channel, resulting in an increase in the flow loss.

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“…This research makes use of a turbulence model known SST (Shear Stress Transport) [12]. Numerous researchers have tested and validated k-ω SST model, and each one of them has come to the conclusion that the model produces accurate results [13][14][15]. For the purpose of solving the fluid flow field, the RANS solver that is included in ANSYS CFX is used.…”

Section: Methodology 21 Cfd Governing Equationmentioning

confidence: 99%

CFD Analysis into the Resistance Characteristics of Remotely Operated Vehicles when Submerges Under Water and Sails on the Surface

Aryawan¹,

Utama²,

Hermawan³

et al. 2023

CFDL

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Remotely operated (underwater) vehicles, commonly known as ROVs, have a wide range of uses in the marine industry, including maintenance and repair. The research examines ROV pressure and resistance, is less likely at the present time. Furthermore, the design and operation of this remotely operated vehicle (ROV) rely heavily on accurate measurements of hydrodynamic loads. Computational Fluids Dynamic (CFD) technique makes it possible to obtain an accurate estimate of the forces that are being applied by the flow around the ROV hull. In this paper, an investigation of the resistance and pressure that the ROV experiences when on the surface and while submerged to a depth of 100 meters is presented. In addition, ROV was evaluated at several speeds, ranging from 0.5 to 1.5 metres per second. The speed of the ROV that is being evaluated will increase when significant impediments are introduced into the environment. This flips the direction of the pressure that is applied to the ROV hull. The CFD approach demonstrates the resistance that is generated on the ROV hull is, for the most part, affected by the speed at which it is moving. In free surface conditions, the average increase in resistance was 78.91%, and in submerged conditions, it was 74.24%. Nevertheless, the variation in test depth is where the main impact of the pressure value can be seen in the CFD simulation. Simulations conducted on the free surface indicate that the pressure on the ROV hull is about 1x10-3 kPa, whereas simulations conducted at a depth of 100 metres below the sea surface indicate that the pressure is approximately 972 kPa

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Parametric uncertainty quantification of SST turbulence model for a shock train and pseudo-shock phenomenon

Cited by 16 publications

References 37 publications

Analysis of the Influence of Antenna Arrangement Parameters on the Aerodynamic Performance of Telecommunication Towers

Analysis of the Influence of Antenna Arrangement Parameters on the Aerodynamic Performance of Telecommunication Towers

Numerical Simulation on the Influence of Inlet Flow Characteristics on the Performance of a Centrifugal Compressor

CFD Analysis into the Resistance Characteristics of Remotely Operated Vehicles when Submerges Under Water and Sails on the Surface

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