Abstract:In this article we describe the details of an ABLE-LBM (Atmospheric Boundary Layer Environment-Lattice Boltzmann Model) validation study for urban building array turbulent flow simulations. The ABLE-LBM large-eddy simulation results were compared with a set of 3D magnetic resonance image (MRI) velocimetry data. The ABLE-LBM simulations used the same building layout and Reynolds numbers operated in the laboratory water channel. The building set-up was an evenly spaced orthogonal array of cubic buildings (height… Show more
“…The numerical model used in this study is a newly developed microscale atmospheric boundary layer model that is called the atmospheric boundary layer environment-lattice Boltzmann model (ABLE-LBM). It is a four-dimensional prognostic LES model based on an MRTLBM [39][40][41][46][47][48]. It is used for fine-scale (temporal: seconds; spatial: meter to tens of meters) atmospheric boundary turbulent flows and the associated transport and dispersion of temperature, moisture, and other scalars (aerosol, smoke).…”
Section: The Able-lbm Modelmentioning
confidence: 99%
“…Instead of numerically solving the NSE, the LBM is a mesoscopic method that tracks the PDF of air parcel (or fictitious particle) motion and collision in certain prescribed sample directions that connect to neighboring computation grids. It can start with the evolution equation of the MRTLBE coupled with the forcing term [39][40][41][46][47][48]…”
Section: The Able-lbm Modelmentioning
confidence: 99%
“…To our knowledge, this is the first effort to develop and validate the capability of the MRTLBM in the simulation of a forest shelterbelt. We have developed an atmospheric boundary layer environment model using the MRTLBM, using this model to simulate the laboratory case of stratified turbulent flows over a ridge terrain [46] and around and overhead urban buildings [47,48]. The results show that this is an accurate and fast model for urban turbulent flow modeling using a graphical processing unit (GPU).…”
Using porous wind barriers for the microclimate modification of agricultural lands, urban areas, and surrounding roads is a ubiquitous practice. This study establishes a new method for numerically modeling the turbulent flow in and around forest shelterbelts using an advanced multiple-relaxation-time lattice Boltzmann model (MRTLBM). A detailed description is presented for a large eddy simulation (LES) of turbulent winds by implementing barrier element drag force in the MRTLBM framework. The model results for a forest shelterbelt are compared with a field observational dataset. The study indicated that our implementation of drag force in MRTLBM is an accurate method for modeling turbulent flows in and around forest patches. Sensitivity analyses of turbulent flow related to the shelterbelt structure parameters and wind directions are also carried out. The analysis indicated that the optimal wind shelter effect in reducing the mean wind speed and turbulent kinetic energy is maximized using a narrow, medium porosity shelterbelt, with the wind direction perpendicular to the shelterbelt. These conclusions are in agreement with other observational and modeling studies. Finally, the computational time of a central processing unit (CPU) and graphics processing unit (GPU) was compared for a large domain with 25 million grids to demonstrate the MRTLBM advantage of LES in regards to computational speed with a mixed forest and building environment. The GPU is approximately 300 times faster than a CPU, and real-time simulation for this large domain is achieved using the Nvidia V100 GPU.
“…The numerical model used in this study is a newly developed microscale atmospheric boundary layer model that is called the atmospheric boundary layer environment-lattice Boltzmann model (ABLE-LBM). It is a four-dimensional prognostic LES model based on an MRTLBM [39][40][41][46][47][48]. It is used for fine-scale (temporal: seconds; spatial: meter to tens of meters) atmospheric boundary turbulent flows and the associated transport and dispersion of temperature, moisture, and other scalars (aerosol, smoke).…”
Section: The Able-lbm Modelmentioning
confidence: 99%
“…Instead of numerically solving the NSE, the LBM is a mesoscopic method that tracks the PDF of air parcel (or fictitious particle) motion and collision in certain prescribed sample directions that connect to neighboring computation grids. It can start with the evolution equation of the MRTLBE coupled with the forcing term [39][40][41][46][47][48]…”
Section: The Able-lbm Modelmentioning
confidence: 99%
“…To our knowledge, this is the first effort to develop and validate the capability of the MRTLBM in the simulation of a forest shelterbelt. We have developed an atmospheric boundary layer environment model using the MRTLBM, using this model to simulate the laboratory case of stratified turbulent flows over a ridge terrain [46] and around and overhead urban buildings [47,48]. The results show that this is an accurate and fast model for urban turbulent flow modeling using a graphical processing unit (GPU).…”
Using porous wind barriers for the microclimate modification of agricultural lands, urban areas, and surrounding roads is a ubiquitous practice. This study establishes a new method for numerically modeling the turbulent flow in and around forest shelterbelts using an advanced multiple-relaxation-time lattice Boltzmann model (MRTLBM). A detailed description is presented for a large eddy simulation (LES) of turbulent winds by implementing barrier element drag force in the MRTLBM framework. The model results for a forest shelterbelt are compared with a field observational dataset. The study indicated that our implementation of drag force in MRTLBM is an accurate method for modeling turbulent flows in and around forest patches. Sensitivity analyses of turbulent flow related to the shelterbelt structure parameters and wind directions are also carried out. The analysis indicated that the optimal wind shelter effect in reducing the mean wind speed and turbulent kinetic energy is maximized using a narrow, medium porosity shelterbelt, with the wind direction perpendicular to the shelterbelt. These conclusions are in agreement with other observational and modeling studies. Finally, the computational time of a central processing unit (CPU) and graphics processing unit (GPU) was compared for a large domain with 25 million grids to demonstrate the MRTLBM advantage of LES in regards to computational speed with a mixed forest and building environment. The GPU is approximately 300 times faster than a CPU, and real-time simulation for this large domain is achieved using the Nvidia V100 GPU.
“…The high efficiency of LBM has made it a good alternative to study such problems, and a range of such studies can be found in Refs. 217–220. Figure 24 shows the time averaged velocity contours of flow around urban building arrays calculated by using BB-LBM.Figure 24.Time averaged velocity contours of flow around urban building arrays by using BB-LBM: isolated cube (left) and array of cubes twice as high as central cube (right).…”
Fluid-structure interaction (FSI) is a very common physical phenomenon which extensively exists in nature, human daily life and many engineering applications. The lattice Boltzmann method (LBM) is an alternative of solving Navier–Stokes equations to obtain complex fluid dynamics. Since the proposal of lattice Bhatnagar–Gross–Krookmodel, the LBM has been improved and applied to various complex flows ranging from laminar flow to turbulent flow and Newtonian flow to non-Newtonian flow. To handle the associated FSI, the bounce-back scheme was proposed and then the immersed boundary method (IBM) was incorporated into the LBM for the simplicity and robustness of IBM in handling complex and moving geometries and the significant efficiency of LBM in solving fluid dynamics. In recent years, the combined frameworks of LBM, that is, bounce-back–lattice Boltzmann method and immersed boundary–lattice Boltzmann method have witnessed a significant development and the successful applications can be found in a range of physical problems such as flow around bluff bodies, flapping wings, wind turbines, aeroacoustics, sea wave modelling and et al. In this paper, the recent progress of LBM and some typical applications involving FSI are reviewed.
“…Schröder [18] conducted an LBM case to validate the wind flow around a typical square block at low Reynolds numbers (Re 2000~8000), and found that the LBM can effectively simulate the flow separation around the building and the unsteady flow separation in the downstream wake region. Wang [19] also conducted an LBM validation study based on the flow field measurements of low Reynolds number square arrays. They analyzed the characteristics of turbulent wind fields around the building under different incoming wind directions and found that LBM with GPU-based large-scale computation can achieve real-time reliable simulations with millions of grid points.…”
It is very important for the wind-resistant design of high-rise buildings to assess wind-induced vibrations efficiently. The Lattice Boltzmann Method-based Large Eddy Simulation and Fluid–Structure Interaction techniques are used to identify the surface wind pressure and wind-induced dynamic response of a CAARC standard high-rise building. Compared with wind tunnel tests, a detailed analysis of the accuracy of simulated wind pressures and base moments of the CAARC model are discussed under multiple wind direction angles. The differences between one-way and two-way Fluid–Structure Interaction simulations are compared under two different reduced wind velocities. The research results show that the simulated mean surface wind pressures of building under seven wind direction conditions have an error within 15% compared to probe measurements, and the average and root mean square base bending moments agree well with the wind tunnel tests. The top transverse wind-induced vibrations of the buildings are significantly larger when the reduced wind velocity reaches 4.6, indicating that aerodynamic damping effects on structural responses should not be overlooked. The research findings of this article provide valuable technical references for the application of LBM methods in the wind load effect assessments of high-rise buildings.
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