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The wind velocity and surface pressure of the model of a group of urban blocks made of low-rise buildings with a high-rise building in the center were measured using a wind tunnel. Not only the time-averaged velocity field, but also the turbulent statistics, i.e., the turbulent kinetic energy, normal component of the Reynolds stresses, gust factor (GF), and probability density function (PDF), and power spectrum density (PSD) of instantaneous velocity components were investigated. Based on the results, the impact of high-rise buildings on the general flow structure and the surrounding pedestrian wind environment was discussed. The presence of high-rise buildings drastically changes the pedestrian wind environment around buildings in terms of time-averaged and instantaneous flow properties due to the complex interaction between the flows around the building and in and above the surrounding street canyons. High-rise buildings create a large GF region where the downwash flow and the street flow collide. A clear correlation between the GF and the time-averaged horizontal velocity magnitude was observed regardless of the height of the central building. The PDF of instantaneous velocity components around the high-rise building was characterized by a large skew not only near the building corners of the high-rise building but also on the surrounding streets. The high-rise building produces large PSDs of the velocity fluctuation mponents, particularly near the upwind corner at a high frequency and on the surrounding street at an intermediate frequency. Furthermore, the results of the time-averaged and instantaneous flow properties provide a useful database for computational fluid dynamics (CFD) validation and model development studies.

In computational fluid dynamics (CFD) simulations of airflow in built environments, the porous-jump model is commonly used to represent extremely thin porous windbreak fences, which have much smaller sizes than the neighborhood computational cells. However, owing to the limited quantitative validation studies that include turbulence characteristics, no clear guidelines exist on modeling such thin porous fences in CFD simulations. In this study, pressure loss coefficients of porous materials with various porosity values and opening shapes were determined using a small wind tunnel while the velocity and turbulence statistics behind the fences were measured in an atmospheric boundary layer wind tunnel. Two separate CFD models based on the Reynoldsaveraged Navier–Stokes equation and porous-jump models were used to mic the airflow in each wind tunnel and then they were validated using the experimental results. The results showed that the pressure loss was accurately predicted by CFD simulations. For wire-mesh fences, a good agreement was obtained between experimental and numerical results for the mean streamwise velocity and turbulent kinetic energy (TKE), whereas the velocity deficit and TKE were overestimated and underestimated, respectively, for the non-wiremesh fences. This study can be used to improve the performance of thin porous windbreak fences.

In this study, wind tunnel experiments were conducted to determine the relationship between the texture of road surfaces and the threshold wind velocity that causes the movement of sparsely distributed gravels. We proposed a method that uses analogous particles having lower densities compared to actual gravel, considering the threshold velocity for gravel is too large to imitate in a typical wind tunnel. We first conducted a preliminary experiment, which confirmed that the threshold velocity for denser prototype particles can be estimated from the density ratios of the analogous and prototype particles. Furthermore, a main experiment was conducted to analyze different road surface textures using pumice stones, as their particle density is less than that of gravels. The results showed that coarser road surfaces exhibited larger threshold velocities for the gravel movement. Quantitatively, the coarsest asphalt concrete exhibited a threshold velocity that was 2.5 times larger than that of the smoothest surface (cement concrete). However, surface coarseness was dependent on the particle size, whereas the effect of particles trapped by the gaps in surfaces was more dominant than the fluid force acting on the particles of a relatively coarse surface. This force balance is reversed for a smooth surface, which indicates the possibility of determining threshold friction velocity from the particle size and surface texture coarseness.