Wind Engineering Joint Usage/Research Center FY2015 Research Result Report

Wind Engineering Joint Usage/Research Center FY2015 Research Result Report Research Field: Wind disaster and wind resistant design Research Period: FY2015 Apr. ~ FY2016 Mar. Research Number: 152004 Research Theme: Interference effect on a square prism based aeroelastic experiments Representative Researcher: Yuan-Lung Lo Budget [FY2015]: 258,000Yen Abstract This paper intends to address that the significant interference effect between two high-rise not only comes from the upstream buildings but also the building existing in the downstream area, especially when the two buildings are close to each other. Aeroelastic vibration test and high-frequency force balance tests were conducted for two identical square prism models with an aspect ratio of 8 under a turbulent boundary layer flow. Critical locations for interfering buildings were discussed and shown with altered force spectrum characteristics and different patterns of response trajectories. Finally, an idealized 2D numerical simulation of CFD was tried for the simulations of some critical cases. Although the absolute values from CFD results could not perfectly be compared with the experimental results, the simulated vorticity movement generated from both buildings could provide an intuitive way for the enhancement of the downstream interference mechanism. 1. Introduction With the unbalanced and extreme growth in the metropolitan areas in the world, grouped high-rise buildings have been marked as one representative style of a big city. Interference effects caused by neighboring buildings are therefore especially concerned for a further improved wind load resistant design rather than assuming isolated buildings. However, due to its complex nature and huge number of disturbances may involve, the interference effects have not been clearly and precisely codified into regulations for practical use. The interference effect problems are still one of the popular and difficult research topics in wind engineering field. For the past several decades, researchers have adopted various methodologies to investigate on the interference effects on overall or local wind loads of high-rise buildings. Variables that may affect the interference mechanism have been widely discussed, such as the approaching flow characteristics, wind directions, building s relative location, cross sectional shape, aspect ratio, Scruton number, Strouhal number, modal frequency, mode shape, et al. (Saunders and Melbourne, 1979; Surry and Mallais, 1983; Bailey and Kwok, 1985; Blessmann and Riera, 1985; Kareem, 1987; Taniike and Inaoka, 1988; Sakamoto and Haniu, 1988; Taniike, 1991, 1992; Zhang et al., 1994, 1995; Sun et al., 1995; Khanduri et al., 1998, 2000; Thepmongkorn et al., 2002; Tang and Kwok, 2004; Xie and Gu, 2004, 2007; Huang and Gu, 2005; Zhao and Lam, 2008; Lam et al., 2008, 2011; Hui et al., 2012, 2013; Fang et al., 2013; Kim et al., 2011, 2013, 2015; Mara et al., 2014; Yu et al., 2015;). In general, wind tunnel tests including simultaneous pressure scanning, base force measuring and response detecting were widely adopted and accumulated a huge amount of data for references. Besides the commonly discussed buildings, say the square prisms or rectangular prisms, important structures such as grouped cylindrical prisms, chimneys, large storage tanks or cladding structures were also involved in interference effect discussions (Kareem et al., 1998; Niemann and Kasperski, 1999; Wang et al., 2014; Uematsu et al., 2015). With the rapid development of computer technology, artificial neural network and database system have been used to further extend the experimental data to more application possibilities; for instance, the evaluation of equivalent static wind load due to interference effect, the extension of interference effect range, the simulation of interfered

wind pressure signals or spectra, the prediction of different models under different flow conditions (English, 1990; Khanduri et al., 1997; English and Fricke, 1999; Zhang and Zhang, 2004). Improvement of numerical simulation technology in calculation of fluid dynamics (CFD) greatly helped the explanation in interference mechanism formation and has gradually become a replacement because of the enormous parametric analysis works based on wind tunnel tests (Zhang et al. 2005; Zhang and Gu, 2008). Other modern facilities, such as Dynamic Particle Image Velocimetry (DPIV), were also adopted for a more intuitive observation tool to enhance the understanding of the mechanism formation (Hui et al., 2013a). Among the involved literatures, high-frequency force balancer and pressure scanning schemes were the most adopted ways for data accumulation. Interference effects were investigated focusing on how the wind force is amplified or shielded and how significant the local pressure may be for the cladding designs. Further, the discussions were mostly focused on the upstream interference effects. The downstream interference effect was seldom discussed and was lack of experimental data for comparisons. The most mentioned finding in downstream interference effect was by Bailey and Kwok (1985), who conducted series of vibration tests and found that the downstream building could initiate a different vibrating motion due to the rhythmic channeling between two buildings. Several research works might show how the wind forces being altered; however, such downstream interference phenomenon was generally ignored since the vibration behavior can only be detected through vibration tests. This study intends to investigate the downstream interference effects by conducting the aeroelastic test and high-frequency force balance test under a suburban turbulent boundary layer flow. Two identical square prisms are chosen as principal and interfering buildings. Fifteen interference locations and seven flow velocities are selected for upstream and downstream interference effect investigations. Response trajectories and wind force spectra are used to explain how different the upstream and downstream interference effects are. Furthermore, 2D numerical simulation is carried out to enhance the understanding of the interference mechanisms when the interfering building is located at downstream area. 2. Experimental Setup Both the high-frequency balance test and vibration test were conducted in the 18 1.8 2.2 m boundary layer wind tunnel of Wind Engineering Research Center at Tokyo Polytechnic University (Photo 1). A 1/400 scale turbulent flow over a sub-urban terrain with a power law index exponent for mean velocity profile of 0.19 was simulated by properly equipped spires, saw barriers, and roughness blocks (Fig. 1). For the vibration test, a rigid aero-elastic square prism model was manufactured for the role of the principal building (Fig. 2). The size of the model was 0.07 m in both width ( B ) and depth ( D ) and 0.56 m in height ( H ), which made it the aspect ratio ( H / B ) f was identified as 6.3 Hz in both along-wind ( x ) equals 8. The fundamental frequency 0 and across-wind ( y ) directions based on free vibration tests; the structural damping ratios, ξ and ξ, were estimated 0.77% in x and 0.73% in y by random decrement technique. x y The generalized mass M was 0.15 kg and the mass-damping parameter was determined by 2 δ = Mξ / ρbh (1) where ρ is the air density. For the aero-elastic model in this study, the mass-damping parameter was 0.35, which was slightly lower than the range of typical full scale high-rise buildings (0.4 0.6) and could be converted to a Scruton number of 1.05 based on the linear mode shape assumption of its rigid elastic feature. The displacement signals were recorded by two laser sensors for x and y directions in the sampling rate of 550 Hz. The sampling length was 16,384 for one sample record and the ensemble size was 15 in order to obtain a statistical result. For the high-frequency force balance test, the square prism model was fixed and un-flexible to the balancer for both horizontal forces measuring in the same sampling conditions. Instantaneous wind velocity was recorded at the model height for further

normalizations. The interfering building was made of acrylic and had the identical size of the principal building; unlike the principal model, this interfering model was made rigid and un-flexible providing only the disturbed flow comes from the upstream or the downstream. The interference locations of interest were focused on those considered significant in general (Fig. 3). Both models were orientated with one face normal to the wind. 3. Experimental Results 3.1 Interfered response characteristics The measured interfered responses are normalized and expressed in terms of buffeting factors, which was suggested by Saunders and Melbourne (1979), against the reduced velocity. The buffeting factor is defined as BF = σ / σ (2) x,interfered x,isolated where RMS response is the standard deviation value of rooftop response calculated directly from the time signal. The reduced velocity is calculated as U = U /( fb) (3) r H 0 where U is the mean wind velocity at the model height. In this study, 15 locations for H interfering model and 7 reduced velocities ( U = 3.1, 6.2, 9.3, 10.8, 12.5, 15.9 and 19.3) r together provided in total 105 cases for the interfered response characteristics. However, it was found during the experiments that 5 cases out of 105 showed distorted signals (Fig. 4). In these 5 cases, the principal model was observed to vibrate so severely that the laser sensor frequently missed its targeting point on the gimbal and resulted in such distorted signals. Fortunately, the helical strings connected to the gimbal were checked to be still in their well-performed conditions, which means although the estimations from these 5 cases may lose the accuracy but the tendency can still be intuitively observed. 3.1.1 Isolated model The across-wind RMS response at the rooftop of the isolated model exhibits the commonly known vortex-induced vibration phenomena due to its small mass-damping parameter in Fig. 5 (Kawai, 1992). The vibration was so dominated by the large amplitude motion due to vortex shedding phenomena except for the first two lower reduced velocities. On the other hand, the along-wind response was relatively small and could be predicted proportional to the reduced velocity. In this study, the vortex-induced response of the isolated model was recorded with no failure occurred to the whole system during the experiments; therefore the denominator in Eq. (2) could be substituted for different reduced velocities for normalization process. 3.1.2 Buffeting factors in responses The along-wind and across-wind buffeting factors of the principal model under interference from 15 locations are presented in Fig. 6 and 7, respectively. Along-wind buffeting factors For interference from upwind locations, amplification in responses increases with the reduced velocity and approaches to a maximum value of 1.4. For interference from side locations, the interfering model makes almost no difference except a slight fluctuation when the reduced velocity comes close to 10, which may be considered a disturbance from the across-wind responses. For those cases with interference from oblique-upwind locations, a buffeting factor of 1.6 is indicated at (3, 3), which is frequently considered as one critical location resulting significant amplification in along-wind responses. It is also indicated that the case at (2, 2) at higher reduced velocities is failed to record due to the miss-pointing of laser sensor. However, it was supposed to be in a severe vibration motion as that at (3, 3).

When the interference comes from the downstream, a clear increasing tendency with the increase of reduced velocity is indicated for the oblique-downwind locations; meanwhile, for the interference from the downwind locations, a nearly constant factor of 1.0 concludes almost no interference happening. The case at (-2, 0) at higher reduced velocities is again failed to record. Across-wind buffeting factors For the across-wind responses, interference effect makes quite different patterns at different reduced velocity levels. The amplification or reduction in buffeting factors can be found to be no larger than 20% at the first lower reduced velocities. However, for those at higher range, the tendency depends significantly on locations. For upwind, side and oblique-downwind locations, the closer to the principal model, the more reduction in buffeting factors can be indicated. For oblique-upwind locations, a general small amplification occurs at (3, 3) and (4, 4) locations. The case at (2, 2) shows that a reduction of 25% occurs around the reduced velocity of 10 and then dramatically increases to a very large amplification with the increase of reduced velocity. The three locations of (-2, 0), (-3, 0) and (-4, 0) have the similar tendency as (2, 2). For the cases at (-3, 0) and (-4, 0), the amplification decays when the reduced velocity is getting higher; nevertheless, the case at (-2, 0) exhibits a very similar trend as (2, 2). These two critical cases are the two cases shown in Fig. 4 in which, the vibration is so great that the laser sensor failed to catch the motion completely. 3.1.3 Response trajectories The response trajectory can show the motion behavior of the model in a more intuitive way and may explain how the movement is interfered by the neighboring model. Aforementioned critical cases are selected to draw their trajectories in regard to certain reduced velocities in Fig. 8 and 9. For the critical cases in the upstream, cases at (2, 2) and (3, 3) are mostly mentioned to show significant upstream interference effects. For the case at (2, 2), it can be concluded from Fig. 4 and Fig. 8 that, when the reduced velocity is larger than 10 and getting even higher, the across-wind vibration is further amplified by the vortex-shedding phenomena. For the case at (3, 3), a general but less-level amplification can be indicated over all the reduced velocities. The amplification is inversely proportional to the relative distance between two models. For the critical cases in the downstream, several cases show different patterns depending on location and reduced velocity as shown in Fig. 9. The case at (-2, 2) at U = r 6.2 shows a left-inclined elliptic shape while the case at (-3, 3) at the same reduced velocity shows no inclination. Such left-inclined elliptic shape was mentioned by Bailey and Kwok (1985) due to the channel between two models being rhythmically narrowed and widened by the oscillation of the upstream model. However, this case does not show a clear resonant-like amplification. It is supposed that the resonant-like amplification can only occur during a very limited reduced velocity range. Therefore the phenomenon may be skipped over due to the larger velocity interval in this study. As the reduced velocity becomes higher, the inclination disappears and the across-wind response is significantly suppressed. The same tendency can be found in the case at (-3, 3) however with decreasing reduction level. The cases at (-2, 0) and (-3, 0) both show an amplification occurring to the across-wind response when the reduced velocity is higher than 10. Further, the amplification is getting larger when the two models are closer. A very thin elliptic shape of trajectory can be generally indicated. 3.2 Interfered force characteristics Along-wind and across-wind forces were measured by the high-frequency force balancer and then processed by FFT method for force spectrum characteristics

investigations to enhance the observation of interfered wind forces. Fig. 10, 11 and 12 show critical cases with respect to the isolated case. For interfered force spectra at the upwind locations, the along-wind turbulence is significantly suppressed at lower frequencies while the across-wind turbulence is amplified. The commonly indicated peak at reduced frequency of 0.1 moves gradually to lower frequencies as the interfering model moves closer to the principal model, which explains the wind forces exerted on the principal model have been altered due to the wake turbulence generated from the upstream model. The cases at oblique-upwind locations show even clearer peaks than the upwind locations in the across-wind direction, especially the critical case at (2, 2). However, the along-wind turbulence has little interference effect observed. It is then interesting to indicate from the cases at side locations that the across-wind spectrum peak moves slightly to higher frequency as the interfering model moves closer to the principal model. The possible explanation is that the narrowed channel between the two models has raised the frequency of vortex shedding generated from the principal model due to flow speed-up. For interfered force spectra due to downstream interfering model, the along-wind turbulence has remained similar to that of the isolated model. The case at (-2, 2) exhibits a quite different spectrum than other two cases at oblique-downwind locations. An obvious hump at the reduced frequency range from 0.01 to 0.03 is indicated, which was also mentioned by Bailey and Kwok (1985) but with slightly different frequency range. As for the cases at downwind locations, the trend of the spectra is similar to that at oblique-upwind locations; however, with the decrease of the distance between two models, the peak not only moves to lower frequencies but also lowers its spectrum value gradually. The two critical cases at (-2, 2) and (-2, 0) may just explain the effect on force spectrum characteristics due to two different interfering sources, as also shown in response trajectories in Fig. 9. 4. CFD Results To enhance the understanding of the aforementioned critical cases either in the upstream or in the downstream, a simplified trial of numerical simulation was conducted by computational fluid dynamic (CFD) technology. The CFD environment was idealized to be a 2D analysis since the experiment of the aeroelastic test was made based on a rigid aeroelastic model. Those identified structural characteristics were adopted and the flow condition at model height was assumed for the 2D simulated approaching flow. The commercial package ANSYS Fluent 15 served as the tool for the 2D fluid-structure-interaction simulation in this study. The Pressure Implicit with Splitting of Operators (PISO) algorithm was adopted was regarded as an extension of Semi-Implicit Method for Pressure-Linked Equations (SIMPLE) due to its better performance in non-iterative computation of unsteady compressible flows. The bounded central difference was used to discretize the convective terms of momentum equations for its relative low diffusivity and the second order implicit scheme was used for time discretization. The dynamic Smagorinsky Lilly model was chosen for sub-grid-scale (SGS) model (Lilly, 1992). Fig. 13 is re-plotted for three critical cases in Fig. 8 and 9. The case at (-2, 0) exhibits a very thin response trajectory shape representing the large amplitude in across-wind vibration as it was expected under the reduced velocity of 19.3. The case at (2, 2) also exhibits an elliptic-like shape as the experimental results under lower reduced velocities. For the case at (-2, 2) under the reduced velocity of 6.2, a left-elliptic shape is obtained to coincide the response trajectory in Fig. 9. Although the absolute values from CFD results are not exactly equal to those from experimental results, the expected tendencies are presented for the enhancement on the interference mechanism from the downstream. Fig. 14 represents a half cycle series of vorticity patterns from the case at (-2, 0). It is indicated that the downstream interfering model does not become an obstacle to the formation of vortex shedding from the principal model; instead, the vortex separated from the principal model converges to the vortex generated from the downstream interfering model (blue vortex from 0/16 to 1/16 cycle; red vortex from 5/16 to 6/16 cycle). The channel between two

models is almost constant and it sometimes provides enough space for the clockwise vortex to roll up to the upper surface of the interfering model (1/16 cycle) or for the counterclockwise vortex to roll down to the bottom surface of the interfering model (4/16 cycle). The vortices in the wake of both models maintain in perfect round shape in a periodic movement as that of an isolated model. 5. Conclusions Downstream interference effect was seldom mentioned in the past. In this study, critical interference locations were selected for the understanding of the formation of interference mechanism either from the upstream or the downstream. Aeroelastic vibration tests, high-frequency force balance tests, and an idealized 2D CFD simulation were conducted for observation and demonstration of difference mechanisms these critical cases could be. From the results, several conclusions are made as below. (1) The interference effects either from the upstream or from the downstream may not only reduce the wind forces on the principal model, but also amplify them at certain critical locations. (2) For the principal model with a small Scruton number, the existence of an interfering model largely determines the vibration behavior at the vortex-induced status depending on locations. (3) Critical cases at (x/b, y/b) = (2, 2) and (-2, 2) were found to be in two different response trajectory shape as indicated by Bailey and Kwok (1985); moreover, another critical case at (-2, 0) was also found in this study with another kind of response trajectory shape, an even larger across-wind vibration and a thinner along-wind vibration. The interfered wind forces were explained through the wind force spectrum shapes in regarded to different reduced velocities. The mechanism of downstream interference effect of the case at (-2, 0) was enhanced by the vorticity patterns of an idealized 2D CFD simulation results. Although the 2D simulation may not be able to provide exact absolute values for parametric comparisons, the movement of the vortex shedding was demonstrated in a more intuitive way for mechanism formation.

6. Notations B D H x y f 0 ξ x ξ y M δ width of principal and interfering models depth of principal and interfering models height of principal and interfering models along-wind direction across-wind direction fundamental frequency of principal model structural damping ratio of principal model in the along-wind direction structural damping ratio of principal model in the across-wind direction generalized mass of principal model mass-damping parameter ρ air density (in kg/m 3 ) BF σ x,interfered σ x,isolated U r U H buffeting factor for response standard deviation of response of principal model with interference effect in the along-wind direction standard deviation of response of principal model without interference effect in the along-wind direction reduced velocity mean velocity at model height

7. Figures Photo 1 Wind tunnel at WERC, TPU Fig. 1 Characteristic profiles of simulated turbulent boundary layer flow

Fig. 2 Diagram of vibration test Fig. 3 Diagram of locations for principal model and interfering model

(x/b, y/b) = (2, 2) Ur = 12.5 (x/b, y/b) = (2, 2) Ur = 15.9 (x/b, y/b) = (2, 2) Ur = 19.3 (x/b, y/b) = (-2, 0) Ur = 15.9 (x/b, y/b) = (-2, 0) Ur = 19.3 Fig. 4 Distorted response signal at critical reduced velocities in this study

3.0 RMS response (mm) 2.5 2.0 1.5 1.0 0.5 0.0 alongwind 0 5 10 15 20 Reduced Velocity U r Fig. 5 RMS response of isolated model

upwind oblique-upwind side oblique-downwind downwind Fig. 6 Along-wind buffeting factor curves of the principal model

upwind oblique-upwind side oblique-downwind downwind Fig. 7 Across-wind buffeting factor curves of the principal model

(x/b, y/b) = (2, 2) under Ur = 9.3 (x/b, y/b) = (2, 2) under Ur = 10.8 (x/b, y/b) = (3, 3) under Ur = 9.3 (x/b, y/b) = (3, 3) under Ur = 10.8 Fig. 8 Response trajectories of critical cases in the upstream (upwind and oblique-upwind)

(x/b, y/b) = (-2, 2) under Ur = 6.2 (x/b, y/b) = (-2, 2) under Ur = 9.3 (x/b, y/b) = (-3, 3) under Ur = 6.2 (x/b, y/b) = (-3, 3) under Ur = 9.3 (x/b, y/b) = (-2, 0) under Ur = 9.3 (x/b, y/b) = (-2, 0) under Ur = 12.5 (x/b, y/b) = (-3, 0) under Ur = 9.3 (x/b, y/b) = (-3, 0) under Ur = 12.5 Fig. 9 Response trajectories of critical cases in the downstream (downwind and oblique-downwind)

Fig. 10 Wind force spectra under interference effects from upwind and oblique-upwind locations Fig. 11 Wind force spectra under interference effects from side locations

Fig. 12 Wind force spectra under interference effects from oblique-downwind and downwind locations

(x/b, y/b) = (2, 2) under Ur = 19.3 (x/b, y/b) = (-2, 0) under Ur = 19.3 (x/b, y/b) = (-2, 2) under Ur = 6.2 Fig. 13 Response trajectories of critical cases with CFD results

Interfering Principal (a) -1/16 cycle (b) 0/16 cycle (c) 1/16 cycle (d) 2/16 cycle (e) 3/16 cycle (f) 4/16 cycle (g) 5/16 cycle (h) 6/16 cycle Fig. 14 Truncated patterns of vorticities at the case of (-2, 0) under Ur = 19.3 (Blue: counterclockwise vorticity; Red: clockwise vorticity)

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9. Published Paper etc. Lo, Y.L., Kim, Y.C., 2015. Investigation on Aerodynamic Behavior of High-rise Buildings under Interference Effects, 2015 Symposium of Progress on Wind Engineering and Structural Dynamics, Nov. 1-2, 2015, Tamsui, Taiwan (Presented) Lo, Y.L., Kim, Y.C., Li, Y.C., Downstream Interference Effect of High-rise Buildings under Turbulent Boundary Layer Flow. (Prepared to submit to international journal) 10. Research Organization 1. Representative Researcher Yuan-Lung Lo/ Assistant Professor, Dept. Civil Eng., Tamkang Univ., Taiwan (ROC) 2. Collaborate Researchers Yong Chul Kim/ Associate Professor, Dept. Architecture, Tokyo Polytechnic Univ., Japan