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Journal of Fluids and Structures
This paper mainly investigates interactions between a tornado and a streamlined single-box bridge deck using large-eddy simulation (LES). Simulation is carried out with respect to an ISU-type tornado vortex simulator with an embedded bridge deck model. Aerodynamic loading characteristics of the bridge deck are compared with available experimental data, in forms of surface pressure coefficients as well as sectional aerodynamic load coefficients. The presence of the bridge deck as well as the horizontal distance from tornado center to bridge deck are then taken into account to reveal the interference of the bridge deck with the tornado flow field. It is shown that the numerical results fit well with the experimental data in most cases, while discrepancies recorded in some cases are potentially due to the limitations of experimental measurement and uncontrollability of flow field similitude. The presence of the bridge deck would destroy the vortex structure generated in an empty simulator and form two new flow regimes with distinct vortex structures above and below the deck. The effects of the variation of spatial relationship between the bridge deck and the tornado-like vortices on two newly formed flow regimes appear to be different, and the difference between the pressure deficits of these two flow regimes result in discrepancies between the surface pressures on the upper and lower surfaces of the bridge deck. The angle of attack and the magnitude of velocity of incoming wind flows are determined for the further purpose of simple parameterization of tornadic effects on bridge decks, and both seem to be influenced by the presence of the bridge deck.
In recent years, the frequency of severe tornado disasters in China has been getting higher and higher. Since the beginning of 2021, at least 4 tornadoes that surpassed EF2 level have occurred in different parts of China. By way of example, an EF2 tornado, according to Chinese state media, was observed in Shangzhi county, Harbin City, Heilongjiang province, China, from 17:30–18:30 on June 1, 2021, which killed one person and injured 16. What makes this tornado special is that it passed right through a bridge of a high-speed railway, causing six trains to be delayed. One of them applied its emergency brake and stopped just a few kilometers from the site of the incident. Although no obvious damage to the bridge was reported, one can hardly deny that the probability of a tornado strike on a bridge exists. In addition, Tamura (2009) recommended that design of line-like structures such as railways, power transmission lines and so on should take tornado effects into account due to this probability. Statistical data shows that, in China, several coastal provinces such as Jiangsu and Guangdong experienced a relatively larger number of severe tornadoes (EF2 or greater) over the 50years between 1961 and 2010 (Fan and Yu, 2015). Coincidently, quite a number of long-span bridges have been constructed in these tornado-prone areas, which should be meticulously examined with regard to tornado effects.
Studies of tornado effects on structures can be divided into three main categories: physical simulation, numerical simulation and analytical modeling. Since the introductions of the Ward-type tornado vortex simulator (Ward, 1972) and the ISU-type tornado vortex simulator (Haan et al., 2008), a large number of experimental studies on tornado-induced wind loads have been conducted, including those on low-rise buildings (Haan et al., 2010, Jischke and Light, 1983), high-rise buildings (Yang et al., 2011) and structures of great importance such as cooling towers (Cao et al., 2015) and trains (Suzuki and Okura, 2016). The authors (2019) experimentally studied the wind loading characteristics of streamlined bridge decks under tornado-like vortices generated by the tornado vortex simulator located at Tongji University. Based on rigid-model wind pressure measurement, their experiments mainly investigated variations of wind loading under a variety of spatial parameters as well as swirl ratio of the tornado-like vortices. However, the measuring coverage under laboratory conditions is limited, and it remains unclear how a bridge model interferes with tornado-like vortices, since they are similar in geometric scale. The lack of interfered flow field data has driven the need to simulate experiments using a numerical approach, which, due to its strong ability to reveal complicated flow structures and achieve good repeatability, has been extensively utilized to study tornado effects on many other structures (e.g., Cao et al., 2018a, Liu and Ishihara, 2015, Xu et al., 2020). Using the analytical approach, Baker and his coworkers have made great efforts to build up an analytical model for calculating tornado wind loads on structures, and a risk based framework using this model has been applied to studies of tornado effects on a low-rise structure and a moving train (Baker and Sterling, 2018a, Baker and Sterling, 2018b). This analytical model decouples the tornado wind load into two parts — the inertial load and the pressure load (i.e.,the load caused by the direct action of air flow and the load caused by tornado-induced pressure deficit). The calculation of inertial wind loads requires wind speeds and force coefficients in a manner similar to that for boundary layer wind. In Baker and Sterling (2018b), the force coefficients of the train for the calculation of inertial wind loads are obtained from boundary layer wind tunnel tests with a directional resolution in yaw angle. As the boundary layer wind tunnel test is to date a necessity for the design of large-span bridges, this methodology should be helpful in avoiding physical or numerical simulations that may be too costly and confined to a limited set of parameters.
Although aerodynamic loading characteristics of bridge decks under tornado-like vortices have been preliminarily investigated using a tornado vortex simulator by the authors (Cao et al., 2019), it is unrealistic to conduct physical experiments for each specific bridge that may be subject to tornado risks. Therefore, it is necessary to analyze in depth the aerodynamic mechanism of tornado effects on bridge loads, such as the part of the wind load induced by the pressure drop of the tornado vortices, the part originating from the aerodynamic effects of tangential wind velocities, and other potential parts. Obviously, only physical experiments cannot provide this information. For example, the attack angles of the incoming tangential wind velocities cannot be obtained from pressure-tapped aerodynamic load measurements. As a powerful alternative, numerical simulation using CFD has a huge advantage in examining information on tornado flow when it interacts with the bridge deck. Thus, conventional boundary layer wind tunnel experimental results of aerodynamic loads on bridge decks can be used to estimate tornado-induced wind loads, together with a pressure drop load model and other potential load models.
In the current paper, an LES-based numerical approach is applied to reproduce some representative cases of physical experiments to determine tornado-induced aerodynamic loads on bridge decks, to clarify how tornado-like flow fields behave under the bridge model’s interference. Section2 introduces the setup of a numerical tornado vortex simulator as well as calculation cases. Section3 validates numerical results of aerodynamic loads on bridge decks by comparison with experimental ones, including surface pressure distributions and sectional aerodynamic load coefficients. In Section4, the interference with tornado flow fields by a bridge deck is presented, including the vortex structure, pressure difference between the upper and lower surfaces of the bridge deck, and the characteristics of the incoming tangential wind flows. This is intended to clarify the aerodynamic mechanisms of tornado effects on the bridge deck. Main conclusions and future prospects are summarized in Section5.
Numerical model, grid system and boundary conditions
As shown in Fig.1a, the bridge model is suspended at a height of 0.2m above the floor of the ISU-type physical simulator, at a variety of distances from the tornado center. Other experimental parameters are detailed in Cao et al. (2019). An LES-based numerical simulator has been developed by Cao et al. (2018b) to simplify but preserve the essential characteristics of the physical simulator. In the current paper, to replicate the experiment, a bridge deck is embedded into the numerical
Results of aerodynamic characteristics and validations
In order to use numerical techniques to clarify the mechanism of tornado-bridge interactions in laboratory simulations, CFD calculation results should be validated by comparison with experimental results. The reliability of a tornado flow field without the presence of a bridge model has already been validated (Cao et al., 2018a) by results obtained from field/experimental data with various mesh resolutions. Since the simulator settings in this study are the same as those in previous studies
Interference with flow fields by bridge deck
In Section3, tornado-induced aerodynamic loading characteristics of the bridge deck were briefly presented from both numerical and physical aspects. However, for physical simulations, flow field measurements have not been carried out when the deck is available since the Cobra probe will inevitably disturbs the flow field, especially for that near the bridge model surface. Therefore, we cannot tell exactly what happens to the flow field around the bridge deck. Since this uncertainty or unknown
In this study, LES-based CFD calculations were carried out to simulate interactions between a streamlined box-girder bridge deck and tornado-like vortices. The CFD results were firstly validated by experimental results with respect to aerodynamic loadings on a bridge deck (including surface pressure coefficients and sectional aerodynamic load coefficients) and then utilized to clarify the influences of a bridge deck on a tornado flow field from perspectives of vortex structures, surface
CRediT authorship contribution statement
Qin Yuhui: Methodology, Software, Calculation, Visualization, Writing – original draft. Cao Jinxin: Conceptualization, Methodology, Validation, Formal analysis, Investigation, Resources, Data curation, Writing – original draft, Writing – review & editing, Supervision, Project administration, Funding acquisition. Cao Shuyang: Software, Validation, Writing – review & editing, Supervision. Ge Yaojun: Writing – review & editing.
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
The authors thank the reviewers whose constructive comments led to an improved paper. This study is funded by the Natural Science Foundation of China (NSFC) (Grant No. 51878504,52178502 and 51720105005) and Research Foundation of State Key Laboratory of Disaster Reduction in Civil Engineering, China(Grant No. SLDRCE19-B-01 and SLDRCE17-04), which is gratefully acknowledged.
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