A Computational Fluid Dynamics Comparison of the Underflow of Different Commercial High-Speed Trains

Transcription

1 Paper 129 A Computational Fluid Dynamics Comparison of the Underflow of Different Commercial High-Speed Trains C. Gil, C. Paz, E. Suárez and M. Conde School of Industrial Engineering University of Vigo, Spain Civil-Comp Press, 2015 Proceedings of the Fifteenth International Conference on Civil, Structural and Environmental Engineering Computing, J. Kruis, Y. Tsompanakis and B.H.V. Topping, (Editors), Civil-Comp Press, Stirlingshire, Scotland Abstract In this paper, an aerodynamic comparison between the underbody flow of three different commercial high-speed trains (ETR500, TGV Duplex and TALGO Avril) has been performed using the commercial software ANSYS Fluent. These models have been selected because of the noticeable differences in the configuration and position of the bogies/wheel sets followed by the manufacturers. The purpose of this study is to elucidate which configuration is aerodynamically more efficient and to evaluate the effect of them on the track, estimating the risk of ballast flight. Three different simulations were performed, revealing that the values of drag force resistance, velocity near the track and wall shear stress in the ballast layer relative to the ETR500 are the highest, followed by the TGV Duplex and the TALGO Avril. The size of the ballast stones with more probability of being displaced in each case was also calculated by two different criteria. This study concluded that the configurations followed by TALGO Avril and ETR500 show, respectively, the best and the worst aerodynamic performance of the selected high-speed trains. Keywords: high-speed train, aerodynamics, ANSYS Fluent, underflow. 1 Introduction Nowadays, the railway industry offers a wide variety of different shapes and configurations in commercial high-speed trains. The pursuit of a greater dynamic stability, a better aerodynamic performance and more attractive designs encourages companies and researchers to improve the current technology and develop new strategies for their high-speed models. Many studies concerning these issues can be found in the literature. The stability, for example, is addressed under diverse possible situations such as trains passing by each other [1], trains under crosswind forces [2] or trains on different ground scenarios [3]. Other authors focus their efforts on the analysis of the aerodynamic influence of specific parts of the models, 1

2 being perhaps the nose-shape the most studied aspect [4,5]. In this field, the development of the computational resources and the improvement of the simulation software in recent years allowed for the simplification of the testing procedures, increasing the flexibility and reducing the time spent on these analysis [6,7]. In addition, genetic algorithms have been also used for these purpose, setting several parameters and optimising them to reach the most efficient design [8,9]. Apart from the nose-shape, some studies have evaluated the behaviour of the flow around the bogies too. This issue has been dealt with both experimental and simulation methods [10,11]. However, the geometry of the underbody has been mainly analysed because of its relation with the flying ballast phenomena [12,13], instead of from the point of view of its aerodynamic performance [14]. In their work, Kwon et al. conducted a series of wind tunnel tests for Korean high-speed train model to evaluate the effect of several modifications of the nose-shape, inter-car gap and bogie-fairing on the total drag force. Similar to this last reference, this paper shows an aerodynamic comparison between the underbody flow of three different commercial high-speed trains (ETR500, TGV Duplex and TALGO Avril). These models have been selected because of the noticeable differences in the configuration and position of the bogies/wheel sets. On the one hand, the ETR500 and TGV Duplex underbodies consist of traditional four-wheel bogies, being placed in the first case at the beginning and end of each carriage and in the second case in the inter-car gap. On the other hand, TALGO Avril uses an original wheel set with only two wheels located in the space between cars. The objectives of this study are therefore: Calculate and compare the drag force exerted on each model, taking into account the length and number of cars of the commercial trains. Analyse the flow near the track and the pressure and wall-shear contours on the ballast layer in each case. Evaluate the turbulence magnitude generated by the shape of each of the three trains. Taking advantage of the development of the computational methods, this study has been carried out through three different Computational Fluid Dynamics (CFD) simulations, one for each model, using the commercial software ANSYS Fluent. 2 Methodology 2.1 Geometrical models Since the purpose of this study is to determine which of the three underbody configurations offers the best aerodynamic performance, the simulation of the entire trains was considered inappropriate. This way, the shape of the nose or the front area of the cars would play a role in the results, and that is not the target of the current paper. The computational domain has been therefore limited to a section of the middle of the train, where the flow is considered to be well-developed and 2

3 independent from the geometry of the power head and the extreme car [15 17]. This section comprises a simplification of a complete intermediate car and half of the previous and the following one, thus simulating the flow passing through two areas of disturbances (bogies/wheel sets). The first half of the model allows for a disturbed flow similar to reality and the second one is used as test section, where the measurements and observations are made. At the beginning and end of the domain, the geometrical model has been extended to let the flow develop and avoid the appearance of backflows. To refer the differences in the flow only to the selected configuration, the shape of the car is shared by the three simulations. In contrast, each model maintains the length of their own cars to keep the resemblance with the real train. Figure 1: Geometrical model of the three high-speed trains As previously mentioned, each one of the selected high-speed trains has a particular underbody configuration (Shown in Figure 1). The strategy followed by the ETR500 manufacturers consists of two bogie sets per car, placed at its beginning and end. Bogies are also used in the TGV Duplex model, but in this case each set is shared by two consecutive intermediate cars, being placed in the gap between them, thus reducing the total amount of necessary bogies. Finally, TALGO Avril high-speed trains use an original wheel set in the space between cars with only two wheels, which reduces the roughness of the geometry relative to the motion elements. On the other hand, the length of the cars is unavoidably related to the selected configuration. Higher the number of axles is, longer the carriages are. For this reason the intermediate cars of the ETR500 are longer than the TGV Duplex ones and these are, in turn, larger than the TALGO Avril ones. Therefore, to allow for comparable simulations, it would be later necessary to extrapolate the results of the simulations considering the characteristics of each configuration, which are described as follows in Table 1: TRAIN MODEL NUMBER OF CARS LENGTH OF EACH CAR (m) TOTAL LENGTH (m) ETR TGV DUPLEX TALGO AVRIL Table 1: Characteristics of the high-speed trains 3

4 Two intermediate cars have been subtracted from the regular total number because a car and a half at the front and half a car at the rear are not considered, since the flow in these regions is affected by the presence of the power head, which has a particular shape in each case. For a more realistic representation of the underfloor flow, the models have been employed in a single-track ballast and rail (STBR) scenario [18] with a simplified 60E1 rail (EN 13674). 2.2 Computational mesh The computational domain has been spatially discretised with an unstructured hexahedral mesh [19] aligned with the inlet flow using the Cutcell scheme of ANSYS Meshing. The same meshing parameters have been followed in the three geometrical models to maintain the accuracy and similarity in all cases. The size of the surface mesh has been set according to a previous simulation of the aerodynamics around an entire ETR500, in which the results of velocity in the underbody were compared to both numerical and experimental data from Rocchi et al. [20]. In this study, two different hexahedral meshes consisting of 22 and 56 million elements (Surface size of H and H, respectively) were created to evaluate the influence of grid resolution. In the nose region, the results of normalised velocity shown good agreement in both cases with the provided data (See Figure 2). However, after the passing of the first bogies, some fluctuations appeared in the simulation with the coarser mesh, determining that the finer grid captures better the flow behaviour in the bogies region. Consequently, a surface cell size of H was considered appropriated for the current work, including as well a fine boundary layer around the models and the rails. Normalised velocity [-] Upper limit Lower limit Coarse mesh Fine mesh ETR500-Rocchi et al Position [m] Figure 2: Comparison of the normalised velocity for both a coarse and a fine mesh with the results by Rocchi et al. [20] 4

5 2.3 Boundary conditions Simulations were carried out on the commercial software ANSYS Fluent. In order to improve the accuracy and to capture better the unsteady phenomena, Scale- Resolving Simulation (SRS) methods have been employed. These methods are able to calculate partially the generated vortexes, providing a better understanding of the turbulence existing in the underbody of a high-speed train. In this case, a Delayed Detached Eddy Simulation (DDES) [21], using a Reynolds-Averaged Navier-Stokes (RANS) model on the walls and resolving the detached flow using Large-Eddy Simulation (LES), was performed. This way, the requirements of mesh resolution near the walls are not so strict and the computational costs are lower. The velocity inlet was set to 300 km/h (83.33 m/s), because at such a high velocity the aerodynamic effects related to drag force are more remarkable and the ballast flying phenomena is easier to occur. The STBR scenario and the ground were defined as moving walls with the same speed as the air, thus reproducing a still atmosphere and avoiding the use of sliding meshes [22]. The simulations were first calculated in steady-state using Realizable k-ϵ to improve the convergence. Then, the cases were changed to transient calculation and DDES model. The time step was selected as a function of the oscillation frequency for a Strouhal number of 0.14 [23] and H as the characteristic length. 3 Results The convergence of the simulations was considered sufficient when the scaled residuals exceeded the recommendation of 10-3 and the mean value of the drag force remained stabilised. Then, one more second was simulated to obtain the results shown in this paper. 3.1 Drag force The characteristic drag force of the test section of each of the selected models has been calculated by averaging the data taken during one second of simulation. In addition, the results were extrapolated to consider the number of cars and the length of each configuration. Following the data shown in Table 1, the drag force given by Fluent was multiplied by the number of cars and divided by the total length, thus obtaining a number that allows for a comparison between cases. The relative aerodynamic contribution of each model is shown in Figure 3, considering the ETR500 as a reference. An interval of two times the standard deviation is also depicted, which represents the turbulent nature of the simulated situation. 5

6 Figure 3: Drag force contribution The results indicate that TALGO Avril offers the best aerodynamic performance of the three selected models, followed by the TGV Duplex. They generate, respectively, around a 40% and an 84% of the drag force produced by the ETR500. It was also revealed that the number of bogies/wheel sets affects strongly to the drag force, since the coefficient is larger for those models with more axles. Consequently, attending only to aerodynamic reasons, a configuration with a wheel set placed in the gap between cars generates less drag resistance than any other model with bogies. In addition, the standard deviation of the TALGO model is the least, which denotes a less turbulent behaviour of the flow with this configuration. 3.2 Underbody flow The flow under the different high-speed trains has been analysed with the purpose of determining the risk of generating ballast flight. Depending on the geometry of the underbody, the flow between the train and the track would vary and would affect the ballast layer to a greater or lesser extent. The results offered in this section have been taken from a certain moment of the simulation, because the number of images necessary to evaluate the transient evolution would be unattainable. In Figure 4, the velocity of the air under the three models in the test section is shown. This velocity is represented as a ratio with respect to the speed of the train (83.33 m/s). According to the maps, the ETR500 generates a more disturbed flow, reaching a velocity ratio of more than 0.7 near the ballast. In contrast, the fluid field in the simulation of TALGO Avril remains almost unaffected by the presence of the wheel set, noticing only some turbulence a certain time after the passing of the wheels. The TGV Duplex is in an intermediate situation, experiencing a considerable level of turbulence but not reaching so high air speeds. 6

7 Velocity ratio [-] ETR500 TGV Duplex TALGO Avril Figure 4: Contours of velocity ratio in the underbody As a consequence of the disturbances generated in the fluid, the wall shear stress values would be higher in those high-speed trains with more underbody roughness. This fact is confirmed by Figure 5, where the contours of wall shear stress in the ballast layer for the three models are depicted. The images show how the ETR500 generates the highest values, followed by the TGV Duplex. In the case of TALGO, the wall shear stress is almost negligible. These results are in agreement with the contours of velocity shown in figure 4. Furthermore, the unsteady nature of the flow can be clearly appreciated, thus confirming the necessity of transient simulations to evaluate the aerodynamic performance of a high-speed train. In this case, the range of values of wall shear stress could slightly vary during the calculation. Wall shear stress [Pa] ETR500 TGV Duplex TALGO Avril Figure 5: Contours of wall shear stress in the ballast layer From the results of the simulation, a further investigation on ballast flight was made. The minimum static pressure and the maximum wall shear stress were identified in each case, because these would be the most unfavourable parameters. Then, two different criteria were used to estimate the maximum particle size that would have a great risk of being displaced or elevated by the slipstream of the train. On the one hand, the force balance shown in Equation (1) was used. P A m g (1) 7

8 where P is the pressure, A the surface of the particle in which the pressure acts, m is the particle mass and g the gravity acceleration (9.81 m/s²). This represents a simplified situation where weight and pressure are the only forces acting on the ballast stones. The current criteria was evaluated for prismatic and spherical particles. In the first case three mass values were tested, being therefore determined the maximum surface exposed to pressure that would be elevated. Consequently, using a ballast density of 2600 kg/m³ [24], the height of the prismatic particle could be calculated. In the second case the diameter of the sphere was directly obtained, considering that only half the particle was in contact with air. On the other hand, the criteria based on the wall shear stress proposed by Kaltenbach et al. [24] was tested (see Equation (2)). 0.5 s a U ( ) U, th A dp g a a 0.5 (2) where U is the friction velocity, U,th the static friction velocity, the wall shear stress, s the ballast density, a the air density (1.225 kg/m³), d p the particle diameter and A 0.1 a constant coefficient. A schematic representation of the results is shown in Figure kg STATIC PRESSURE Prismatic shape 0.05 kg 0.10 kg Spherical shape WALL SHEAR STRESS ETR500 TGV DUPLEX H L L = 33 mm H = 17 mm d d = 52 mm TALGO AVRIL Figure 6: Representation of the critical sizes for ballast flight The results show that regular shapes could be displaced by the passing of the ETR500 or the TGV Duplex. However, the stones that TALGO Avril would elevate are not real, because they should have a very large surface compared to its height, to maintain a small weight. In the case of spherical particles, the wall shear stress criteria is more conservative, since the critical size is lower than the one obtained 8

9 with the pressure equation. As shown, the ETR500 is capable of displacing the greatest stones, because it generates a higher disturbance in the track. 3.3 Turbulence The responsability for the differences in the behaviour of the underflow for each train model belongs to the level of turbulence generated. This issue depends on the shape of the gap between intermediate cars and the geometry of the bogies/wheel set. To compare the three models, an isosurface of Q-criterion (second invariant of the velocity gradient) coloured by turbulent kinetic energy is shown in Figure 7. Turbulent kinetic energy [J/kg] ETR500 TGV Duplex TALGO Avril Figure 7: Isosurface of Q-criterion coloured by turbulent kinetic energy The level of turbulence around the ETR500 is shown as uniform in the entire train, whereas in the second case the disturbances appear only in the underbody. In the TALGO Avril the turbulence is developed along the train, being greater in the end of the domain. The energy carried by the vortexes is also different in each case. In the models with bogies (ETR500 and TGV Duplex), the contours of turbulent kinetic energy depicted have a larger value than in the case of TALGO Avril, where the existing vortexes have almost no energy. 4 Conclusions In this paper, a comparison between the underflow of three different commercial high-speed trains (ETR500, TGV Duplex and TALGO Avril) was done. A section of each of the selected models was simulated using CFD techniques to evaluate the behaviour of the air around the train and its effect on the track. As expected, the different underbody configurations (Two bogies per car, one bogie in the intercar gap and a wheel-set between cars, respectively) led to dissimilar fluid fields, being the ETR500 model the one that generates more disturbances and the TALGO Avril the one that disturbs the least. Consequently, the values of drag force resistance, velocity near the track and wall shear stress in the ballast layer relative to the ETR500 are the highest, followed by the TGV Duplex and the TALGO Avril. In addition, the minimum pressure and the maximum wall shear stress in the track were identified and the shape of the ballast stones with a risk of being displaced by the flow in each case was estimated using two different criteria. Summarising, this study 9

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