Dispersion of ultrafine particles in the wake of car models: A wind tunnel study

Journal of Wind Engineering & Industrial Aerodynamics 198 (2020) 104109

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Dispersion of ultrafine particles in the wake of car models: A wind tunnel study Romain Rodriguez a, Fr
ed
eric Murzyn a, *, Amine Mehel b, Frederique Larrarte c a

ESTACA West Campus, Department of Mechanical Engineering, Air Quality and Depollution Group, Rue Georges Charpak, 53000, Laval, France ESTACA Paris Saclay Campus, Department of Mechanical Engineering, Air Quality and Depollution Group, Avenue Paul Delouvrier, 78066, Saint Quentin en Yvelines, France c University Gustave Eiffel, IFSTTAR, Department of Geotechnics, Environment, Natural Risks and Earth Sciences, 14-20 Boulevard Newton, 77447, Marne La Vall
ee Cedex 2, France b

A R T I C L E I N F O

A B S T R A C T

Keywords: Dispersion Ultrafine particle Particle number concentration Ahmed body Wake flow Recirculation region Wind tunnel LASER Doppler velocimetry

Worldwide around 7 million annual deaths are due to air pollution. Among all pollutants, Ultrafine Particles (UFP) cause strong adverse effects. In this paper, the dispersion of UFP is studied in the wake of car models characterized by different rear slant angles (ϕ). Velocities and UFP concentrations are collected in a wind tunnel. The influence of the flow topology on the dispersion of these UFP is discussed. The results indicate that its structure strongly influences their dispersion. Whatever the rear slant angle is, the size of the recirculation region is a key parameter governing the dispersion of these UFP. For ϕ ¼ 0 , the flow is almost symmetric and concentration levels are higher and homogeneous in the close wake. The recirculation region is the largest one. The dispersion is enhanced in both horizontal and spanwise directions. For ϕ ¼ 25 , the flow is attached on the rear slant leading to a strong downwash effect. The volume of the recirculation region is the smallest. Longitudinal vortices develop from the edges of car model entrapping particles. Particle Number Concentration field is no more symmetric. For ϕ ¼ 35 , results are almost similar to those obtained for ϕ ¼ 0 . Comparisons with previous studies are discussed and possible applications are suggested.

1. Introduction Air quality improvement is a key issue with important consequences in terms of public health and environmental issues. In France, the atmospheric pollution often reaches peaks above recommended thresholds in big cities such as Paris, Lyon or Lille leading to traffic restrictions (Mehel et al., 2019). There are huge economic related challenges as well as health concerns. As an example, in France, the annual cost of air pollution has been estimated to 101 Billions of Euros. This is twice as tobacco. Per year, 650000 days of work stoppage are recorded due to air pollution. At a larger scale, the economic shortfall in the world is about 200 Billions of Euros (Daycard-Heid, 2019). It is worthwhile to note that other consequences are linked with this issue such as global warming or fouling of buildings. Overall, it greatly impacts the total cost for humanity as well as for the environment. The surrounding air contains gaseous pollutants (nitrogen oxides, sulfur dioxide or Volatile Organic Compounds (VOC) such as benzene) and particles. According to the French Environment and Energy Management Agency (ADEME, 2018),

they are issued from agriculture, transports, industries, heating as well as green waste burning … Particles can be classified according to their size as coarse particles (diameter between 2.5 μm and 10 μm), fine particles (diameter between 0.1 μm and 2.5 μm) and ultrafine particles (known as UFP, diameter below 100 nm). Among all UFP emissions sources, transportation systems contribute to up to 90% of the total emissions in number (Mejia et al., 2007; Manigrasso et al., 2019). As it will be explained below, these smallest particles are more toxic than the larger ones. They are not dangerous because of their mass but because of their number. Furthermore, they can infiltrate the car cabin increasing commuter’s exposure (Airparif, 2007; Hudda et al., 2011; Hudda et al., 2012; Joodatnia et al., 2013; Knibbs and de Dear., 2010; Knibbs et al., 2010; Knibbs et al., 2011; Mehel et al., 2019; Morin et al., 2009; Polednik et al., 2018; Xu and Zhu, 2013). It is well-known that Diesel engines play an important role (ADEME, 2018) for primary particles and nitrogen oxide emissions. There are other sources of emission such as brakes, tyre wear and roadworks (dust). Such particles are also harmful because of their small sizes and their chemical nature. Nevertheless, they are out of the

* Corresponding author. E-mail address: [email protected] (F. Murzyn). https://doi.org/10.1016/j.jweia.2020.104109 Received 26 August 2019; Received in revised form 19 January 2020; Accepted 20 January 2020 Available online xxxx 0167-6105/© 2020 Elsevier Ltd. All rights reserved.

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Journal of Wind Engineering & Industrial Aerodynamics 198 (2020) 104109

of Large Eddy Simulation (LES) to predict flow features (Tunay et al., 2016). From wind tunnel investigations, the sensitivity to experimental conditions was discussed by Thacker et al. (2012). On the one hand, a drag discrepancy of 10% was depicted for the same rear slant angle (ϕ ¼ 25 ) depending on the flow separation on the rear slant (sharp versus rounded edge). On the other hand, a lot of data (velocities and pressure) was collected and the main flow properties such as length of the recirculation region, the positions of vortices and their centres were clearly depicted for 0 <ϕ < 40 and different Reynolds numbers. Then, 2D and 3D maps of mean and turbulent flow properties are available in the literature. Rodriguez (2018) presented a detailed review of the state-of-the-art. Based on that, it has been shown that, depending on the rear slant angle (ϕ), different flow topologies can be generated representing real situations. Working with such car models is then relevant to discuss UFP dispersion. Nevertheless, the correlation between PNC and flow topology has never been studied to date. Based on this statement, a thorough work was undertaken for different shapes of vehicles. In this paper, an overview of results on that topic issued from wind tunnel investigations is addressed. First, the experimental facilities, the instrumentation, data acquisition modes and analysis methods are detailed. The three reduced scale and simplified car models (known as Ahmed bodies) with different rear slant angles (ϕ ¼ 0 , 25 and 35 ) are presented. In the third section, the most significant results are exposed for both velocity and PNC fields. Correlations between them are discussed. The fourth section aims at discussing our experimental approach with some previous studies. In the last section, a conclusion suggests further studies that may be undertaken in a close future.

scope of the present paper. For a Diesel engine, at the exit of the tailpipe, the particle size distribution (PSD) exhibits two peaks. The main one is the first that corresponds to particles having a diameter around 10 nm (nuclei mode). They are numerous but their contribution to the total mass is weak. The second one is depicted around 200 nm (accumulation mode). In that size range, particles are less numerous but heavier. In the past, it has been clearly demonstrated that UFP can reach the alveolar region of the human lung with greater efficiency than larger particles. They can deposit in alveoli due to their rapid diffusion. They can also damage pulmonary cells and enter blood and respiratory systems (Buzea et al., 2007). Recently, Valentino et al. (2016) stated that “maternal exposure to diluted diesel engine exhaust alters placental function and induces intergenerational effects in rabbits” meaning that UFP can cross placenta barrier exposing foetus. According to Buzea et al. (2007), nanoparticles are able to contaminate any part of the human body including the brain. Air pollution is responsible for aggravation of cardiopulmonary and respiratory diseases such as bronchitis, asthma, lung cancer and exacerbation of allergies (Araujo et al., 2008; Delfino et al., 2005; Diaz-Sanchez et al., 2003; Manigrasso and Avino, 2012; Manigrasso et al., 2019; Pope et al., 2002; Silverman et al., 2012; Sioutas et al., 2005; Tissot, 1999; Valberg, 2004; Verrier et al., 2002; Zweiman et al., 1972). Furthermore, it can be responsible for other adverse effects such as visibility reduction for drivers (known as particle fog) which increases the risk for accidents or a decline in agricultural yields (Bell et al., 2004). As an example, the decrease of the latter point was assessed to be about 10% around Paris for wheat by INRA (Daycard-Heid, 2019). In 2019, a new study revealed even more alarming conclusions (Lelieveld et al., 2019). The surrounding pollution may kill twice compared to previous estimations. The worsening of air quality due to human activities may be responsible for about 8.8 millions of death per year in the world, 2.8 millions of them being in China and 67000 in France (against 48000 commonly considered). In France, that means that air pollution kills as much as tobacco (72000) and more than alcohol (49000). Worldwide, previous data suggested around 4.5 millions of death. Furthermore, Lelieveld et al. (2019) attribute 40%–80% of untimely deaths to cardiovascular diseases linked to air pollution. Having that in mind, it has become crucial to get a better understanding of pollutant’s dynamics in the wake of a vehicle. In the present article, attention is drawn to particles emitted from the tailpipe. Once released in the atmosphere, they can either disperse in the surrounding environment or infiltrate the car cabin of the following vehicles increasing commuter’s exposure. Previous studies have shown that this infiltration can be more or less important depending on ventilation settings (Mehel et al., 2019) but only a few were interested in the pollutant dispersion from their source (Richards, 2002; Gosse, 2005; Kanda et al., 2006; Carpentieri et al., 2012; Mehel and Murzyn, 2015). Most of them considered gaseous pollutant and passive scalar (Richards, 2002; Gosse, 2005; Kanda et al., 2006; Carpentieri et al., 2012). Consequently, they did not provide PNC fields that would be more relevant. Then, there is still a lack of knowledge about real PNC exposure that prevents epidemiologic studies to be reliable. This is the reason why it has been hard to fix any recommendation about UFP exposure in the early 2000s according to World Health Organization (WHO). Mehel and Murzyn (2015) performed a preliminary study using UFP. They measured PNC in the wake of simplified car model showing the strong influence of the flow topology on the UFP dispersion. From a fluid mechanics point of view, Gillieron and Kourta (2011) recalled that the governing parameter of the flow developing in the wake of a car is the rear slant angle. In the earlier 1980s, Ahmed et al. (1984) proposed a simplified geometry of a vehicle called the Ahmed body. Since that, it has been widely investigated both numerically (Corallo et al., 2015; Guilmineau, 2008; Tunay et al., 2016) and experimentally (Gosse, 2005; Lienhart and Becker, 2003; Lienhart et al., 2002; Thacker et al., 2012; Tunay et al., 2014, 2016; Rodriguez, 2018; Watkins and Vino, 2008). From the numerical point of view, the influence of turbulence models, aspect ratio and stilts were discussed showing, for instance, the accuracy

2. Experimental facilities, instrumentation and data acquisition and analysis 2.1. Wind tunnel tests Measurements were conducted in the wind tunnel at ESTACA West Campus in Laval. It is an open circuit tool manufactured by Deltalab. The test section is 1 m in length (Lwt) and 0.3 m in both width (Wwt) and height (Hwt). The maximum wind speed is Umax ¼ 40 m/s. A detailed and accurate calibration of the experimental facility with an empty test section was performed before the present study (Rodriguez, 2018) and the most relevant properties of the incoming flow were assessed (Rodriguez, 2018). That is the boundary layer (thickness and type), the velocity gradient and the flow homogeneity. The most important results tend to indicate that the turbulence level was below 1% on the streamwise direction (out of the boundary layer). Furthermore, our boundary layer was turbulent with a maximum thickness (δ) of 12 mm at the exit. Lastly, the velocity gradient was low (<4% over the whole length). Overall, the conditions were partially developed. Fig. 1 presents the wind tunnel. The white arrow indicates the flow direction.

Fig. 1. Overview of the test section with LASER Doppler Velocimettry (LDV) system and a car model. 2

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Journal of Wind Engineering & Industrial Aerodynamics 198 (2020) 104109

2.2. Reduced-scale car models: Ahmed bodies The flow regime associated with the wake dynamics is linked with the drag force. This is particularly true for Ahmed bodies. Many studies pointed out the relation between the rear part of the car model with the structures of the wake flow (Leclerc, 2008; Thacker, 2010; Barros (2015)). They mentioned that the drag due to the rear part of the car represents almost 30% of the total drag. Considering the experimental results giving the drag coefficient as a function of the rear slant angle (ϕ) (Ahmed et al., 1984), three behaviors were clearly depicted: - ϕ<~10 : the flow is 2D out of the walls and considered as square back. The streamlines reveal a toric shape of the recirculation region. In the centreline of the car model, two counter rotating vortices develop in the close wake; - ~10 <ϕ<~30 : the wake flow is defined as fastback. The flow is 3D due to the interaction of the turbulent structures developing in the wake. In this case, it is sometimes partially detached on the rear slant. Longitudinal vortices appear coming from the lateral sides of the vehicle. They lead to an increase of the drag, this drag being maximum for ϕ~30 . In the close wake the toric shape of the recirculation region is still observed. Its length is smaller compared to that measured for ϕ < 10 . Overall, the structure of the wake flow is much more complex compared to the first case. The sensitivity to experimental conditions is also more effective; - ϕ>~30 : the situation is closed to that observed for ϕ<~10 . The flow is then considered as square back. After reaching its peak, the drag suddenly decreases (drag crisis) and recovers a level closed to that measured for ϕ ¼ 0 . On the rear slant, the flow is fully detached. Out of the walls, it can be considered as a 2D flow.

Fig. 2. Sketches of the car models: below, rear and side views (lengths in mm).

assessed in the context of air quality in transportation systems. This issue is more crucial in cities where people are mainly exposed to air pollution. As a consequence, the flow developing in the wake of a car in an urban city environment was simulated. Then, according to French regulations, the speed of the incoming flow must be 50 km/h (13.9 m/s), which is the speed limit in cities in France. Considering the size of the wind tunnel, the Reynolds similitude can not be achieved unless working with unrealistic velocities. Then, to select this upstream velocity, the ratio between the speed of the car (U0) and the velocity of the exhausted particles at the end of the tailpipe (Utp) was kept constant. Equation (2) gives this relation.

In the present experiments, these three flow topologies were examined. Then, measurements were conducted in the wake of three Ahmed bodies having rear slant angles ϕ given by ϕ ¼ 0 , 25 and 35 . Scale of models was 0.19 with respect to the original one developed by Ahmed et al. (1984). In terms of dimensions, they were 0.196 m in length (L), 0.054 m in height (h) and 0.073 m in width (l). The models were fixed on the floor of the test section by a cylindrical rod (diameter 5 mm) and four stilts. The height (hs) and diameter (ds) of these stilts were 15 mm and 6 mm, respectively. This height was chosen to be larger than the boundary layer thickness. Accordingly, the dimensionless ground clearance was Hs ¼ hs/h ¼ 0.28. To avoid any correction of wall effects, the models were designed so that the blockage coefficient was below 5% (West and Apelt, 1982). This coefficient is given by the ratio between the frontal area of the car and the area of the test section (Wang et al., 2013) (Eq. (1)). B¼

h*l Wwt *Hwt



U0 Utp



 ¼ wind tunnel

U0 Utp

 (2) real situation

Here, Utp is the ratio between the flow rate (m3/s) at the tailpipe exit and its corresponding cross section (m2). According to Comit
e des Constructeurs Français d’Automobiles (2017), a representative car has an average stroke volume Vcyl ¼ 1.486 L. Following Roberge et al. (2006), the flow rate at the tailpipe Qtailpipe, vehicle is given by Equation (3): 1 Qtailpipe; vehicle ¼ eVcyl Ωm 2

(3)

Where e is the efficiency of the engine and Ωm the speed of the engine. According to Heywood (1988) and Hancke (2009), e ¼ 0.9 and Ωm ¼ 2200 RPM (Rotation Per Minute) for a vehicle in an urban environment. Considering a tailpipe diameter of 0.055 m, then Qtailpipe, vehicle is 0.0245 m3/s. This gives Utp ¼ 10.3 m/s and U0/Utp~1.35 for real conditions. Taking into account all relevant parameters of the experimental facilities (for instance the diameter of the tailpipe in the wind tunnel and the characteristics of the particle generator detailed in section 2.4.2), the incoming air flow velocity was constant and fixed to the value U0 ¼ 14.3 m/s (Rodriguez, 2018). This ensures U0/Utp~1.35 for the experiments. Compared to previous studies (Richards, 2002; Gosse, 2005; Kanda et al., 2006; Carpentieri et al., 2012), this is a novelty. Finally, the corresponding Reynolds number based on the height of the car model (Eq. (4)) was 49500.

(1)

Three sketches of the models with below, rear and side views are shown on Fig. 2. O (0, 0, 0) is the origin of the coordinate system. It is located at the bottom of the rear face of the car and on the centreline of the wind tunnel. x is the streamwise direction (positive downstream), y is the vertical direction (positive upwards) and z is the spanwise direction (positive from right to left when looking from the back of the vehicle). The tailpipe has an outer/inner diameters of 6 mm and 4 mm, respectively. These settings were chosen taking into account the boundary layer thickness and the averaged velocity of the UFP at the exit of the tailpipe. The exit of the tailpipe (center) is located at X ¼ x/h ¼ 0, Y ¼ y/h ¼ 0.06 and Z ¼ z/h ¼ 0.31. One can refer to Rodriguez (2018) for more details.

Re ¼ 2.3. Determination of experimental conditions

U0 *h

υ

(4)

Where ν is the kinematic viscosity of air. It is acknowledged that the present Reynolds number is one order of

As presented above, the goal of the present study was to analyse particle dispersion in the wake of car models. This phenomenom was 3

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the highest level to ensure highest SNR (Signal to Noise Ratio) for PNC measurements. This gave a mass flow rate of particles of about 6.5 mg/h. Similarly, the nitrogen flow rate was set at 8 L/min. Note that the recommendation of the manufacturer at that spark frequency was 6.5 L/ min (minimum). Taking into account the inner diameter of the exhaust pipe (4 mm), the exit velocity of the particles was Utp ¼ 10.6 m/s.

magnitude lower than it would be in real situation. Nevertheless, Barros (2015), Lahaye (2014), Gosse (2005) and Ahmed et al. (1984) indicated that the main flow structures remain the same for a large range of Reynolds numbers as well as the velocity profiles in the wake. The recirculation region was also quite stable in these studies with Reynolds numbers up to 106. This was confirmed by comparing the present findings with previous results covering a large range of Reynolds numbers show similar trends, making the present study meaningful. Lastly, for ϕ ¼ 25 , Leclerc (2008) showed the same behavior for the pressure distributions on the rear slant for 67000
2.4.3. Electrical low pressure impactor (ELPI) For PNC measurements (number of UFP per cm3 for each given position), an ELPI was used. This device enabled measurement of real-time PSD and concentration in the size range of 6 nm–10 μm with 1 Hz sampling rate. It has been developed by the University of Tampere (Finland). Its features include real-time stand-alone operation, wide sample concentration range, wide particle size range and robust structure for operation even in harsh conditions. Considering all features, the use of the ELPI was well-suited for our measurements. It was previously used (Mehel and Murzyn, 2015) showing its satisfying performances. Overall, the operating principle can be divided into three major parts:

2.4. Instrumentation 2.4.1. LASER Doppler Velocimetry (LDV) Velocity measurements were recorded with a 2D LDV system manufactured by DANTEC dynamics (model 2D Flow Explorer). The two pairs of LASER beams have wavelengths of 660 nm and 785 nm. Fringe spacings were 5.45 μm and 6.40 μm in the longitudinal and vertical directions, respectively. Diameter and length of the measuring volume in the z-direction are 168 μm and 2.81 mm respectively for the first component (horizontal) and 200 μm and 3.34 mm for the second component (vertical). The focal length is 500 mm and Bragg cell frequency shift is 80 MHz. The LDV system was fixed on a 2D displacement table. It was controlled by BSA Flow Software v5.03.00. The fog used in this study for seeding was the SAFEX inside Nebelfluid Extra Clean provided by DANTEC. The fog generator model was SAFEX S 195 G. It had an adjustable flow rate. The mean diameter of the generated droplets was 1.068 μm. According to Algieri et al. (2005), Rodriguez et al. (2018) and Rodriguez et al. (2019), the accuracy of the measurements is then ensured with respect to the present experimental conditions. Note that the lowest point for LDV measurements was 20 mm above the bottom. Below, the optical path of the LASER beams associated with the vertical component of the velocity was blocked by this bottom.

1) Particle charging; 2) Size classification throughout a cascade impactor; 3) Electrical detection by sensitive electrometers. The particles were first charged into a known charge level in the Corona charger. After that, the particles entered a cascade low-pressure impactor with 14 electrically insulated collection stages. The particles were collected in the different impactor stages according to their inertia (aerodynamic diameter). The electric charge carried by particles into each impactor stage was then measured in real time by sensitive electrometers. This current signal was directly proportional to the particle number concentration per stage (size range). Measured current signals were converted to particle size distribution using particle size dependent relations describing the properties of the charger and the impactor stages. The result was particle number concentration and size distribution in real-time. For more details, one can refer to Rodriguez (2018). In order to satisfy the isokinetic condition, the velocity of the aerosol suction must be equal to the flow velocity at the measuring point to avoid any divergence of the streamlines. Nevertheless, this could not be ensured during experimentations. So, based on the upstream velocity, this condition led to a sampling probe diameter of ~3.86 mm. Consequently, a diameter of 4 mm for the sampling probe was chosen. At this stage, for experimental constraints, the sampling probe was bended. It is worthwhile to note that two models of such probes were used with lengths of 25 and 50 mm. A preliminary calibration study proved the robustness of this choice (Rodriguez, 2018). Fig. 3 shows the devices used for PNC measurements as well as and the experimental arrangement. Similarly, the lowest point for PNC measurements was 13 mm above the bottom due to the bending of the sampling probe.

2.4.2. PALAS Particles were generated by a PALAS DNP 2000. It is a nano-scale test generator of aerosols from monolithic graphite. The resulting carbon agglomerates are similar to Diesel soots (Evans et al., 2003) with respect to particle size distribution (Fig. 1). This system required nitrogen as the carrier gas. This gas caused virtually no change in the density of the exhaust gas being measured. From a technical point of view, PALAS was used to generate a jump spark between two graphite electrodes under high voltage. It then ripped tiny amount of graphite material from the electrodes at high temperatures. The graphite material that was vaporized by this spark then condensed to form extremely tiny particles. The high number concentration can result in the coagulation of these very small particles into agglomerates. By adding mixed air, the aerosol was able to be diluted, enabling the defined adjustment of the agglomerate formation. The energy converted in each spark remained constant due to the constant sparkover voltage. This constant energy in each individual spark guaranteed stable particle size distribution. A technically sophisticated control of the distance between the electrodes during burn-off ensured very high long-term stability. The mass flow rate was quickly and easily adjusted within a wide range using the spark frequency. The digital regulation of the frequency and the continuous regulation of the voltage guaranteed a more specific regulation of the distance between the two electrodes. This enabled a higher constancy of the particle size distribution and the mass flow. Due to its excellent reproducibility and high level of functional reliability, the DNP digital 2000 was especially well suited for our experiments (Evans et al., 2003; Oberd€ orster et al., 2004; Price et al., 2014; Mehel and Murzyn, 2015). Indeed, as mentioned above, the generated aerosol distribution was very similar to the distribution of Diesel soot particles from a combustion engine. In terms of PSD, a preliminary study showed that more than 93% of the particles have a diameter between 30 and 109 nm (Rodriguez, 2018). For the present study, the spark frequency was set at 200 Hz. This is

Fig. 3. Experimental arrangement for ELPI and PALAS during measurements. 4

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the spanwise direction, 5 positions were studied (Z ¼ 0.62, 0.31, 0, 0.31 and 0.62) for X < 2.89. For X > 2.89, 7 positions were studied (Z ¼ 1.85, 1.24, 0.62, 0, 0.62, 1.24 and 1.85). This was done to cover a wider area to get a better assessment of the dispersion in the far field. Overall, PNC were measured for 1926 positions for the three car models. Fig. 5a (side view) and Fig. 5b (top view) show the measuring points for PNC.

2.5. Data acquisition and analysis Preliminary studies were undertaken as a calibration work. First, the convergence of the LDV data and their statistical accuracy were ensured. Based on it, measurements lasted 90 s with 3000 samples as a minimum value (Rodriguez, 2018). Measurements took place in the wake of the three car models. The covered domain spread as follow: 0.09
3. Results In this section, both mean and turbulent properties of the wake for the three car models are of interest. First, an overview of the mean flows is presented. In a second time, the fluctuating part of the flows is depicted. U corresponds to the horizontal component of the velocity vector while V is the vertical one. u’ and v’ are the corresponding RMS values. 3.1. Overview of the wake flows Firstly, the results dealing with the mean flow characteristics are presented according to the rear slant angles. Fig. 6 is dedicated to the 2D maps of the velocity vectors in the wake of the 3 models. The dimensionless modulus of the velocity is shown as a color map. Same scales are used to make the comparisons easier. At this stage, the tailpipe is not installed. Nevertheless, its influence as well as that of the exhaust flow will be discussed later. These preliminary results are mandatory to validate the whole experimental methodology by comparison with the existing data available in the literature. First, the recirculation length (Lrec) is considered. It is defined as the largest distance between the rear face of the car and the position for which a negative component of the horizontal velocity (U) is detected. The results are indicated in Table 1. This is in agreement with previous findings (Tunay et al., 2014; Lahaye, 2014; Wang et al., 2013) for relatively similar experimental conditions. Furthermore, the existence of two contra-rotating vortices for each case is pointed out. Depending on the rear slant angle, they are more or less developed. The upper one is clockwise while the lower one is counter clockwise. Their positions are given in Table 2. For the case ϕ ¼ 0 (Fig. 6, (a)), the properties of U and V are respectively almost symmetric and antisymmetric according to Y ¼ 0.5. For ϕ ¼ 25 (Fig. 6, (b)), the general trend of the flow is pointing downward except in the closest part of the rear face of the car model due to the presence of the lower vortex. The attachment of the flow on the rear slant is observed for this configuration. As a consequence, the vertical component of the velocity is mostly negative. Note that the position of the lower vortex was not possible as velocity measurements were not allowed closed to the bottom of the wind tunnel for technical reasons. For

Fig. 4. a. Measuring points for LDV in the wake of the car models (side view). b. Measuring points for LDV in the wake of the car models (rear view). 5

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Fig. 5. a. Measuring points for PNC in the wake of the car models (side view). b. Measuring points for PNC in the wake of the car models (top view).

Table 1 Comparison of recirculation length with the literature for similar experimental conditions. Lrec/h

ϕ ¼ 0

ϕ ¼ 25

ϕ ¼ 35

Present study Literature

1.39 1.50 (Lahaye, 2014) 7%

0.58 0.57 (Tunay et al., 2014) 2%

1.06 1.07 (Wang et al., 2013) 1%

Deviation from the literature

Table 2 Comparison of the positions (X, Y, Z) of upper and lower vortices in the symmetry plane Z ¼ 0 with the literature for similar experimental conditions (N/A: Not Available). Positions of vortices

ϕ ¼ 0

ϕ ¼ 25

ϕ ¼ 35

Present study

Upper: (0.62, 0.84, 0) Lower: (0.70, 0.14, 0) Upper: (0.93, 0.84, 0) Lower: (0.68, 0.20, 0) Lahaye (2014)

Upper: (0.19, 0.37, 0) Lower: N/A

Upper: (0.21, 0.70, 0) Lower: N/A

Upper: (0.17, 0.30, 0) Lower: (0.35, 0.05, 0) Tunay et al. (2014)

Upper: (0.28, 0.69, 0) Lower: (0.44, 0.11, 0) Tunay et al. (2014)

Literature

Fig. 6. 2D maps (XY) of the velocity vectors and dimensionless velocity magnitude in the wake of the 3 car models (a: ϕ ¼ 0 , b: ϕ ¼ 25 , c: ϕ ¼ 35 ) in the symmetry plane Z ¼ 0.

ϕ ¼ 35 (Fig. 6, (c)), the flow on the rear slant is detached. As a consequence, the downwash effect of the flow is less important compared to ϕ ¼ 25 . As for ϕ ¼ 25 , the position of the lower vortex was not determined. For comparison, results from previous studies are also provided in Table 2 showing good agreements. In terms of fluctuations, the dimensionless Turbulent Kinetic Energy (TKE*, Eq. (5)) and Reynolds Shear Stresses (SS*, Eq. (6)) are presented on Fig. 7 and Fig. 8. In 2D, they are given by Equation (5) and Equation

(6), respectively. TKE* ¼

SS* ¼

6

1 u’2 þ v’2 2 U 20

u’v’ U 20

(5)

(6)

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Journal of Wind Engineering & Industrial Aerodynamics 198 (2020) 104109

Fig. 7. 2D maps (XY) of TKE* in the wake of the 3 car models in the symmetry plane Z ¼ 0 (a: ϕ ¼ 0 , b: ϕ ¼ 25 and c: ϕ ¼ 35 ).

Fig. 8. 2D maps (XY) of SS* in the wake of the 3 car models in the symmetry plane Z ¼ 0 (a: ϕ ¼ 0 , b: ϕ ¼ 25 and c: ϕ ¼ 35 ).

The dotted lines on Figs. 7 and 8 correspond to the boundary of the recirculation region while A and B account for the center positions of the upper and lower vortices, respectively. A and B are determined from the streamlines deduced from the velocity measurements. In the following figures, large black dotted lines refer to the boundary of the recirculation region obtained from velocity measurements while tiny black dotted lines refer to the boundary of the recirculation region deduced from flow symmetry. In some cases, B can not be determined for technical reasons (too close to the bottom of the wind tunnel). These plots provide some useful information regarding the flow dynamics. In the literature, it is often admitted that an increase in the Reynolds Shear Stresses (SS) leads to an increase of Turbulent Kinetic Energy (TKE). In other words, high gradient regions for turbulent kinetic energy often correspond to high shear stress regions. According to Lienhart et al. (2002, 2003), peaks of TKE are located at the same positions as peaks of turbulent shear stresses. Overall, these results were in agreement with those findings. For ϕ ¼ 0 , high TKE levels are found in the upper half (Y > 0.50) over a relatively large area. For ϕ ¼ 25 and 35 , highest values are mostly in the lower half (Y < 0.50) and spread over a relatively smaller area. For ϕ ¼ 0 , 25 and 35 , in the symmetry plane (Z ¼ 0), the corresponding values of the peaks of TKE are given in Table 3. In terms of magnitude, the corresponding maximum turbulence intensities (Ix ¼ u’/U0) are 29%, 29% and 31%, respectively. Similar conclusions were revealed for the vertical component of the velocity (Iy ¼ v’/U0). Overall, these results are in good agreement with those of Tunay et al. (2014) for ϕ ¼ 25 and 35 . The shear stresses represent the correlation between the fluctuations of the horizontal and vertical components of the velocity vector. On the one hand, SS are negative in the upper part of the wake flow where the vertical component V was negative and the horizontal component U was positive.

On the other way, SS are positive in the lowest part of the flow where both U and V are positive. For ϕ ¼ 0 , SS were almost symmetric with respect to Y ¼ 0.5 until X~3. In terms of magnitude, they are slightly larger in the upper part compared to the lower one. For ϕ ¼ 25 , high shear stress regions were located in the lower part of the flow. It shows that the flow seems much more unstable in this lower region for this configuration. Nevertheless, this 2D map is not complete for the closest part of the bottom. This configuration was associated with the smallest recirculation region. For ϕ ¼ 35 , this was an intermediate situation between ϕ ¼ 0 and ϕ ¼ 25 . The largest values are found in the lower region. Table 3 details all these information. Finally, this preliminary study allowed us to validate our experimental setup. Indeed, these results were in good agreements with some previous studies in similar experimental conditions. Two different regions were clearly identified. One accounts for the near wake (0
Table 3 Properties of TKE* and SS* with the corresponding positions (X, Y, Z) in the wake of the 3 car models. Rear slant angle

ϕ ¼ 0

ϕ ¼ 25

ϕ ¼ 35

TKE*max Position SS*max Position SS*min Position

0.07 (0.99, 0.83, 0) 0.026 (1.05, 0.18, 0) 0.043 (1.22, 0.83, 0)

0.07 (0.26, 0.09, 0) 0.035 (0.32, 0.09, 0) 0.021 (0.65, 0.36, 0)

0.08 (0.49, 0.09, 0) 0.044 (0.82, 0.09, 0) 0.020 (0.05, 0.93, 0)

7

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3.2. Influence of the tailpipe system and exhaust flow on the wake flow properties Before injecting particles, a study was conducted to analyse the influence of the tailpipe system and the exhaust flow on the wake flow properties. This is new and innovative as the previous studies compared mass concentration fields with flow topologies without tailpipe. Fig. 9 and Fig. 10 show the results with (dots) and without (lines) the tailpipe and the exhaust flow for ϕ ¼ 25 for 2 different vertical planes Z (Z ¼ 0.23 in blue and Z ¼ 0.45 in red). Fig. 9 is for U (mean) and Fig. 10 is for u’ (RMS of U). These figures indicate that the results for both mean and RMS values for the horizontal component of the velocity are similar with and without the tailpipe. It means that the presence of the exhaust system does not significantly affect the mean and turbulent flow dynamics in the wake of this car model. It can be explained by the fact that the velocity difference between the upstream flow and the exhaust one is small. Then, the deficit of linear momentum of the latter one is easily counterbalanced by the surrounding underbody upcoming flow. It is important to note that comparable results were obtained for ϕ ¼ 0 and 35 for mean and RMS values of U and V. Precisely, for the mean velocities, the difference between with and without tailpipe are below 0,04U0 while it only reaches 0,02U0 for the RMS values.

Fig. 10. Comparison of the RMS horizontal velocity (u’) with (WT) and without (WOT) the tailpipe system for Z ¼ 0.23 and Z ¼ 0.45 (ϕ ¼ 25 ).

3.3. UFP concentration in the wake of the Ahmed body (ϕ ¼ 0 ) Measurements were collected in a wide 3D domain downstream of the three car models. In this section, attention is focused on 2D maps of PNC in the wake of the 3 car models. Dimensionless PNC (PNC*, Eq. (7)) are presented. All concentrations were divided by a reference level (Cref) which corresponds to the PNC measured at the exit of the tailpipe (Cref~6.96.107 part/cm3). That is: PNC* ¼

PNC PNC ¼ Cref 6:96*107

(7)

For the next figures, black dots correspond to the positions where measurements were done. a) Case ϕ ¼ 0 Fig. 11 show the results in three different vertical planes (XY) for the squared back model (Z ¼ 0.31, 0 and 0.31). The first one (Z ¼ 0.31) was aligned with the tailpipe while the second one (Z ¼ 0) corresponded to the symmetry plane. The highest levels of dimensionless PNC are found for Z ¼ 0.31. In this case, measurements were aligned with the tailpipe exit. High levels of PNC* were measured over a wide area in both streamwise and vertical directions. The peak for PNC* (~0.33) was measured at (X ¼ 0.57; Y ¼ 0.04; Z ¼ 0.31). That is one third of the level measured at the tailpipe exit. As X increases, PNC* decreases down to 0.1 (X ¼ 1.27) and 0.01 (X ¼ 3.46). In the vertical direction, PNC* ¼

Fig. 11. 2D maps (XY) of PNC* in the wake of the Ahmed body (ϕ ¼ 0 ) for Z ¼ 0.31 (a: tailpipe plane), Z ¼ 0 (b: symmetry plane) and Z ¼ 0.31 (c).

0.01 spreads up to y/h ¼ 0.90 even if ejection occurs at Y < 0. This was almost the full height of the vehicle. It can be explained by the flow topology described in the previous section. As soon as they are ejected from the tailpipe, the particles are entrapped within the recirculation region which is the largest for this configuration (Lrec/h ¼ 1.39). Their motions are mostly governed by the two vortices depicted by the LDV measurements in the close wake. Overall, it is still obvious that most of the particles are found in the lower part of the flow for Z ¼ 0.31. For Z ¼ 0 (symmetry plane), the PNC* levels are significantly lower compared to those measured for Z ¼ 0.31. PNC* is always below 0.10. Nevertheless, a homogeneous distribution of PNC* is depicted for Z ¼ 0 over the total height of the car model. In the close wake, PNC* reaches 0.03 and levels were between 0.01 and 0.10 up to X ¼ 3.95. The toric shape of the turbulent structure appearing in the recirculation region explains this finding (Rodriguez, 2018). The combination of the lower and upper vortices was capable of capturing particles and carrying them from the bottom to the upper part of the flow. Similarly, the horizontal turbulent

Fig. 9. Comparison of the mean horizontal velocity (U) with (WT) and without (WOT) the tailpipe system for Z ¼ 0.23 and Z ¼ 0.45 (ϕ ¼ 25 ). 8

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structures disperse the particles in the spanwise direction. Overall, for Z ¼ 0, the PNC* map is almost symmetric with respect to Y ¼ 0.50. This was comparable to the velocity field given for the same dimensionless position Z. Lastly, for Z ¼ 0.31, PNC* levels are significantly lower compared to those depicted for Z ¼ 0.31 and 0. Practically, PNC*<0.01 for X>0.80. Nevertheless, some particles are still conveyed in the spanwise direction by the turbulent structures of the flow. Finally, PNC*>0.001 everywhere in the 2D map. Lastly, the vertical mixing is efficient, as the corresponding 2D velocity map tended to be symmetric. For a full description of the dispersion of the particles in the wake of the car model, additional 2D horizontal maps (XZ) are presented for different dimensionless distances above the bottom of the wind tunnel (Fig. 12). That is for Y ¼ 0.04, 0.33 and 0.70. Y ¼ 0.04 is located in the vicinity of the tailpipe exit which is less than 2 mm below. For Y ¼ 0.04, there is no black dotted line as there is no recirculation in this part of the flow. The highest levels are obviously measured for Y ¼ 0.04 and Z ¼ 0.31, aligned with the tailpipe exit. Up to X ¼ 1.60, PNC* are larger than 0.01. In this case, most of particles are kept in the half width (tailpipe side) of the body. Above (Y ¼ 0.33), in the recirculation region, horizontal mixing occurred and concentration homogenization was then strongly enhanced. As a consequence, the PNC* field became more symmetric with respect to Z ¼ 0 in the far wake. It was then the mixing caused by the recirculation region that governed the particle dynamics in the close wake. The same results were observed for Y ¼ 0.70. Particles are brought in the upper part of the flow by the recirculation region and the horizontal mixing led to a symmetric field of PNC* with respect to Z ¼ 0.

Fig. 13 present three vertical maps of PNC* corresponding to the same dimensionless positions Z ¼ 0.31, 0 and 0.31 for the case ϕ ¼ 25 . As seen for ϕ ¼ 0 , the highest levels for PNC* are measured for Z ¼ 0.31 (PNC*max ¼ 0.14 at X ¼ 0.57, Y ¼ 0.06 and Z ¼ 0.31). PNC* are larger than 0.01 up to X ¼ 3.20. This is a shorter distance compared to ϕ ¼ 0 . The vertical spreading is weaker as well: for Y < 0.34, PNC* does not exceed 0.01. Above, levels are even smaller. One more time, this is caused by the flow topology downstream of the car model: the recirculation region was less volumic (Lrec/h ¼ 0.58) as the flow was attached on the rear slant leading to a more pronounced downwash effect compared to ϕ ¼ 0 . Similarly, PNC* are between 0.001 and 0.01 up to X ¼ 2.50. Lastly, for this flow configuration, longitudinal vortices arise from the edges of the car model and develop downstream. Out of the recirculation region, they become predominant. Then, they catch and carry particles away from the symmetry plane of the model, in the same side of the tailpipe. As a consequence, PNC* levels are very low for Z ¼ 0 and 0.31. This is a typical feature associated with this rear slant angle. For Z ¼ 0, PNC* are always below 0.01. The downwash effect is still strong and the maximum values for PNC* are always found in the lower part of the flow for X < 2. Further downstream, PNC* increases again to reach more than 0.01 for Y ¼ 0.40. Then, the distribution of PNC* is not homogeneous for Z ¼ 0 while it was the case for ϕ ¼ 0 . For Z ¼ 0.31, PNC* is always below 0.001 even in the close wake. This behavior differs from that observed for ϕ ¼ 0 . For ϕ ¼ 25 , the longitudinal vortices tend to play a key role in particle entrapment. Fig. 14 show 2D (XZ) maps of the PNC* for ϕ ¼ 25 for 3 dimensionless positions Y. As for ϕ ¼ 0 , for Y ¼ 0.04, there is no black dotted line as there is no recirculation in this part of the flow. Similarly, for Y ¼ 0.70, it is above the recirculation region. So there is not a black dotted line. From the results corresponding to Y ¼ 0.04, it is confirmed that longitudinal vortices influence the particle dynamics. Most of the UFP

(b) Case ϕ ¼ 25

Fig. 12. 2D maps (XZ) of PNC* in the wake of the Ahmed body (ϕ ¼ 0 ) for Y ¼ 0.04 (a: tailpipe level), Y ¼ 0.33 (b) and Z ¼ 0.70 (c).

Fig. 13. 2D maps (XY) of PNC* in the wake of the Ahmed body (ϕ ¼ 25 ) for Z ¼ 0.31 (a: tailpipe plane), Z ¼ 0 (b: symmetry plane) and Z ¼ 0.31 (c). 9

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Fig. 15. 2D maps (XY) of PNC* in the wake of the Ahmed body (ϕ ¼ 35 ) for Z ¼ 0.31 (a: tailpipe plane), Z ¼ 0 (b: symmetry plane) and Z ¼ 0.31 (c).

corresponding to this position (Z ¼ 0.31) exhibit a strong correlation with those presented for ϕ ¼ 0 at the same dimensionless position Z. Up to X ¼ 0.88 (3.07, respectively), PNC* are above 0.10 (0.01, respectively). The dispersion is also important in the vertical direction (PNC*>0.01 up to Y ¼ 0.66 in the close wake). These findings confirm that the size of the recirculation region is of primary importance regarding particle dispersion. Furthermore, due to the detached flow over the rear slant, there is no more strong downwash effect compared to the case ϕ ¼ 25 . For Z ¼ 0 (symmetry plane), PNC* are below 0.1. Nevertheless, the distribution seems to be homogeneous over the height of the car model in the close wake. This is due to the size of the recirculation (Lrec/h ¼ 1.06) region which is larger than that measured for ϕ ¼ 25 (Lrec/h ¼ 0.58). From X ¼ 2.23, PNC* decrease below 0.01. Far downstream, the homogeneity of PNC* is lost in the vertical direction and particles tend to accumulate in the lower part (Y < 0.50). For Z ¼ 0.31, lower levels are measured (PNC*<0.01). Nevertheless, the recirculation region allows a mixing in the horizontal direction in the close wake. Fig. 16 exhibit 2D horizontal maps (XZ) for 3 different dimensionless distances above the bottom of the wind tunnel (Y ¼ 0.04, 0.33 and 0.70). Once again, for Y ¼ 0.04, there is no black dotted line as there is no recirculation in this part of the flow. At the tailpipe level (Y ¼ 0.04), concentrations are relatively high. For Z < 0, PNC* are larger than 0.1 for X < 2 while they are roughly 0.001 for Z > 0. Beyond X ¼ 2, differences are weaker as PNC* levels are about 0.01. In this case, the PNC* distribution is not strictly symmetric with respect to Z ¼ 0. More particles are found for Z < 0 (tailpipe side). Above (Z ¼ 0.33), the recirculation area is crossed. This enables the enhancement of the horizontal mixing even if PNC* is still three times larger in the tailpipe side compared to the levels observed on the other side (Z > 0). Finally, at the highest dimensionless distance above the ground level (Z ¼ 0.70), the distribution of PNC* is more homogeneous (PNC*~0.01) in the close wake as we are still in the recirculation region.

Fig. 14. 2D maps (XZ) of PNC* in the wake of the Ahmed body (ϕ ¼ 25 ) for Y ¼ 0.04 (a: tailpipe level), Y ¼ 0.33 (b) and Z ¼ 0.70 (c).

emitted from the tailpipe are entrapped in the half width of the tailpipe because of the longitudinal vortex which arises from the edge of the car model. Particle paths are diverted from the symmetry plane (Z ¼ 0) towards the external part of the flow (Z < 0). Furthermore, at this dimensionless distance above the bottom, the recirculation region is not crossed yet. On the opposite side (Z > 0), PNC* are very low. The mixing on the spanwise direction can not take place. Above the tailpipe level (Z ¼ 0.33), the PNC* field is still not symmetric at all while it was for ϕ ¼ 0 . This result confirms the combined influence of the longitudinal vortices above mentioned and the very small recirculation region due to the downwash effect. Furthermore, at this stage, the recirculation region is not large enough to catch particles and drive them on the other side of the car model (Z > 0): the length of the recirculation region was only 0.58 h for ϕ ¼ 25 (it was 1.39 h for ϕ ¼ 0 ). For Z > 0, PNC* is less than 0.001 while it reaches 0.1 for Z < 0. Z ¼ 0 can then be associated with a virtual boundary between the longitudinal vortices emitted from the right and left edges of the car model, respectively. In the horizontal map (Y ¼ 0.70), very low levels are measured. This is mostly due to the attachment of the flow on the rear slant. For Z > 0, above the recirculation region, mixing can not occur and particles can not be conveyed from the tailpipe to this upper region. c) Case ϕ ¼ 35 Fig. 15 present the PNC* field for the last car model (ϕ ¼ 35 ) for the same planes Z ¼ 0.31, 0 and 0.31. As for ϕ ¼ 0 and 25 , the highest levels of PNC* are located in the tailpipe axis, that is for Z ¼ 0.31. PNC*max is 0.20 at X ¼ 0.57, Y ¼ 0.04 and Z ¼ 0.31. Overall, the results 10

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Table 4 Experimental conditions for Richards (2002), Gosse (2005), Kanda et al. (2006) and Carpentieri et al. (2012). Study

Reynolds number

Car model and rear slant angle (ϕ)

Pollutant

Present study

49500

Particles

Richards (2002) Gosse (2005)

335000 5600 and 17600 7100 and 14000 12000 and 48000

Ahmed bodies, ϕ ¼ 0 , 25 and 35 MIRA Ahmed bodies, ϕ ¼ 5 , 25 and 40 Passenger car and truck Vauxhall Astravan

Gas tracer

Kanda et al. (2006) Carpentieri et al. (2012)

Gas tracer Heated air Gas tracer

 For ϕ ¼ 0 , the recirculation region is the largest one and the flow is also almost symmetric vertically and horizontally leading to higher and more homogeneous PNC* levels in the close wake of the car model;  For ϕ ¼ 25 , the attachment of the flow on the rear slant leads to a smaller recirculation region and prevents from a homogeneous mixing over the whole height of the car model. Furthermore, the longitudinal vortex on the side of the tailpipe and developing from the edge of the car model is capable of trapping the particles in the corresponding half width of the model. On the other side, because of a weaker mixing, concentrations are lower;  For ϕ ¼ 35 , some similitudes are found with the case ϕ ¼ 0 as the flow is detached on the rear slant angle. Nevertheless, the recirculation length is smaller for ϕ ¼ 35 than for ϕ ¼ 0 . The present results are discussed with respect to previous experimental studies undertaken in wind tunnels. Four studies are considered: Richards (2002), Gosse (2005), Kanda et al. (2006) and Carpentieri et al. (2012). They were selected as they all dealt with pollutant dispersion in the wake of vehicles. Table 4 summarizes their experimental conditions. It underlines the novelty of the present study considering that previous works mostly used gas tracer or heated air while particles were used here. Similarly, PNC fields were depicted in the present work while in the past mass concentration fields were described. In the first one, Richards (2002) developed a numerical model to assess pollution dispersion in the near wake of a vehicle. As part of it, she worked in a wind tunnel with the MIRA (Motor Industry Research Association) car model. She measured the concentration of a tracer gas in the near-wake (X < 1) of her 33% scaled model by FID (Flame Ionisation Detector). Among her most significant results, she firstly pointed out the influence of the recirculation region and its contra-rotating vortex structure. Secondly, she also depicted a general upward dispersion of the tracer gas confirming that pollutant was drawn up into the recirculation region by the lower internal vortex. Thirdly, she stated that a rapid dispersion occurred away from the source with concentration values falling to 7% of the maximum value within 50 mm of the source. Her findings exhibit some similarities with the present results meaning that the recirculation region has a major influence on the pollutant dynamics; let it be gas or particles. Gosse (2005) was interested in the dispersion of a passive scalar (temperature) in the close wake of Ahmed bodies with three rear slant angles (ϕ ¼ 5 , 25 and 40 ). Scale of his models was 1/50 compared to that of Ahmed et al. (1984). It is worthwhile to note that our corresponding scale is 1/20. Heated air was ejected from a tailpipe with a velocity comparable to that of the incoming flow. His results showed a Reynolds dependence of the passive scalar field for ϕ ¼ 25 while it is almost 2D for ϕ ¼ 5 and 40 whatever the Reynolds number. In the close wake, the influence of the recirculation region on the passive scalar field was underlined as well as the role of the longitudinal vortices for ϕ ¼ 25 further downstream. He also suggested that the mixing occurred rapidly in the wake with a favoured dispersion in the spanwise direction. This

Fig. 16. 2D maps (XZ) of PNC* in the wake of the Ahmed body (ϕ ¼ 35 ) for Y ¼ 0.04 (a: tailpipe level), Y ¼ 0.33 (b) and Z ¼ 0.70 (c).

4. Discussion These 2D horizontal and vertical maps of PNC highlight new insights about particle dispersion in the wake of vehicles. Overall, they show that:  At a distance of X ¼ 0.50 downstream of the tailpipe, PNC is rapidly divided by a factor 3 to 14 depending on the rear slant angle;  For the three rear slant angles, highest levels of PNC are found in line with the tailpipe exit;  In the close wake, the volume of the recirculation region is a key parameter governing mixing and dispersion of particles in both vertical and spanwise directions;  Particles are emitted below the recirculation region. Nevertheless, the shearing revealed from the LDV measurements allows the carriage of UFP within the low pressure region associated with lower vortex;  In a second time, another part of these UFP is shifted vertically to the upper part of the flow due to the interaction with the upper vortex;  Meanwhile, a portion of the UFP in the recirculation region are conveyed horizontally on both sides of the symmetry plane through the same turbulent system; For all conditions (ϕ ¼ 0 , 25 and 35 ), the flow dynamics is strongly influenced by the toric vortex developing in the recirculation region. For ϕ ¼ 25 , the longitudinal vortices emitted from the edges of the car model are crucial. The turbulent structure of the wake flow plays a key role in the particle dispersion in the wake of the car models. By looking more carefully at each experimental conditions, the present results point out that: 11

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finding was mostly pronounced for ϕ ¼ 25 . Similarly, these results tend to indicate a different feature for ϕ ¼ 25 due to these longitudinal vortices. Kanda et al. (2006) worked in a wind tunnel to assess exhaust gas dispersion from two models of road vehicles (a sedan and a small-size truck, respectively). Their scale was 1/20 compared to real size vehicles. Reynolds numbers were 7100 and 14000, respectively. They mentioned that the presence of the car enhanced the dispersion in a significant way. They also suggested that the position of the tailpipe was important. Indeed, for the small size truck (similar to a squared back vehicle), they stated that the exhaust gas diffusion would have been suppressed for an exhaust pipe on the top of the truck. Furthermore, they affirmed that the most affected region should be in the near-wake where mixing rapidly occurs. In the present study, the role of the near-wake with its recirculation region is pointed out as well as the tailpipe position on the PNC field downstream of a vehicle. Carpentieri et al. (2012) carried out wind tunnel measurements downstream of reduced scale car models (similar to 2004 Vauxhall Astra Van). They worked with a 1/5 scale model for the near-wake characterization and a 1/20 scale model for far-wake investigation. A passive gas tracer was used with an exit velocity as low as possible to provide a passive release. They highlighted the effect of the recirculation region and the corresponding vortices. According to their measurements, the plume was not Gaussian, especially in the near-wake. Their study was presented as a “first step” in order to assess nanoparticle dispersion in the wake of a vehicle. In that sense, this experimental work may be considered as a further step. Furthermore, they identified some differences between results provided by experiments and those given by a numerical model (CAR BUILD) which assumes a Gaussian plume. Concentrations measured in line with the tailpipe in the wind tunnel were larger than those predicted by the model. Indeed, this model was based on a complete mixing assumption. From the experimental measurements, this hypothesis must be obviously revised and the position of the tailpipe was then a relevant parameter which was not taken into account in the numerical model. Finally, they emphasized that nanoparticle dispersion in the wake of a real car was a complex phenomena as “emitted particles undergo a range of very fast transformation processes just after their release from the tailpipe while the passive tracer gas is affected only by dilution”. Although difficult, it should be taken into account for wind tunnel investigations.

conditions. For ϕ ¼ 25 , the influence of the longitudinal vortices emitted from the edges of the car was also underlined. Overall, this paper brings new insights regarding the dispersion of particles (UFP) in the wake of cars. To date, studies dealing with this topic are quite limited. Most of them used passive tracers to address this issue leading to mass concentration fields. For the first time, UFP having a PSD similar to that of a Diesel engine were used. The present results can be used to improve existing numerical models as well as to provide data for real PNC exposure rates for UFP epidemiologic studies. Combined with on board measurements, it is believed that they may contribute to some recommendation in terms of ventilation settings, driving modes and/or air intake and tailpipe positioning to limit pollutant infiltration in the car cabin. Nevertheless, further investigations are required to identify the role of parameters such as the yaw angle and the incoming velocity on the dynamics of particles in the wake of cars. Studying more realistic car shapes, changing the tailpipe’s position, size and/or angle would be interesting as well. Furthermore, working on the experimental setup could be done to allow measurements closed to the bottom. Last but not least, the improvement of analytical models (non Gaussian) would be possible. 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. CRediT authorship contribution statement Romain Rodriguez: Methodology, Validation, Formal analysis,
de
ric Murzyn: ConcepInvestigation, Data curation, Visualization. Fre tualization, Methodology, Validation, Investigation, Writing - original draft, Writing - review & editing, Supervision. Amine Mehel: Supervision. Frederique Larrarte: Writing - review & editing, Supervision. Acknowledgements The authors acknowledge the financial support of ESTACA (Ecole Sup
erieure des Techniques A
eronautiques et de Construction Automobile) and Laval Agglom
eration. They both funded the PhD research project of Romain Rodriguez.

5. Conclusions and perspectives

References

In the present paper, the dispersion of UFP in the wake of three Ahmed bodies having different rear slant angles (ϕ ¼ 0 , 25 and 35 ) was studied. This is an innovative approach as UFP were used for the first time. Experimental results were obtained in a wind tunnel with reduced scale models. The incoming velocity was U0 ¼ 14.3 m/s corresponding to a Reynolds number based on the height of the vehicle of 49500. These conditions were defined to be representative of a vehicle in an urban environment. Velocities were recorded with a 2D LDV system. Particles were generated with a PALAS DNP 2000 and PNC were measured using an ELPI. PSD of these UFP corresponds to that of a Diesel engine. A particular attention was dedicated to data acquisition and treatment method. A first set of experimental data were acquired to characterize the flow dynamics downstream of the three Ahmed bodies without the exhaust system. Basic flow features were characterized (recirculation length, vortex center positions, turbulent kinetic energy and Reynolds shear stresses). The results indicated recirculation lengths of 1.39 h, 0.58 h and 1.06 h (h being the height of the car) for ϕ ¼ 0 , 25 and 35 , respectively. It was shown that the presence of the exhaust system as well as the exhausted flow did not significantly affect the former results. Then, UFP concentrations were assessed in the wake of the three car models. The strong correlation between the flow topology and the UFP concentration fields was demonstrated. The key role of the two vortices developing in the recirculation region was highlighted for all experimental

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