# Experimental and numerical investigation of dam break flow propagation through various obstacle configurations

Elisa Beteille, Sébastien Boyaval, Frédérique Larrarte, Eric Demay

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Elisa Beteille, Sébastien Boyaval, Frédérique Larrarte, Eric Demay. Experimental and numerical investigation of dam break flow propagation through various obstacle configurations. SimHydro 2023: New modelling paradigms for water issues?, Nov 2023, Chatou, France. 10.1007/978-981-97-4072-7_18. hal-04344859

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# EXPERIMENTAL AND NUMERICAL INVESTIGATION OF DAM BREAK FLOW PROPAGATION THROUGH VARIOUS OBSTACLE CONFIGURATIONS

Elisa Beteille<fnref n="1" />

EDF R&D, Laboratoire National d'Hydraulique et Environnement (LNHE), Chatou, France

LHSV, Ecole des Ponts, EDF R&D, Chatou, France

elisa.beteille@edf.fr

Sébastien Boyaval,

LHSV, Ecole des Ponts, EDF R&D, Chatou, France

Materials, Inria, Paris, France

sebastien.boyaval@enpc.fr

Frédérique Larrarte

LHSV, Ecole des Ponts, EDF R&D, Chatou, France

Univ Gustave Eiffel, Marne-la-Vallée, France

frederique.larrarte@univ-eiffel.fr

Eric Demay

EDF R&D, Laboratoire National d'Hydraulique et Environnement (LNHE), Chatou, France

eric.demay@edf.fr

## KEY WORDS

Unsteady flow, Urban flooding, Laboratory experiments, Image analysis measurement, Surface velocity field, LSPIV, Numerical modelling, CFD, code_saturne

## ABSTRACT

Dam break failures can lead to the rapid propagation of flood waves across large areas, causing significant urban or industrial flooding. Such events would cause catastrophic risks to downstream populations and result in severe structural damage. Therefore, it is essential to forecast flood wave propagation over spaces containing macro-roughness, such as buildings, to assess and mitigate these risks. In this paper, datasets are provided from reduced scale physical experiments of transient flow through complex geometries. Specifically, the paper examines the propagation of flood waves over two idealized configurations. The experiments are conducted in a rectangular horizontal open channel, where flow conditions are achieved by rapidly opening a gate holding a volume of water. To assess the impact of obstacles on the flow behavior, different obstacle configurations and sizes are investigated and compared. The experiments provide complete water hydrographs upstream and downstream of the breach. Conductive and acoustic gauges are positioned at ten locations to track the wavefront and water depth variation. Additionally, Large-Scale Particle Image Velocimetry (LSPIV) digital image technique is employed to obtain instantaneous free surface velocity profiles and water surface patterns. Then, numerical simulations of the observed flows are performed using the open-source Navier-Stokes solver code_saturne. The free surface evolution is described using the Volume-Of-Fluid (VOF) method. The results are discussed, and the comparison between experimental data and numerical simulation results demonstrates a good agreement.

## 1. INTRODUCTION

A hydraulic structure failure can lead to flood wave propagation in urban areas, which could result in catastrophic risks to downstream populations and severe structural damage. It is essential to predict the dominant physical phenomena involved in flood wave propagation over areas containing macro-roughness, such as buildings, to assess and mitigate these risks. Dam breaks are a typical example of extreme flood with unsteady and rapidly varying flow leading to complex physical phenomena that are not yet sufficiently-well

<footnote n="1">¹ Corresponding author</footnote>
forecasted by numerical models [1]. Since these types of extreme flooding are rarely observed, there is missing
real-case event data available [2]. Therefore, laboratory tests on such flows are valuable for validating
numerical models and understanding their patterns [3,4].

Dam break flow has been extensively reproduced in laboratory tests and a few urban flooding scenarios have already been performed. First, some experiments investigated the physical characteristics of dam break flow in rectangular channels [5–9]. Additionally, some experiments focused on analyzing the impact of dam break waves on isolated obstacles of different shapes [10–12]. Other investigations explored the influence of different obstacle configurations on the flow [13,14]. The objective was to reproduce idealized suburban districts and to focus, as in the previous studies, on the behavior of the flow in the surroundings of that area. It has also been demonstrated that the presence of multiple obstacles complexifies the flow in this area of interest [15]. More recently, non-intrusive techniques, such as image analysis measurements with high frequency camera, has been used to study dam break flows. On the other hand, dam break flow has been extensively studied numerically using various numerical methods. An accurate description of this type of flow can be obtained by solving the Reynolds-Averaged Navier-Stokes (RANS) equations, complemented by a turbulent model [6, 7, 10, 16, 17]. Specifically, the free surface flow position can be predicted using the VOF (Volume-Of-Fluids) method [18]. While actual VOF methods model the propagation of dam break wave with a good accuracy, adding obstacles into the flow complexifies the prediction of the free surface flow position. The complex physical phenomenon induced by obstacles on the flow are not yet sufficiently-well forecasted by numerical models, particularly during wave impact.

Thus, to improve the prediction of unsteady urban flooding and the knowledge of the complex physics induced by the presence of macro-rugosities on the path of the flood wave, this paper presents an additional experimental and numerical study. This work incorporates recent and adapted measurement techniques to provide a complete water hydrograph both upstream and downstream of the breach. The outline of the paper is as follows. Section 1 presents the laboratory experiments performed at EDF Lab Chatou in France. The different configurations studied, and the metrology used are discussed. The numerical model is presented in Section 3. The experimental and numerical results are compared, in Section 4, for a simple dam break flow case and for two geometrical configurations. The major features of the flow and the similarities between models are compared and discussed by using the water level measurements, the instantaneous velocity fields, and images analysis measurements.

## 2. LABORATORY EXPERIMENTS

### 2.1 Experimental setup

The experiments are carried out in a rectangular and horizontal channel at EDF Lab Chatou in France (Figure 1). The facility is 16 meters long, 2 meters wide, and 0.5 meters high with a uniform PVC bottom. The breach, 0.5 meters wide and 0.31 meters high, is created through a rectangular PVC sluice gate activated by a pneumatic cylinder. Leaks at the breach are avoided by pressurizing the cylinder when filling the tank and adding grease along the gate's guides.

<figure><img src="image_2.png" /><figcaption>**Figure 1:** Schematic views of the experimental set-up (m): (a) plan and (b) longitudinal section.</figcaption></figure>

The opening time of the gate, obtained from video tracking, is about 0.4 s and is above the recommended value from [9], $t_{gate} = 1.25(h_0/g)^{1/2} = 0.2$ s, with $g = 9.81 \text{ m/s}^2$ the gravitational acceleration and $h_0$ the initial reservoir water depth. However, as shown in [19], the error in measurements produced by the opening time of the gate decreases while the distance from the gate increases. Since the area of interest
is located 1.5 m downstream of the gate, this error is considered negligible. Also, the width of the gate was defined so the hydraulic jump due to the reflection of the flow on the side wall does not impact the area of interest, located 1 to 3 meters away from the gate.

## 2.2 Performed test and configurations

All experiments are realized in dry bed condition with an initial depth $h_0 = [0.25-0.251]$ m (±0.5 mm). The dry-bed condition is achieved using a water hoover between each test. Two different configurations of obstacles are studied in this paper. The obstacles used are 0.1 m cubes representing idealized buildings. The first configuration, called 1MR, is a single obstacle in the center of the channel and aligned with the main direction of the flow (Figure 2, left). The second configuration, called 9MR, corresponds to an idealized suburban district already studied for steady flow [20,21] (Figure 2, right). In this case, cubes are all separated by 0.1 m. These two configurations are compared to the original dam break flow case, called 0MR, where there is no obstacle inside the channel.

<figure><img src="image_3.png" /><figcaption>**Figure 2.** Plan view of the configuration studied, (a) 1MR: one single macro-rugosity and (b) 9MR: 3x3 aligned macro-rugosities.</figcaption></figure>

## 2.3 Flow measurement

### 2.3.1 Wave gauge

The free surface position is measured with two types of wave gauges listed in Table 2. Four conductive wave gauges, with an accuracy of 0.1 mm, are placed upstream of the gate and six acoustic gauges, with an accuracy of 1 mm, are placed downstream of the gate. This choice has been made because of the intrusiveness of the resistive gauge. Note that for the following results, the initial time $t = 0$ s corresponds to the start of the breach opening. As presented in Figure 3, the probes are located in areas of interest such as the obstacles' surroundings.

<table><caption>**Table 1:** List of probe types and locations (m)</caption><thead><tr><th></th><th>Type</th><th>x</th><th>y</th></tr></thead><tbody><tr><td>R1</td><td>Resistive</td><td>4.00</td><td>0</td></tr><tr><td>R2</td><td>Resistive</td><td>4.00</td><td>0.50</td></tr><tr><td>R3</td><td>Resistive</td><td>6.50</td><td>0</td></tr><tr><td>R4</td><td>Resistive</td><td>6.50</td><td>-0.15</td></tr><tr><td>A1</td><td>Acoustic</td><td>8.35</td><td>0</td></tr><tr><td>A2</td><td>Acoustic</td><td>8.55</td><td>0</td></tr><tr><td>A3</td><td>Acoustic</td><td>8.65</td><td>-0.10</td></tr><tr><td>A4</td><td>Acoustic</td><td>8.75</td><td>0</td></tr><tr><td>A5</td><td>Acoustic</td><td>8.85</td><td>-0.30</td></tr><tr><td>A6</td><td>Acoustic</td><td>9.15</td><td>0</td></tr></tbody></table>

The repeatability of the experiment was investigated for each configuration. All wave gauges were compared for different numbers of replicates between 2 and 15. Since the standard deviation was similar and smaller than 1 mm for all different numbers of tests, the evolution of the free surface is set as the mean of three replicates.
<figure><img src="image_4.png" /><figcaption>**Figure 3:** Plan view of the sensors' locations, (a) 1MR: one single macro-rugosity and (b) 9MR: 3x3 aligned macro-rugosities.</figcaption></figure>

### 2.3.2 LSPIV analysis

The instantaneous free surface flow velocity around obstacles is retrieved using Large-Scale Particle Image Velocimetry (LSPIV) digital image technique. A high-velocity laboratory camera, with a resolution of 1024x1024 pixels and a recording rate of 250 fps, is placed vertically above the channel. Different types of seeding particles are added to the flow: 2 cm spherical polystyrene, 1.5 cm to 0.5 cm rectangular polystyrene, and 1 cm foam spherical particles. The different shapes and sizes are used to capture small flow patterns and improve image detection. Some of them are dropped inside the channel before the beginning of the experiment to capture the propagation of the flood wavefront. Also, in order to optimize LSPIV analysis and given the flow symmetry in the longitudinal direction, the camera is placed to capture only one side of the channel. The recorded image sequences were analyzed with the open-source software Fudaa-LSPIV [22,23] that embeds all the steps of LSPIV through a user-friendly interface. The main postprocessing step are summarized in Figure 4. First, step 1 corresponds to a lens distortion correction and background removal routine of the raw images. Then a 3D orthorectification of the images is applied based on 8 Ground Reference Points (GRP) obtained by photogrammetry of the channel. During step 2, a velocity analysis of each image is performed on a uniform grid of approximately 50 pixels per cell in the x and y directions. Since a LSPIV calculation uses a flat free surface hypothesis, a constant water depth is set to 0.04 m. This value is the average numerical water depth obtained for the 0MR case in the measurement zone. After this, the instantaneous velocity fields are available at each time step. Then, a filter is applied on each instantaneous velocity field, to remove erroneous vectors based on correlation threshold and vector component threshold. A correlation threshold is set between [0.2,0.98] and a median test [24] as a spatial coherency filter is applied to the vector component threshold. The next step calculates the average velocity field between the three repetitions for each filtered velocity field. Finally, a variable time-averaged is computed from the previous averaged velocity fields. In this paper, the time average is set to 0.1 s, so that all velocity fields are averaged over 25 instantaneous velocity fields.

<figure><img src="image_5.png" /><figcaption>**Figure 4:** Summary of the main postprocessing steps for LSPIV analysis.</figcaption></figure>

### 2.3.3 Image analysis measurement

The position of the free surface is measured, as described in section 2.3.1, using acoustic wave gauges located near the position of the obstacles. However, the response time of these types of probes is 64 ms, which is too slow to accurately capture the water height during the collision between the dam break wave and the obstacle. To gain accuracy, a camera has been placed on the side of the channel, with an acquisition frequency of 100 fps. Image analysis is carried out using the LabVIEW software, and the main post-processing steps are outlined below. Firstly, a lens distortion correction and background removal routine are applied to the raw images, resulting in Figure 5a. Then, a 2D calibration is performed converting pixel measurements to meters. A binarization process follows, using an adaptive threshold value that is adjusted for each acquisition. A Region of Interest (ROI) is defined as a vertical line that can be shifted horizontally to become a rectangle. In this
study, a vertical pixel line is established 5 cm upstream of the obstacle (refer to Figure 5b for an illustration, where the green line represents the ROI). An edge detection operation is executed on this line, and the highest value is retained under the assumption that it corresponds to the free surface position. The ROI is then horizontally shifted by 1 pixel until it reaches a point 6 cm upstream of the obstacle. The final value for the free surface position is calculated as the mean of all the highest values detected. This approach minimizes drop detection and measurement noise. The definition of the ROI's boundaries corresponds closely to the position of probe A2, ensuring comparability with wave gauge measurements. Finally, the data are averaged across two replicates to enhance accuracy.

<figure><img src="image_6.png" /><figcaption>**Figure 5:** Case 1MR, side view. Illustration of the main steps of the water heigh image analysis measurement, (a) raw image and (b) binarized image and free surface detection, red line: obstacle edges, green line: ROI and red point: edge detection.</figcaption></figure>

## 3. NUMERICAL MODEL

The open source Computational Fluid Dynamics solver code_saturne [25] with the Volume Of Fluid module [18] is used to perform the numerical simulations. The computational domain is 12.00 m long, 2 m wide, and 0.4 m high. The three-dimensional system is represented by a hexahedral volumes mesh. A uniform mesh refinement is made in the z axis while a refinement in interest zones such as the breach or around the obstacles is made. A mesh sensitivity analysis show that mesh convergence is achieved (Figure 5). Thus, the mesh used for the study resulted in a total number of cells of 7,000,000 (see Figure 6 for an illustration). Four different cell sizes are used in the x and y directions and a uniform vertical refinement is applied with dz = 0.005 m (80 cells along the z axis). The refinement zones are represented on figure 6, the green zone corresponds to dx = dy = 0.04 m, the blue zone to dx = dy = 0.02 m, the orange zone to dx = dy = 0.01 m and the red zone to dx = dy = 0.005 m.

<figure><img src="image_7.png" /><figcaption>**Figure 5:** Case 0MR. Mesh sensitivity analysis for 4 different mesh refinements : 200,000 cells (green line), 3,500,000 cells (red line), 7,000,000 cells (blue line) and 19,000,000 cells (yellow line) at different location, (a) R3 and (b) A1.</figcaption></figure>
<figure><img src="image_8.png" /><figcaption>**Figure 6:** Mesh representation of the numerical model (top view). Four refinement zones are represented by different colors: green ($dx = dy = 0.04$ m), blue ($dx = dy = 0.02$ m), orange ($dx = dy = 0.01$ m) and red ($dx = dy = 0.005$ m).</figcaption></figure>

Concerning the boundary conditions, all walls are set as a non-slip wall condition except for the surface $z = 0.4$ m which is defined as a symmetry and the surface $x = 12$ m which is set as a free outlet. A constant volume of fluid (7 x 2 x 0.25 m) corresponding to an initial reservoir water height of 0.25 m is set. The simulation is considered isothermal and the $k-\epsilon$ with linear production [7,16,26] is used. To optimize the results, the free surface is compressed using the drift method [18,27]. Each case was run for a duration of $t = 25$s. An adaptive time step is used to keep the courant number under the unity. Then, the numerical results are qualitatively and quantitatively tested through comparisons with the experimental data.

Note that using the VOF module involves an additional post-processing step to retrieve the water height. Here, the volume fraction of water is used to calculate the position of the free surface and so, the water height. The following method is applied to obtain a local estimation of the water level for each probe. First, a column of one cell wide and over the full height of the domain is defined. The resulting water height at each time step is the ratio on this column of the volume of water and its total volume, multiplied by its total height.

# 4. RESULTS

First, the water height is studied at different position, then the velocity field around the obstacle is compared to the LSPIV results. Finally, the wave impact is compared between two measurement type: wave gauge and image analysis.

## 4.1 Water height time history

The results presented in this subsection focus on the comparison of water level variations between the experimental and numerical study for the two configurations studied. Figure 7 shows the comparison upstream, R3, and downstream, A1, A3 and A4, of the gate for case 1MR. Figure 9 shows the comparison upstream, R3, and downstream, A1, A5 and A6, of the gate for case 9MR. The frequency acquisition is set to 50 Hz and stopped at $t = 25$ s.

### 4.1.1 Case 1MR

For probes located upstream of the gate, one can see the presence of oscillations of the water height (Figure 7a) that involves a variation in the flow rate through the breach. There is a good similarity between experimental and numerical curves showing the ability of the numerical model to reproduce the oscillations inside the reservoir. This phenomenon, which has not been widely documented in previous experimental dam-break studies [28–30] makes the numerical reproduction of such flows even more challenging. Figure 8 illustrates the time variation of the velocity profile through the gate at different positions and highlights the complexity of the flow upstream of the gate. Downstream at position A1, the water depth is not impacted by the presence of the macro-rugosity, also there is also a good agreement between experimental and numerical results. Larger differences between experimental and numerical results can be observed for probes located closer to the obstacle (Figures 7c and 7d). This can be explained by the presence of hollows and humps due to the obstacle, inducing very-small scale free surface variations. Further work on the numerical post-processing water height calculation might be of interest. The numerical simulation underestimates the surge water height (Figure 7c). This may be due to a different position of the surge in the simulation and shows the importance of post-processing choices for numerical models using the VOF module. Downstream of the obstacle at position A4, see Figure 7d the numerical water height shows a similar shape compared to the experimental data. The peak visible for the experimental data at $t \approx 2s$, is due to drops passing over the obstacle during wave impact.

Note that the arrival time of the dam break wave seems to be faster for the simulation (Figure 7) which can be explained by not considering numerically the gate opening time (see subsection 2.1).
<figure><img src="image_9.png" /><figcaption>**Figure 7:** Case 1MR. Water depth variations comparison between experimental and numerical data at different positions: (a) R3, (b) A1, (c) A3 and (d) A4.</figcaption></figure>

<figure><img src="image_10.png" /><figcaption>**Figure 8:** Case 0MR. Vertical velocity profile evolution through the breach (x = -0.075 m) at different positions: (a) y = 0 m (b) y = 0.2 m.</figcaption></figure>

### 4.1.2 Case 9MR

For probes located upstream of the gate, Figure 9a, there is a good similarity between experimental and numerical curves as for the previous case. Downstream of the gate at position A1, the numerical model over-estimate the water depth by 30% during 15 s and then progressively reduces its error. As for case 1MR, larger differences between experimental and numerical results can be observed for probes located closer to the obstacle configuration (Figure 9c and 9d). On the side, at position A5, see Figure 9c, the numerical model under-estimates the water height and do not correctly predict the arrival time of the dam break wave. The same tendency is observed for position A6, located downstream the obstacles and inside the wake zone, see Figure 9d.
<figure><img src="image_11.png" /><figcaption>**Figure 9:** Case 9MR. Water depth variations comparison between experimental and numerical data at different positions: (a) R3, (b) A1, (c) A5 and (d) A6.</figcaption></figure>

## 4.2 Free surface flow description

The results presented in this subsection focus on the comparison of the free surface flow velocity between experimental and numerical results for the three configurations studied. The different steps of post-processing are presented in previous Section 2.3.2. Figures 10, 11 and 12 present the free surface flow, obtained with the LSPIV method (averaged from 25 instantaneous frames), and the numerical free surface defined at a volumic fraction $\alpha = 0.5$ at 4 different time steps. The color map on each result represents the norm of the horizontal velocity and the vector map is normalized. Each black rectangle represents an obstacle. White rectangles visible on the low-left side of the LSPIV results correspond to filtered data due to very transparent water and the lack of seeding particles that lead to some erroneous velocity gradients. LSPIV measurements allow us to capture the unsteady features of the dynamics induced by the presence of obstacles with a frequency acquisition of 250 fps. They also highlight the presence of a surge. This jump creates a low-velocity magnitude zone close to the geometries. Moreover, a wake zone downstream of the obstacles is observable (Figure 11 and 12), with a low water height.

Numerically, the patterns obtained with the VOF simulation are found to be very similar to the patterns of the experimental ones. In particular, the position of the reflected wave coming from the side walls is similar and varies similarly while the unsteady wave propagates. Also, the surge in front of the obstacles (Figures 11 and 12) is observed in the numerical results, but with an under-estimated size. This might be adjusted by using different values of the threshold value of the volumic fraction $\alpha$ to change the position of the free surface (out of the scope of the present work). More specifically, for case 0MR (Figure 10), the velocity propagation and the shape of the dam break wave are well reproduced at all times.

Qualitatively, the numerical simulation was able to predict the unsteady flow behaviour at the different studied times. However, a possible improvement is at the surge zone. This may be subject of further investigations. Also, note that the presented numerical fields are instantaneous while the experimental ones are 25 frames time averaged.
<figure><img src="image_12.png" /></figure>

<figure><img src="image_13.png" /></figure>

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<figure><img src="image_15.png" /></figure>

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<figure><img src="image_17.png" /></figure>

<figure><img src="image_18.png" /></figure>

<figure><img src="image_19.png" /><figcaption>**Figure 10:** Case 0MR. Free surface flow velocity comparison between (a) experimental (25 frames time averaged) and (b) numerical results ($\alpha = 0.5$) at different time step.</figcaption></figure>
<figure><img src="image_20.png" /></figure>

<figure><img src="image_21.png" /></figure>

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<figure><img src="image_27.png" /><figcaption>**Figure 11:** Case 1MR. Free surface flow velocity comparison between (a) experimental (25 frames time averaged) and (b) numerical results ($\alpha = 0.5$) at different time step.</figcaption></figure>
<figure><img src="image_28.png" /></figure>

<figure><img src="image_29.png" /></figure>

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<figure><img src="image_35.png" /><figcaption>**Figure 12:** Case 9MR. Free surface flow velocity comparison between (a) experimental (25 frames time averaged) and (b) numerical results ($\alpha = 0.5$) at different time step.</figcaption></figure>
## 4.3 Wave impact comparison

As explained in the previous section 2.3.3, acoustic wave gauges are not able to capture the very fast phenomenon induced by the impact between the dam break wave and the droplets associated. Figure 13 illustrates the free surface profile during the impact and highlights the presence of droplet in the measurement area. An image analysis method is thus developed to measure more accurately the evolution of the water height during the impact. Figure 14 shows a comparison between the acoustic wave gauge measurement and image analysis for cases 1MR et 9MR. Results show that the height impact rises to 0.25 m, which is much higher than the wave gauge results. It is an interesting result complementing the database to verify numerical models.

Note that the image analysis could not be performed any longer due to the obstruction of the view during a quick instant due to the passage of water over the side walls.

<figure><img src="image_36.png" /><figcaption>**Figure 13:** Snapshot of the free-surface profile at t = 1.5s for case 1MR. Red line represents A2 position. Grey surface represents the cube.</figcaption></figure>

<figure><img src="image_37.png" /><figcaption>**Figure 14:** Wave height comparison at position A2 between wave gauge measurements (black), image analysis (blue) and numerical simulation (green) for case (a) 1MR and (b) 9MR.</figcaption></figure>

Figure 15 presents a slice view of the water depth during the wave impact. The red line corresponds to the cell column where the calculation of the water height is performed, which is close to the surge but doesn't capture it. It can explain the differences between the experimental and numerical results on Figure 13. Further investigations on the post-processing method will be carried out to obtain more accurate unsteady water height predictions.

<figure><img src="image_38.png" /><figcaption>**Figure 15:** Wave height visualization of the numerical simulation at t = 1.5s for case 1MR (side view). Red line represents A2 position. Grey surface represents the cube. Dark blue surface corresponds to y = 0 m and $\alpha \le 0.5$.</figcaption></figure>
# 5. CONCLUSIONS

This paper presents a new experimental and numerical study for unsteady dam break wave propagation over various macro-roughness configurations. Essential physical quantities, including water height and the horizontal velocity field of the free surface, are investigated within regions of interest. The experimental findings are subject to both quantitative and qualitative comparisons with numerical results. A simple dam break case and two configurations of obstacles are studied, and some interesting features of the flow around the obstacles are highlighted. Moreover, the outcome from the laboratory experiments constitutes a valuable new dataset for validating three-dimensional (3D) models.

Oscillation waves were observed upstream of the breach for all configurations. This phenomenon induces a variation in the flow rate through the gate and impacts the flow behavior downstream of the gate. The numerical findings show a good reproduction of these oscillations. Moreover, it has been shown that the flow downstream of the gate is highly impacted by the presence of macro-rugosities. Two main observations are made: first, the surge, in front of obstacles, and then, the wake zone position and variation in time, downstream of the obstacles. Results obtained with the VOF module of code_saturne correctly reproduced the creation of the surge and wake zone around the obstacles configuration. Still, the water height closer to the obstacles presented a numerical underestimation.

Further analysis must thus be performed on the post-processing method for VOF numerical models to obtain smoother and more accurate unsteady water heigh predictions. Finally, future work aims to extend this experimental protocol to new obstacle configurations representative of suburban areas and to study their impact on the flow on a larger scale.

# ACKNOWLEDGEMENTS

Elisa Beteille acknowledges the financial support of her PhD research program provided by the French ANRT (Association Nationale de la Recherche et de la Technologie) with CIFRE Grant 2021/0912. The authors thank the POMPHY team (EDF Lab Chatou, France) for support during the manufacturing of the experimental device and the code_saturne development team for the valuable discussions on parameterizing the numerical model.

# REFERENCES AND CITATIONS

[1] Zech, Y., Soares-Frazão, S., and Van Emelen, S. (2015) Modelling of fast hydraulic transients: issues, challenges, perspectives. *La Houille Blanche*. (5), 5–15.

[2] Aureli, F., Maranzoni, A., and Petaccia, G. (2021) Review of Historical Dam-Break Events and Laboratory Tests on Real Topography for the Validation of Numerical Models. *Water*. 13 (14), 1968.

[3] Aureli, F., Maranzoni, A., Petaccia, G., and Soares-Frazão, S. (2023) Review of Experimental Investigations of Dam-Break Flows over Fixed Bottom. *Water*. 15 (6), 1229.

[4] Mignot, E., Li, X., and Dewals, B. (2019) Experimental modelling of urban flooding: A review. *Journal of Hydrology*. 568 334–342.

[5] Garoosi, F., Nicole Mellado-Cusicahua, A., Shademani, M., and Shakibaeinia, A. (2022) Experimental and numerical investigations of dam break flow over dry and wet beds. *International Journal of Mechanical Sciences*. 215 106946.

[6] Yang, S., Yang, W., Zhang, C., Qin, S., Wei, K., and Zhang, J. (2022) Experimental and numerical study on the evolution of wave front profile of dam-break waves. *Ocean Engineering*. 247 110681.

[7] Kocaman, S., Evangelista, S., Guzel, H., Dal, K., Yilmaz, A., and Viccione, G. (2021) Experimental and Numerical Investigation of 3D Dam-Break Wave Propagation in an Enclosed Domain with Dry and Wet Bottom. *Applied Sciences*. 11 (5638), 1–21.

[8] Melis, M. (2018) Dam-break wave propagation on a rough surface: Experimental and numerical study, Falcolta di Ingeneria, 2018.

[9] Lauber, G. and Hager, W.H. (1998) Experiments to dambreak wave: Horizontal channel. *Journal of Hydraulic Research*. 36 (3), 291–307.

[10] Kocaman, S., Evangelista, S., Viccione, G., and Güzel, H. (2020) Experimental and Numerical Analysis of 3D Dam-Break Waves in an Enclosed Domain with a Single Oriented Obstacle. *Environmental Sciences Proceedings*. 2 (1), 35.

[11] Liu, L., Sun, J., Lin, B., and Lu, L. (2018) Building performance in dam-break flow – an experimental study. *Urban Water Journal*. 15 (3), 251–258.
[12] Soares-Frazão, S. and Zech, Y. (2007) Experimental study of dam-break flow against an isolated obstacle. *Journal of Hydraulic Research*. 45 (sup1), 27–36.

[13] Dong, B., Xia, J., Zhou, M., Deng, S., Ahmadian, R., and Falconer, R.A. (2021) Experimental and numerical model studies on flash flood inundation processes over a typical urban street. *Advances in Water Resources*. 147 103824.

[14] Soares-Frazão, S. and Zech, Y. (2008) Dam-break flow through an idealised city. *Journal of Hydraulic Research*. 46 (5), 648–658.

[15] Li, X., Erpicum, S., Mignot, E., Archambeau, P., Pirotton, M., and Dewals, B. (2021) Influence of urban forms on long-duration urban flooding: Laboratory experiments and computational analysis. *Journal of Hydrology*.

[16] Ozmen-Cagatay, H. and Kocaman, S. (2010) Dam-break flows during initial stage using SWE and RANS approaches. *Journal of Hydraulic Research*. 48 (5), 603–611.

[17] Bigdeli, M., Taheri, M., and Mohammadian, A. (2022) Numerical modeling of dam-break flood flows for dry and wet sloped beds. *ISH Journal of Hydraulic Engineering*. 1–11.

[18] Banon, A. (2019) Volume Of Fluid method for numerical simulation of flow weir, École de technologie supérieure université du Québec, 2019.

[19] von Häfen, H., Goseberg, N., Stolle, J., and Nistor, I. (2019) Gate-Opening Criteria for Generating Dam-Break Waves. *Journal of Hydraulic Engineering*. 145 (3), 04019002.

[20] Larrarte, F., Goutal, N., and Doumic, A. (2022) Floods in housing estate: some experimental data. in: Proc. 39th IAHR World Congr., International Association for Hydro-Environment Engineering and Research (IAHR), pp. 6981–6986.

[21] Doumic, A., Larrarte, F., Rtimi, R., and Goutal, N. (2021) Investigation of the hydraulics in flooded housing estate. in: SimHydro, p. 9.

[22] Jodeau, M., Hauet, A., Le Coz, J., Faure, J.-B., and Bodart, G. (2022) Fudaa-LSPIV User Manual (v 1.9.2).

[23] Le Coz, J., Jodeau, M., Hauet, A., Marchand, B., and Le Boursicaud, R. (2014) Image-based velocity and discharge measurements in field and laboratory river engineering studies using the free Fudaa-LSPIV software. in: A. Schleiss, G. de Cesare, M. Franca, M. Pfister (Eds.), River Flow 2014, CRC Press, pp. 1961–1967.

[24] Westerweel, J. and Scarano, F. (2005) Universal outlier detection for PIV data. *Experiments in Fluids*. 39 (6), 1096–1100.

[25] Archambeau, F., Méchitoua, N., and Sakiz, M. (2004) Code Saturne: A Finite Volume Code for the computation of turbulent incompressible flows - Industrial Applications. *International Journal on Finite Volumes*. 1 (1), http://www.latp.univ-mrs.fr/IJFV/spip.php?article3.

[26] Guimet, V. and Laurence, D. (2002) A linearised turbulent production in the $k-\epsilon$ model for engineering applications. in: Eng. Turbul. Model. Exp. 5, Elsevier, pp. 157–166.

[27] Deshpande, S.S., Anumolu, L., and Trujillo, M.F. (2012) Evaluating the performance of the two-phase flow solver interFoam. *Computational Science & Discovery*. 5 (1), 014016.

[28] Ozmen-Cagatay, H., Turhan, E., and Kocaman, S. (2022) An experimental investigation of dam-break induced flood waves for different density fluids. *Ocean Engineering*. 243 110227.

[29] Espartel, L. and Manica, R. (2021) Experiments on initial stages of development of dam-break waves. *RBRH*. 26 e6.

[30] Hooshyaripor, F., Tahershamsi, A., and Razi, S. (2017) Dam break flood wave under different reservoir's capacities and lengths. *Sādhanā*. 42 (9), 1557–1569.