surface flow image velocimetry (sfiv) for hydraulics...

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18th International Symposium on the Application of Laser and Imaging Techniques to Fluid MechanicsLISBON | PORTUGAL JULY 4 – 7, 2016 Surface Flow Image Velocimetry (SFIV) for hydraulics applications J. Tellez 1,* , M. Gómez 1 , B. Russo 2 and J.M. Redondo 3 1: Dept. of civil and environmental engineering, Technical University of Catalonia, Spain 2: Technical College of La Almunia (University of Zaragoza), Spain 3: Dept. of physics, Technical University of Catalonia, Spain * Correspondent author: [email protected] Keywords: environmental flows, flow visualization, flow measurements, Surface Flow Image Velocimetry (SFIV) ABSTRACT Surface Flow Image Velocimetry (SFIV), is a practical extension of Particle Image Velocimetry (PIV), as one of the major effective techniques in hydraulics providing velocity and vorticity fields in fast flow laboratory experiments or in field conditions. SFIV uses similar algorithms than conventional PIV, and these tools have a great deal in common with specific pattern matching used in synthetic schlieren. This paper presents an application to characterize the hydraulic behavior of a grate inlet in the area of urban drainage in order to reproduce the velocity field near the grates, as this is one of the important factors for the design of improved inlet systems and prevention of urban flooding. With a high speed camera it is possible to capture images of very high resolution and speed, which combined with the techniques SFIV for image processing, we may generate dynamic velocity and vorticity fields as well as local fluxes around the grate inlet, and combined with flow depth data, evaluate local Froude numbers. The average surface velocity measured by the imaging technique is a good approximation, especially for shallow flows, but it is also possible to extrapolate the technique to rivers, canals, or other hydraulic structures. 1. Introduction Flow visualization is useful to understand the mechanics of a particular flow field and the information provided is invaluable for rapid feedback during experimental development (Adrian & Westerweel 2011). This may be particularly important when a single camera for PIV provides a 2D image of the real complex flow. Surface Flow Image Velocimetry, or SFIV, as an improvement on standard PIV, refers here to the application of several methods used in experimental fluid mechanics to determine instantaneous field values of the vector velocity by measuring the displacements of surface waves or perturbations of surface flows (Stagonas & Müller 2007; Fujita et al. 1998). This technique uses basic PIV methods for experimental fluid mechanics, geared and calibrated towards the

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18th International Symposium on the Application of Laser and Imaging Techniques to Fluid Mechanics・LISBON | PORTUGAL ・JULY 4 – 7, 2016

Surface Flow Image Velocimetry (SFIV) for hydraulics applications

J. Tellez1,*, M. Gómez1, B. Russo2 and J.M. Redondo3 1: Dept. of civil and environmental engineering, Technical University of Catalonia, Spain

2: Technical College of La Almunia (University of Zaragoza), Spain 3: Dept. of physics, Technical University of Catalonia, Spain

* Correspondent author: [email protected]

Keywords: environmental flows, flow visualization, flow measurements, Surface Flow Image Velocimetry (SFIV)

ABSTRACT

Surface Flow Image Velocimetry (SFIV), is a practical extension of Particle Image Velocimetry (PIV), as one of the

major effective techniques in hydraulics providing velocity and vorticity fields in fast flow laboratory experiments

or in field conditions. SFIV uses similar algorithms than conventional PIV, and these tools have a great deal in

common with specific pattern matching used in synthetic schlieren. This paper presents an application to

characterize the hydraulic behavior of a grate inlet in the area of urban drainage in order to reproduce the velocity

field near the grates, as this is one of the important factors for the design of improved inlet systems and prevention

of urban flooding. With a high speed camera it is possible to capture images of very high resolution and speed,

which combined with the techniques SFIV for image processing, we may generate dynamic velocity and vorticity

fields as well as local fluxes around the grate inlet, and combined with flow depth data, evaluate local Froude

numbers. The average surface velocity measured by the imaging technique is a good approximation, especially for

shallow flows, but it is also possible to extrapolate the technique to rivers, canals, or other hydraulic structures.

1. Introduction Flow visualization is useful to understand the mechanics of a particular flow field and the information provided is invaluable for rapid feedback during experimental development (Adrian & Westerweel 2011). This may be particularly important when a single camera for PIV provides a 2D image of the real complex flow. Surface Flow Image Velocimetry, or SFIV, as an improvement on standard PIV, refers here to the application of several methods used in experimental fluid mechanics to determine instantaneous field values of the vector velocity by measuring the displacements of surface waves or perturbations of surface flows (Stagonas & Müller 2007; Fujita et al. 1998). This technique uses basic PIV methods for experimental fluid mechanics, geared and calibrated towards the

18th International Symposium on the Application of Laser and Imaging Techniques to Fluid Mechanics・LISBON | PORTUGAL ・JULY 4 – 7, 2016

understanding and tracking of the motions of surface features, such as capillary waves and micro-vortices. The practical development of these techniques lead to measurements of the whole average surface flows, the instantaneous fields of scalars and velocity vectors, the divergence and vorticity fields, the spectral behavior and even higher moment local descriptors (Adrian 1991; Tellez et al. 2015). We present a practical application, together with the experimental procedures in order to show some new results focused in a general methodology that we have developed in the area of urban drainage. Flumen Research Institute of the Civil and Environmental Engineering Department (ECA) with the Department of Physics (DP) of the Technical University of Catalonia (UPC) has been working on the measurement of the hydraulic capacity of different types of grates for certain geometries through a street full scale physical model on a platform for testing grate inlets located in the Hydraulics Laboratory show in the figure 1 (Tellez et al. 2015; Russo et al. 2013; Gómez 2008).

Fig. 1 Platform in operation. Laboratory of hydraulics. UPC-BarcelonaTech

In order to further deepen on the analysis of the hydraulic behavior of sewer grates during an event of extreme rain, we obtained accurate velocity fields for this type of wide and shallow flows, just a few centimeters depth using high resolution images to determine the flow in the proximity to the grate. This has been done without the need of adding tracer particles to the flow, but mainly focusing in the monitoring of the current flow shapes on the surface. (Tellez et al., 2015).

18th International Symposium on the Application of Laser and Imaging Techniques to Fluid Mechanics・LISBON | PORTUGAL ・JULY 4 – 7, 2016

For SFIV we validate with experimental data shallow flows, but extrapolation to larger depths, and in realistic environmental flows, such as river streams where it is possible to detect enough disturbances, local capillary waves, vortices or wakes, SFIV may also be applied, but considering a typical conditions of geometry of rivers and with the correct parameter of image processing the resulted of mean velocity will have some errors of approximation. In addition, to a very high resolution camera and high frame speed, and together with a large computer capacity, the image analysis was performed through the implementation of programs of advanced image processing for fluid mechanics, such as ImaCalc developed at UPC, DigImage and DigiFlow developed by DAMTP (Univ. of Cambridge), which were used during the experimental campaign. (Dalziel 2012; Dalziel and Redondo, 2007). Indeed, the methodology carried out can become a useful tool to understand the hydraulic behavior of the flow approaching the inlet, even when the traditional measuring equipment has serious problems and limitations (Tellez et.al, 2015). This method is able to generate complex velocity fields with simple tools and it appears as a flexible tool for application both in the laboratory and the field. We determined the velocity field in the vicinity of the grate and the approach flow distribution for different combinations of longitudinal and transverse slopes and flow rates for the platform (Tellez et al., 2016). It is important also to control the shear and vorticity levels as well as the divergence in order to check on the three dimensionality of the surface flow. An advantage of the SFIV analysis is the possibility of evaluating intermittency both in space and time, as well as the fluxes of mass, momentum and vorticity (Villa et al., 2014). Under laboratory conditions it is possible to obtain reliable velocities, vortices and discharges from image techniques. These were found in good agreement with the results measured with more traditional techniques, such as mechanical, ADV sonic velocimetry and electromagnetic EMG flowmeters (Rodriguez et al., 1999) within the Laboratory of Hydraulics of UPC. Next we describe the background for the technique and the experimental method, in section 4 we present the results and finally the conclusions

18th International Symposium on the Application of Laser and Imaging Techniques to Fluid Mechanics・LISBON | PORTUGAL ・JULY 4 – 7, 2016

2. Theoretical Background In general, the Particle Image Velocimetry method (PIV) is a classical velocity measurement through the video camera that returns instantaneous fields of the vector velocity by the fundamental definition of velocity and estimate the local velocity u from:

ttxxtxu

∆∆

=),(),( (1)

where ∆x is the displacement of a marker, located at x at time t, over a short time interval ∆t separating observations of the marker images (Adrian 1991) (Figure 2).

Fig. 2 System of video recording for surface waves or perturbations in the surface flow In this section, we discuss only the advantage of the use of the algorithm used in the techniques described in DigiFlow as “pattern matching refractometry”, and how this may be applied to provide accurate quantitative measurements of two-dimensional flows with density non-homogeneity. The algorithm used: ¨synthetic schlieren¨ is a novel technique for producing qualitative visualizations of density fluctuations and has its origins in the classical optical schlieren and moiré fringe techniques (Dalziel et al. 1998), well known visualization techniques, and provide useful information in situations where shadowgraph is of little or no value (Dalziel 2012). The synthetic schlieren also provides qualitative visualizations of a density field and these tools may be scaled to cope with flows in significantly large domains without the expense of large

Video array Camera lens

Focal length Field of view

18th International Symposium on the Application of Laser and Imaging Techniques to Fluid Mechanics・LISBON | PORTUGAL ・JULY 4 – 7, 2016

parabolic mirrors. Furthermore this method can be extrapolated to obtain even three-dimensional and turbulent flows (Dalziel et al. 1998). The method of synthetic schlieren has three different approaches to measure flows with DigiFlow such as line refractometry, dot tracking refractometry and pattern matching refractometry. The final method has its origins in PIV techniques and was the main method used in the correlation and analysis of image for our SFIV experiments. 3. Experimental Implementation The experiment consists of the fixed laboratory facilities, shown in figure 1: hydraulic platform of grate inlet, light equipment (reflectors) and a grate. The mobile installations are the high speed and resolution camera connected to a computer. The images were taken over a wide test area, which had dimensions of 5.5 m long and 4 m wide with an effective work area of 1.5 m long and 3 m wide near to the grate inlet. The tilting platform allows to modify the longitudinal slopes between 0% to 10% and the transversal slopes from 0% to 4%. The maximum flow achievable during our experiments was 200 l/s. The lighting of the focus area of the camera in the laboratory should be maximized in order to use a lower sensitivity because some high values could produce excessive noise in the image. In order to obtain images with high resolutions with 150 frames per second recorded, it was decided to place an artificial lighting with two reflectors of 500 and 1000 Watts, strategically located to provide the best possible lighting in the focus area. Besides, platform was painted with color gray because it was the color that allowed the best to see the shapes or surface waves, and at the same time avoiding reflections. There are also some marks around the grate inlet and at certain control points, used to reference the image processing analysis. The camera used was a model MV2-D1280-640 CMOS and mount adapter C to F-Nikon. The optics is a lens standard Nikon 50mm, it has a field angle of 45 degrees similar to the human eye, offering high quality and brightness, plus accessories and power supply. The camera has a capacity to take videos up to 488 frames per second being its maximum resolution of 1280 x 1024 pixels. The first step to have a correct configuration of the camera was defined the opening of the shutter to allow the light entry. And with Teledyne DALSA the X64 Xcelera-CL PX4 FRAME

18th International Symposium on the Application of Laser and Imaging Techniques to Fluid Mechanics・LISBON | PORTUGAL ・JULY 4 – 7, 2016

GRABBER software, be provided the application to capture the sequence of video with an interface called Sapera, these tools was used to configure the camera and capture videos. Furthermore, the camera was located above of the platform to a height of 4 m to capture the videos. Considering that the platform can adopt changes of slope in the transverse direction of 0% to 4% and longitudinally from 0% to 10%, and with the proposed to correct its angle of incidence, we measured the focus area on the platform that have a variation of area from 94.70 cm. x 118 cm. when fully flat and from 104.60 cm. x 130.10 cm. with longitudinal slope of 10% and transversal slope of 4%, having a ratio average of 10 pixels/cm.

Fig. 3 Experimental set-up for SFIV techniques

4. Results To validate the results of the SFIV technique, a comparison was made of the surface velocities obtained with the mean flow velocities estimated from the formula of Manning, if we do not have transversal slopes, and the modified Izzard equation (Izzard & Hicks, 1947), in case of

CCD Camera

PC with frame-grabber

500 watt halogen lamps 1000 watt halogen lamps

grate

Field of view

Flow direction Water surface

3 m

18th International Symposium on the Application of Laser and Imaging Techniques to Fluid Mechanics・LISBON | PORTUGAL ・JULY 4 – 7, 2016

triangular cross-sections, which is more appropriate for these cases. From the hydraulic point of view we can consider the streets as one-dimensional conduits in free surface, where the channel length is greater than the width. After the capture and storage of videos, data is processed with the software VirtualDub, in order to cut the videos of some black parts outside the study area. Once the videos are prepared with the right sizes for all flow and geometrical combinations, we calculate the velocity fields through DigiFlow program. Simulations in DigiFlow were made by setting some parameters in order to maintain a similarity in the results: videos with 8-bit greyscale equivalent to a range of colors from 0 to 256, the correlation method used was the synthetic schlieren (Sutherland et al., 1999), the cells of interrogation for all combinations are 20 x 20 pixels equivalent to approximately 2 cm. x 2 cm, with a resolution of 1280 x 1024 pixels and an image flowrate of 150 frames per second. The average velocity fields are shown for different flows in figure 4.

Flowrate= 200 l/s, longitudinal slope= 4% and transverse slope= 0%

Flowrate= 150 l/s, longitudinal slope= 10% and transverse slope= 2%

Flow direction

Flow direction

18th International Symposium on the Application of Laser and Imaging Techniques to Fluid Mechanics・LISBON | PORTUGAL ・JULY 4 – 7, 2016

Flowrate= 100 l/s, longitudinal slope= 2% and transverse slope= 4%

Flowrate= 50 l/s, longitudinal slope= 1% and transverse slope= 4%

Flowrate= 25 l/s, longitudinal slope= 2% and transverse slope= 2%

Fig. 4 Field velocity around the grate Barcelona1

Flow direction

Flow direction

Flow direction

18th International Symposium on the Application of Laser and Imaging Techniques to Fluid Mechanics・LISBON | PORTUGAL ・JULY 4 – 7, 2016

To check the results of the velocity field, some results of case studies show a small difference of the comparison of the average velocity obtained by the conventional method through the Manning equation or Izzard shown are detailed in Table 1, with the results of processing digital images obtained through DigiFlow.

Table 1.- Values of velocities obtained Flowrate Longitunald

slope Transversal

slope Ydepth VDigiflow VManning o Izzard

[l/s] [%] [%] [m] [m/s] [m/s]

200 4 0 0,032 1,48 1,53

150 10 2 0,040 2,29 2,14

100 2 4 0,070 1,26 1,42

50 1 4 0,061 0,93 0,90

25 2 2 0,030 0,85 0,79

Assessment of the methodology about the comparison of velocity with DigiFlow versus velocity with Izzard equation (Figure 5), although it should be noted that the velocity of Izzard is regarded as average velocity, but since we work with maximum water depths of up to 15 cm, we can say that they should not be very different. It was compared for different flowrates ranging from 25 l/s to 200 l/s in cases with a geometry different street in their longitudinal and transverse slopes it can be seen that the slope of the line for these case studies is m = 0,921, showing that it is very close to one which indicates that the data are very similar with a good correlation of R2 = 0.96.

y = 0.921x + 0.102R² = 0.960

0

0.5

1

1.5

2

2.5

3

0 0.5 1 1.5 2 2.5 3

Izza

rd V

eloc

ity (m

/s)

Velocity with Digiflow (m/s)

Fig. 5 Comparison of velocity with SFIV techniques vs. Izzard velocity

18th International Symposium on the Application of Laser and Imaging Techniques to Fluid Mechanics・LISBON | PORTUGAL ・JULY 4 – 7, 2016

Another utility that provides this technique SFIV is that from the velocity fields obtained for each

combination of geometry and flow of approximation, we can estimate the flow captured by the grate

through the development of a mass balance in the grate inlet with code developed in Matlab.

Table 2.- Values of flowrate captured by the gate

Flowrate Longitunal slope

Transversal slope

FlowrateExperiment FlowrateDigiflow DiferenceFlowrate

[l/s] [%] [%] [l/s] [l/s] [l/s]

200 4 0 12 10,98 1,02

150 10 2 13,47 11,79 1,68

100 2 4 29,55 28,52 1.03

50 1 4 20,19 13,52 6,67

25 2 2 9,37 10,06 0,69

Thus, the values show in the Table 2, show the differences of least than 1 l/s when the slopes are greater

than 2%, but having some problems for longitudinal slopes of 0%, 1% and sometimes 2%, associated to a

small velocities, for this reason these techniques have more accuracy for supercritical flows.

5. Conclusion Surface Flow Image velocimetry (SFIV) provides non-invasive and efficient new technique for complex flow measurement in real time, able to reproduce the field velocity and the structure of the flow in the surface flow. The precision of the technique allows to determine for the tested case, the vorticity and divergence around the grate as shown in figure 6 for experiment with average velocity of 1.45 m/s for a flowrate of 200 l/s with longitudinal slope of 4% and transversal slope of 0%, here we show the velocity fluctuations too by subtracting the mean value. Surface Flow Image Velocimetry (SFIV) is very useful to determine the fields of surface velocities through wave forms analysis on the surface of the fluid. It works better when the flow regime is supercritical because in these cases the flow has major disturbances in the surface which allow us to have better correlation to determine the magnitude and direction of the velocity for the flowrate.

18th International Symposium on the Application of Laser and Imaging Techniques to Fluid Mechanics・LISBON | PORTUGAL ・JULY 4 – 7, 2016

Fig. 6 Fluctuations by subtracting the mean flow. Flowrate= 200 l/s, longitudinal slope= 4% and

transverse slope= 0% References Adrian, R.J. (1991) Particle-Imaging Techniques for Experimental Fluid Mechanics. Annual Review of Fluid Mechanics, 23(1), pp.261–304. Adrian, R.J. & Westerweel, J. (2011) Particle Image Velocimetry, Cambridge University Press. Dalziel, S. B. (2012) DigiFlow User Guide, Cambridge, England: Department of Applied

Mathematics and Theoretical Physics (DAMTP) - University of Cambridge. Cambridge. United kingdom.

Dalziel, S.B., Hughes, G.O. & Sutherland, B.R. (1998) Synthetic Schlieren. Paper 062. Proceedings of the 8th international Symposium on Flow Visualization, In: Carlomagno; Grant (ed), Tennessee, United States. Dalziel, S.D. and Redondo J.M. (2007) New visualization and self-similar analysis in experimental turbulence studies. Models, Experiments and Computation in Turbulence. CIMNE, Barcelona, Spain. Fujita, I., Muste, M. & Kruger, A. (1998) Large-scale particle image velocimetry for flow analysis in hydraulic engineering applications. Journal of Hydraulic Research, 36(3), pp.397–414. Gómez, M., 2008. Urban hydrology course (in spanish) . Second Ed., Barcelona, España. Technical University of Catalonia. Barcelona. Spain. Izzard, C.F. & Hicks, W.I. (1947) Hydraulics of runoff from developed surfaces. Highway Research Board Proceedings, vol 26. pp 129-150. Washington, United States. Rodriguez A., Sánchez A., Redondo J.M., Mosso C (1999) Macro turbulence measurements with electromagnetic and ultrasonic sensors: a comparison under high-turbulent flows.

Flow direction

18th International Symposium on the Application of Laser and Imaging Techniques to Fluid Mechanics・LISBON | PORTUGAL ・JULY 4 – 7, 2016

Experiments in fluids 27, 31-42. Russo, B., Gómez, M., Tellez, J. (2013) Methodology to Estimate the Hydraulic Efficiency of Nontested Continuous Transverse Grates. Journal of Irrigation and Drainage Engineering, 139(10), pp.864–871. Stagonas, D. & Müller, G. (2007) Wave field mapping with particle image velocimetry. Ocean Engineering, 34 (11-12), pp.1781–1785. Stucki, P. (1979) Advances in Digital Image Processing: Theory Application Implementation Sutherland, B.R. et al. (1999) Visualization and measurement of internal waves by “synthetic schlieren”. Part 1. Vertically oscillating cylinder. Journal of Fluid Mechanics, 390, pp.93–126. Tellez J., Gómez M., Russo B. & Redondo, J.M. (2015) A simple measuring technique of surface flow velocity to analyze the behavior of velocity fields in hydraulic engineering applications. Geophysical Research Abstracts - EGU General Assembly 2015. Tellez J., Gómez M., Russo B. & Redondo, J.M. (2016) Characterize the hydraulic behavior of grate inlet in urban drainage to prevent the urban’s flooding. Geophysical Research Abstracts Vol. 18, EGU2016-648, 2016 EGU General Assembly 2016. Tellez J., Gómez M., Russo B. (2015) Technique for obtaining surface velocity field of the flow in the vicinity of sewer grates. Water Engineering Conference, Córdoba, Spain. (In Spanish) Villa T., Tellez J., Sanchez J.M., Redondo J. M., Sotillos L., Diez M. (2014) Diffusion in fractal wakes and convective thermoelectric flows. Geophysical Research Abstracts - EGU General Assembly 2014, Vol. 16.