1 Optimizing recording speed and interrogation window for rotating flow recorded in the ambient light PIV analysis

2025-04-28 0 0 943.72KB 12 页 10玖币

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Optimizing recording speed and interrogation window for rotating flow recorded in the

ambient light: PIV analysis

Shailee P Shah1, Nayan Mumana1, Preksha Barad1, Rucha P Desai1#, Pankaj S Joshi2

1 Department of Physical Science, P D Patel Institute of Applied Sciences, Charotar University of Science

and Technology, CHARUSAT Campus, Changa – 388 421, Gujarat, India.

2 International Centre for Cosmology, Charotar University of Science and Technology, CHARUSAT

Campus, Changa – 388 421, Gujarat, India.

# E-mail address for correspondence: ruchadesai.neno@charusat.ac.in

Abstract

The present study reports PIV analysis of the surface flow profile using a smartphone camera in ambient light instead

of high-tech equipment like a professional camera and high-power laser/ LEDs. Additionally, it provides a stepwise

method for optimizing recording speed and interrogation window size for the vortex flow generated at different

rotational frequencies of the magnetic stirrer. The optimization method has been explained with an example of the

vortex flow generated by a magnetic stirrer. The analysis has been carried out using the Matlab-based application

PIVlab. Finally, the optimized parameters have been compared with the Burger vortex model, which shows good

agreement with the PIV data. The proposed method can also determine the sureface flow of opaque liquids.

Keywords

Particle image velocimetry (PIV), smartphone camera, ambient light, vortex flow, recording speed (fps- frames per

second), flow visualization, the velocity profile

1. Introduction

Flow measurement and visualization are inseparable parts of fluid mechanics. Visualization of simple laminar flow to

complex turbulent flow is possible due to analytical and computational fluid flow simulations. However, experimental

measurements and visualization are equally crucial for the application and educational point of view. Particle Image

Velocimetry (PIV) is well- established and vastly used technique for the experimental velocity estimation of fluid

flow (Raffel et al., 2007). A typical PIV setup consists of a high-power multi-pulsed leaser sheet (to illuminate tracer

seeded flow), a high-speed camera (to record the motion of the illuminated flow), a synchronizer (to synchronize laser

pulse with a camera), and additional optical components & its arrangements (to convert laser beam into a sheet). In

this method, initially, the flow geometry can be traced by the tracer particles illuminated by a laser sheet, and

subsequently, flow geometry can be captured by the high-speed camera. Later, the captured images/ video can be

processed by the standard PIV software. Finally, the software estimates the velocity based on the displacement of

tracers using cross-correlation between two frames (Raffel et al. 2007)(2016). PIV, a non-destructive imaging-based

technique, has gained interest among the scientific community, researchers, and academicians. Moreover, the

technique can be applied to other fields, such as oceanography, marine biology, zoology, and microbiology(Raffel et

al., 2007)(Minichiello et al., 2020).

Despite having advantages, PIV techniques have several limitations say the need for trained human resources, proper

maintenance, space, and safety hazards associated with a high-power pulsed laser (class 4, >500mW), and above all,

the high cost of all the instruments involved (Minichiello et al. 2020). All these factors force educational institutions

to restrict their use for new learners. On the other hand, various commercial PIV systems have been developed for

educational purposes (e.g., THERMOFLOW, ePIV, HEMOFLOW, MiniPIV) (Minichiello et al. 2020) to enable users

the ease of operation with limited variable components. For example, users can only change the inlet and outlet

parameters, water level, and seeding density. Additionally, scientists and technologists have been working towards

developing a PIV system with the motto of ease of operation, using advanced technology with slick models of

equipment with less space utilization, economical, and minimal maintenance.

In PIV analysis, significant technological advancement has provided alternatives for the high-tech equipment, e.g.,

high-power pulsed lasers can be replaced with high-power LEDs and high-speed professional cameras with

smartphone cameras, which in turn makes the overall PIV system safe, simple, easy to operate, and notably economical

(Kashyap et al.; Buchmann et al. 2010; Willert et al. 2010; Harshani et al. 2015; Hain et al. 2016; Dai et al. 2017;

Aguirre-Pablo et al. 2017). Tomographic PIV, 3D PIV, mIPIV, and smartPIV are a few examples of technological

developments. Tomographic PIV uses multiple smartphone cameras and different colored LEDs (Aguirre-Pablo et al.

2017), while the 3D PIV technique uses a single camera and structured light illumination (Aguirre-Pablo et al. 2019).

Both these studies show good agreement with the standard stereo-PIV data for the same flow. Simultaneously, mobile-

based applications for PIV measurement, such as mIPIV and smartPIV, have been developed from the educational

perspective (Minichiello et al. 2020; Cierpka et al. 2021). It provides the live visualization of flow, allows users to

capture the flow at various fps, and gives the data as a text file and vector image (Cierpka et al. 2021). In all these

papers, either high-power lasers or high-power LEDs have been used. Contrary, the present work focuses on using

ambient light for the water vortex generated using a magnetic stirrer.

Additionally, the effect of recording speed with different frames per second (fps), i.e., 30, 120, and 240 fps, has been

illustrated here using the smartphone camera. Most publications mainly report either a trial-and-error method for

selecting an interrogation window (IW) or the results without specifying the effect of IW. However, IW is an integral

part of the process which directly affects the final output; it should be adequately addressed. Hence, here we have

given a stepwise process for selecting the interrogation window (IW). The optimization step is critical learning for

beginners. Here, we followed ITTC guidelines (2016) to optimize the interrogation window size. Results have been

analyzed using the MatLab-based open-source extension PIVlab (Thielicke and Stamhuis 2014).

2. Experimental

A water vortex was generated in a cylindrical glass beaker using a magnetic stirring bar. Figure 1(a) shows a schematic

of the experimental setup for generating the water vortex. The dimensions of the vessel and the stirrer bar are given

in Table 1. The experiments have been carried out for different rotational speeds (ω) i.e., 8.33s-1, 10.00s-1, 11.66s-1,

and 13.33s-1 of the magnetic stirrer bar. Here, the vortex depth was measured experimentally using a ruler.

2a h

H’

0 5 0 0

R= 10.5 cm

H= 11 cm

Figure 1 (a) Schematic representation of experimental setup, (b) Vortex generated using magnetic

stirrer. A half width of the vortex has been determined based on the cylindrical wall of dye.

Half- width

(a)

(b)

Simultaneously, the surface flow has been captured from the top of the vessel using a mobile camera (refer to Table

2) with different recording speeds, i.e., 30, 120, and 240 fps (see Figure 1(a)). The position of the mobile phone was

fixed throughout the experiments.

Table 1 Dimensions of a vessel and magnetic stirrer bar

Dimensions

The diameter of a vessel (2R)

0.105  0.001 m

Height of vessel

0.150  0.001 m

Filled water at a height (H)

0.110  0.001 m

Length of the stirrer bar (a)

0.020  0.001 m

Width of the stirrer bar (d)

0.009  0.001 m

Next, the half-width of the vortex was measured by injecting the fluorescent dye near the center to see the illuminated

cylindrical vortex wall (Figure 1(b)). The radius of the cylindrical wall is equivalent to the critical radius (rc) or a half-

width (2b) of the vortex (Halász et al. 2007). To measure the rc an image of the vortex was captured and later analyzed

using PIVlab. The scale was initially calibrated during the PIV analysis using the calibration stick by entering the

known distance (in meters). Once the calibration is done, PIV uses this scale for further analysis. In the present

experiment, the vortex half-width (rc or 2b) determined from PIV was 0.0094±0.0002 m. The apparent advantage of

PIV analysis is its accuracy compared to visual observation.

2.1 Data extraction from the PIVlab

The videos were recorded at different fps using the "One Plus Nord 2" mobile phone camera. Camera features are

given in Table 2.

Model Name

OnePlus Nord-2

Camera Sensor

Sony Exmor IMX766

Pixel Size

1.0 µm

Lens Quantity

50 MP

OIS, Optical Zoom, Autofocus

YES

Aperture

f/1.88

Video recording

• 4K at 30 fps

• 1080p at 30/60 fps

• 720p at 30/60 fps

Super slow-motion video recording

• 1080p at 120 fps

• 720p at 240 fps

Table 2 Camera features

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1Optimizingrecordingspeedandinterrogationwindowforrotatingflowrecordedintheambientlight:PIVanalysisShaileePShah1,NayanMumana1,PrekshaBarad1,RuchaPDesai1#,PankajSJoshi21DepartmentofPhysicalScience,PDPatelInstituteofAppliedSciences,CharotarUniversityofScienceandTechnology,CHARUSATCampus,Changa–388421,...

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1 Optimizing recording speed and interrogation window for rotating flow recorded in the ambient light PIV analysis

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