A short review of the literature on application and development of SIV methods is presented in this section, considering optical arrangements, image processing methods and velocimetry software.
2.1 Schlieren optical methods
Toepler, Focusing Schlieren and Background Oriented Schlieren (BOS) arrangements are among the most used SIV systems. Toepler methods also can have different configurations for SIV: one-mirror, lens and Z-type. Jonassen et al. (2006) measured turbulent flow velocities using Toepler SIV and carried out one of the first studies with different optical configurations and, according to the authors, the best results were obtained using LED light sources. Biswas and Qiao (2017) studied a high-velocity helium jet with a Z-type Toepler method using vertical and horizontal knife orientations and shadowgraphy. Their results were similar to laser PIV data for both shadowgraphy and the schlieren method with the knife in horizontal position and cut fraction of 40%. Gena et al. (2020) used a Toepler one-mirror optical array to measure the velocities of the human thermal plume. They verified that quantitative schlieren results had good agreement with hot-wire anemometer and thermistor data measured at discrete points along the plume. Nematollahi et al. (2020) developed a SIV system using a modified Toepler Z-type arrangement, for the diagnostic of organic Rankine cycles in subsonic and supersonic flow regimes and obtained results similar to PIV data. Wang et al. (2021) also used a Toepler Z-type array to study the flow velocities in hydrogen and methane flame ignition processes. Rong et al. (2021) used a one-mirror optical system combined with a color filter to detect and measure the velocity of pollutants emitted in the atmospheric air.
Concerning Toepler optical systems, Z-type configurations allow work distances far from the mirrors, what makes them attractive for studies of sprays, plasmas, flames, wind and shock tunnels. Toepler systems using only one mirror present a higher sensitivity, equal to twice the focal length (2X), while Z-type Toepler systems show a sensitivity proportional to the focal length (1X) (Settles 2001). Besides, systems with only one mirror have lower costs than systems with two mirrors, and in the case of systems using large mirrors, over 0.5 m diameter, their values can be very high. However, in one-mirror systems the test object must be close to the mirror, what can be a limiting factor when two-phase or reactive flows are analysed. Toepler systems using only lenses are advantageous for investigating small scale flows, since they can provide a higher spatial resolution compared to systems with mirrors. For example, Kim et al. (2020) adopted a Toepler lens system to visualize bacteria-size particles within droplets.
A focusing schlieren optical system was developed by Fu and Wu (Wu 2001) to perform velocimetry by correlation of images of buoyant flows generated from gas explosion ejection and gas fires. Hargather et al. (2011) used a focusing schlieren system for studies of supersonic flows in wind tunnels. However, they verified that Toepler methods provided better velocimetry results than focusing schlieren. One important aspect of their work was the improvement of the SIV by LED lighting. According to the authors, LED application enables intense lighting, with good light distribution from a small source when compared to traditional lamps. The focusing schlieren systems present an advantage over Toepler methods because they may provide three-dimensional images of the flow, while Toepler methods are limited to two-dimensional analysis.
BOS is the most versatile method of all schlieren systems. The recent wide utilization of this method lies in two main factors, the first is the simplicity and low cost of its components, BOS systems can be used for flow velocity analysis using smartphones (Aguirre-Pablo et al. 2017; Settles 2018). And the second reason is with regard to the possibility of obtaining the analysis of large areas, such as a helicopter in flight (Raffel 2015) or shock waves from explosive tests (Winter and Hargather 2019). However, BOS does not present the same sensitivity as Toepler methods and small gradients in temperature, pressure or density may not be observed. Goldhahn and Seume (2007) pointed out that the determining factors in the sensitivity of the BOS technique are the camera resolution, the software used and the increase in the focal length of the camera's lens and the camera proximity of the test fluid.
2.2 Schlieren Image Processing
Digital filters have been used to improve the quality of schlieren images since the initial utilization of digital cameras. For schlieren velocimetry applications, filters were first used by Wu (2001). The most common filters for processing schlieren images are the gray scale conversion of color images, edge detection, noise reduction, contrast balance, background subtraction and high-pass. Biswas and Qiao (2017) have studied different types of filters and the best results were obtained with noise removal, contrast balance and Laplacian filters.
2.3 PIV and SIV software
The first velocity estimates by schlieren images were related to shock waves. Ernest Mach utilized the optical arrangement developed by his contemporary August Toepler to visualize shock waves in flows (Krehl and Engemann 1995). The first measurement of velocity in a flow using a Schlieren optical array and a high-speed conventional camera was performed by Townend (1936) whereas the first application of a schlieren system for velocimetry with a high-speed digital camera and a commercial PIV software was made by Wu (2001).
Due to the development of low-cost and high-speed cameras and computers with high data processing capacity, there has been a growing increase in the development and use of the SIV technique. Among the software used in velocimetry, the following stand out: i) traditional PIV - commercial or open and free code; ii) specific correlation velocimetry software developed for schlieren images; iii) codes that use machine learning and artificial intelligence to calculate flow velocity.
Currently, conventional PIV software programs are the most commonly used for SIV. The advantage of using these PIV software packages is their long-time improvement and their ability to measure the many parameters of interest in fluid mechanics.
The pioneering work in software development for SIV was that of Hargather et al. (2011) who developed a Matlab code using the “normxcorr2” function. Wills et al. (2020) adapted a PIV code with the normxcorr2 function, and determined the velocity of supersonic flows using images with a resolution of 4.5 pixels/mm. Wang et al. (2021) developed and optimized a schlieren motion estimation (SME) algorithm capable of calculating the velocity in flaming ignition processes.
Cai et al. (2021) developed a powerful BOS method capable of measuring the three-dimensional field of pressure and velocity that uses neural networks to perform flow tomography. Znamenskaya and Doroshchenko (Znamenskaya and Doroshchenko 2021), developed an edge detection method using machine learning, enabling the calculation of supersonic velocities in shock tubes.
In the present work, the OpenPIV software (Ben-Gida et al. 2020), in MATLAB version, was adopted. This software package contains toolboxes for calculation of different flow characteristics, including mean and turbulent velocity fields, vorticities, auto-correlations and energy terms.