Multi-exposed recordings for 3D Lagrangian particle tracking with Multi-Pulse Shake-The-Box

The recent introduction of the Multi-Pulse Shake-The-Box (MP-STB) method opened the possibility of extending 3D Lagrangian particle tracking (LPT) to the investigation of high-speed flows, where long time-resolved sequences of recordings are currently not available due to the limited acquisition frequency of high-speed systems. The MP-STB technique makes use of an iterative approach to overcome the limitations posed by the short observation time offered by a multi-pulse recording sequence. Multi-pulse sequences are typically obtained by synchronizing multiple illumination systems to generate bursts of laser pulses where the time separation can be freely adjusted down to less than a microsecond. Several strategies can be adopted for the recording of multi-pulse sequences; a dual camera system can be adopted to separate the single pulses onto the camera frames (either by means of polarization or timing), while the use of multi-exposed frames allows for the employment of a single imaging system, largely reducing the complexity and cost of the experimental setup. The main strategies to generate multi-pulse recording sequences are presented here; the application and performances of the MP-STB method are discussed based on the analysis of experimental data from the investigation of three turbulent boundary layer flows at velocities ranging from 10 to approximately 30 m/s. Results show the capability of the MP-STB technique in reconstructing accurate track fields which can be exploited both to describe instantaneous flow structures and to produce highly spatially resolved statistics by means of ensemble average in small bins. The iterative reconstruction and tracking strategy for MP-STB can be successfully adapted to the case of multi-exposed frames. Results suggest that, despite the increase in particle image density resulting from the double-exposed particle images, the adoption of multi-exposed recordings has the potential to become the technique of choice for the recording of multi-pulse sequences suitable for Lagrangian particle tracking in high-speed flows.Graphical abstract

[1]  Bernhard Wieneke,et al.  Multi-frame pyramid correlation for time-resolved PIV , 2012 .

[2]  Dirk Michaelis,et al.  Vibration Compensation for Tomographic PIV using Single Image Volume Self Calibration , 2011 .

[3]  Bernhard Wieneke,et al.  Tomographic particle image velocimetry , 2006 .

[4]  Paul Blinde,et al.  Determination of instantaneous pressure in a transonic base flow using four-pulse tomographic PIV , 2015 .

[5]  Andreas Schröder,et al.  Large-scale volumetric flow measurement in a pure thermal plume by dense tracking of helium-filled soap bubbles , 2017 .

[6]  Andreas Schröder,et al.  Lagrangian 3D particle tracking for multi-pulse systems: performance assessment and application of Shake-The-Box , 2016 .

[7]  Christian Willert,et al.  Dual-Volume and Four-Pulse Tomo PIV using polarized laser light , 2013 .

[8]  Armin Gruen,et al.  Particle tracking velocimetry in three-dimensional flows , 1993, Experiments in Fluids.

[9]  Fulvio Scarano,et al.  A high-order time-accurate interrogation method for time-resolved PIV , 2013 .

[10]  Ronald J. Adrian,et al.  Hairpin vortex organization in wall turbulencea) , 2007 .

[11]  A. Schröder,et al.  Shake-The-Box: Lagrangian particle tracking at high particle image densities , 2016, Experiments in Fluids.

[12]  Jürgen Kompenhans,et al.  Fundamentals of multiple plane stereo particle image velocimetry , 2000 .

[13]  Andreas Schröder,et al.  Volumetric Multi-Pulse Particle Tracking Measurement for Separated Laminar Transitional Flow Investigations , 2016 .

[14]  Fulvio Scarano,et al.  Material acceleration estimation by four-pulse tomo-PIV , 2014 .

[15]  Christian J. Kähler,et al.  Lagrangian 3D particle tracking in high-speed flows: Shake-The-Box for multi-pulse systems , 2016 .

[16]  M. Novara,et al.  Comparative assessment of pressure field reconstructions from particle image velocimetry measurements and Lagrangian particle tracking , 2017 .

[17]  B. W. Oudheusden,et al.  PIV-based pressure measurement , 2013 .

[18]  Fulvio Scarano,et al.  Dense velocity reconstruction from tomographic PTV with material derivatives , 2016 .

[19]  Tobias Jahn,et al.  Volumetric Flow Field Measurement: An Implementation of Shake-The-Box , 2018 .

[20]  Christian J. Kähler,et al.  Higher order multi-frame particle tracking velocimetry , 2013 .

[21]  S. Gesemann,et al.  Time-resolved large-scale volumetric pressure fields of an impinging jet from dense Lagrangian particle tracking , 2018 .

[22]  Fulvio Scarano,et al.  An efficient and accurate approach to MTE-MART for time-resolved tomographic PIV , 2015 .

[23]  Fulvio Scarano,et al.  Advances in iterative multigrid PIV image processing , 2000 .

[24]  C. Kähler,et al.  On the uncertainty of digital PIV and PTV near walls , 2012 .

[25]  Bernhard Wieneke,et al.  Volume self-calibration for 3D particle image velocimetry , 2008 .

[26]  Reinhard Geisler A fast double shutter system for CCD image sensors , 2014 .

[27]  J. Westerweel,et al.  Universal outlier detection for PIV data , 2005 .

[28]  C. Kähler,et al.  On the resolution limit of digital particle image velocimetry , 2012 .

[29]  Fulvio Scarano,et al.  On the velocity of ghost particles and the bias errors in Tomographic-PIV , 2011 .

[30]  Bernhard Wieneke,et al.  Non-uniform optical transfer functions in particle imaging: calibration and application to tomographic reconstruction , 2013 .

[31]  Tobias Jahn Volumetrische Strömungsvermessung: Eine Implementierung von Shake-The-Box , 2017 .

[32]  Kees Joost Batenburg,et al.  Motion tracking-enhanced MART for tomographic PIV , 2010 .

[33]  Christian Willert,et al.  Investigation of a high Reynolds number turbulent boundary layer flow with adverse pressure gradients using PIV and 2D- and 3D- Shake-The-Box , 2018 .

[34]  B. Wieneke Iterative reconstruction of volumetric particle distribution , 2013 .

[35]  Christian J. Kähler,et al.  Fundamentals of multiframe particle image velocimetry (PIV) , 2007 .

[36]  Andreas Schröder,et al.  From Noisy Particle Tracks to Velocity, Acceleration and Pressure Fields using B-splines and Penalties , 2016 .

[37]  Thomas Ahlefeldt,et al.  3D Lagrangian particle tracking using 4-pulse Shake-The-Box synchronised with microphone measurements on a subsonic jet at Mach 0.9 , 2016 .

[38]  Ramis Örlü,et al.  Assessment of direct numerical simulation data of turbulent boundary layers , 2010, Journal of Fluid Mechanics.