Book contents
- Frontmatter
- Contents
- Contributors
- 1 Microscopy of soft materials
- 2 Computational methods to study jammed systems
- 3 Soft random solids: particulate gels, compressed emulsions, and hybrid materials
- 4 Langmuir monolayers
- 5 Computer modeling of granular rheology
- 6 Rheological and microrheological measurements of soft condensed matter
- 7 Particle-based measurement techniques for soft matter
- 8 Cellular automata models of granular flow
- 9 Photoelastic materials
- 10 Image acquisition and analysis in soft condensed matter
- 11 Structure and patterns in bacterial colonies
- Index
- References
7 - Particle-based measurement techniques for soft matter
Published online by Cambridge University Press: 05 July 2014
Edited by
Book contents
- Frontmatter
- Contents
- Contributors
- 1 Microscopy of soft materials
- 2 Computational methods to study jammed systems
- 3 Soft random solids: particulate gels, compressed emulsions, and hybrid materials
- 4 Langmuir monolayers
- 5 Computer modeling of granular rheology
- 6 Rheological and microrheological measurements of soft condensed matter
- 7 Particle-based measurement techniques for soft matter
- 8 Cellular automata models of granular flow
- 9 Photoelastic materials
- 10 Image acquisition and analysis in soft condensed matter
- 11 Structure and patterns in bacterial colonies
- Index
- References
Summary
Introduction
Optical measurement techniques are ubiquitous across many disciplines of science. Since so much of our everyday interaction with the world around us is based on vision, optical investigations feel very natural and, when possible, are often the preferred interrogation technique.
While the sophistication of optical measurement has certainly increased with time, the basic idea remains the same: the physical system of interest is illuminated with visible light (which is assumed to interact with the system only passively) and is imaged by a photosensitive detector. In the early days of optical measurement, film was the preferred medium, and optical studies were by and large static. The few dynamic measurements that were made involved long or multiple exposures and tedious reconstructions done by hand [1]. With the advent of digital imaging and large-scale digital storage, however, optical measurements can now easily address dynamic questions, with enough temporal and spatial resolution to measure a wide range of quantities and sufficient storage to gather enough samples for well-converged statistics. In physics, we are often interested in velocities and accelerations, which give us access to momentum, energy, and force; such dynamic quantities are now accessible with imaging techniques.
- Type
- Chapter
- Information
- Publisher: Cambridge University PressPrint publication year: 2010
References
[1] and , “The rate of dissipation of energy and the energy spectrum in a low-speed turbulent jet,” T. Am. Gœphys. Union 37, 13–26 (1956).Google Scholar
[2] , “The 12th international symposium on flow visualization,” J. Visualization 10, 123–128 (2007).Google Scholar
[3] , , , , , , and , “Particle-based techniques,” in , , and (eds.), Springer Handbook of Experimental Fluid Mechanics, pp. 287-362 (Springer-Verlag, Berlin, 2007).
[4] and , “Equation of motion for a small rigid sphere in a nonuniform flow,” Phys. Fluids 26, 883–9 (1983).Google Scholar
[5] , , , , , and , “Acceleration statistics of inertial particles in turbulent flow,” Eur. Phys. J. B 66, 531–6 (2008).Google Scholar
[6] , , and , “Transport of finite-sized particles in chaotic flow,” Phys. Rev. Lett. 101, 174504 (2008).Google Scholar
[7] , “Tracer particles and seeding for particle image velocimetry,” Meas. Sci. Technol. 8, 1406–16 (1997).Google Scholar
[8] , , , , and , “Turbulent transport of material particles: An experimental study of finite size effects,” Phys. Rev. Lett. 99, 184502 (2007).Google Scholar
[9] , “Particle-imaging techniques for experimental fluid mechanics,” Annu. Rev. Fluid Mech. 23, 261–304 (1991).Google Scholar
[10] , “Fundamentals of digital particle image velocimetry,” Meas. Sci. Technol. 8, 1379–92 (1997).Google Scholar
[11] and , “A hybrid digital particle tracking velocimetry technique,” Exp. Fluids 22, 199–211 (1997).Google Scholar
[12] , , and , “Statistical particle tracking velocimetry using molecular and quantum dot tracer particles,” Exp. Fluids 41, 869–80 (2006).Google Scholar
[13] , “Interative image deformation methods in PIV,” Meas. Sci. Technol. 13, R1-R19 (2002).Google Scholar
[14] , , and , “Super-resolution particle imaging velocimetry,” Meas. Sci. Technol. 6, 754–68 (1995).Google Scholar
[15] , , and , “Lagrangian acceleration measurements at large Reynolds numbers,” Phys. Fluids 10, 2268–80 (1998).Google Scholar
[16] , , , , and , “Measurement of particle accelerations in fully developed turbulence,” J. Fluid Mech. 469, 121–60 (2002).Google Scholar
[17] , , and , “Experimental Lagrangian acceleration probability density function measurement,” Physica D 193, 245–51 (2004).Google Scholar
[18] , , and , “Measuring Lagrangian statistics in intense turbulence,” in , , and (eds.), Springer Handbook of Experimental Fluid Mechanics, pp. 789–99 (Springer-Verlag, Berlin, 2007).Google Scholar
[19] and , “An experimental investigation of the relative diffusion of particle pairs in three-dimensional turbulent flow,” J. Fluid Mech. 422, 207–23 (2000).Google Scholar
[20] , , , and , Numerical Recipes in C: The Art of Scientific Computing (Cambridge University Press, Cambridge, 1992).Google Scholar
[21] , , , and , “Algorithms for fully automated three-dimensional particle tracking velocimetry,” Exp. Fluids 17, 209–19 (1994).Google Scholar
[22] , , and , “Particle tracking velocimetry in three-dimensional flows. Part 1. Photogrammetric determination of particle coordinates,” Exp. Fluids 15, 13346 (1993).Google Scholar
[23] , , and , “A quantitative study of three-dimensional Lagrangian particle tracking algorithms,” Exp. Fluids 40, 301–13 (2006).Google Scholar
[24] , , and , “Establishing motion correspondence using extended temporal scope,” Artif. Intell. 145, 227–43 (2003).Google Scholar
[25] and , “Methods of digital video microscopy for colloidal studies,” J. Colloid Interf. Sci. 179, 298–310 (1996).Google Scholar
[26] , , and , “Particle tracking velocimetry in three-dimensional flows. Part II. Particle tracking,” Exp. Fluids 15, 279–94 (1993).Google Scholar
[27] , , and , “Resolving motion correspondence for densely moving points,” IEEE T. Pattern Anal. 23, 54–72 (2001).Google Scholar
[28] and , “An extension of the Munkres algorithm for the assignment problem to rectangular matrices,” Commun. ACM 14, 802–4 (1971).Google Scholar
[29] , , and , “Experimental and numerical study of the Lagrangian dynamics of high Reynolds turbulence,” New J. Phys. 6, 116 (2004).Google Scholar
[30] , “Tracking Lagrangian trajectories in position-velocity space,” Meas. Sci. Technol. 19, 075105 (2008).Google Scholar
[31] , , and , “Experimental measurements of stretching fields in fluid mixing,” Phys. Rev. Lett. 88, 254501 (2002).Google Scholar
[32] , , , , and , “Uncovering the Lagrangian skeleton of turbulence,” Phys. Rev. Lett. 98, 144502 (2007).
[33] and , “Curvature fields, topology, and the dynamics of spatiotemporal chaos,” Phys. Rev. Lett. 99, 194502 (2007).Google Scholar
[34] and , “Dynamic topology in spatiotemporal chaos,” Phys. Fluids 20, 064104 (2008).Google Scholar
[35] , “Particle tracking in three-dimensional space,” in (ed.), “Three-dimensional velocity and vorticity measuring and image analysis techniques,” pp. 129–52 (Kluwer Academic Publishers, Dordrecht, The Netherlands, 1996).Google Scholar
[36] , , , , , and , “3D scanning particle tracking velocimetry,” Exp. Fluids 39, 923–34 (2005).Google Scholar
[37] , , , , , and , “Lagrangian particle tracking in three dimensions via single-camera inline digital holography,” New J. Phys. 10, 125013 (2008).Google Scholar
[38] , , , and , “Airbornedigital holographic system for cloud particle measurements,” Appl. Optics 43, 5987–95 (2004).Google Scholar
[39] and , “Recent developments of PIV towards 3D measurements,” Top. Appl. Phys. 112, 127–54 (2008).Google Scholar
[40] , , , , , , and , “Spatio-temporal analysis of eukaryotic cell motility by improved force cytometry,” Proc. Natl. Acad. Sci. 104, 13343–8 (2007).Google Scholar
[41] , , and , “Real-time image compression for high-speed particle tracking,” Rev. Sci. Instr. 78, 023704 (2007).Google Scholar