Dr. Mark P. Wernet Profile

Dr. Mark P. Wernet

Acting Chief at NASA Glenn Research Ctr

SPIE Involvement:

Author

Proceedings Article | 31 August 2000 Paper

Approach for particle sizing using DPIV

Amy Mielke, Mark Wernet, Jaikrishnan Kadambi

Proceedings Volume 4076, (2000) https://doi.org/10.1117/12.397946

KEYWORDS: Particles, Charge-coupled devices, Light scattering, Sensors, Monte Carlo methods, Diffraction, Mie scattering, Computer simulations, CCD image sensors, Scattering

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Many industrial and fossil fuel energy processes involve two phase flows for mass transit. In order to improve and better understand these two phase flows, knowledge of both the droplet/particle size and spatial distribution are required. The useful diagnostic tools should be able to make in-situ measurements without disturbing the flow field so that undisturbed flow measurements can be obtained. This suggests the need for a novel non-intrusive optical technique that can provide instantaneous measurements of particle size and velocity at multiple spatial points in planar (2-D) fields. Digital Particle Image Velocimetry (DPIV) is being studied as a candidate technique for making these measurements. A Monte-Carlo simulation has been developed that simulates the PIV optical recording system and the electric field scattered from particles in the flow. The simulation incorporates diffraction and the variation in light sheet intensity across the depth of field of the optical system. The simulation also computes the Mie scattered electric fields and images these onto the CCD detector. For small size particles, diffraction effects of the optical system dominate the recorded particle image light intensity distribution on the CCD array, and precludes our ability to determine their size. However, for larger sized particles other effects become more dominant, such as the glare spots in optically clear particles. The simulation allows us to examine the Mie scattered electric field of the particles recorded on the CCD and use the higher order structure in the recorded images to determine particle size. A technique for sizing is proposed which uses the separation between two glare spots visible on the particle image to estimate the particle diameter. The results show that the input particle size distribution to the simulation can be reasonably reproduced using the proposed sizing technique. Analysis of experimental PIV images also demonstrated that this technique is capable of providing moderate accuracy particle size estimates.

Proceedings Article | 21 November 1997 Paper

PIV for turbomachinery applications

Mark Wernet

Proceedings Volume 3172, (1997) https://doi.org/10.1117/12.279732

KEYWORDS: Particles, Laser Doppler velocimetry, Image processing, Cameras, Data processing, Data acquisition, Image acquisition, Velocity measurements, CCD cameras, Imaging systems

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Proceedings Article | 21 November 1997 Paper

Particle imaging technique for size, velocity, and concentration measurements in particle-laden flows

W. Martin, Jaikrishnan Kadambi, Mark Wernet

Proceedings Volume 3172, (1997) https://doi.org/10.1117/12.293409

KEYWORDS: Particles, Error analysis, Image processing, Velocity measurements, Charge-coupled devices, Statistical analysis, Signal detection, Image analysis, Light scattering, Spatial resolution

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Proceedings Article | 29 September 1995 Paper

Fuzzy-inference-enhanced information recovery from digital PIV using cross-correlation combined with particle tracking

Mark Wernet

Proceedings Volume 2546, (1995) https://doi.org/10.1117/12.221509

KEYWORDS: Particles, Cameras, Fuzzy logic, Spatial resolution, Particle image velocimetry

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Particle Image Velocimetry provides a means of measuring the instantaneous 2-component velocity field across the planar region of a seeded flow field. In this work only two camera, single exposure images are considered where both cameras have the same view of the illumination plane. Two competing techniques which yield unambiguous velocity vector direction information have been widely used for reducing the single exposure. multiple image data: cross-correlation and particle tracking. Correlation techniques yiedl averaged velocity estimates over subregions of the flow, whereas particle tracking technique give individual particle velocity estimates. The correlation technique requires identification of the correlation peak on the correlation plane corresponding to the average displacement of particles across the subregion. Noise on the images and particle dropout contribute to spurious peaks on the correlation plane, leading to misidentification of the true correlation peak. The subsequent velocity vector maps contain spurious vectors where the displacement peaks have been improperly identified. Typically these spurious vectors are replaced by a weighted average of the neighboring vectors, thereby decreasing the independence of the measurements. In this work fuzzy logic techniques are used to determine the true correlation displacement peak even when it is not the maximum peak on the correlation plane, hence maximizing the information recovery from the correlation operation, maintaining the number of independent measurements and minimizing the number of spurious velocity vectors. correlation peaks are correctly identified in both high and low seed density cases. The correlation velocity vector map can then be used as a guide for the particle tracking operation. Again fuzzy logic techniques are used, this time to identify the correct particle image pairings between exposures to determine particle displacements, and thus velocity. The advantage of this technique is the improved spatial resolution which is available from the particle tracking operation. Particle tracking alone may not be possible in the high seed density images typically required for achieving good results from the correlation technique. This two staged approach offers a velocimetric technique capable of measuring particle velocities with high spatial resolution over a broad range of seeding densities.

Proceedings Article | 2 December 1993 Paper

Fuzzy logic particle tracking velocimetry

Mark Wernet

Proceedings Volume 2005, (1993) https://doi.org/10.1117/12.163754

KEYWORDS: Particles, Fuzzy logic, Image processing, Process control, Velocimetry, Control systems, Velocity measurements, Systems modeling, Digital recording, Data processing

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Proceedings Article | 1 December 1991 Paper

Ground-based PIV and numerical flow visualization results from the surface-tension-driven convection experiment

Alexander Pline, Mark Wernet, Kwang-Chung Hsieh

Proceedings Volume 1557, (1991) https://doi.org/10.1117/12.49601

KEYWORDS: Particles, Photodynamic therapy, Video, Data acquisition, Photography, Crystals, Image processing, Cameras, Velocity measurements, Frame grabbers

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Showing 5 of 6 publications

Conference Committee Involvement (1)

Aerospace Applications

7 July 2004 | Cleveland, Ohio, United States

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