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Research Papers: Fundamental Issues and Canonical Flows

Observation of the Development of Secondary Features in a Richtmyer–Meshkov Instability Driven Flow

[+] Author and Article Information
Tennille Bernard

Department of Mechanical Engineering,
University of New Mexico,
Albuquerque, NM 87131
e-mail: tenncb10@unm.edu

C. Randall Truman

Mem. ASME
Professor
Department of Mechanical Engineering,
University of New Mexico,
Albuquerque, NM 87131
e-mail: truman@unm.edu

Peter Vorobieff

Mem. ASME
Professor
Department of Mechanical Engineering,
University of New Mexico,
Albuquerque, NM 87131
e-mail: kalmoth@unm.edu

Clint Corbin

Department of Mechanical Engineering,
University of New Mexico,
Albuquerque, NM 87131
e-mail: clcorbin@unm.edu

Patrick J. Wayne

Department of Mechanical Engineering,
University of New Mexico,
Albuquerque, NM 87131
e-mail: pwayne@unm.edu

Garrett Kuehner

Department of Mechanical Engineering,
University of New Mexico,
Albuquerque, NM 87131
e-mail: garrett.kuehner@gmail.com

Michael Anderson

Illinois Rocstar, LLC,
Champaign, IL 61826
e-mail: mjanderson@illinoisrocstar.com

Sanjay Kumar

Associate Professor
Department of Mechanical Engineering,
University of Texas, Brownsville,
TX 78520
e-mail: sanjay.kumar@utb.edu

From here on, the word “spike” in the text will refer to this feature, which is driven by shock focusing. It is comprised of heavy gas entering the surrounding light gas, but distinct in its physical origin from the RMI “spike” according to traditional terminology.

1Corresponding author.

Contributed by the Fluids Engineering Division of ASME for publication in the JOURNAL OF FLUIDS ENGINEERING. Manuscript received December 31, 2013; final manuscript received June 5, 2014; published online September 10, 2014. Assoc. Editor: Samuel Paolucci.

J. Fluids Eng 137(1), 011206 (Sep 10, 2014) (6 pages) Paper No: FE-13-1759; doi: 10.1115/1.4027829 History: Received December 31, 2013; Revised June 05, 2014

Richtmyer–Meshkov instability (RMI) has long been the subject of interest for analytical, numerical, and experimental studies. In comparing results of experiment with numerics, it is important to understand the limitations of experimental techniques inherent in the chosen method(s) of data acquisition. We discuss results of an experiment where a laminar, gravity-driven column of heavy gas is injected into surrounding light gas and accelerated by a planar shock. A popular and well-studied method of flow visualization (using glycol droplet tracers) does not produce a flow pattern that matches the numerical model of the same conditions, while revealing the primary feature of the flow developing after shock acceleration: the pair of counter-rotating vortex columns. However, visualization using fluorescent gaseous tracer confirms the presence of features suggested by the numerics; in particular, a central spike formed due to shock focusing in the heavy-gas column. Moreover, the streamwise growth rate of the spike appears to exhibit the same scaling with Mach number as that of the counter-rotating vortex pair (CRVP).

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Figures

Grahic Jump Location
Fig. 1

Schematic of experimental setup. Top: side view. The pressurized driver section (left) is separated from the driven section by a diaphragm that is ruptured by a puncturer (dashed lines, labeled P). As the shock (schematically shown) propagates through the driven section, its progress is monitored by two pressure transducers (PT1 and PT2). Glycol droplets suspended in gas (air, air–SF6 mix, or air–SF6-acetone mix) are injected into the test section vertically, forming a seeded cylindrical column. The flow is illuminated with a horizontal laser sheet through an optical window in the end of the runoff section. The flow is illuminated with several pulsed lasers forming a single laser sheet, illuminating the horizontal centerline cross section of the shock tube. A 45° mirror above the test section reflects the view of the illuminated plane toward the camera. Bottom: close-up of the laser-illuminated flow visualization plane in the test section as seen by the camera, showing the cross section of the initial conditions and a dynamic image with a CRVP.

Grahic Jump Location
Fig. 2

Comparison of flow visualization with glycol tracers (top) and numerical modeling (bottom) of RMI developing in a heavy-gas column with a cylindrical cross section and an initially diffuse interface between the heavy gas and the surrounding light gas (after [19]). Mach number is 1.7, Atwood number is 0.5. Shock direction is from left to right. The leftmost image in each row represents the initial conditions immediately before shock arrival from the left. Time intervals between subsequent dynamic images are 50 μs. Experimental images are inverted, so darker areas correspond to seeded (injected) flow.

Grahic Jump Location
Fig. 3

PLIF image acquired at M = 1.7 about 600 μs after shock acceleration, with observable features labeled. Vertical image extent is 2 cm. The image is inverted (darker parts correspond to more fluorescence). A reflection off the bottom wall of the test section is also labeled.

Grahic Jump Location
Fig. 4

Visualization of the same PLIF image using two different palettes. The tone curve on the left emphasizes low-brightness features, and displays intensity levels (based on original 16-bit image) 1200–1600. On the right, intensity levels 1000–9000 are similarly displayed, resulting in a much shallower tone curve.

Grahic Jump Location
Fig. 5

Experimental flow visualization using PLIF and Mie scattering off droplets for three Mach numbers. Flow direction is from left to right. Experimental images are inverted, so darker areas correspond to flow seeded with droplets (label “Mie”) or marked with acetone tracer (label “PLIF”). Extent of imaged area is 10.09 cm. Individual image timings (with time t = 0 corresponding to shock reaching the center of the gas column) are labeled.

Grahic Jump Location
Fig. 6

Growth rates of the CRVP (top row) and the spike (bottom row) as the function of time after shock acceleration and of downstream distance. Schematic above the top row of plots illustrates how the streamwise feature size was determined from the image (left), using spanwise-averaged intensity (right).

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