Dr. Jon Black Lunch-n-Learn

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An album containing 5 videos.

Dr Black is the new Director for the Center for Space Research and Assurance at AFIT. He is an Associate Professor of Aerospace Engineering within the Aeronautics and Astronautics department at AFIT. He holds a BS in Industrial Engineering from the University of Illinois at Urbana-Champaign in 2001 and a MS Mechanical and Aerospace Engineering, Joint Institute for Advancement of Flight Sciences (joint NASA Langley Research Center and George Washington University program) in 2003. He received his PhD in Mechanical Engineering from the University of Kentucky in 2006. Dr.

Stratified Wavy Flow

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Stratified wavy flow of R134a in a horizontal 7mm ID Channel. Video taken at 1000fps and played back at 16 fps. Entire 27 second video represents about one half of a second of flow.

Rotary Engine Flame Tracking

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The visualization of flame propagation in Stratified Charge Rotary Engine aids in combusting tracking. By using three chambers it is possible to view the interactions between the chambers.

Flow Visualization in Dragonfly Flight

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Flowing seed point visualization is used to capture leading edge vortex formation, attachment and shedding as well as forewing-hindwing wake interaction in the simulated flow around a pair of digitally reconstructed dragonfly wings. Seed points are injected into the flow at chordwise cuts 75% from the wing roots and advected over time while streamlines are integrated in the instantaneous vector fields. The camera’s focal point is fixed to the forewing root while the camera moves to remain approximately parallel to the forewing’s leading edge.

Silver Nanoparticles Illuminated Under a Darkfield Microscope

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This image was captured using a hyperspectral microscope (CytoViva, Auburn, AL). The different scattered colors provide information about the size and shape of the nanoparticles, and it has been shown that blue, green, yellow, and red correlate with sphere, pentagon, rounded-triangle, and triangle shaped particles, respectively (Mock et al., 2002). This data can be stored in a software program to later identify silver nanoparticles with specific properties within more complex environments, such as cells.

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