TY - CONF

T1 - High-Speed Schlieren Imaging And PIV Of Unsteady Free Jet Injection With Plume Formation

AU - Leithold-Peyha, Mario

AU - Weiß, Christian

N1 - Conference code: 21

PY - 2024/7

Y1 - 2024/7

N2 - The aim of this work is to investigate schlieren image correlation velocimetry for flow field quantification of gaseousjet injection in non-manipulable apparatus like flow chambers. Such flow cases often struggle using tracer-basedmethods: Seeding particles may locally cause technical problems, or the plant design prevents principal opportunityof tracer adding, both of which lead to a reduced method repertory. This is specifically the case under flow conditions,where contamination of apparatus internals by seeding particles should be avoided completely.Therefore, in this paper we explore a seedingless, refraction-based method to quantify the velocity field of a jet plume.As experimental flow case we examine a transient jet release into a closed compartment under nearly atmosphericconditions. For simplification and greater clarity, the laboratory model geometry is kept essentially two-dimensional,thus we chose a flat-jet nozzle as injection device. The experimental investigations cover high speed schlieren imagingand laser sheet visualization followed by digital image correlation. Combining the traditionally qualitative schlierenapproach for flow visualization with Fast Fourier Transform and cross-correlation algorithms, we calculated thevelocity vector field of an unsteady jet plume formation. Furthermore, we determined the axial jet velocity profile atsteady state conditions. Our research findings highlight the applicability of schlieren image correlation velocimetry tospatially quantify gaseous jet formation at encased flow sections. Concluding, the results coincide with data fromparticle image velocimetry measurements and point out the potential of expanding flow diagnostics to hitherto hardlyexplored (industrial) flow cases.

AB - The aim of this work is to investigate schlieren image correlation velocimetry for flow field quantification of gaseousjet injection in non-manipulable apparatus like flow chambers. Such flow cases often struggle using tracer-basedmethods: Seeding particles may locally cause technical problems, or the plant design prevents principal opportunityof tracer adding, both of which lead to a reduced method repertory. This is specifically the case under flow conditions,where contamination of apparatus internals by seeding particles should be avoided completely.Therefore, in this paper we explore a seedingless, refraction-based method to quantify the velocity field of a jet plume.As experimental flow case we examine a transient jet release into a closed compartment under nearly atmosphericconditions. For simplification and greater clarity, the laboratory model geometry is kept essentially two-dimensional,thus we chose a flat-jet nozzle as injection device. The experimental investigations cover high speed schlieren imagingand laser sheet visualization followed by digital image correlation. Combining the traditionally qualitative schlierenapproach for flow visualization with Fast Fourier Transform and cross-correlation algorithms, we calculated thevelocity vector field of an unsteady jet plume formation. Furthermore, we determined the axial jet velocity profile atsteady state conditions. Our research findings highlight the applicability of schlieren image correlation velocimetry tospatially quantify gaseous jet formation at encased flow sections. Concluding, the results coincide with data fromparticle image velocimetry measurements and point out the potential of expanding flow diagnostics to hitherto hardlyexplored (industrial) flow cases.

KW - seedingless, schlieren image correlation velocimetry, PIV-algorithm, unsteady gaseous jet injection, plume formation

UR - https://www.lisbonsymposia.org/_files/ugd/2a3ff9_6838805541e6441b8866ff5e2218c633.pdf

U2 - 10.55037/lxlaser.21st.72

DO - 10.55037/lxlaser.21st.72

M3 - Paper

T2 - 21st International Symposium on the Application of Laser and Imaging Techniques to Fluid Mechanics

Y2 - 8 July 2024 through 11 July 2024

ER -