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Velocity Measurements of Hydrogen Jets Using the Optical Flow Method

Abstract

Concentration and velocity measurements are crucial for developing and validating hydrogen jet models, which  provide  scientific  bases  for hydrogen  safety  analyses.  The  concentration   fields  have  been visualized and accurately measured using laser diagnostic methods based on lase Rayleigh and Raman scattering  techniques.  However,  the  velocity  measurements  are  more   challenging.  Particle  image velocimetry (PIV) has been commonly used for measuring velocities in turbulent flows by seeding tracer particles into the flow and assuming the particles intimately following the flow.  However, sometimes the  particle  seeding  is  difficult  or  disturbs  the   flow.  Moreover, simultaneously  concentration  and velocity measurements are very difficult when using PIV systems to measure the velocities. Therefore, the optical flow velocimetry (OFV) method was used to resolve the velocity fields from the scalar fields or  particle  images  of  hydrogen   jets.  In the  present  work,  the  velocity  field  and  particle  images  of hydrogen  jets   were  simulated  using  FLUENT  with  the  large  eddy simulation (LES)  model  and  the particle images were then used to resolve the velocity field by the OFV method. The OFV results were compared with the CFD simulations to verify their accuracy. The results show that the OFC method was an  efficient,  low-cost  way  to  extract the  velocity  fields  from  particle  images.  The OFV  method accurately  located  the  large  vortices  in  the  flow  and  the  velocity distribution of  the  high-velocity gradients regions was consistent with the CFD results. The present study lays a foundation for using the OFV  method  to directly  resolve  the  velocity fields from  the  concentration  fields  of  hydrogen  jets measured by laser diagnostics.

Funding source: This study was supported by the National Natural Science Foundation of China (No. 51706125)
Related subjects: Safety
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2021-09-24
2022-11-27
http://instance.metastore.ingenta.com/content/conference3474
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