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DTSTART:19700329T010000
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CATEGORIES:Engineering Fluids Group Seminar
SUMMARY:Data assimilating mean velocity measurements into 
 computational fluid dynamics - Sean Symon (Univers
 ity of Southampton)
DTSTART;TZID=Europe/London:20230310T124500
DTEND;TZID=Europe/London:20230310T134500
UID:TALK195154AThttp://talks.cam.ac.uk
URL:http://talks.cam.ac.uk/talk/index/195154
DESCRIPTION:Data assimilation is the principle of combining un
 certain measurements from experiments with an impe
 rfect model to obtain a better prediction than eit
 her experiments or simulations can offer independe
 ntly. Data assimilation removes noise\, fills in m
 issing experimental data and reduces uncertainty a
 ssociated with ambiguous modelling parameters in s
 imulations such as turbulence production or bounda
 ry conditions. In this talk\, several methods for 
 assimilating mean velocity measurements into low-f
 idelity computational fluid dynamics (CFD) are dis
 cussed. The experimental data are obtained from pa
 rticle image velocimetry (PIV) and each method int
 roduces an unknown forcing term into the Reynolds-
 averaged Navier-Stokes (RANS) equations. An optimi
 sation problem is formulated whereby the unknown f
 orcing is updated such that the discrepancy betwee
 n the experimental mean velocity and the CFD is mi
 nimised. The talk will address how data assimilati
 on can overcome several limitations of PIV such as
  sparsity\, limited field of view and noise. \n
LOCATION:LR5
CONTACT:Paras Vadher
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