BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Talks.cam//talks.cam.ac.uk//
X-WR-CALNAME:Talks.cam
BEGIN:VEVENT
SUMMARY:Statistical averaging\, smoothing and filtering - Prof. Anvar Shuk
 urov (Newcastle)
DTSTART:20190218T140000Z
DTEND:20190218T150000Z
UID:TALK115453@talks.cam.ac.uk
CONTACT:Dr William Béthune
DESCRIPTION:Theory of turbulence is based on ensemble averaging\, but this
  type of averaging is not practical in most laboratory measurements\, astr
 onomical observations and numerical simulations as it requires very large 
 number of independent realisations of random fields involved. An alternati
 ve\, widely used in many applications\, and indeed the only one possible i
 n astronomy\, is the smoothing or filtering of random fields (in fact the 
 output of any astronomical instrument is a smoothed or filtered physical f
 ield). However\, spatial (or temporal) smoothing or filtering do not satis
 fy the Reynolds rules of averaging. Similarly\, modern numerical simulatio
 ns of turbulent flows are performed in spatial and temporal domains of a r
 elatively small size and ensemble averaging is out of question. Thus\, ana
 lyses of such numerical simulations employ various averages (such as plane
  averages) that satisfy the Reynolds rules. However\, such averages can be
  physically inappropriate\, e.g.\, when the mean quantities do not need to
  be independent of any spatial coordinates. We discuss the approach to spa
 tial smoothing and filtering that allows one to avoid this difficulty and 
 to derive consistently averaged quantities and equations that retain a ful
 l 3D structure.
LOCATION:MR14\,  Centre for Mathematical Sciences\, Wilberforce Road\, Cam
 bridge
END:VEVENT
END:VCALENDAR