[Crib-list] SPEAKER: Yuexia Luna Lin (SEAS, Harvard Univ.) -- Computational Research in Boston and Beyond Seminar (CRIBB) -- Friday, March 6, 2020 from 12:00 PM - 1:00 PM in Building 32, Room 124 (STATA)

[Shirley Entzminger]

  	                 Computational Research in Boston and Beyond Seminar
  				             (CRIBB)



DATE:		Friday, March 6, 2020

TIME:		12:00 PM to 1:00 PM

LOCATION:	Building 32, Room 124

  		  Enter... 32 Vassar Street
  		           Cambridge, MA


  	        (Pizza & beverages will be provided at 11:45 AM outside
  		         Room 32-124


TITLE:		Reference map technique: a fully Eulerian method for
 		fluid-structure interactions


SPEAKER:	Yuexia Luna Lin (SEAS, Harvard University)


ABSTRACT:

Fluid-structure interactions (FSI) are abundantly observed in contexts 
ranging from swimming in the pool, to industrial level manufacturing, to 
bacteria collective motion on a petri dish.  However, the governing 
equations are only analytically trackable in the simple cases, making 
simulations key to understand this fantastic class of problems. 
Conventional computational methods often create a dilemma for 
fluid-structure interaction (FSI) problems.  Typically, solids are 
simulated using a Lagrangian approach with a grid that moves with the 
material, whereas fluids are simulated using an Eulerian approach with a 
fixed spatial grid. FSI methods often require some type of interfacial 
coupling between the two different perspectives.  We present a fully 
Eulerian FSI method that addresses these challenges.  The method makes use 
of reference map, which maps the solid in the current space to the 
reference space. Reference map is a common concept in finite strain 
theory, but it has been under-utilized as a primary variable for solid and 
FSI simulations.  A challenge in applying the reference map technique 
(RMT) in FSI is to extrapolate reference map values from grid cells 
occupied by the solids to unoccupied grid cells, in order to calculate 
derivative using finite difference schemes.  This challenge becomes more 
acute when applying RMT to simulations in 3D.  We develop an extrapolation 
algorithm based on least-square linear regression that is suitable for 
parallelization.  We show examples to demonstrate that RMT is well suited 
for simulating soft, highly-deformable materials and many-body contact 
problems.  Joint work with Nicholas Derr and Chris H. Rycroft (SEAS, 
Harvard University) and Ken Kamrin (Mechanical Engineering, MIT).


===================================================================

Massachusetts Institute of Technology
Cambridge, MA


For information about the Computational Research in Boston and Beyond Seminar
(CRIBB), please visit....

  			http://math.mit.edu/crib/



===

Shirley A. Entzminger
Administrative Assistant II
Department of Mathematics
Massachusetts Institute of Technology
77 Massachusetts Avenue
Building 2, Room 350A
Cambridge, MA 02139
PHONE:	(617) 253-4994
FAX:	(617) 253-4358
E-mail:	daisymae at math.mit.edu
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