Computational Mechanics

, Volume 54, Issue 4, pp 921–932

Shape optimization of pulsatile ventricular assist devices using FSI to minimize thrombotic risk

Original Paper

DOI: 10.1007/s00466-013-0967-z

Cite this article as:
Long, C.C., Marsden, A.L. & Bazilevs, Y. Comput Mech (2014) 54: 921. doi:10.1007/s00466-013-0967-z

Abstract

In this paper we perform shape optimization of a pediatric pulsatile ventricular assist device (PVAD). The device simulation is carried out using fluid–structure interaction (FSI) modeling techniques within a computational framework that combines FEM for fluid mechanics and isogeometric analysis for structural mechanics modeling. The PVAD FSI simulations are performed under realistic conditions (i.e., flow speeds, pressure levels, boundary conditions, etc.), and account for the interaction of air, blood, and a thin structural membrane separating the two fluid subdomains. The shape optimization study is designed to reduce thrombotic risk, a major clinical problem in PVADs. Thrombotic risk is quantified in terms of particle residence time in the device blood chamber. Methods to compute particle residence time in the context of moving spatial domains are presented in a companion paper published in the same issue (Comput Mech, doi:10.1007/s00466-013-0931-y, 2013). The surrogate management framework, a derivative-free pattern search optimization method that relies on surrogates for increased efficiency, is employed in this work. For the optimization study shown here, particle residence time is used to define a suitable cost or objective function, while four adjustable design optimization parameters are used to define the device geometry. The FSI-based optimization framework is implemented in a parallel computing environment, and deployed with minimal user intervention. Using five SEARCH/POLL steps the optimization scheme identifies a PVAD design with significantly better throughput efficiency than the original device.

Keywords

Pulsatile VAD Residence time Fluid–structure interaction Isogeometric analysis Optimization SMF 

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.T-3 Fluid Dynamics and Solid MechanicsLos Alamos National LaboratoryLos AlamosUSA
  2. 2.Department of Mechanical and Aerospace EngineeringUniversity of California, San DiegoLa JollaUSA
  3. 3.Department of Structural EngineeringUniversity of California, San DiegoLa JollaUSA

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