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DTSTAMP:20181221T160727Z
LOCATION:D165
DTSTART;TZID=America/Chicago:20181111T160000
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UID:submissions.supercomputing.org_SC18_sess147_ws_cafcw114@linklings.com
SUMMARY:Toward a Computational Simulation of Circulating Tumor Cell Transp
 ort in Vascular Geometries
DESCRIPTION:Workshop\nApplications, Deep Learning, Exascale, Workshop Reg 
 Pass\n\nToward a Computational Simulation of Circulating Tumor Cell Transp
 ort in Vascular Geometries\n\nGounley, Draeger, Randles\n\nComputational m
 odels can provide much needed insight into the mechanisms driving cancer c
 ell trajectory. However, capabilities must be expanded to enable simulatio
 ns in larger sections of micro- and meso-vasculature and account for the m
 ore complex fluid dynamic patterns that occur in patient-derived vascular 
 geometries. The increased size and complexity of these simulations demands
 , in turn, the development of highly flexible and scalable computational f
 rameworks. In this work, we extend the massively parallel hemodynamics sol
 ver HARVEY to perform the necessary fluid-structure interaction for CTC tr
 ansport in high-resolution blood flow. We couple lattice Boltzmann and fin
 ite element methods, for the fluid and cells, respectively, with the immer
 sed boundary method for the fluid-structure interaction. Parallelized with
  MPI, HARVEY is designed to handle the sparse and tortuous blood vessels e
 ncountered in patient-derived vascular geometries while maintaining comput
 ational efficiency. HARVEY can be scaled to simulate vasculature geometrie
 s containing hundreds of millions of blood cells, equivalent to blood volu
 mes on the order of tens of milliliters. In sum, the resulting framework h
 as the potential to significantly improve the model fidelity of CTC simula
 tions with respect to both the complexity and size of vascular geometries 
 being considered.
URL:https://sc18.supercomputing.org/presentation/?id=ws_cafcw114&sess=sess
 147
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