Based on advances in computer algorithms for modeling complex fluid mechanics problems, scientists today are able to simulate, in three dimensions, the flow of blood and the interaction between blood and the arterial wall. When we combine these new algorithms with access to large-scale computational resources, we get a glimpse of what might be an emerging tool for enhanced medical diagnostics.
|Tayfun Tezduyar|| |
Today flow simulation and modeling can provide far better understanding of the interaction between blood as a fluid and the flexible blood vessels serving to transport the blood. This enhanced understanding combined with new computational capabilities may soon add a new tool for the physician, that when combined with traditional imaging techniques, may soon revolutionize medical diagnostics of aneurysms.
The numerical methods used in the computer modeling described here were introduced and implemented on parallel computing platforms by the Team for Advanced Flow Simulation and Modeling (T*AFSM). The powerful set of numerical methods introduced by the T*AFSM and used in this computation includes the quasi-direct fluid-structure interaction method [1, 2] recently developed by the T*AFSM at Rice University. The computation was carried out on the Cray XD1 supercomputer recently procured by the Computer and Information Technology Institute (CITI) at Rice in support of far-reaching computational research.
One of the major computational challenges in cardiovascular fluid mechanics is accurate modeling of the fluid-structure interactions between the blood flow and arterial walls. The blood flow depends on the arterial geometry, and the deformation of the arterial wall depends on the blood flow. The mathematical equations governing the blood flow and arterial deformations need to be solved simultaneously, with proper kinematic and dynamic conditions coupling the two physical systems.
Using a computed tomography (CT) model of a segment of the middle cerebral artery of a 57 year-old male, a computer model is able to closely approximate the width and extent of a cerebral aneurysm. The CT model of the artery approximated in this computation was reported in  and the blood flow rate used in the computation during the systolic cycle is a close approximation to the one reported in . The computation was carried out on the new Cray XD1 at Rice University.
Blood-flow patterns at an instant during the systolic cycle
The figure above shows the bloodflow patterns at an instant during the systolic cycle. The group of three images below shows the arterial shape at three different instants during the systolic cycle. The computation was carried out by graduate student Bryan Nanna and research scientist Sunil Sathe, as part the T*AFSM research in cardiovascular fluid mechanics.
Arterial shape at three different instants during the
systolic cycle. Click for larger image
Access to the new Cray XD1 allowed researchers with T*AFSM to carry out simulations significantly faster (3.5 times faster than on an older Intel Xeon based Linux cluster), giving the T*AFSM researchers quick feedback as the they increase the scope and accuracy of their computer modeling techniques. Moving forward, the team will also be able to scale up simulations providing better accuracy and ultimately develop new and better models that can match the conditions more closely, yielding even better insight and understanding.
“With access to such large scale resources locally, we are able to move our computer modeling research forward to new and challenging applications such as cardiovascular fluid-structure interactions,” said Tayfun Tezduyar, James F. Barbour Professor in Mechanical Engineering and T*AFSM Leader. “The Cray XD1 is about to transform our research since it permits us to address these new challenges with a level of modeling accuracy previously not feasible because of a lack of sufficient computational power.”
The Cray XD1, a.k.a. ADA1, was acquired with a grant from the National Science Foundation in a partnership with AMD and Cray. The system, ADA, is host to 336 2.2 Giga Hertz Dual-Core AMD Opteron processors, a total 1.4 TB2 of memory, and in excess of 20 TB of disk storage. The system clocks in at about 3 TeraFlop3. The Computer and Information Technology Institute (CITI) at Rice University led this acquisition from its inception, coordinating the proposal development, system procurement, and deployment. A team of more than 30 faculty members from Rice spanning Engineering, Natural Sciences, and Social Sciences participated in the effort to bring this system to Rice to support large-scale computing.
The Computer and Information Technology Institute (CITI) is a research-centric institute dedicated to the advancement of applied interdisciplinary research in the areas of computation and information technology.
 T.E. Tezduyar, S. Sathe, R. Keedy and K. Stein, “Space-Time Techniques for Finite Element Computation of Flows with Moving Boundaries and Interfaces,” Proceedings of the III International Congress on Numerical Methods in Engineering and Applied Sciences, Monterrey, Mexico, CD-ROM (2004).
 T.E. Tezduyar, S. Sathe, R. Keedy and K. Stein, “Space-Time Finite Element Techniques for Computation of Fluid-Structure Interactions,” Computer Methods in Applied Mechanics and Engineering, 195 (2006) 2002-2027.
 R. Torii, M. Oshima, T. Kobayashi, K. Takagi and T.E. Tezduyar, “Influence of Wall Elasticity in Patient-Specific Hemodynamic Simulations,” Computers & Fluids, published online, December 2005.
 R. Torii, M. Oshima, T. Kobayashi, K. Takagi and T.E. Tezduyar, “Computer Modeling of Cardiovascular Fluid-Structure Interactions with the Deforming-Spatial-Domain/Stabilized Space- Time Formulation,” Computer Methods in Applied Mechanics and Engineering, 195 (2006) 1885-1895
1 The Cray XD1 system at Rice was named after Ada Byron, also known as Lady Lovelace and often counted among the early women pioneers in computing (http://en.wikipedia.org/wiki/Ada_Lovelace)
2 TB is short for terabytes and is a measurement term for data storage capacity equal to approximately 1000 gigabytes (http://en.wikipedia.org/wiki/Terabyte)
3 TeraFLOPS: In computing, FLOPS (or flops) is an abbreviation of FLoating point Operations Per Second. This is used as a measure of a computer's performance, especially in fields of scientific calculations that make heavy use of floating point calculations. A TeraFLOP is the abbreviation used to denote a trillion FLOPS (http://en.wikipedia.org/wiki/Teraflop)
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