The Center for Interdisciplinary Scientific Computation (CISC) endeavors to promote research that crosses academic unit boundaries by holding lunchtime matchmaking seminars. Each seminar features a snapshot of scientific computation research by two colleagues with an opportunity for discussion. Lunch is provided. The details of past and future seminars can be found here.
The third seminar will be held Wednesday, October 11 from 12:45–1:45 p.m. in the Robert A. Pritzker Science Center, Room 129. For details and to RSVP click here by noon on Tuesday, October 10.
The fourth seminar will be held on Wednesday, October 18 from 12:45–1:45 p.m. in the Robert A. Pritzker Science Center, Room 129. RSVP here by noon on Tuesday, October 17. The is seminar will feature the following two talks.
John G. Georgiadis, chair and R. A. Pritzker Professor of Biomedical Engineering
Lattice Boltzmann Methods for Simulation of Diffusion-Weighted Magnetic Resonance Physics in Muscle or Brain
Diffusion tensor imaging allows in vivo measurement of the directional diffusion of water in muscle or brain. The correct interpretation of the results hinges on modeling microstructural information, water transport, and proton MR imaging physics. They have developed a class of Lattice Boltzmann methods to integrate the Bloch-Torrey partial differential equation, which governs this physics, in large domains containing cylindrical cells surrounded by complex extracellular matrix. Parallel implementation in an eight-core CPU computer system demonstrates linear speed-up, and plans are made to port this code to a multicore CPU/GPU platform.
Shuwang Li, associate professor of applied mathematics
Interface problems and an adaptive time-step scheme
Many physical and biological problems involve interfaces separating different domains. To efficiently compute the dynamics of the interface, they have developed an adaptive time-step scheme and test its performance in expanding/shrinking interface problems. The idea is to map the original time and space onto a new time and space such that the interface can evolve at an arbitrary speed in the new rescaled frame. In particular, for the expanding/shrinking interface problem, they choose (1) the space scaling function so that the expanding/shrinking interface is always mapped back to its initial size, i.e. the interface does not expand/shrink in the rescaled frame; (2) the time scaling function to speed up or slow down the motion of the interface, especially at later times when the interface expands slowly or shrinks extremely fast. Examples will be shown.