Department of Mathematics

Event calendar for the Department of Mathematics

Mathias J. Krause: Fluid Flow Optimization with Lattice Boltzmann Methods with Applications

For many medical as well as technical applications the accurate knowledge of fluid flow dynamics, e.g. flow rates or wall shear stresses, is fundamental to understand and describe underlying processes. A coupling of simulation and measurement (CFD-MRI) promises a significant progress in terms of the accuracy of the obtained flow data, even in situations of low image contrast. Compared to today’s state-of-the-art, the new approach may achieve patient-friendly diagnostics by reducing the required contrast agent. Furthermore, the increase of accuracy allows treating new scenarios and as a result, unanswered medical questions, e.g. perfusion disorders, can be addressed.

In the talk, an overall strategy for numerical simulation and optimisation of fluid flow is intro-duced. The integrative approach takes advantage of numerical simulation, high performance computing and newly developed mathematical optimization techniques, all based on a mesoscopic model description and on Lattice Boltzmann Methods (LBM) as discretisation strategies. The resulting algorithms are implemented in a highly generic way in the frame-work of the open source library OpenLB ( The approaches and re-alisations are illustrated by means of various fluid flow simulation and optimisation exam-ples. Thereby, the main focus is placed on the CFD-MRI approach. Details are given for the 3D fluid flow optimisation problem formulation, the derivation of a first order optimality sys-tem and the solving process with gradient-based methods using Adjoint Lattice Boltzmann Methods. Validation and first application results (cf. Figure, an illustration of the CFD-MRI approach applied to a human aorta) are presented and discussed.

How to join:

The talk is held online via Zoom. You can join with the link

Referent:Dr. Mathias J. Krause, Lattice Boltzmann Research Group, Karlsruher Institut für Technologie (KIT)

Zeit: 11:30 Uhr

Ort: online

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