05 Fakultät Informatik, Elektrotechnik und Informationstechnik
Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/6
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Item Open Access Flexible and efficient data mapping for simulation of coupled problems(2026) Schneider, David; Uekermann, Benjamin (Jun.-Prof. Dr.)Multi-physics simulations model various physical phenomena and their interactions. Examples include climate models or the simulation of fusion reactors. Modeling more physical phenomena in the same simulation often provides new insights. This poses significant challenges for the underlying methods and the simulation software itself. Decomposing a multi-physics simulation into its parts is an effective way to tame the inherent complexity. The coupling library preCICE allows for such partitioned simulations, coupling simulation models without access to their internal numerics. While preCICE is well-suited for conventional, mesh-based surface couplings, its applicability breaks down in alternative scenarios due to restrictive data-mapping algorithms. These algorithms apply spatial mapping operators to statically defined coupling meshes and are generally not designed for large problems. As a result, they hinder the flexible and efficient simulation of relevant applications, including volumetric couplings, high-order couplings, and mesh-particle couplings. To overcome these limitations, this work focuses on four main aspects: first, developing a scalable partition-of-unity radial-basis-function interpolation customized for coupled problems; second, implementing data-parallel kernel methods on CPUs and GPUs to ensure cross-platform efficiency; third, enabling immediate access to meshes received from coupling partners for user-defined mapping operators; fourth, computing a mapping operator just-in-time on temporary coordinates for the seamless coupling of meshless solvers. Taken together, these concepts enable plug-and-play integration of diverse numerical models in multi-physics simulations. Large-scale volumetric couplings are now feasible and efficient, breaking the traditional accuracy-efficiency trade-off. Multi-physics couplings can exploit spatial high-order convergence rates of existing models for high-fidelity simulations, while preserving full black-box compatibility. The simulation of fluid-particle couplings can be modularized and leverage already-existing models for both the simulation of the mesh-based fluid and the particles. In the end, the robust implementation, the gained efficiency, and the flexibility significantly extend the applicability of preCICE and benefit its vibrant user community. Beyond preCICE, the presented concepts provide generally applicable building blocks for scalable, modular multi-physics coupling.Item Open Access Learning structured models for active planning : beyond the Markov paradigm towards adaptable abstractions(2018) Lieck, Robert; Toussaint, Marc (Prof. Dr.)