LEADER 04004nam 22005295 450 001 9910770279203321 005 20251113190531.0 010 $a9783031451584 010 $a3031451589 024 7 $a10.1007/978-3-031-45158-4 035 $a(MiAaPQ)EBC31018104 035 $a(Au-PeEL)EBL31018104 035 $a(DE-He213)978-3-031-45158-4 035 $a(CKB)29364115800041 035 $a(OCoLC)1415893118 035 $a(EXLCZ)9929364115800041 100 $a20231213d2023 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aModeling, Simulation and Optimization of Fluid Dynamic Applications /$fedited by Armin Iske, Thomas Rung 205 $a1st ed. 2023. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2023. 215 $a1 online resource (165 pages) 225 1 $aLecture Notes in Computational Science and Engineering,$x2197-7100 ;$v148 311 08$aPrint version: Iske, Armin Modeling, Simulation and Optimization of Fluid Dynamic Applications Cham : Springer,c2024 9783031451577 327 $a1. Lower Bounds for the Advection-Hyperdiffusion Equation -- 2. Modeling and Simulation of Parabolic Trough Collectors using Nanofluids -- 3. Adaptive DG Methods for 1D unsteady Convection-Diffusion Problems on a Moving Mesh -- 4. Anisotropic Kernels for Particle Flow Simulation -- 5. An Error-Based Low-Rank Correction for Pressure Schur Complement Preconditioners -- 6. Radon-based Image Reconstruction for MPI using a continuously rotating FFL -- 7. Numerical Simulation of an idealized coupled Ocean-Atmosphere Climate Model -- 8. Application of p-Laplacian relaxed steepest Descent to Shape Optimizations in two-phase Flows -- 9. Computing High-Order p-Harmonic Descent Directions and Their Limits in Shape Optimization. 330 $aThis book describes recent collaborations combining the expertise of applied mathematicians, engineers and geophysicists within a research training group (RTG) on "Modeling, Simulation and Optimization of Fluid Dynamic Applications?, funded by the Deutsche Forschungsgemeinschaft (DFG). The focus is on mathematical modeling, adaptive discretization, approximation strategies and shape optimization with PDEs. The balanced research program is based on the guiding principle that mathematics drives applications and is inspired by applications. With this leitmotif the RTG advances research in Modeling, Simulation and Optimization by an interdisciplinary approach, i.e., to stimulate fundamental education and research by highly complex applications and at the simultaneously transfer tailored mathematical methods to applied sciences. The reported research involves nine projects and addresses challenging fluid dynamic problems inspired by applied sciences, such as climate research & meteorology, energy, aerospace & marine engineering, or medicine. More fundamental research concerning analysis, approximation and numerics is also covered. The material represents a successful attempt to exchange research paradigms between different disciplines and thus displays a modern approach to basic research into scientifically and societally relevant contemporary problems. 410 0$aLecture Notes in Computational Science and Engineering,$x2197-7100 ;$v148 606 $aMathematics$xData processing 606 $aComputational Science and Engineering 606 $aComputational Mathematics and Numerical Analysis 615 0$aMathematics$xData processing. 615 14$aComputational Science and Engineering. 615 24$aComputational Mathematics and Numerical Analysis. 676 $a003.3 700 $aIske$b Armin$0768209 701 $aRung$b Thomas$01460863 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910770279203321 996 $aModeling, Simulation and Optimization of Fluid Dynamic Applications$93660810 997 $aUNINA