Bio


I am Lin Fu 傅林, graduated from Technical University of Munich as a Ph.D. My research topics are multidisciplinary. My first major concern is to propose the novel high-order TENO schemes (targeted ENO) for hyperbolic conservation laws and the corresponding linear, nonlinear dissipation and dispersion control approaches. Secondly, I develop numerical methods for incompressible and compressible multi-phase simulations including the complex interface tracking algorithms and the high-order discretization algorithms. Thirdly, I develop novel smoothed-particle hydrodynamics (SPH) and Centroidal Voronoi Particle (CVP) based load-balancing method for high-performance parallel computing. Moreover, a general large-scale parallel framework is proposed for adaptive smoothing-length particle simulations, e.g. the SPH method. At last, I propose novel SPH and CVP based domain decomposition method for general-purpose isotropic and anisotropic unstructured mesh generation.

Honors & Awards


  • National scholarship, Chinese Ministry of Education (2008-2009)
  • Summa cum laude (passed with highest distinction) of Ph.D thesis, Technical University of Munich (2017-10-05)
  • CTR postdoctoral fellowship, Center for Turbulence Research, Stanford University (2018-2020)

Professional Education


  • Ph.D, Technical University of Munich, Fluid Mechanics (2017)
  • Master of Science, Northwestern Polytechnical University, Fluid Mechanics (2013)
  • Bachelor of Science, Northwestern Polytechnical University, Engineering (2010)

Current Research and Scholarly Interests


Turbulence and modeling
• Incompressible and compressible wall-bounded turbulence.
• Isotropic turbulence and shock-turbulence interaction.
• Subgrid-scale (SGS) model.
• Wall-modeled large-eddy simulation.
• Shock-boundary-layer interaction.
• Shock-induced transition.
• Flow stability.
High-order numerical scheme for conservation laws
• Novel high-order TENO schemes (targeted ENO) for hyperbolic conservation laws.
• Low-dissipation low-dispersion optimal finite-difference schemes.
• Novel implicit large eddy simulation(ILES) model.
• New TENO reconstruction framework.
Interface tracking method for multi-phase flow
• Multi-scale and multi-resolution simulations.
• Low-dissipation numerical approach for level-set based interface advection.
• Explicit reinitialization and extending algorithm for level-set function.
• Compressible multi-phase flow simulations based on sharp interface method.
Smoothed-particle hydrodynamics (SPH) method
• Numerical discretization algorithms for SPH method.
• Large-scale simulation framework for SPH method.
Partitioning and domain decomposition methods
• Novel physics-driven SPH based partitioning method for Adaptive Mesh Refinement (AMR) mesh.
• Novel Centroidal Voronoi Particle (CVP) based domain decomposition method.
• Large-scale parallelization algorithms for the partitioning method.
Unstructured mesh generation
• Novel SPH based isotropic and anisotropic unstructured mesh generation.
• Novel CVP based mesh generation.
• Multi-material/regional unstructured mesh generation.
• Partitioning and parallel algorithms for adaptive unstructured mesh.
RANS methodology for aerodynamics
• CPU and GPU based parallel multi-block flow solvers for complex geometries, e.g. aircraft.
• High-resolution numerical methods, e.g. Riemann solver and reconstruction schemes.
• State-of-the-art turbulence models for engineering problems.

All Publications


  • A Lagrangian Inertial Centroidal Voronoi Particle method for dynamic load balancing in particle-based simulations Computer Physics Communications Ji, Z., Fu, L., Hu, X., Adams, N. 2019; 239: 53-63
  • Improved Five- and Six-Point Targeted Essentially Nonoscillatory Schemes with Adaptive Dissipation AIAA Journal Fu, L., Hu, X., Adams, N. 2019; 57 (3): 1143-1158

    View details for DOI 10.2514/1.J057370

  • A new multi-resolution parallel framework for SPH Computer Methods in Applied Mechanics and Engineering Ji, Z., Fu, L., Hu, X., Adams, N. 2019; 346: 1156-1178
  • A low-dissipation finite-volume method based on a new TENO shock-capturing scheme Computer Physics Communications Fu, L. 2019; 235: 25-39
  • High-order low-dissipation targeted ENO schemes for ideal magnetohydrodynamics Journal of Scientific Computing Lin, F., Qi, T. 2019
  • Detonation Simulations with a Fifth-Order TENO Scheme Communications in Computational Physics Dong, H., Fu, L., Zhang, F., Liu, Y., Liu, J. 2019; 25 (5)
  • Parallel fast-neighbor-searching and communication strategy for particle-based methods Engineering Computations Fu, L., Ji, Z., Hu, X., Adams, N. 2019

    View details for DOI 10.1108/EC-05-2018-0226

  • A hybrid method with TENO based discontinuity indicator for hyperbolic conservation laws Communications in Computational Physics Fu, L. 2019; 26: 973-1007
  • A very-high-order TENO scheme for all-speed gas dynamics and turbulence Computer Physics Communications Fu, L. 2019
  • An optimal particle setup method with Centroidal Voronoi Particle dynamics Computer Physics Communications Fu, L., Ji, Z. 2019; 234: 72-92
  • A targeted ENO scheme as implicit model for turbulent and genuine subgrid scales Communications in Computational Physics Fu, L., Hu, X., Adams, N. 2019; 26: 311-345
  • An isotropic unstructured mesh generation method based on a fluid relaxation analogy Computer Methods in Applied Mechanics and Engineering Fu, L., Han, L., Hu, X., Adams, N. 2019; 350C: 396-431
  • A new class of adaptive high-order targeted ENO schemes for hyperbolic conservation laws Journal of Computational Physics Fu, L., Hu, X., Adams, N. 2018; 374: 724-751
  • A physics-motivated Centroidal Voronoi Particle domain decomposition method JOURNAL OF COMPUTATIONAL PHYSICS Fu, L., Hu, X. Y., Adams, N. A. 2017; 335: 718-735
  • Single-step reinitialization and extending algorithms for level-set based multi-phase flow simulations Computer Physics Communications Fu, L., Hu, X., Adams, N. 2017; 221: 63-80
  • A novel partitioning method for block-structured adaptive meshes Journal of Computational Physics Fu, L., Litvinov, S., Hu, X., Adams, N. 2017; 341: 447-473
  • Targeted ENO schemes with tailored resolution property for hyperbolic conservation laws Journal of Computational Physics Fu, L., Hu, X., Adams, N. 2017; 349: 97-121
  • A family of high-order targeted ENO schemes for compressible-fluid simulations JOURNAL OF COMPUTATIONAL PHYSICS Fu, L., Hu, X. Y., Adams, N. A. 2016; 305: 333-359
  • A multi-block viscous flow solver based on GPU parallel methodology COMPUTERS & FLUIDS Fu, L., Gao, Z., Xu, K., Xu, F. 2014; 95: 19-39