The idea of multi-level improves the convergence from where you are to what you dream.
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- Ph.D., Applied Mathematics, The Hong Kong University of Science and Technology (HKUST), Hong Kong, 2017
- MSc, Applied Mathematics, Chang’an University, China, 2010
- BSc, Information and Computing Science, Jilin University, China, 2007
Honors & Awards
- Best Paper Award, HPCChina2017 (2nd Author)
- 1st Prize for the 2017 East Asia SIAM Student Paper Competition (1st Author)
Li Luo's research interest include Scalable Parallel Algorithms, Computational Fluid Dynamics (CFD).
Discuss with the top class faculty, work with the world-class equipment, and enjoy the most diversified culture on the planet.
Why did you choose your field of research?
Simulation of large flow problems is computationally demanding, such as the two-phase flow and the blood flow in realistic cases. The use of supercomputers and highly scalable parallel algorithms is necessary.
P2Pflow: a Parallel two-Phase flow solver
P2Pflow is a parallel finite element solver for incompressible two-phase flow problems on 3D unstructured mesh. The solver is scalable on supercomputers such as Tianhe2 and Shaheen2 with 10,000+ cores. P2Pflow consists of the following two modules:
- Module 1. A semi-implicit linear solver for the phase-field model with Cahn-Hilliard-Navier-Stokes equations, used for the simulation of liquid-gas-solid interaction.
- Module 2. A fully implicit nonlinear solver for the two-phase flow problem in porous media, used for oil reservoir simulation. A two-level Newton-Krylov-Schwarz method is used for solving the algebraic system arising from the discontinuous Galerkin discretization.