PyFR Symposium 2020 Addin ing Mult ltiphase Capabili lities to - - PowerPoint PPT Presentation
PyFR Symposium 2020 Addin ing Mult ltiphase Capabili lities to to PyF yFR Xi Deng 1 , Pierre Boivin 2 , Peter Vincent 1 1. Imperial College London 2. Aix-Marseille University Contents 1. Research Background 2.Numerical Model for Reactive
Xi Deng1, Pierre Boivin2, Peter Vincent1
2.Numerical Model for Reactive Multiphase Flow
2
Multi-scale in space:
Discontinuous large scale: shock waves, shear layers, material interface Smooth small scale: turbulence, acoustic waves
Multi-scale in time:
Large scale: flow dynamics, Small scale: Detonation waves (explosion)
Multi-physics processes:
Multi-phases, combustion, phase-transition, fluid-structure interaction and so on Advanced CFD solver should at least be able to solve multi-scale and multi-physics problems, and be compatible and scalable with modern computational hardware.
3
Multi-scale
PyFR is an open-source CFD solver, which is promising for solving multi- scale and multi-physics problems.
4
Problems:
Multi-domain Multi-physics
Status of PyFR:
Based
high
flux reconstruction (FR), PyFR has great advantage
scale- resolving simulation (DNS and LES) CPU, Nvidia GPU, AMD GPU Challenging for any high order CFD solver
5
Challenging for models: Describe main physical processes without significantly increasing complexity
Challenging for numerical method: More accurate and robust
Firstly, we construct a reactive multi-phase model which can be integrated into PyFR
6
Homogeneous assumption
Advantages: This model can be solved as Navier-Stokes
Limitations: 1. Mixture pressure and temperature should be defined 2. Mechanical and thermo equilibrium assumption may not be true
7
By considering real fluid effects, the Noble-Abel Stiffened Gas (NASG) equation
8
1. Only one component may be found in liquid form, which k=1. Its corresponding vapor has index k=2 2. The heat capacity is assumed to be a constant at low temperatures. 3. The liquid is assumed to be locally absent at high temperatures, where the gaseous heat capacity is no longer be constant. These assumptions are reasonable for most cryogenic jets under subcritical condition Thus the EOS with constant Cp for real fluid: The EOS with variable Cp for idea gas:
9
We need to define the mixture P and T based on the mixture rules Mixture T for liquid Mixture P for liquid Mixture P for gas Mixture T for gas (with Newton solver )
10
Finite rate model:
(expensive and complicated)
Instead,we assume that relaxation to thermodynamic equilibrium is immediate Since total mass and energy are constant during phase transition: Using conservation law and thermochemical equilibrium condition:
11
Mixture rule for dynamic viscosity and thermal diffusion coefficient: For liquid phase, the µ and λ can be assumed to be constant and be independent of temperature, then for gas phase For diffusion velocity: where
12
Considering a chemical system of N species involving M reactions as Then the source term is calculated as where progress rate is evaluated by
13
Evaporation is yielded with the shock compression and condensation is caused due to the rarefaction expansion wave
14
Cavitation bubble will be produced with decreased pressure caused by expansion waves
15
The 12-step skeletal mechanism for H2-O2 combustion Cantera reference (plain line), and the proposed numerical solver (red dashed line):
Simulation of liquid oxygen and gaseous hydrogen rocket engine
16
Before ignition
Simulation of liquid oxygen and gaseous hydrogen rocket engine
17
After ignition
Conclusion
18
reactive multiphase has been constructed.
the fast phase transition relaxation solver and the combustion model with detailed chemistry.
involving shock wave, moving material interface, phase transition and combustion.
equation, it can be integrated into PyFR directly.
Shock-bubble interaction
19
Krypton Cp_kry=247.47 J/kg/k Cp_air=1003.5 J/kg/k
20