A Python framework for developing parallelized Computational Fluid Dynamics software to solve the hyperbolic 2D Euler equations on distributed, multi-block structured grids.

Last update: Nov 22, 2022

Overview

pyHype: Computational Fluid Dynamics in Python

pyHype is a Python framework for developing parallelized Computational Fluid Dynamics software to solve the hyperbolic 2D Euler equations on distributed, multi-block structured grids. It can be used as a solver to generate numerical predictions of 2D inviscid flow fields, or as a platform for developing new CFD techniques and methods. Contributions are welcome! pyHype is in early stages of development, I will be updating it regularly, along with its documentation.

The core idea behind pyHype is flexibility and modularity. pyHype offers a plug-n-play approach to CFD software, where every component of the CFD pipeline is modelled as a class with a set interface that allows it to communicate and interact with other components. This enables easy development of new components, since the developer does not have to worry about interfacing with other components. For example, if a developer is interested in developing a new approximate riemann solver technique, they only need to provide the implementation of the FluxFunction abstract class, without having to worry about how the rest of the code works in detail.

NEW: Geometry not alligned with the cartesian axes is now supported!
NEW: 60% efficiency improvement!
COMING UP: Examples of simulations on various airfoil geometries, and a presentation of the newly added mesh optimization techniques.
COMING UP: Examples of simulations on multi-block meshes.

Explosion Simulation

Here is an example of an explosion simulation performed on one block. The simulation was performed with the following:

600 x 1200 cartesian grid
Roe approximate riemann solver
Venkatakrishnan flux limiter
Piecewise-Linear second order reconstruction
Green-Gauss gradient method
RK4 time stepping with CFL=0.8
Reflection boundary conditions

The example in given in the file examples/explosion.py. The file is as follows:

from pyHype.solvers import Euler2D

# Solver settings
settings = {'problem_type':             'explosion',
            'interface_interpolation':  'arithmetic_average',
            'reconstruction_type':      'conservative',
            'upwind_mode':              'primitive',
            'write_solution':           False,
            'write_solution_mode':      'every_n_timesteps',
            'write_solution_name':      'nozzle',
            'write_every_n_timesteps':  40,
            'CFL':                      0.8,
            't_final':                  0.07,
            'realplot':                 False,
            'profile':                  True,
            'gamma':                    1.4,
            'rho_inf':                  1.0,
            'a_inf':                    343.0,
            'R':                        287.0,
            'nx':                       600,
            'ny':                       1200,
            'nghost':                   1,
            'mesh_name':                'chamber'
            }

# Create solver
exp = Euler2D(fvm='SecondOrderPWL',
              gradient='GreenGauss',
              flux_function='Roe',
              limiter='Venkatakrishnan',
              integrator='RK4',
              settings=settings)

# Solve
exp.solve()

Double Mach Reflection (DMR)

Here is an example of a Mach 10 DMR simulation performed on five blocks. The simulation was performed with the following:

500 x 500 cells per block
HLLL flux function
Venkatakrishnan flux limiter
Piecewise-Linear second order reconstruction
Green-Gauss gradient method
Strong-Stability-Preserving (SSP)-RK2 time stepping with CFL=0.4

The example in given in the file examples/dmr/dmr.py. The file is as follows:

from pyHype.solvers import Euler2D

# Solver settings
settings = {'problem_type':             'mach_reflection',
            'interface_interpolation':  'arithmetic_average',
            'reconstruction_type':      'conservative',
            'upwind_mode':              'conservative',
            'write_solution':           False,
            'write_solution_mode':      'every_n_timesteps',
            'write_solution_name':      'machref',
            'write_every_n_timesteps':  20,
            'plot_every':               10,
            'CFL':                      0.4,
            't_final':                  0.25,
            'realplot':                 True,
            'profile':                  False,
            'gamma':                    1.4,
            'rho_inf':                  1.0,
            'a_inf':                    1.0,
            'R':                        287.0,
            'nx':                       50,
            'ny':                       50,
            'nghost':                   1,
            'mesh_name':                'wedge_35_four_block',
            'BC_inlet_west_rho':        8.0,
            'BC_inlet_west_u':          8.25,
            'BC_inlet_west_v':          0.0,
            'BC_inlet_west_p':          116.5,
            }

# Create solver
exp = Euler2D(fvm='SecondOrderPWL',
              gradient='GreenGauss',
              flux_function='HLLL',
              limiter='Venkatakrishnan',
              integrator='RK2',
              settings=settings)

# Solve
exp.solve()

High Speed Jet

Here is an example of high-speed jet simulation performed on 5 blocks. The simulation was performed with the following:

Mach 2 flow
100 x 1000 cell blocks
HLLL flux function
Venkatakrishnan flux limiter
Piecewise-Linear second order reconstruction
Green-Gauss gradient method
RK2 time stepping with CFL=0.4

The example in given in the file examples/jet/jet.py. The file is as follows:

from pyHype.solvers import Euler2D

# Solver settings
settings = {'problem_type':             'subsonic_rest',
            'interface_interpolation':  'arithmetic_average',
            'reconstruction_type':      'primitive',
            'upwind_mode':              'conservative',
            'write_solution':           True,
            'write_solution_mode':      'every_n_timesteps',
            'write_solution_name':      'kvi',
            'write_every_n_timesteps':  20,
            'plot_every':               10,
            'CFL':                      0.4,
            't_final':                  25.0,
            'realplot':                 False,
            'profile':                  False,
            'gamma':                    1.4,
            'rho_inf':                  1.0,
            'a_inf':                    1.0,
            'R':                        287.0,
            'nx':                       1000,
            'ny':                       100,
            'nghost':                   1,
            'mesh_name':                'jet',
            'BC_inlet_west_rho':        1.0,
            'BC_inlet_west_u':          0.25,
            'BC_inlet_west_v':          0.0,
            'BC_inlet_west_p':          2.0 / 1.4,
            }

# Create solver
exp = Euler2D(fvm='SecondOrderPWL',
              gradient='GreenGauss',
              flux_function='HLLL',
              limiter='Venkatakrishnan',
              integrator='RK2',
              settings=settings)

# Solve
exp.solve()

Mach Number:

Density:

Current work

Integrate airfoil meshing and mesh optimization using elliptic PDEs
Compile gradient and reconstruction calculations with numba
Integrate PyTecPlot to use for writing solution files and plotting
Implement riemann-invariant-based boundary conditions
Implement subsonic and supersonic inlet and outlet boundary conditions
Implement connectivity algorithms for calculating block connectivity and neighbor-finding
Create a fully documented simple example to explain usage
Documentation!!

Major future work

Use MPI to distrubute computation to multiple processors
Adaptive mesh refinement (maybe with Machine Learning :))
Interactive gui for mesh design
Advanced interactive plotting

A Python framework for developing parallelized Computational Fluid Dynamics software to solve the hyperbolic 2D Euler equations on distributed, multi-block structured grids.

Related tags

Overview

pyHype: Computational Fluid Dynamics in Python

Explosion Simulation

Double Mach Reflection (DMR)

High Speed Jet

Current work

Major future work

Owner

Mohamed Khalil

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