Source code and data for the paper Data Assimilation in Large Prandtl Rayleigh-Benard Convection from Thermal Measurements by A. Farhat, N. E. Glatt-Holtz, V. R. Martinez, S. A. McQuarrie, and J. P. Whitehead.

BibTeX

@article{FGMMW2020RBDAfromThermal,
    title     = {Data Assimilation in Large {P}randtl {R}ayleigh-{B}{\'e}nard Convection from Thermal Measurements},
    author    = {Farhat, A. and Glatt-Holtz, N. E. and Martinez, V. R. and McQuarrie, S. A. and Whitehead, J. P.},
    journal   = {SIAM Journal on Applied Dynamical Systems},
    volume    = {19},
    number    = {1},
    pages     = {510--540},
    year      = {2020},
    publisher = {SIAM}
}

Contents

Disclaimer: most scripts in this repository require the dedalus package; see the dedalus install guide. A quick way to test that your dedalus installation is working properly for this repository is to run python3 data_assimilation.py --test.

Code

• base_simulator.py: defines a BaseSimulator class base for managing data storage locations, simulation information, and other housekeeping items.

• boussinesq2d.py: defines classes that extend BaseSimulator and set up the simulation with dedalus. The actual simulation code is in BoussinesqDataAssimilation2D.setup() and BoussinesqDataAssimilation2D.simulate(); the class also includes visualization routines for post-processing.

• data_assimilation.py: script for parsing arguments and starting a simulation with boussinesq2d.py.

• merge.py: script for combining simulation data and calling visualization routines.

• plot_tools.py: visualization routines for comparing results from multiple simulations.

• plot_mu_ra_relation.py: a simple curve-fitting routine for one of the figures.

• plot_all.sh and plot_all_p3.sh: commands for figure creation with merge.py, plot_tools.py, and plot_mu_ra_relation.py.

Data Files

• default.h5: an initial data set for testing.

• infinite_prandtl/: numerical simulation results for experiments in which Pr is infinite.

• finite_prandtl/: numerical simulation results for experiments in which Pr is finite, but large.

• hybrid_prandtl/: numerical simulation results for experiments in which the data comes from a model with finite Pr, but the assimilating model assumes Pr to be infinite.

• old_data/: numerical simulation results from a previous version of the paper.

Figures

• figures/ folder containing the actual figures used in the paper.

• .mplstyle: matplotlib configuration file.