Balbi_2022

Workflow information

  • Documentation page:

  • Version: 1.0

  • Date of record creation: 2024-12-03

  • Date of upload to firebench: 2024-12-03

  • Version/tag/commit firebench: 0.3.1a0

Configuration

  • Rate of spread model: Rothermel using firebench.ros_models.Balbi_2022_fixed_SFIRE implementation.

  • Number of point Sobol: 2^10

Specific inputs

  • The environmental variables chosen for this test are:

    • WIND_SPEED from -15 m s-1 to 15 m s-1,

    • SLOPE_ANGLE from -45 deg to 45 deg,

    • FUEL_MOISTURE_CONTENT from 1% to 50%.

  • Default values are used for optional inputs.

Hardware/software description

  • Apple M2, macOS 14.7.1

  • Python 3.10.8

Results

Fig.1 shows the execution time aggregated for all fuel classes (total) and for each fuel class. Minor discrepancies can be observed across fuel categories, mostly due to differences in the average number of iterations needed to converge. Overall, the performance is very similar for each fuel category, and a mean execution time of 19.11 \(\mu\)s over 106,496 samples.

blockdiagram

Fig. 1 : Execution time boxplot for Balbi 2022 rate of spread model using Anderson13 fuel model. Fliers points not shown on the figure.

Data

  • path to data:

  • 01_generate_data.py: f239568a63427ebb83fb00cfa955088e2b1d35abdb063794b08303f4a7cdcef8

  • 02_plot_data.py: 3252272615d568451b75cc700b6afd6b3b939904fe370cb3f4dd6fdd8129caec

  • 03_create_record.py: cf7544abadcf6ccd0497e11a87e674d594c1500fe3c212e76177650372c6ba0f

  • firebench.log: d5104db25bf477348f8da4dd1f520a9c48a6ecd329c274478e7d45f56db9c683

  • output_data.h5: 75673400b6ae742a9b5e11ddd7340e68e216f872057c638f899d9cd0afc05e1f

  • efficiency_box.png: 6cdbb667bfb4a345c5f7597104d9db17af1432e9b061c404a8496c159f8a8552