MAPLEAF: Modular Aerospace Prediction Lab for Engines and Aero Forces

6-DOF Rocket Flight Simulation Framework

Install:

pip install MAPLEAF

Usage:

Running a Simulation

mapleaf path/to/SimDefinitionFile.mapleaf

Example config files are in the ./MAPLEAF/Examples/Simulations folder

Simulation Definition Files

More info, and descriptions of all possible options in: SimDefinitionTemplate.mapleaf

Format is a simple key-value syntax similar to JSON or YAML.
Dictionaries can be nested arbitrarily deeply and are brace-delimited.
Keys and values in a dictionary are separated by the first whitespace in their line
No multiline values

Example segment of a Sim Definition file:

SimControl{
  timeDiscretization    RK45Adaptive

  TimeStepAdaptation{
    controller          PID
    PID.coefficients    -0.01 -0.001 0
    targetError         0.0001
  }
}

Code folding is very helpful in maintaining an overview of these files:

The possible top level dictionaries are 'Monte Carlo', 'SimControl', 'Environment', and 'Rocket'. Of these, only the 'Rocket' dictionary is strictly required to run a simulation, and defines the rocket's initial position/velocity and the inertial/aerodynamic/control models used to simulate it.
The rocket is defined by nested subdictionaries, where the first level of nesting defines the rocket's stage(s) and the second level defines the rocket component(s) in each stage:

Default values from the defaultConfigValues dictionary in MAPLEAF/IO/SimDefinition.py will fill in when keys are undefined. Default values mostly match those in the SimDefinitionTemplate.mapleaf file.

Simulation Outputs

Depending on the options specified in the SimControl dictionary, MAPLEAF simulations can output:

• Detailed tabulated simulation position, component force, aerodynamic coefficient and control logs (see SimControl.loggingLevel):

• Flight animations (see SimControl.plot)
  

• Flight path visualizations (see SimControl.plot)
  

• Plots of any logged parameter (see SimControl.plot)
  

Monte Carlo Simulations

Monte Carlo simulations propagate uncertainties in simulation inputs through to simulation outputs.
Any scalar or vector parameter in simulation definition files can be made probabilistic by adding a second parameter with _stdDev appended to the name:

To execute a batch run of this now-probabilistic simulation, create the top-level 'Monte Carlo' dictionary (see SimDefinitionTemplate.mapleaf)

From that, you can obtain distributions of outputs like flight paths or landing locations:

Developers

To extend MAPLEAF, re-use its libraries or otherwise work with the code, have a look at README_Dev.md the code/api documentation website