Usage

[[TODO: Walk through an example of how to use the library to design and use a wing.]]

Developing models

[[TODO: use the paraglider state dynamics to explain how to use the library by working backwards from the state dynamics until you get to component models.]]

Hierarchy

State dynamics models are interfaces to system dynamics models, which in turn are built from component models.

For example, the hierarchy to build up a state dynamics model for a paraglider:

• StateDynamics

  • SystemDynamics

    • Wing

      • Foil

        • FoilLayout

        • FoilSections

          • Profiles

          • Coefficients

        • FoilAerodynamics

      • LineGeometry

    • Harness

Running simulations

[[TODO: elaborate]]

"""Example simulation using a pre-built paraglider model."""

import pfh.glidersim as gsim
import scipy.interpolate


# Component models: use a pre-built wing and add a suitable harness
wing = gsim.extras.wings.niviuk_hook3(size=23, verbose=False)
harness = gsim.paraglider_harness.Spherical(
    mass=75,
    z_riser=0.5,
    S=0.55,
    CD=0.8,
    kappa_w=0.1,
)

# The system dynamics model provides the physical accelerations
paraglider = gsim.paraglider.ParagliderSystemDynamics6a(wing, harness)

# Build a control input sequence for right brake using linear interpolation:
# the input is 0 until t=3, increases to 1 over t=3..5, holds at 1 until t=22,
# decreases to zero over t=22..23, and holds at 0 indefinitely.
delta_br = scipy.interpolate.interp1d(
    [0, 3, 5, 22, 23],  # times
    [0, 0, 1, 1, 0],  # percentages
    fill_value=0,
    bounds_error=False,
)

# Inputs to the state dynamics are either constants or functions of time `t`
sim_parameters = {
    "delta_a": 0.0,
    "delta_bl": 0.0,
    "delta_br": delta_br,
    "delta_w": 0.0,
    "rho_air": 1.225,
    "v_W2e": (0, 0, 0),  # Uniform global wind velocity
}

# The state dynamics model provides the state derivatives
model = gsim.simulator.ParagliderStateDynamics6a(paraglider, **sim_parameters)

# Setup and run the simulation
state0 = model.starting_equilibrium()  # Start the simulation at equilibrium
dt = 0.5  # Record the state every 0.5 seconds
T = 25  # Run for 25 seconds
times, states = gsim.simulator.simulate(model, state0, dt=dt, T=T)

# 3D plot: position over time
points = gsim.extras.simulation.sample_paraglider_positions(model, states, times)
gsim.extras.plots.plot_3d_simulation_path(**points)

A paraglider simulation with a short right turn, marking the relative positions of the wing and payload every 0.5 seconds.