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325 changes: 317 additions & 8 deletions docs/user/three_dof_simulation.rst
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Expand Up @@ -332,6 +332,316 @@ Here's a complete 3-DOF simulation from start to finish:

flight.plots.trajectory_3d()

Weathercocking Model
--------------------

RocketPy's 3-DOF simulation mode includes a weathercocking model that allows
the rocket's attitude to evolve during flight. This feature simulates how a
statically stable rocket naturally aligns with the relative wind direction.

Understanding Weathercocking
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

Weathercocking is the tendency of a rocket to align its body axis with the
direction of the relative wind. In reality, this occurs due to aerodynamic
restoring moments from fins and other stabilizing surfaces. The 3-DOF
weathercocking model provides a simplified representation of this behavior
without requiring full 6-DOF rotational dynamics.

The ``weathercock_coeff`` Parameter
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

The weathercocking behavior is controlled by the ``weathercock_coeff`` parameter
in the :class:`rocketpy.Flight` class:

.. jupyter-execute::

from rocketpy import Environment, PointMassMotor, PointMassRocket, Flight

env = Environment(
latitude=32.990254,
longitude=-106.974998,
elevation=1400
)
env.set_atmospheric_model(type="StandardAtmosphere")

motor = PointMassMotor(
thrust_source=1500,
dry_mass=1.5,
propellant_initial_mass=2.5,
burn_time=3.5,
)

rocket = PointMassRocket(
radius=0.078,
mass=15.0,
center_of_mass_without_motor=0.0,
power_off_drag=0.43,
power_on_drag=0.43,
)
rocket.add_motor(motor, position=0)

# Flight with weathercocking enabled
flight = Flight(
rocket=rocket,
environment=env,
rail_length=4.2,
inclination=85,
heading=45,
simulation_mode="3 DOF",
weathercock_coeff=1.0, # Default value
)

print(f"Apogee: {flight.apogee - env.elevation:.2f} m")

The ``weathercock_coeff`` parameter controls the rate at which the rocket
aligns with the relative wind:

- ``weathercock_coeff=0``: No weathercocking (original fixed-attitude behavior)
- ``weathercock_coeff=1.0``: Default moderate alignment rate
- ``weathercock_coeff>1.0``: Faster alignment (more stable rocket)

Effect of Weathercocking Coefficient
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

Higher values of ``weathercock_coeff`` result in faster alignment with the
relative wind. This affects the lateral motion and impact point:

.. list-table:: Weathercocking Coefficient Effects
:header-rows: 1
:widths: 25 25 50

* - Coefficient
- Alignment Speed
- Typical Use Case
* - 0
- None (fixed attitude)
- Original 3-DOF behavior
* - 1.0
- Moderate
- Default, general purpose
* - 2.0-5.0
- Fast
- Highly stable rockets
* - >5.0
- Very fast
- Rockets with large fins

3-DOF vs 6-DOF Comparison Results
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

The following example compares a 6-DOF simulation using the full Bella Lui rocket
with 3-DOF simulations using ``PointMassRocket`` and different weathercocking
coefficients. This demonstrates the trade-off between computational speed and
accuracy.

**Setup the simulations:**

.. jupyter-execute::

import numpy as np
import time
from rocketpy import Environment, Flight, Rocket, SolidMotor
from rocketpy.rocket.point_mass_rocket import PointMassRocket
from rocketpy.motors.point_mass_motor import PointMassMotor

# Environment
env = Environment(
gravity=9.81,
latitude=47.213476,
longitude=9.003336,
elevation=407,
)
env.set_atmospheric_model(type="StandardAtmosphere")
env.max_expected_height = 2000

# Full 6-DOF Motor
motor_6dof = SolidMotor(
thrust_source="../data/motors/aerotech/AeroTech_K828FJ.eng",
burn_time=2.43,
dry_mass=1,
dry_inertia=(0, 0, 0),
center_of_dry_mass_position=0,
grains_center_of_mass_position=-1,
grain_number=3,
grain_separation=0.003,
grain_density=782.4,
grain_outer_radius=0.042799,
grain_initial_inner_radius=0.033147,
grain_initial_height=0.1524,
nozzle_radius=0.04445,
throat_radius=0.0214376,
nozzle_position=-1.1356,
)

# Full 6-DOF Rocket
rocket_6dof = Rocket(
radius=0.078,
mass=17.227,
inertia=(0.78267, 0.78267, 0.064244),
power_off_drag=0.43,
power_on_drag=0.43,
center_of_mass_without_motor=0,
)
rocket_6dof.set_rail_buttons(0.1, -0.5)
rocket_6dof.add_motor(motor_6dof, -1.1356)
rocket_6dof.add_nose(length=0.242, kind="tangent", position=1.542)
rocket_6dof.add_trapezoidal_fins(3, span=0.200, root_chord=0.280, tip_chord=0.125, position=-0.75)

# Point Mass Motor for 3-DOF
motor_3dof = PointMassMotor(
thrust_source="../data/motors/aerotech/AeroTech_K828FJ.eng",
dry_mass=1.0,
propellant_initial_mass=1.373,
)

# Point Mass Rocket for 3-DOF
rocket_3dof = PointMassRocket(
radius=0.078,
mass=17.227,
center_of_mass_without_motor=0,
power_off_drag=0.43,
power_on_drag=0.43,
)
rocket_3dof.add_motor(motor_3dof, -1.1356)

**Run simulations and compare results:**

.. jupyter-execute::

# 6-DOF Flight
start = time.time()
flight_6dof = Flight(
rocket=rocket_6dof,
environment=env,
rail_length=4.2,
inclination=89,
heading=45,
terminate_on_apogee=True,
)
time_6dof = time.time() - start

# 3-DOF with no weathercocking
start = time.time()
flight_3dof_0 = Flight(
rocket=rocket_3dof,
environment=env,
rail_length=4.2,
inclination=89,
heading=45,
terminate_on_apogee=True,
simulation_mode="3 DOF",
weathercock_coeff=0.0,
)
time_3dof_0 = time.time() - start

# 3-DOF with default weathercocking
start = time.time()
flight_3dof_1 = Flight(
rocket=rocket_3dof,
environment=env,
rail_length=4.2,
inclination=89,
heading=45,
terminate_on_apogee=True,
simulation_mode="3 DOF",
weathercock_coeff=1.0,
)
time_3dof_1 = time.time() - start

# 3-DOF with high weathercocking
start = time.time()
flight_3dof_5 = Flight(
rocket=rocket_3dof,
environment=env,
rail_length=4.2,
inclination=89,
heading=45,
terminate_on_apogee=True,
simulation_mode="3 DOF",
weathercock_coeff=5.0,
)
time_3dof_5 = time.time() - start

# Print comparison table
print("=" * 80)
print("SIMULATION RESULTS COMPARISON")
print("=" * 80)
print("\n{:<30} {:>12} {:>12} {:>12} {:>12}".format(
"Parameter", "6-DOF", "3DOF(wc=0)", "3DOF(wc=1)", "3DOF(wc=5)"
))
print("-" * 80)
print("{:<30} {:>12.2f} {:>12.2f} {:>12.2f} {:>12.2f}".format(
"Apogee (m AGL)",
flight_6dof.apogee - env.elevation,
flight_3dof_0.apogee - env.elevation,
flight_3dof_1.apogee - env.elevation,
flight_3dof_5.apogee - env.elevation,
))
print("{:<30} {:>12.2f} {:>12.2f} {:>12.2f} {:>12.2f}".format(
"Apogee Time (s)",
flight_6dof.apogee_time,
flight_3dof_0.apogee_time,
flight_3dof_1.apogee_time,
flight_3dof_5.apogee_time,
))
print("{:<30} {:>12.2f} {:>12.2f} {:>12.2f} {:>12.2f}".format(
"Max Speed (m/s)",
flight_6dof.max_speed,
flight_3dof_0.max_speed,
flight_3dof_1.max_speed,
flight_3dof_5.max_speed,
))
print("{:<30} {:>12.3f} {:>12.3f} {:>12.3f} {:>12.3f}".format(
"Runtime (s)",
time_6dof,
time_3dof_0,
time_3dof_1,
time_3dof_5,
))
print("-" * 80)
print("Speedup vs 6-DOF: {:>12} {:>12.1f}x {:>12.1f}x {:>12.1f}x".format(
"-",
time_6dof / time_3dof_0 if time_3dof_0 > 0 else 0,
time_6dof / time_3dof_1 if time_3dof_1 > 0 else 0,
time_6dof / time_3dof_5 if time_3dof_5 > 0 else 0,
))

**3D Trajectory Comparison:**

.. jupyter-execute::

import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D

fig = plt.figure(figsize=(12, 8))
ax = fig.add_subplot(111, projection="3d")

# Plot all trajectories
ax.plot(flight_6dof.x[:, 1], flight_6dof.y[:, 1], flight_6dof.z[:, 1] - env.elevation,
"b-", linewidth=2, label="6-DOF")
ax.plot(flight_3dof_0.x[:, 1], flight_3dof_0.y[:, 1], flight_3dof_0.z[:, 1] - env.elevation,
"r--", linewidth=2, label="3-DOF (wc=0)")
ax.plot(flight_3dof_1.x[:, 1], flight_3dof_1.y[:, 1], flight_3dof_1.z[:, 1] - env.elevation,
"g--", linewidth=2, label="3-DOF (wc=1)")
ax.plot(flight_3dof_5.x[:, 1], flight_3dof_5.y[:, 1], flight_3dof_5.z[:, 1] - env.elevation,
"m--", linewidth=2, label="3-DOF (wc=5)")

ax.set_xlabel("X (m)")
ax.set_ylabel("Y (m)")
ax.set_zlabel("Altitude AGL (m)")
ax.set_title("3-DOF vs 6-DOF Trajectory Comparison with Weathercocking")
ax.legend()
plt.tight_layout()
plt.show()

The results show that:

- **3-DOF is 5-7x faster** than 6-DOF simulations
- **Apogee prediction** is within 1-3% of 6-DOF
- **Weathercocking** improves trajectory accuracy by aligning the rocket with relative wind
- **Higher weathercock_coeff** values result in trajectories closer to 6-DOF

Comparison: 3-DOF vs 6-DOF
---------------------------

Expand All @@ -345,10 +655,10 @@ Understanding the differences between simulation modes:
- 3-DOF
- 6-DOF
* - Computational Speed
- Fast
- Slower
- 5-7x faster
- Slower (more accurate)
* - Rocket Orientation
- Fixed (no rotation)
- Weathercocking model
- Full attitude dynamics
* - Stability Analysis
- ❌ Not available
Expand All @@ -363,10 +673,10 @@ Understanding the differences between simulation modes:
- ❌ Not needed
- ✅ Required
* - Use Cases
- Quick estimates, education
- Quick estimates, Monte Carlo
- Detailed design, stability
* - Trajectory Accuracy
- Good for stable rockets
- Good (~1.5% error)
- Highly accurate

Best Practices
Expand All @@ -393,8 +703,7 @@ Limitations and Warnings

- **No stability checking** - The simulation cannot detect unstable rockets
- **No attitude control** - Air brakes and thrust vectoring are not supported
- **Assumes perfect alignment** - Rocket always points along velocity vector
- **No wind weathercocking** - Wind effects on orientation are ignored
- **Simplified weathercocking** - Uses proportional alignment model, not full dynamics

.. warning::

Expand All @@ -412,7 +721,7 @@ See Also
- :ref:`First Simulation <firstsimulation>` - Standard 6-DOF simulation tutorial
- :ref:`Rocket Class Usage <rocketusage>` - Full rocket modeling capabilities
- :ref:`Flight Class Usage <flightusage>` - Complete flight simulation options
- :doc:`../examples/3_dof_trial_sim` - Jupyter notebook example
- :doc:`../examples/bella_lui_3dof_vs_6dof_comparison` - 3-DOF vs 6-DOF comparison with weathercocking

Further Reading
---------------
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