Rocket Launch Simulation and Analysis using RocketPy

Introduction

Imagine launching a high-power rocket, its trajectory soaring into the sky, with every detail meticulously planned and analyzed. This article will guide you through that very process using RocketPy, a cutting-edge Python library for simulating rocket flights. From setting up your rocket’s components to running simulations and visualizing data, we’ll cover each step to help you master the art of rocketry. Whether you’re a student eager to understand the dynamics of rocket launches or a seasoned engineer looking to refine your simulations, this tutorial offers practical insights and hands-on techniques to elevate your rocketry projects.

Learning Objectives

• Gain a comprehensive understanding of the RocketPy library and its capabilities for simulating rocket launches.
• Learn how to define and configure various rocket components, such as the solid motor, rocket body, fins, and parachutes.
• Perform rocket flight simulations and understand how to interpret the results.
• Use plotting libraries like Matplotlib to visualize simulation data and perform Fourier analysis.
• Identify and resolve common issues that may arise during the simulation process.

This article was published as a part of the Data Science Blogathon.

What is RocketPy?

RocketPy is a Python library designed for simulating and analyzing high-power rocket flights. It provides a comprehensive toolkit for modeling rocket components, such as solid motors, fins, and parachutes, and for simulating their behavior during launch and flight. With RocketPy, users can define rocket parameters, perform detailed simulations, and visualize results through plots and data exports. It’s an invaluable resource for students, engineers, and enthusiasts looking to understand and predict rocket performance with precision and ease.

Download Required Data Files

To get started, download the essential data files needed for our simulation. Execute the following commands to obtain these files:

!pip install rocketpy
!curl -o NACA0012-radians.csv https://raw.githubusercontent.com/RocketPy-Team/RocketPy/master/data/calisto/NACA0012-radians.csv
!curl -o Cesaroni_M1670.eng https://raw.githubusercontent.com/RocketPy-Team/RocketPy/master/data/motors/Cesaroni_M1670.eng
!curl -o powerOffDragCurve.csv https://raw.githubusercontent.com/RocketPy-Team/RocketPy/master/data/calisto/powerOffDragCurve.csv
!curl -o powerOnDragCurve.csv https://raw.githubusercontent.com/RocketPy-Team/RocketPy/master/data/calisto/powerOnDragCurve.csv

Import Necessary Libraries and Initialize Environment

Start by importing the required libraries and setting up the environment. This involves defining the location and atmospheric conditions:

from rocketpy import Environment, SolidMotor, Rocket, Flight
import datetime

# Initialize environment
env = Environment(latitude=32.990254, longitude=-106.974998, elevation=1400)
tomorrow = datetime.date.today() + datetime.timedelta(days=1)
env.set_date((tomorrow.year, tomorrow.month, tomorrow.day, 12))
env.set_atmospheric_model(type="Forecast", file="GFS")
env.info()

The Environment class is used to set the geographical location and atmospheric conditions. This information is crucial for accurate simulation results. 

Understanding Solid Motor Characteristics

Define the motor parameters, including thrust profiles, dimensions, and physical properties:

Pro75M1670 = SolidMotor(
    thrust_source="Cesaroni_M1670.eng",
    dry_mass=1.815,
    dry_inertia=(0.125, 0.125, 0.002),
    nozzle_radius=33 / 1000,
    grain_number=5,
    grain_density=1815,
    grain_outer_radius=33 / 1000,
    grain_initial_inner_radius=15 / 1000,
    grain_initial_height=120 / 1000,
    grain_separation=5 / 1000,
    grains_center_of_mass_position=0.397,
    center_of_dry_mass_position=0.317,
    nozzle_position=0,
    burn_time=3.9,
    throat_radius=11 / 1000,
    coordinate_system_orientation="nozzle_to_combustion_chamber",
)
Pro75M1670.info()

The SolidMotor class defines the motor’s physical properties and performance characteristics, which are vital for understanding its contribution to the rocket’s flight.  

Configuring Rocket Dimensions and Components

Define the rocket’s parameters, including its dimensions, components, and motor integration:

calisto = Rocket(
    radius=127 / 2000,
    mass=14.426,
    inertia=(6.321, 6.321, 0.034),
    power_off_drag="powerOffDragCurve.csv",
    power_on_drag="powerOnDragCurve.csv",
    center_of_mass_without_motor=0,
    coordinate_system_orientation="tail_to_nose",
)

calisto.set_rail_buttons(upper_button_position=0.0818, lower_button_position=-0.618, angular_position=45)
calisto.add_motor(Pro75M1670, position=-1.255)
calisto.add_nose(length=0.55829, kind="vonKarman", position=1.278)
calisto.add_trapezoidal_fins(n=4, root_chord=0.120, tip_chord=0.060, span=0.110, position=-1.04956, cant_angle=0.5, airfoil=("NACA0012-radians.csv", "radians"))
calisto.add_tail(top_radius=0.0635, bottom_radius=0.0435, length=0.060, position=-1.194656)

calisto.all_info()

The Rocket class is used to define the rocket’s structural components, such as fins and nose cones. The proper definition of these components affects the rocket’s stability and aerodynamics.  

Mass Plots

Adding and Configuring Parachutes for Safe Recovery

Add parachutes to ensure a safe recovery of the rocket:

Main = calisto.add_parachute(
    "Main",
    cd_s=10.0,
    trigger=800,
    sampling_rate=105,
    lag=1.5,
    noise=(0, 8.3, 0.5),
)

Drogue = calisto.add_parachute(
    "Drogue",
    cd_s=1.0,
    trigger="apogee",
    sampling_rate=105,
    lag=1.5,
    noise=(0, 8.3, 0.5),
)

The lateral parachutes are crucial for slowing down the rocket during descent. Parameters like drag coefficient and deployment conditions ensure a safe landing.

Running and Analyzing Your Rocket Flight Simulation

Run the flight simulation with the defined rocket and environment:

test_flight = Flight(
    rocket=calisto, environment=env, rail_length=5.2, inclination=85, heading=0
)
test_flight.all_info()

The Flight class simulates the rocket’s trajectory based on the defined parameters. It provides detailed information about the flight.  

Export the Flight Trajectory to KML

Export the flight trajectory for visualization in tools like Google Earth:

test_flight.export_kml(file_name="trajectory.kml", extrude=True, altitude_mode="relative_to_ground")

Exporting to KML allows you to visualize the rocket’s path and analyze its flight characteristics.

Perform Analysis and Plotting

Conduct further analysis and visualize the results:

 from rocketpy.utilities import apogee_by_mass, liftoff_speed_by_mass
import numpy as np
import matplotlib.pyplot as plt

# Plot Apogee and Liftoff Speed by Mass
apogee_by_mass(flight=test_flight, min_mass=5, max_mass=20, points=10, plot=True)
liftoff_speed_by_mass(flight=test_flight, min_mass=5, max_mass=20, points=10, plot=True)

# Simulate and analyze the first 5 seconds of flight
flight = Flight(
    rocket=calisto,
    environment=env,
    rail_length=5.2,
    inclination=90,
    heading=0,
    max_time_step=0.01,
    max_time=5,
)

# Perform a Fourier Analysis
Fs = 100.0
Ts = 1.0 / Fs
t = np.arange(1, 400, Ts)  # time vector
y = flight.attitude_angle(t) - np.mean(flight.attitude_angle(t))
n = len(y)  # length of the signal
k = np.arange(n)
T = n / Fs
frq = k / T  # two sides frequency range
frq = frq[range(n // 2)]  # one side frequency range
Y = np.fft.fft(y) / n  # fft computing and normalization
Y = Y[range(n // 2)]

# Create the plot
fig, ax = plt.subplots(2, 1)
ax[0].plot(t, y)
ax[0].set_xlabel("Time")
ax[0].set_ylabel("Signal")
ax[0].set_xlim((0, 5))
ax[0].grid()
ax[1].plot(frq, abs(Y), "r")  # plotting the spectrum
ax[1].set_xlabel("Freq (Hz)")
ax[1].set_ylabel("|Y(freq)|")
ax[1].set_xlim((0, 5))
ax[1].grid()
plt.subplots_adjust(hspace=0.5)
plt.show()

The analysis and plotting section helps in understanding the rocket’s performance and dynamics through visualizations like apogee by mass, liftoff speed by mass, and Fourier analysis of the attitude angle.

Conclusion

RocketPy gives a comprehensive system for mimicking and analyzing rocket flights. By taking after this directly, you’ll set up reenactments, analyze the comes about, and visualize the information successfully. Whether you’re a specialist or a proficient, RocketPy makes a difference in accomplishing your rocketry objectives.

Key Takeaways

• The article provides a full walkthrough of the rocket simulation process using RocketPy, from initial setup to result analysis.
• Perusers will pick up hands-on encounters with Python code bits, empowering them to apply hypothetical information to down-to-earth rocket reenactments.
• Understanding the parts of different rocket components and their setup is significant for precise reenactments and fruitful rocket dispatches.
• Visualizing reenactment information makes a difference in a way better understanding of the rocket’s execution and flow, making complex information more available.
• The article addresses common issues and their solutions, and provides additional resources for advanced learning and community support.

Frequently Asked Questions

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Soumyadarshani Dash

I'm Soumyadarshani Dash, and I'm embarking on an exhilarating journey of exploration within the captivating realm of Data Science. As a dedicated graduate student with a Bachelor's degree in Commerce (B.Com), I have discovered my passion for the enthralling world of data-driven insights.

My dedication to continuous improvement has garnered me a 5⭐ rating on HackerRank, along with accolades from Microsoft. I've also completed courses on esteemed platforms like Great Learning and Simplilearn. As a proud recipient of a virtual internship with TATA through Forage, I'm committed to the pursuit of technical excellence.

Frequently immersed in the intricacies of complex datasets, I take pleasure in crafting algorithms and pioneering inventive solutions. I invite you to connect with me on LinkedIn as we navigate the data-driven universe together!