The Enhanced Projectile Motion Model
Atmospheric Density Modeled with Observed Data
computational physics, data modeling, projectile motion, atmospheric drag
Executive Summary
Using actual observational data, this research adds the mechanics of atmospheric drag to the traditional projectile motion model. The U.S. Standard Atmosphere 1976 (NASA) provided the atmospheric density data, which covers elevations from sea level up to 50 km—a range that easily encompasses conventional projectile trajectories.
Physically implausible conditions are assumed by the ideal projectile model. The simulation generates trajectories that are more in line with reality by modeling air density as a function of altitude and including it into the drag force calculation. The entire process is documented in this report, including the sourcing and cleaning of data, the whole methodology of creation of the atmospheric density model to the creation of the final improved simulation.
The findings demonstrate that computational modeling and data science methods can enhance a basic physical model.
Purpose of This Project
This project was started as a self-practice exercise in computational data modeling, specifically integrating standard physics with real-world observational data to enhance an idealized model. This was a conscious step toward numerical mathematical modeling in Python, as my prior work had been on data science.
The projectile motion problem was an obvious place to start because it is theoretically well-understood, making it simple to gauge how much the simulation improves with the addition of real-world physics. One of the easiest modifications to the ideal model and a useful starting point for this type of modeling is drag force, which is directly dependent on atmospheric density.