Project Overview
This repository hosts a Jupyter Notebook detailing the performance estimation of a medium-range jet airplane modeled after the Boeing 737. The analysis encompasses various flight performance aspects using computational methods in Python.
Analysis Aspects
The performance estimation covers the following aspects:
- Drag Polar: Calculation and visualization of the drag characteristics.
- Level Flight Performance: Analysis includes stalling speed, maximum and minimum speed determination.
- Steady Climb Performance: Estimation of maximum rate and angle of climb, service ceiling, and absolute ceiling.
- Range and Endurance: Evaluation of the aircraft’s flight range and endurance capabilities.
- Steady Level Co-ordinated Turn: Computation of the minimum radius and maximum rate of turn.
- Take-off and Landing Distances: Calculation of required distances for take-off and landing phases.
Repository Structure
Performance_Estimation_B737.ipynb: The Jupyter Notebook containing all the computations and visualizations.data/: Directory containing data files used in the calculations (if applicable).figures/: Directory where generated plots and figures are saved.requirements.txt: A list of Python dependencies required to run the notebook.
How to Run the Notebook
To run this analysis, you need to have Python and Jupyter Notebook installed. Follow these steps:
- Clone the repository:
git clone https://github.com/your-username/jet-airplane-performance-estimation.git
- Navigate to the repository directory:
cd jet-airplane-performance-estimation
- Install dependencies:
pip install -r requirements.txt
- Launch the Jupyter Notebook:
jupyter notebook
- Open
Performance_Estimation_B737.ipynb from the Jupyter interface.
- Run the cells in sequence to view the analysis and results.
Results
The notebook will provide:
- Detailed calculations for each aspect of performance estimation.
- Plots illustrating the drag polar, flight envelopes, and other relevant performance figures.
- A comprehensive discussion of the results in the context of the Boeing 737 performance characteristics.
For inquiries or contributions, please contact ragireddysuresh@gmail.com.