https://github.com/danalex-03/kmsp-b747_loci_riskq
MATLAB code and supporting data for energy-based subset simulation of Loss of Control In-Flight risk during Boeing 747 final approach onto KMSP Runway 30R.
https://github.com/danalex-03/kmsp-b747_loci_riskq
aerospace flight-data loss-of-control-in-flight matlab subset-simulation
Last synced: 3 months ago
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MATLAB code and supporting data for energy-based subset simulation of Loss of Control In-Flight risk during Boeing 747 final approach onto KMSP Runway 30R.
- Host: GitHub
- URL: https://github.com/danalex-03/kmsp-b747_loci_riskq
- Owner: DanAlex-03
- Created: 2025-06-20T16:26:18.000Z (4 months ago)
- Default Branch: main
- Last Pushed: 2025-07-06T11:25:30.000Z (3 months ago)
- Last Synced: 2025-07-06T12:24:10.109Z (3 months ago)
- Topics: aerospace, flight-data, loss-of-control-in-flight, matlab, subset-simulation
- Language: MATLAB
- Homepage:
- Size: 8.58 MB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# LOC-I Risk Modeling using Subset Simulation and Energy-Based Metrics
This repository contains MATLAB code and supporting datasets developed for a thesis project that quantifies the probability of **Loss of Control In-Flight (LOC-I)** during the final approach phase of a **Boeing 747-300**, using a combination of physical energy modeling, flight data analysis, and rare-event simulation via **Subset Simulation**.
## Project Overview
The model focuses on the last **1000 ft AGL** before touchdown at **KMSP Runway 30R**, using Quick Access Recorder (QAR) data from over 4200 flights. It estimates the failure probability that the aircraft’s total energy drops below a defined threshold, indicating potential LOC-I.
Key components:
- Energy-rate modeling based on aerodynamic, thrust, and gravity force components.
- Data-driven statistical fitting of parameters across all flights.
- Definition of failure based on cumulative energy deficit (below threshold).
- Use of **Subset Simulation with MCMC sampling** to estimate rare-event probabilities.
The simulation includes both:
- An **overall failure probability** (integrated over entire approach),
- A **time-dependent per-second failure probability**, revealing how risk evolves during descent.
## Requirements
- MATLAB R2021b or newer
- [Subset Simulation Toolbox (TUM FSD)](https://www.fs.tum.de/en/aircraft/projects/software-tools/)
- Curve Fitting Toolbox
- Distribution Fitter App
- Parallel Computing Toolbox
## Key Features
- Energy model integrating control inputs: AoA, N1, pitch, bank, elevator, fuel mass, airspeed, altitude, and crosswind
- Dynamic per-second failure probability estimation
- Ranking of input parameters using both manual and toolbox-assisted sensitivity analysis
- Export-ready plots and Excel outputs for visualization
## Example Results
- Estimated LOC-I probability over full approach: **~3.57 × 10⁻⁸**
- The time-dependent failure probability was fit using a power-law model:
P_F(t) ≈ 10^(a·t^b + c), with a goodness of fit R² = 0.9913.
- Sensitivity analysis reveals **angle of attack**, **crosswind**, and **N1** as most influential
## License and Permissions
This repository is **not licensed for reuse or redistribution**. Please contact the author for permission before using any part of the code or data.
## Acknowledgments
Developed as part of an undergraduate thesis (FTMD ITB, Student ID: 13621021) titled *Risk Quantification of Aerodynamic Stall and In-Flight Loss of Control (LOC-I) Events During Aircraft Approach*. Simulation methodology based on the TUM FSD Subset Simulation Toolbox and supervised by Dr. -Ing. Ir. Javensius Sembiring.