capstone_throttleable_engine_2025-26

2025-2026 SARP Capstone Project — a throttleable ethanol / nitrous engine injector testbed.

This repository includes:

• software (software/) — Python DAQ, valve actuation, throttle control, and web GUI
• hardware (hardware/) — KiCAD PCB design for DAQ, valve actuation, and servo control
• analysis (analysis/) — Thermal, structural, and control system analysis

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Software

Package: deep-thrott-code v0.1.0
Requires: Python ≥ 3.10

Installation

pip install -e .

Running the GUI

The system is split into two servers:

Server	Default address	Role
Backend	http://0.0.0.0:6001	DAQ, valve control, F3C sequencer, Socket.IO
GUI	http://127.0.0.1:5000	Serves the web frontend only

When you open the GUI in a browser, the frontend JS automatically connects to the backend via Socket.IO on port 6001 (same host, different port). The backend streams live sensor data at ~10 Hz and receives commands (valve actuation, sequence control, start/stop logging) from the GUI.

Running both on the same machine:

# Terminal 1 — start the backend
python -m deep_thrott_code.main --host 0.0.0.0 --port 6001

# Terminal 2 — start the GUI server
python -m deep_thrott_code.gui.run_gui --host 0.0.0.0 --port 5000

Once the server is running, open any browser on the same network and navigate to:

http://<host-ip>:5000

If running locally, just go to http://localhost:5000 or http://127.0.0.1:5000.
If running on a Raspberry Pi, use the Pi's IP address: http://192.168.x.x:5000.

Running backend on a Pi, GUI on your laptop:

# On the Pi
python -m deep_thrott_code.main --host 0.0.0.0 --port 6001

# On your laptop (point GUI at the Pi's IP)
python -m deep_thrott_code.gui --backend http://192.168.x.x:6001 --host 127.0.0.1 --port 5000

Then open http://localhost:5000 on your laptop.

What you see in the browser:

The GUI is a single-page app with:

• Line control tabs — PID diagrams with live valve state and pressure readouts for ethanol and nitrous lines
• DAQ tabs — 18 real-time sensor plots (auto-scaled, 300-point history)
• Sequence panel — step-by-step fire sequence tracking with manual step execution
• Settings — simulation toggle, test selection (hotfire / cold flow), sensor selection, theme

CLI flags (main backend):

Flag	Description
--host	Bind host (default 0.0.0.0)
--port	Bind port (default 6001)
--simulation	Run without hardware (sensor simulation)
--no-gui-server	Start backend only, no Flask server
--autostart	Automatically start DAQ on launch
--no-sequencer	Disable the F3C fire sequencer
--debug	Enable Flask debug mode

Structure

software/src/deep_thrott_code/
├── main.py               # Entry point
├── backend/              # App factory, GUI command handlers, DAQ runtime
├── gui/                  # Flask + Socket.IO web interface (routes, sockets)
├── daq/                  # Data acquisition — ADC drivers and sensor interfaces
├── f3c/                  # Sequencer and valve control
├── control/              # PID throttle controller and servo characterization
└── config/               # Default configuration files

Utility scripts (software/scripts/):

• hotfire.py — Hotfire sequence runner
• calibrate_sensors.py — Sensor calibration
• plot_daq_csv.py — Plot data from DAQ CSV logs
• adc_smoke_test.py — ADC hardware smoke test

Dependencies

Package	Purpose
Flask, Flask-SocketIO	Web GUI server
NumPy, SciPy	Numerical computation
PyYAML	Configuration parsing
PySerial	Serial communication
Matplotlib	Data visualization
RPi.GPIO, pigpio, spidev	GPIO and SPI (Linux/RPi only)
eventlet (optional)	Async server mode

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Hardware

KiCAD project located in hardware/cda-pcb/. Includes schematic, PCB layout, Gerber files, and custom symbols/footprints.

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Analysis

• analysis/control_dev/ — Control system models (MATLAB and Python)
• analysis/engine_dev/ — Structural analysis (Python, based on GRACE methodology)