---
name: propulsion-test-analysis-fd1d045ddc5e
description: Skill for propulsion system ground test data acquisition and analysis
allowed-tools:
  - Read
  - Write
  - Glob
  - Grep
  - Edit
  - WebFetch
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metadata:
  version: "1.0"
  category: aerospace-engineering
  tags:
    - propulsion
    - testing
    - data-acquisition
    - validation
graph:
  domains: [domain:aerospace-engineering]
  specializations: [specialization:aerospace-engineering]
  skillAreas: [skill-area:physics-simulation, skill-area:statistical-analysis, skill-area:sensor-fusion]
  roles: [role:research-engineer, role:lab-technician]
---

# Propulsion Test Data Analysis Skill

## Purpose
Support propulsion system ground testing through comprehensive data acquisition configuration, real-time analysis, and test-to-prediction correlation.

## Capabilities
- Test cell instrumentation configuration
- Data acquisition system setup
- Real-time performance calculation
- Test-to-prediction correlation
- Thrust stand calibration verification
- Measurement uncertainty analysis
- Test matrix optimization
- Health monitoring parameter tracking

## Usage Guidelines
- Verify instrumentation calibration before each test campaign
- Define clear success criteria and abort conditions
- Monitor critical parameters in real-time during testing
- Apply appropriate measurement corrections and uncertainty propagation
- Correlate test results with analytical predictions
- Document all test conditions, anomalies, and lessons learned

## Dependencies
- LabVIEW
- MATLAB
- Data acquisition systems
- Test cell control systems

## Process Integration
- AE-006: Propulsion System Testing


---
Source attribution: a5c-ai
Original project: https://github.com/a5c-ai/babysitter
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Mega AI Hub.

## Upstream license notice

MIT License

Copyright (c) 2026 Gabriel Moreira

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.



# Mega AI Hub resource metadata

Creator / publisher: a5c-ai
Original project: https://github.com/a5c-ai/babysitter
Attribution basis: Upstream repository explicitly recorded in package mirror path

Fields of work: Data & Analytics, Development & Engineering, Product Management, Project & Program Management
Roles: Data Analyst, Product Manager, Project Manager, QA / Test Engineer, Technical Product Manager
Specialties: API, Testing
Tools: Labview, Matlab
Country applicability: Country not specified
Classification basis: Source catalog labels
Instruction SHA-256: a9701b2aeaf7a0e46f7036def12384e6aca25101d3b9046705581b5cd8c4c4dc