Fatigue Life Predictor Skill
SkillDev toolsFatigue life prediction skill for implants and load-bearing devices using validated approaches
Use Fatigue Life Predictor Skill in Claude, ChatGPT or Ahel Desktop
Free. Sign in, add Fatigue Life Predictor Skill and connect your AI. About a minute.
Also: Claude Code · Cursor · Codex
Then ask your AI: use the Fatigue Life Predictor Skill
Details
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
Account requirements not reviewed. Check the skill instructions before use; Ahel provides instructions and does not run this skill.
No other account needed.
Add Ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
What this skill tells your AI
The instructions your AI receives, as published by a5c-ai/babysitter in library/specializations/domains/science/biomedical-engineering/skills/fatigue-life-predictor/SKILL.md and read by Ahel’s review.
Purpose
The Fatigue Life Predictor Skill estimates fatigue life of medical implants and load-bearing devices using established methodologies per ASTM and ISO standards, supporting design verification and regulatory submissions.
Capabilities
- S-N curve generation and analysis
- Strain-life fatigue modeling
- Multiaxial fatigue assessment
- Fretting fatigue evaluation
- Corrosion fatigue considerations
- Goodman diagram construction
- Run-out criteria application
- Notch sensitivity analysis
- Statistical treatment of fatigue data
- Design allowable determination
- Fatigue test correlation
Usage Guidelines
When to Use
- Predicting implant fatigue life
- Designing fatigue testing protocols
- Correlating FEA with bench testing
- Supporting design verification
Prerequisites
- Stress analysis completed
- Material fatigue properties available
- Loading spectrum defined
- Surface finish characterized
Best Practices
- Use appropriate fatigue methodology for loading type
- Account for mean stress effects
- Consider physiological environment effects
- Correlate predictions with bench testing
Process Integration
This skill integrates with the following processes:
- Finite Element Analysis for Medical Devices
- Orthopedic Implant Biomechanical Testing
- Design Control Process Implementation
- Verification and Validation Test Planning
Dependencies
- fe-safe software
- ANSYS nCode
- ASTM F1717/F2077 standards
- Material fatigue databases
- FEA stress results
Configuration
fatigue-life-predictor:
methodologies:
- stress-life
- strain-life
- fracture-mechanics
loading-types:
- constant-amplitude
- variable-amplitude
- multiaxial
mean-stress-corrections:
- Goodman
- Gerber
- Morrow
environment:
- air
- saline
- body-fluid
Output Artifacts
- Fatigue life predictions
- S-N curves
- Goodman diagrams
- Safety factor calculations
- Test correlation reports
- Design recommendations
- Statistical analysis results
- Regulatory submission summaries
Quality Criteria
- Methodology appropriate for loading conditions
- Material data from validated sources
- Mean stress effects properly accounted
- Environmental factors considered
- Predictions correlated with testing
- Documentation supports regulatory review
Signals
- GitHub stars
- 2k
- Forks
- 113
- Last commit
- Sep 2026
Advanced
- Item type
- skill
- Key
fatigue-life-predictor- Source
- github.com/a5c-ai/babysitter