crash-simulation
Crash simulation setup and analysis for occupant protection and regulatory compliance
Profile →npx skills add a5c-ai/babysitter --skill crash-simulation --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Crashworthiness CAE Skill ## Purpose Enable crash simulation setup and analysis for occupant protection optimization and regulatory compliance testing across frontal, side, rear, and pedestrian impact scenarios. ## Capabilities - LS-DYNA, Radioss, PAM-CRASH model preparation - Crash barrier and dummy model setup - Material card calibration (metals, plastics, foams) - Energy absorption optimization - Intrusion measurement and tracking - Occupant injury criteria calculation (HIC, chest G, femur load) - NCAP and FMVSS regulation test setup - Pedestrian protection simulation ## Usage Guidelines - Calibrate material models against component test data - Validate dummy models against certification tests - Use mesh sizes appropriate for crash simulation accuracy - Monitor energy balance and mass scaling effects - Track intrusion at critical occupant locations - Generate comprehensive crash reports for design reviews ## Dependencies - LS-DYNA - Radioss - PAM-CRASH - ANSA/META pre/post ## Process Integration - SAF-003: Crashworthiness Development - TVL-001: Vehicle-Level Validation Testing - TVL-003: Homologation and Type Approval
- Purpose
- Capabilities
- Usage Guidelines
- Dependencies
- Process Integration
What does the crash-simulation skill do?
Crash simulation setup and analysis for occupant protection and regulatory compliance
How do I install it?
Run `npx skills add a5c-ai/babysitter --skill crash-simulation --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From a5c-ai/babysitter, a repository with 1,642 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.