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pfc5-servo-calibration

Design and audit PFC 5.0 wall servo, loading-rate control, equilibrium checks, micro-to-macro calibration, two-target local solves, DOE campaigns, and independent confirmation for asphalt models.

The English summary is being prepared. Showing the original description.

See how to install

Files included (6)

  • SKILL.md2.4 KB
  • agents/openai.yaml241 B
  • dependencies.json117 B
  • references/calibration-contract.md908 B
  • scripts/dual_target_solver.py3.1 KB
  • scripts/servo_gain.py1.4 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

PFC5 Servo And Calibration

Use this skill for compaction pressure, confining/load control, Marshall/rutting reaction control, Burger fitting, or multi-target PFC5 calibration.

Required Inputs

  • controlled axis, actuator, sign convention, target and tolerance;
  • effective stiffness estimate, timestep/update interval, velocity limits;
  • active micro-parameters with units/bounds;
  • macro targets, tolerances, experimental provenance and run budget;
  • baseline save, seed policy and evaluator output schema.

Workflow

  1. Prove wall/axis/reaction sign with a short motion probe.
  2. Estimate effective stiffness and choose a conservative dimensionless gain.
  3. Clamp actuator velocity and record target, reaction, error, gain and velocity.
  4. Require equilibrium/inertia checks before accepting a stage.
  5. Calibrate in sequence: elastic response, strength/interface, time dependence, then post-peak/rutting behavior.
  6. Use the two-target solver only when exactly two active levers produce a well-conditioned local response matrix.
  7. For larger problems use DOE with real PFC5 runs; treat regression/surrogates as proposal tools only.
  8. Confirm the final parameters on an independent seed or loading condition.

Use scripts/servo_gain.py for a bounded proportional step and scripts/dual_target_solver.py for a guarded local 2x2 solve. Read calibration-contract.md before campaigns.

Working Rules

  • Do not prescribe reaction force by writing a read-only contact-force quantity.
  • Do not tune more parameters than the data can identify.
  • Reject near-singular local solves; do not hide them with huge parameter jumps.
  • Every proposed parameter set needs a true PFC5 confirmation run.

Output Contract

Return controller equations/signs, gain and clamp, histories, parameter/target tables, run manifest, conditioning diagnostics, confirmation result and runtime status.

Local Contents

  • references/calibration-contract.md — servo and campaign gates.
  • scripts/servo_gain.py — bounded controller-step calculator.
  • scripts/dual_target_solver.py — conditioned two-target update.
  • agents/openai.yaml — interface metadata.

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