# Playbook — DOE (Phase 1 Landscape)

## Scope
Design of Experiments for Hydrotech Beam: baseline + LHS samples to map design space.

## Standard flow
1. Prepare clean state (archive previous results if needed)
2. Run DOE with explicit backend
3. Validate outputs
4. Evaluate gate criteria
5. Decide next phase (rerun bounds/constraints or move to TPE)

## Commands
### Real engineering DOE
```powershell
python .\run_doe.py --backend nxopen --model-dir "<PATH_TO_NX_MODELS>" --clean --study-name hydrotech_beam_doe_phase1_real
```

### Debug DOE only (synthetic)
```powershell
python .\run_doe.py --backend stub --clean --study-name hydrotech_beam_doe_phase1_stub
```

## Interpretation checklist
- `geo_infeasible` high: geometry bounds/checks may be too broad or too strict
- `fully_feasible = 0`: constraints may be too strict for current design space
- Very low runtime and suspiciously smooth outputs: likely stub execution

## Decision branch
- If gate passed: proceed to TPE seeded by feasible points
- If gate failed:
  - adjust constraints and/or DV bounds
  - rerun clean DOE

## Documentation requirement
After each DOE run, update:
- run record
- decision and rationale
- next action owner