- Remove all .sync-conflict-* files - Remove temp _temp_part_properties.json files - Add USER_GUIDE.md - Add dashboard docs (Executive, Technical, Operations, Master Plan) - Add playbooks (DOE, NX_REAL_RUN, SYNCTHING_RECOVERY) - Update iteration results Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
40 lines
1.2 KiB
Markdown
40 lines
1.2 KiB
Markdown
# Playbook — DOE (Phase 1 Landscape)
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## Scope
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Design of Experiments for Hydrotech Beam: baseline + LHS samples to map design space.
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## Standard flow
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1. Prepare clean state (archive previous results if needed)
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2. Run DOE with explicit backend
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3. Validate outputs
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4. Evaluate gate criteria
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5. Decide next phase (rerun bounds/constraints or move to TPE)
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## Commands
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### Real engineering DOE
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```powershell
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python .\run_doe.py --backend nxopen --model-dir "<PATH_TO_NX_MODELS>" --clean --study-name hydrotech_beam_doe_phase1_real
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```
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### Debug DOE only (synthetic)
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```powershell
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python .\run_doe.py --backend stub --clean --study-name hydrotech_beam_doe_phase1_stub
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```
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## Interpretation checklist
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- `geo_infeasible` high: geometry bounds/checks may be too broad or too strict
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- `fully_feasible = 0`: constraints may be too strict for current design space
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- Very low runtime and suspiciously smooth outputs: likely stub execution
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## Decision branch
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- If gate passed: proceed to TPE seeded by feasible points
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- If gate failed:
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- adjust constraints and/or DV bounds
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- rerun clean DOE
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## Documentation requirement
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After each DOE run, update:
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- run record
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- decision and rationale
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- next action owner
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