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Atomizer/projects/hydrotech-beam
Antoine 017b90f11e feat(hydrotech-beam): Phase 1 LHS DoE study code
Implements the optimization study code for Phase 1 (LHS DoE) of the
Hydrotech Beam structural optimization.

Files added:
- run_doe.py: Main entry point — Optuna study with SQLite persistence,
  Deb's feasibility rules, CSV/JSON export, Phase 1→2 gate check
- sampling.py: 50-point LHS via scipy.stats.qmc with stratified integer
  sampling ensuring all 11 hole_count levels (5-15) are covered
- geometric_checks.py: Pre-flight feasibility filter — hole overlap
  (corrected formula: span/(n-1) - d ≥ 30mm) and web clearance checks
- nx_interface.py: NX automation module with stub solver for development
  and NXOpen template for Windows/dalidou integration
- requirements.txt: optuna, scipy, numpy, pandas

Key design decisions:
- Baseline enqueued as Trial 0 (LAC lesson)
- All 4 DV expression names from binary introspection (exact spelling)
- Pre-flight geometric filter saves compute and prevents NX crashes
- No surrogates (LAC lesson: direct FEA via TPE beats surrogate+L-BFGS)
- SQLite persistence enables resume after interruption

Tested end-to-end with stub solver: 51 trials, 12 geometric rejects,
39 solved, correct CSV/JSON output.

Ref: OPTIMIZATION_STRATEGY.md, auditor review 2026-02-10
2026-02-10 22:15:06 +00:00
..
2026-02-10 08:00:22 +00:00
2026-02-10 08:00:22 +00:00
2026-02-10 08:00:22 +00:00
2026-02-10 08:00:22 +00:00

Hydrotech Beam — Structural Optimization

Client: Hydrotech (internal test fixture) Channel: #project-hydrotech-beam Created: 2026-02-08 Status: Technical Breakdown Complete — Awaiting Gap Resolution


Objective

Optimize a sandwich I-beam with lightening holes: minimize mass while meeting stiffness and strength constraints.

Key Numbers

Metric Baseline Target
Mass ~974 kg Minimize
Tip displacement ~22 mm ≤ 10 mm
Von Mises stress TBD ≤ 130 MPa

Design Variables

Variable Range Type
Half-core thickness 1040 mm Continuous
Face thickness 1040 mm Continuous
Hole diameter 150450 mm Continuous
Hole count 515 Integer

Approach

Two-phase optimization:

  1. DoE (LHS, 4050 trials) — map the landscape
  2. TPE (Bayesian, 60100 trials) — converge to optimum

Total budget: ~100150 NX evaluations, est. 25 hours compute.

Project Structure

hydrotech-beam/
├── README.md              ← You are here
├── CONTEXT.md             # Intake requirements
├── BREAKDOWN.md           # Technical analysis
├── DECISIONS.md           # Decision log
├── models/                # Reference NX models (golden copies)
├── kb/                    # Living knowledge base
│   ├── components/        # Per-component knowledge
│   ├── materials/         # Material data
│   ├── fea/               # FEA model knowledge
│   └── dev/               # Generation documents
├── images/                # Screenshots, plots, renders
├── studies/               # Optimization campaigns
│   └── 01_doe_landscape/  # (first study — pending)
└── deliverables/          # Final reports and recommendations

Key Documents

Team

Role Agent Status
Manager 🎯 Manager Coordinating
Technical Lead 🔧 Tech Lead Breakdown complete
CEO Antoine Gap resolution pending