2026-02-15 08:00:21 +00:00
# Study: 01_doe_landscape — Hydrotech Beam
> See [../../README.md](../../README.md) for project overview.
## Purpose
Map the design space of the Hydrotech sandwich I-beam to identify feasible regions, characterize variable sensitivities, and prepare data for Phase 2 (TPE optimization). This is Phase 1 of the two-phase strategy (DEC-HB-002).
## Quick Facts
| Item | Value |
|------|-------|
| **Objective ** | Minimize mass (kg) |
| **Constraints ** | Tip displacement ≤ 10 mm, Von Mises stress ≤ 130 MPa |
| **Design variables ** | 4 (3 continuous + 1 integer) |
| **Algorithm ** | Phase 1: LHS DoE (50 trials + 1 baseline) |
| **Total budget ** | 51 evaluations |
| **Constraint handling ** | Deb's feasibility rules (Optuna constraint interface) |
| **Status ** | ✅ Pipeline operational — first results obtained 2026-02-11 |
| **Solver ** | DesigncenterNX 2512 (NX Nastran SOL 101) |
| **Solve time ** | ~12 s/trial (~10 min for full DOE) |
| **First results ** | Displacement=17.93mm, Stress=111.9MPa |
## Design Variables (confirmed via NX binary introspection)
| ID | NX Expression | Range | Type | Baseline | Unit |
|----|--------------|-------|------|----------|------|
| DV1 | `beam_half_core_thickness` | 10–
| DV2 | `beam_face_thickness` | 10–
| DV3 | `holes_diameter` | 150–
| DV4 | `hole_count` | 5–
## Usage
### Prerequisites
```bash
pip install -r requirements.txt
```
Requires: Python 3.10+, optuna, scipy, numpy, pandas.
### Development Run (stub solver)
```bash
# From the study directory:
cd projects/hydrotech-beam/studies/01_doe_landscape/
# Run with synthetic results (for pipeline testing):
python run_doe.py --backend stub
# With verbose logging:
python run_doe.py --backend stub -v
# Custom study name:
python run_doe.py --backend stub --study-name my_test_run
```
### Production Run (NXOpen on Windows)
```bash
# On dalidou (Windows node with DesigncenterNX 2512):
cd C:\Users\antoi\Atomizer\projects\hydrotech-beam\studies\01_doe_landscape
conda activate atomizer
python run_doe.py --backend nxopen --model-dir "../../models"
```
> ⚠️ `--model-dir` can be relative — the code resolves it with `Path.resolve()`. NX requires fully resolved paths (no `..` components).
### Resume Interrupted Study
```bash
python run_doe.py --backend stub --resume --study-name hydrotech_beam_doe_phase1
```
### CLI Options
| Flag | Default | Description |
|------|---------|-------------|
| `--backend` | `stub` | `stub` (testing) or `nxopen` (real NX) |
| `--model-dir` | — | Path to NX model files (required for `nxopen` ) |
| `--study-name` | `hydrotech_beam_doe_phase1` | Optuna study name |
| `--n-samples` | 50 | Number of LHS sample points |
| `--seed` | 42 | Random seed for reproducibility |
| `--results-dir` | `results/` | Output directory |
| `--resume` | false | Resume existing study |
| `--clean` | false | Delete Optuna DB and start fresh (history DB preserved) |
| `-v` | false | Verbose (DEBUG) logging |
## Files
| File | Description |
|------|-------------|
| `run_doe.py` | Main entry point — orchestrates the DoE study |
| `sampling.py` | LHS generation with stratified integer sampling |
| `geometric_checks.py` | Pre-flight geometric feasibility filter |
| `nx_interface.py` | AtomizerNXSolver wrapping optimization_engine |
| `iteration_manager.py` | Smart retention — last 10 + best 3 with full data |
| `requirements.txt` | Python dependencies |
| `OPTIMIZATION_STRATEGY.md` | Full strategy document |
| `results/` | Output directory (CSV, JSON, Optuna DB) |
| `iterations/` | Per-trial archived outputs |
## Output Files
After a study run, `results/` will contain:
| File | Description |
|------|-------------|
| `doe_results.csv` | All trials — DVs, objectives, constraints, status |
| `doe_summary.json` | Study metadata, statistics, best feasible design |
| `optuna_study.db` | SQLite database (Optuna persistence, resume support) |
| `history.db` | **Persistent ** SQLite — all DVs, results, feasibility (survives `--clean` ) |
| `history.csv` | CSV mirror of history DB |
### Iteration Folders
Each trial produces `iterations/iterNNN/` containing:
| File | Description |
|------|-------------|
| `params.json` | Design variable values for this trial |
| `params.exp` | NX expression file used for this trial |
| `results.json` | Extracted results (mass, displacement, stress, feasibility) |
| `*.op2` | Nastran binary results (for post-processing) |
| `*.f06` | Nastran text output (for debugging) |
**Smart retention policy** (runs every 5 iterations):
- Keep last 10 iterations with full data
- Keep best 3 feasible iterations with full data
- Strip model files from all others, keep solver outputs
## Architecture
```
run_doe.py
├── sampling.py Generate 50 LHS + 1 baseline
│ └── scipy.stats.qmc.LatinHypercube
├── geometric_checks.py Pre-flight feasibility filter
│ ├── Hole overlap: span/(n-1) - d ≥ 30mm
│ └── Web clearance: 500 - 2·face - d > 0
├── nx_interface.py AtomizerNXSolver (wraps optimization_engine)
│ ├── NXStubSolver → synthetic results (development)
│ └── AtomizerNXSolver → real DesigncenterNX 2512 SOL 101 (production)
├── iteration_manager.py Smart retention (last 10 + best 3)
├── Optuna study
│ ├── SQLite storage (resume support)
│ ├── Enqueued trials (deterministic LHS)
│ └── Deb's feasibility rules (constraint interface)
└── history.db Persistent history (append-only, survives --clean)
```
## Pipeline per Trial
```
Trial N
│
├── 1. Suggest DVs (from enqueued LHS point)
│
├── 2. Geometric pre-check
│ ├── FAIL → record as infeasible, skip NX
│ └── PASS ↓
│
├── 3. Restore master model from backup
│
├── 4. NX evaluation (IN-PLACE in models/ directory)
│ ├── Write .exp file with trial DVs
│ ├── Open .sim (loads model chain)
│ ├── Import expressions, rebuild geometry
│ ├── Update FEM (remesh)
│ ├── Solve SOL 101 (~12s)
│ └── Extract: mass (p173 → _temp_mass.txt), displacement, stress (via OP2)
│
├── 5. Archive outputs to iterations/iterNNN/
│ └── params.json, params.exp, results.json, OP2, F06
│
├── 6. Record results + constraint violations
│
├── 7. Log to Optuna DB + history.db + CSV
│
└── 8. Smart retention check (every 5 iterations)
```
## Phase 1 → Phase 2 Gate Criteria
Before proceeding to Phase 2 (TPE optimization), these checks must pass:
| Check | Threshold | Action if FAIL |
|-------|-----------|----------------|
| Feasible points found | ≥ 5 | Expand bounds or relax constraints (escalate to CEO) |
| NX solve success rate | ≥ 80% | Investigate failures, fix model, re-run |
| No systematic crashes at bounds | Visual check | Tighten bounds away from failure region |
## Key Design Decisions
- **Baseline as Trial 0** — LAC lesson: always validate baseline first
- **Pre-flight geometric filter** — catches infeasible geometry before NX (saves compute, avoids crashes)
- **Stratified integer sampling** — ensures all 11 hole_count levels (5-15) are covered
- **Deb's feasibility rules** — no penalty weight tuning; feasible always beats infeasible
- **SQLite persistence** — study can be interrupted and resumed
- **No surrogates** — LAC lesson: direct FEA via TPE beats surrogate + L-BFGS
## NX Integration Notes
**Solver:** DesigncenterNX 2512 (Siemens rebrand of NX). Install: `C:\Program Files\Siemens\DesigncenterNX2512` .
The `nx_interface.py` module provides:
- **`NXStubSolver` ** — synthetic results from simplified beam mechanics (for pipeline testing)
- **`AtomizerNXSolver` ** — wraps `optimization_engine` NXSolver for real DesigncenterNX 2512 solves
Expression names are exact from binary introspection. Critical: `beam_lenght` has a typo in NX (no 'h') — use exact spelling.
### Outputs extracted from NX:
| Output | Source | Unit | Notes |
|--------|--------|------|-------|
| Mass | Expression `p173` → `_temp_mass.txt` | kg | Journal extracts after solve |
| Tip displacement | OP2 parse via pyNastran | mm | Max Tz at free end |
| Max VM stress | OP2 parse via pyNastran | MPa | ⚠️ pyNastran returns kPa — divide by 1000 |
### Critical Lessons Learned (2026-02-11)
1. **Path resolution: ** Use `Path.resolve()` NOT `Path.absolute()` on Windows. `.absolute()` doesn't resolve `..` components — NX can't follow them.
2. **File references: ** NX `.sim` files have absolute internal refs to `.fem` /`.prt` . Never copy model files to iteration folders — solve in-place with backup/restore.
3. **NX version: ** Must match exactly. Model files from 2512 won't load in 2412 ("Part file is from a newer version").
4. **pyNastran: ** Warns about unsupported NX version 2512 but works fine. Safe to ignore.
## References
- [OPTIMIZATION_STRATEGY.md ](./OPTIMIZATION_STRATEGY.md ) — Full strategy document
- [../../BREAKDOWN.md ](../../BREAKDOWN.md ) — Tech Lead's technical analysis
- [../../DECISIONS.md ](../../DECISIONS.md ) — Decision log
- [../../CONTEXT.md ](../../CONTEXT.md ) — Project context & expression map
---
*Code: 🏗️ Study Builder (Technical Lead) | Strategy: ⚡ Optimizer Agent | Updated: 2026-02-11*
