440 lines
20 KiB
Markdown
440 lines
20 KiB
Markdown
# Arsenal Development Plan — Atomizer Multi-Solver Integration
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> **Status:** DRAFT — pending CEO approval
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> **Date:** 2026-06-25
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> **Authors:** Technical Lead (architecture + feasibility), Auditor (risk + gates), Manager (orchestration)
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> **Source docs:** Arsenal V3 Final, Tool-Agnostic Architecture, Multi-Solver Roadmap, Arsenal Reference
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---
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## 1. Executive Summary
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**Goal:** Integrate the 80/20 highest-leverage open-source tools from the Atomizer Arsenal into V2, enabling fully scripted optimization without NX GUI dependency.
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**What this unlocks:**
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- Linux-headless optimization loops (no NX license bottleneck)
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- 100s–1000s of trials per campaign (vs. current NX-constrained budgets)
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- Multi-solver validation (CalculiX vs Nastran cross-checking)
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- Path to CFD and multi-physics (expansion sprints)
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**The 80/20 stack (6 sprints):**
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| Priority | Tool | Category | Why |
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|----------|------|----------|-----|
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| 🔴 P1 | CalculiX | FEA solver | Free structural solver, covers 80% of use cases |
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| 🔴 P1 | Gmsh | Meshing | Universal mesher, Python API, STEP import |
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| 🔴 P1 | Build123d | CAD | Code-native geometry, LLM-perfect, headless |
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| 🔴 P1 | meshio + pyNastran | Converters | Format glue between all tools |
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| 🔴 P1 | PyVista + ParaView | Post-processing | Automated visualization pipeline |
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| 🟡 P2 | pymoo | Optimization | Multi-objective (NSGA-II/III) |
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| 🟡 P2 | OpenFOAM | CFD | Thermal/flow screening |
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| 🟢 P3 | preCICE | Coupling | Thermo-structural coupling |
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| 🟢 P3 | OpenMDAO | MDO | System-level optimization |
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**Antoine's time commitment:** ~2–3 hours per sprint for validation gates.
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**HQ autonomous work:** days of implementation per sprint.
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---
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## 2. Architecture Overview
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The Arsenal integrates through Atomizer's 3-layer tool-agnostic architecture:
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```
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┌─────────────────────────────────────────────────────────┐
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│ Layer 3: OPTIMIZATION INTELLIGENCE │
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│ AtomizerSpec v3.0 │ Optuna/pymoo │ LAC │ LLM Agents │
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│ ── never touches tool-specific formats ── │
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├─────────────────────────────────────────────────────────┤
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│ Layer 2: TOOL PROCESSORS (deterministic Python) │
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│ Geometry: nx_geometry │ build123d_geometry │ step_import│
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│ Meshing: gmsh_mesher │ nx_mesher │
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│ Solvers: nastran_solver │ calculix_solver │ openfoam │
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│ Convert: meshio_converter │ pynastran_bridge │
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│ Post: pyvista_post │ paraview_post │
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├─────────────────────────────────────────────────────────┤
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│ Layer 1: UNIVERSAL DATA CONTRACTS │
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│ AtomizerGeometry │ AtomizerMesh │ AtomizerBCs │
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│ AtomizerMaterial │ AtomizerResults │
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│ ── solver-agnostic dataclasses (the Rosetta Stone) ── │
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└─────────────────────────────────────────────────────────┘
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```
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**Key rule:** Adding a new tool = writing ONE processor file. Contracts never change per tool.
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### 2.1 V2 Repository Target Layout
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```
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atomizer/
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├── contracts/
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│ ├── geometry.py # AtomizerGeometry
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│ ├── mesh.py # AtomizerMesh
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│ ├── boundary_conditions.py # AtomizerBCs
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│ ├── material.py # AtomizerMaterial
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│ ├── results.py # AtomizerResults
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│ └── validators.py # Cross-contract sanity checks
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├── processors/
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│ ├── base.py # Abstract base classes
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│ ├── geometry/
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│ │ ├── build123d_geometry.py
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│ │ ├── nx_geometry.py
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│ │ └── step_import.py
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│ ├── meshing/
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│ │ ├── gmsh_mesher.py
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│ │ └── nx_mesher.py
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│ ├── solvers/
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│ │ ├── nastran_solver.py
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│ │ ├── calculix_solver.py
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│ │ └── openfoam_solver.py # Sprint 4
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│ ├── converters/
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│ │ ├── meshio_converter.py
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│ │ └── pynastran_bridge.py
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│ └── postprocessing/
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│ ├── pyvista_post.py
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│ └── paraview_post.py
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├── orchestrator/
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│ ├── pipeline.py # Solver-agnostic run sequencing
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│ ├── auto_select.py # Toolchain routing logic
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│ └── coupling.py # Sprint 5: preCICE
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├── optimization/
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│ ├── engine.py # Core optimization loop
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│ ├── optuna_backend.py
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│ └── pymoo_backend.py # Sprint 6
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└── mcp_servers/ # Sprint 2-3
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├── calculix/
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├── gmsh/
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├── build123d/
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└── pynastran/
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```
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---
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## 3. Current Environment Assessment
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| Item | Status | Action Required |
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|------|--------|----------------|
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| V2 repo (`atomizer/` package) | ❌ Not yet created — still V1 flat layout | Sprint 0: scaffold package structure |
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| pyNastran | ✅ Installed | None |
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| CalculiX (ccx) | ❌ Not installed | `apt install calculix-ccx` or Docker |
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| Gmsh | ❌ Not installed | `pip install gmsh pygmsh` |
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| Build123d | ❌ Not installed | `pip install build123d` |
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| meshio | ❌ Not installed | `pip install meshio` |
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| PyVista | ❌ Not installed | `pip install pyvista` |
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| ParaView/pvpython | ❌ Not installed | `apt install paraview` |
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| pymoo | ❌ Not installed | `pip install pymoo` (Sprint 6) |
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| OpenFOAM | ❌ Not installed | Docker recommended (Sprint 4) |
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**First blocker:** Package installs on T420. Either direct install or Docker-based dev environment.
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---
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## 4. Sprint Plan
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### Sprint 0: Environment + Scaffold (1–2 days)
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**Goal:** Working dev environment and V2 package skeleton.
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| Task | Owner | Autonomy | Deliverable |
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|------|-------|----------|-------------|
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| Install core Python packages (gmsh, build123d, meshio, pyvista) | Developer/IT | 🟢 Full | Working imports |
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| Install CalculiX (`apt install calculix-ccx`) | Developer/IT | 🟢 Full | `ccx` on PATH |
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| Scaffold `atomizer/` package with `__init__.py` stubs | Developer | 🟢 Full | Package importable |
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| Create `tests/benchmarks/` with 3 analytical reference cases | Tech Lead | 🟢 Full | JSON expected-value files |
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**Analytical benchmarks (known-answer problems):**
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1. **Cantilever beam** — tip deflection = PL³/3EI (linear static)
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2. **Plate with hole** — SCF ≈ 3.0 at hole edge (stress concentration)
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3. **Simply supported beam** — first natural frequency = (π²/L²)√(EI/ρA) (modal)
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**Antoine gate:** None — this is infrastructure.
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---
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### Sprint 1: Contracts + Structural Bridge Baseline (1 week)
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**Goal:** Contract-driven NX/Nastran baseline with format conversion verification.
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| Task | Owner | Autonomy | Deliverable |
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|------|-------|----------|-------------|
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| Implement 5 contract dataclasses | Developer | 🟢 95% | `contracts/*.py` with full type hints |
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| Implement `validators.py` | Developer | 🟢 95% | Unit-consistent checks, BC physics checks |
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| Implement `processors/base.py` abstract classes | Tech Lead → Developer | 🟢 95% | `GeometryProcessor`, `MeshProcessor`, `SolverProcessor` ABCs |
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| Wrap existing NX/Nastran into `nastran_solver.py` | NX Expert → Developer | 🟡 70% | Existing workflow through new interface |
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| Implement `meshio_converter.py` | Developer | 🟢 95% | BDF ↔ INP ↔ MSH ↔ VTK round-trip |
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| Implement `pynastran_bridge.py` | Developer | 🟢 95% | BDF read/modify, OP2 parse → AtomizerResults |
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| Implement `pipeline.py` skeleton | Tech Lead → Developer | 🟢 90% | Sequential pipeline runner |
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| Unit tests for all contracts + converters | Developer | 🟢 95% | pytest suite passing |
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**Success criterion:** Existing NX/Nastran workflow passes through new architecture with zero regression.
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**Antoine gate:** Provide 3 trusted benchmark studies with known expected outputs for parity check.
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**Risk:** Hidden assumptions in legacy NX/Nastran parsing may break when abstracted.
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**Mitigation:** Run full diff on old vs new output before declaring parity.
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---
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### Sprint 2: Open Structural Lane — CalculiX + Gmsh + Build123d (1–2 weeks)
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**Goal:** Full Linux-headless structural optimization loop with zero NX dependency.
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| Task | Owner | Autonomy | Deliverable |
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|------|-------|----------|-------------|
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| Implement `build123d_geometry.py` | Developer | 🟢 90% | DV dict → Build123d → STEP |
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| Implement `step_import.py` | Developer | 🟢 95% | STEP → AtomizerGeometry |
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| Implement `gmsh_mesher.py` | Developer | 🟢 90% | STEP → Gmsh → AtomizerMesh (with quality metrics) |
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| Implement `calculix_solver.py` | Tech Lead → Developer | 🟡 80% | .inp generation + ccx exec + .frd parsing → AtomizerResults |
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| Implement `pyvista_post.py` | Developer | 🟢 95% | AtomizerResults → contour plots (PNG/VTK) |
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| Implement `optuna_backend.py` (adapted) | Optimizer → Developer | 🟢 90% | Contract-aware Optuna loop |
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| Run 3 analytical benchmarks through full pipeline | Tech Lead | 🟢 90% | Pass/fail report vs known answers |
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| CalculiX vs Nastran parity comparison | Tech Lead | 🟡 70% | Delta report on shared benchmark |
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**Demo scenario:**
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```
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Parametric bracket (thickness, fillet_radius, rib_width)
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→ Build123d generates STEP
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→ Gmsh meshes
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→ CalculiX solves (SOL 101 equivalent)
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→ PyVista renders stress contour
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→ Optuna optimizes for min mass @ stress constraint
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→ Full loop on Linux, no NX
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```
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**Success criteria:**
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- [ ] 3 analytical benchmarks pass within 2% of theory
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- [ ] CalculiX vs Nastran delta < 5% on stress/displacement for shared benchmark
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- [ ] Full optimization loop completes 50+ trials unattended
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**Antoine gate:**
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1. Approve CalculiX vs Nastran parity tolerance (proposed: 5% on stress, 3% on displacement)
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2. Validate one benchmark result manually
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3. Review Build123d geometry quality for representative model
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**Risks:**
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- Gmsh mesh quality on sharp fillets → **Mitigation:** define mesh size presets, add Jacobian quality check
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- CalculiX .frd parsing edge cases → **Mitigation:** test against multiple element types (CQUAD4 equivalent, CHEXA equivalent)
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- Build123d geometry failures on complex shapes → **Mitigation:** start with simple parametric bracket, escalate complexity gradually
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---
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### Sprint 3: MVP Hardening + Client-Grade Post-Processing (1 week)
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**Goal:** Production-quality outputs from both solver lanes, side-by-side comparison capability.
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| Task | Owner | Autonomy | Deliverable |
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|------|-------|----------|-------------|
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| Implement `paraview_post.py` | Developer | 🟢 90% | Publication-quality figures (headless pvpython) |
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| Implement `auto_select.py` | Tech Lead → Developer | 🟡 75% | Toolchain routing rules (NX lane vs open lane) |
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| Implement `spec/validator.py` | Developer | 🟢 95% | AtomizerSpec v3.0 schema validation |
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| Dual-lane comparison report | Post-Processor → Developer | 🟢 85% | Side-by-side Nastran vs CalculiX with pass/fail |
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| Regression test suite | Auditor → Developer | 🟢 90% | Automated benchmark + parity checks |
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| MCP-CalculiX server | MCP Engineer → Developer | 🟡 70% | Tool-call interface for CalculiX |
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| MCP-Gmsh server | MCP Engineer → Developer | 🟡 70% | Tool-call interface for Gmsh |
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| Documentation: Integration Guide | Secretary | 🟢 95% | `docs/DEV/INTEGRATION-GUIDE.md` |
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**Success criteria:**
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- [ ] Dual-lane comparison passes on all 3 benchmarks
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- [ ] Automated regression suite runs in CI
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- [ ] MCP servers pass basic smoke tests
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**Antoine gate:**
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1. Approve report template and required figure list
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2. Define auto-select routing rules (when NX vs when open-source)
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3. Sign off MVP as "usable for real studies"
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**🏁 MVP EXIT — after Sprint 3, Atomizer can run full structural optimization on Linux without NX.**
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---
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### Sprint 4: CFD Lane — OpenFOAM (1–2 weeks)
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**Goal:** Automated CFD/thermal screening within the same orchestration framework.
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| Task | Owner | Autonomy | Deliverable |
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|------|-------|----------|-------------|
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| Install OpenFOAM (Docker recommended) | IT | 🟢 Full | Working `simpleFoam` / `buoyantSimpleFoam` |
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| Implement `openfoam_solver.py` | Tech Lead → Developer | 🟡 65% | Case generation + execution + result parsing |
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| Extend `gmsh_mesher.py` with CFD presets | Developer | 🟡 75% | Boundary layer meshing, inflation layers |
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| Extend contracts for CFD quantities | Tech Lead → Developer | 🟡 70% | Pressure, velocity, temperature fields in AtomizerResults |
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| 2 CFD validation cases | Tech Lead | 🟡 60% | Lid-driven cavity + pipe flow (known analytical/reference) |
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**Demo scenario:**
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```
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Electronics enclosure airflow
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→ STEP → Gmsh CFD mesh → OpenFOAM (buoyantSimpleFoam)
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→ PyVista thermal map + pressure drop
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→ Variant ranking by max temperature
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```
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**Antoine gate:**
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1. Lock one validated starter case template before generalization
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2. Define screening-fidelity defaults (mesh size, turbulence model)
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3. Validate thermal results against engineering judgment
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**Risk:** OpenFOAM setup complexity is high. Dictionary validation is error-prone.
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**Mitigation:** Start with one locked template, generalize only after it works.
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---
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### Sprint 5: Coupled Thermo-Structural — preCICE (1–2 weeks)
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**Goal:** Two-way coupled OpenFOAM ↔ CalculiX simulations.
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| Task | Owner | Autonomy | Deliverable |
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|------|-------|----------|-------------|
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| Install preCICE + adapters | IT | 🟢 Full | preCICE + CalculiX adapter + OpenFOAM adapter |
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| Implement `coupling.py` | Tech Lead → Developer | 🟡 60% | Coupled orchestration with convergence monitoring |
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| 1 coupled benchmark | Tech Lead | 🔴 50% | Heated plate with thermal expansion |
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**Antoine gate:** Approve coupling parameters and convergence criteria.
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**Risk:** Coupling divergence, debugging complexity.
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**Mitigation:** Conservative time-step, explicit convergence checks, one golden benchmark.
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---
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### Sprint 6: Multi-Objective + MDO — pymoo + OpenMDAO (1–2 weeks)
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**Goal:** Pareto optimization across multiple objectives and disciplines.
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| Task | Owner | Autonomy | Deliverable |
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|------|-------|----------|-------------|
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| Implement `pymoo_backend.py` | Optimizer → Developer | 🟢 85% | NSGA-II/III alongside Optuna |
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| Pareto front visualization | Post-Processor → Developer | 🟢 90% | Interactive Pareto plots |
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| OpenMDAO integration (if scope allows) | Tech Lead → Developer | 🟡 60% | MDO wiring for multi-discipline |
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| 1 multi-objective demo | Optimizer + Tech Lead | 🟡 70% | Mass vs stress vs temperature Pareto |
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**Antoine gate:** Define objective scaling and hard constraints.
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---
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## 5. Semi-Autonomous Workflow
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```
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┌─────────────────────────────────────────────────────────┐
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│ PER-SPRINT LOOP │
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│ │
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│ 1. Antoine picks sprint / approves scope [YOU] │
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│ 2. HQ researches + designs architecture [AUTO] │
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│ 3. Auditor reviews design for risks [AUTO] │
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│ 4. Antoine approves architecture (15 min) [YOU] │
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│ 5. Developer implements + writes tests [AUTO] │
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│ 6. Auditor reviews code against protocols [AUTO] │
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│ 7. Antoine validates one benchmark (2-3 hrs) [YOU] │
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│ 8. Merge → next sprint [AUTO] │
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│ │
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│ Your time: ~2-3 hours/sprint │
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│ HQ time: days of implementation/sprint │
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└─────────────────────────────────────────────────────────┘
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```
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**What runs fully autonomously (steps 2-3, 5-6):**
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- Research tool capabilities, formats, Python bindings
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- Design processor architecture and contract extensions
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- Implement Python adapters, parsers, converters
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- Write and run unit tests against analytical benchmarks
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- Audit code against Atomizer protocols
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- Generate regression reports
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**What needs your engineering judgment (steps 1, 4, 7):**
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- Tool priority sequencing (strategic call)
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- Architecture approval (15-min review)
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- Cross-solver parity acceptance (is 5% delta OK?)
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- Benchmark validation (does this match physics?)
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- Geometry quality assessment (does Build123d output look right?)
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---
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## 6. Quality Gates (Auditor-Defined)
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### Per-Processor Gate
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- [ ] Processor implements abstract base class correctly
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- [ ] Round-trip test: contract → native format → solve → parse → contract
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- [ ] At least 1 analytical benchmark passes within tolerance
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- [ ] Unit test coverage ≥ 80% for parser logic
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- [ ] Error handling for: missing files, solver crash, malformed output
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- [ ] Documentation: input/output formats, known limitations
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### Per-Sprint Gate
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- [ ] All processor gates pass
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- [ ] Integration test: full pipeline from AtomizerSpec → results
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- [ ] Regression: no existing tests broken
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- [ ] Parity check (if applicable): new solver vs reference solver
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- [ ] Tech Lead sign-off on physics validity
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- [ ] Auditor sign-off on code quality + protocol compliance
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### MVP Gate (Sprint 3 Exit)
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- [ ] 3 analytical benchmarks pass (cantilever, plate-hole, modal)
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- [ ] CalculiX vs Nastran parity < 5% stress, < 3% displacement
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- [ ] 50-trial optimization completes unattended
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- [ ] Dual-lane comparison report generates automatically
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- [ ] Antoine validates one real-world study through the new pipeline
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- [ ] All regression tests pass in CI
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---
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## 7. Risk Register
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| # | Risk | Impact | Likelihood | Mitigation | Owner |
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|---|------|--------|------------|------------|-------|
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| R1 | CalculiX vs Nastran parity exceeds tolerance | High | Medium | Start with simple geometries, document element type mapping, investigate mesh sensitivity | Tech Lead |
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| R2 | Gmsh mesh quality on complex geometry | Medium | Medium | Define quality thresholds, add Jacobian/aspect-ratio checks, fallback presets | Tech Lead |
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| R3 | Build123d limitations on complex parametric models | Medium | Low | Start simple, escalate complexity, keep NX lane as fallback | Developer |
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| R4 | Contract design locks in wrong abstractions | High | Low | Freeze contracts only after Sprint 1 validation, allow minor evolution in Sprint 2 | Tech Lead + Auditor |
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| R5 | Package dependency conflicts on T420 | Low | Medium | Use venv or Docker dev environment | IT |
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| R6 | OpenFOAM setup complexity delays Sprint 4 | Medium | High | Docker-first approach, one locked template | IT + Tech Lead |
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| R7 | Scope creep into expansion tools before MVP stable | High | Medium | Hard gate: no Sprint 4+ work until Sprint 3 exit criteria met | Manager + Auditor |
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| R8 | MCP server maintenance burden | Low | Medium | MVP cap at 4 MCP servers, thin wrappers only | MCP Engineer |
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---
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## 8. Tool Installation Reference
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### Sprint 0-2 (Core)
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```bash
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# Python packages
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pip install gmsh pygmsh build123d meshio pyvista
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# CalculiX solver
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sudo apt install calculix-ccx
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# ParaView (Sprint 3)
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sudo apt install paraview
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```
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### Sprint 4+ (Expansion)
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```bash
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# OpenFOAM via Docker
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docker pull openfoam/openfoam-dev
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# preCICE
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sudo apt install libprecice-dev python3-precice
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# pymoo
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pip install pymoo
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# OpenMDAO
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pip install openmdao
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```
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---
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## 9. Success Metrics
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| Metric | Sprint 3 Target | Sprint 6 Target |
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|--------|----------------|----------------|
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||
| Solver lanes operational | 2 (Nastran + CalculiX) | 4 (+OpenFOAM + coupled) |
|
||
| Optimization trials/hr (bracket-class) | 50+ | 100+ |
|
||
| Analytical benchmarks passing | 3 | 8+ |
|
||
| Cross-solver parity verified | Nastran ↔ CalculiX | + OpenFOAM thermal |
|
||
| Automation level (no human in loop) | 70% | 85% |
|
||
| MCP servers | 2 (CalculiX, Gmsh) | 4 |
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---
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## 10. Immediate Next Steps
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||
|
||
1. **Antoine:** Approve this plan and Sprint 0-1 scope
|
||
2. **IT/Developer:** Run Sprint 0 package installs (est. 1-2 hours)
|
||
3. **Tech Lead:** Finalize contract dataclass specs with field-level detail
|
||
4. **Developer:** Scaffold `atomizer/` package structure
|
||
5. **Auditor:** Prepare benchmark expected-value files for 3 analytical cases
|
||
6. **Manager:** Create Mission Dashboard tasks for Sprint 0 + Sprint 1
|
||
|
||
---
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*This plan is a living document. Update after each sprint retrospective.*
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