feat: Add TrialManager and DashboardDB for unified trial management

- Add TrialManager (trial_manager.py) for consistent trial_NNNN naming
- Add DashboardDB (dashboard_db.py) for Optuna-compatible database schema
- Update CLAUDE.md with trial management documentation
- Update ATOMIZER_CONTEXT.md with v1.8 trial system
- Update cheatsheet v2.2 with new utilities
- Update SYS_14 protocol to v2.3 with TrialManager integration
- Add LAC learnings for trial management patterns
- Add archive/README.md for deprecated code policy

Key principles:
- Trial numbers NEVER reset (monotonic)
- Folders NEVER get overwritten
- Database always synced with filesystem
- Surrogate predictions are NOT trials (only FEA results)

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

CLAUDE.md

@@ -140,8 +140,10 @@ Atomizer/
 │   └── extensions/          # EXT_01 - EXT_04
 ├── optimization_engine/     # Core Python modules
 │   ├── extractors/          # Physics extraction library
-│   └── gnn/                 # GNN surrogate module (Zernike)
+│   ├── gnn/                 # GNN surrogate module (Zernike)
+│   └── utils/               # Utilities (dashboard_db, trial_manager)
 ├── studies/                 # User studies
+├── archive/                 # Deprecated code (for reference)
 └── atomizer-dashboard/      # React dashboard
 ```
 
@@ -170,6 +172,70 @@ python run_gnn_turbo.py --trials 5000
 
 **Full documentation**: `docs/protocols/system/SYS_14_NEURAL_ACCELERATION.md`
 
+## Trial Management & Dashboard Compatibility
+
+### Trial Naming Convention
+
+**CRITICAL**: Use `trial_NNNN/` folders (zero-padded, never reused, never overwritten).
+
+```
+2_iterations/
+├── trial_0001/          # First FEA validation
+│   ├── params.json      # Input parameters
+│   ├── results.json     # Output objectives
+│   ├── _meta.json       # Metadata (source, timestamps, predictions)
+│   └── *.op2, *.fem...  # FEA files
+├── trial_0002/
+└── ...
+```
+
+**Key Principles:**
+- Trial numbers are **global and monotonic** - never reset between runs
+- Only **FEA-validated results** are trials (surrogate predictions are ephemeral)
+- Each trial folder is **immutable** after completion
+
+### Using TrialManager
+
+```python
+from optimization_engine.utils.trial_manager import TrialManager
+
+tm = TrialManager(study_dir, "my_study_name")
+
+# Create new trial (reserves folder + DB row)
+trial = tm.new_trial(params={'rib_thickness': 10.5}, source="turbo")
+
+# After FEA completes
+tm.complete_trial(
+    trial_number=trial['trial_number'],
+    objectives={'wfe_40_20': 5.63, 'mass_kg': 118.67},
+    weighted_sum=175.87,
+    is_feasible=True
+)
+```
+
+### Dashboard Database Compatibility
+
+All studies must use Optuna-compatible SQLite schema for dashboard integration:
+
+```python
+from optimization_engine.utils.dashboard_db import DashboardDB
+
+db = DashboardDB(study_dir / "3_results" / "study.db", "study_name")
+db.log_trial(params={...}, objectives={...}, weighted_sum=175.87)
+```
+
+**Required Tables** (Optuna schema):
+- `trials` - with `trial_id`, `number`, `study_id`, `state`
+- `trial_values` - objective values
+- `trial_params` - parameter values
+- `trial_user_attributes` - custom metadata
+
+**To convert legacy databases:**
+```python
+from optimization_engine.utils.dashboard_db import convert_custom_to_optuna
+convert_custom_to_optuna(db_path, "study_name")
+```
+
 ## CRITICAL: NX Open Development Protocol
 
 ### Always Use Official Documentation First