Files

Antoine d1261d62fd refactor: Major project cleanup and reorganization

## Removed Duplicate Directories
- Deleted old `dashboard/` (replaced by atomizer-dashboard)
- Deleted old `mcp_server/` Python tools (moved model_discovery to optimization_engine)
- Deleted `tests/mcp_server/` (obsolete tests)
- Deleted `launch_dashboard.bat` (old launcher)

## Consolidated Code
- Moved `mcp_server/tools/model_discovery.py` to `optimization_engine/model_discovery/`
- Updated import in `optimization_config_builder.py`
- Deleted stub `extract_mass.py` (use extract_mass_from_bdf instead)
- Deleted unused `intelligent_setup.py` and `hybrid_study_creator.py`
- Archived `result_extractors/` to `archive/deprecated/`

## Documentation Cleanup
- Deleted deprecated `docs/06_PROTOCOLS_DETAILED/` (14 files)
- Archived dated dev docs to `docs/08_ARCHIVE/sessions/`
- Archived old plans to `docs/08_ARCHIVE/plans/`
- Updated `docs/protocols/README.md` with SYS_15

## Skills Consolidation
- Archived redundant study creation skills to `.claude/skills/archive/`
- Kept `core/study-creation-core.md` as canonical

## Housekeeping
- Updated `.gitignore` to prevent `nul` and `_dat_run*.dat`

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

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

2025-12-12 11:24:02 -05:00

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Advanced Dashboard Enhancement Plan

Objective

Elevate the Atomizer Dashboard to a "Gemini 3.0 level" experience, focusing on scientific rigor, advanced visualization, and deep integration with the optimization engine. This plan addresses the user's request for a "WAY better" implementation based on the initial master prompt.

1. Advanced Visualization Suite (Phase 3 Enhancements)

Goal: Replace basic charts with state-of-the-art scientific visualizations.

1.1 Parallel Coordinates Plot

Library: Recharts (custom implementation) or D3.js wrapped in React.
Features:
- Visualize high-dimensional relationships between design variables and objectives.
- Interactive brushing/filtering to isolate high-performing designs.
- Color coding by objective value (e.g., mass or stress).

1.2 Hypervolume Evolution

Goal: Track the progress of multi-objective optimization.
Implementation:
- Calculate hypervolume metric for each generation/batch.
- Plot evolution over time to show convergence speed and quality.

1.3 Pareto Front Evolution

Goal: Visualize the trade-off surface between conflicting objectives.
Implementation:
- 2D/3D scatter plot of objectives.
- Animation slider to show how the front evolves over trials.
- Highlight the "current best" non-dominated solutions.

1.4 Parameter Correlation Matrix

Goal: Identify relationships between variables.
Implementation:
- Heatmap showing Pearson/Spearman correlation coefficients.
- Helps users understand which variables drive performance.

2. Iteration Analysis & 3D Viewer (Phase 4)

Goal: Deep dive into individual trial results with 3D context.

2.1 Advanced Trial Table

Features:
- Sortable, filterable columns for all variables and objectives.
- "Compare" mode: Select 2-3 trials to view side-by-side.
- Status indicators with detailed tooltips (e.g., pruning reasons).

2.2 3D Mesh Viewer (Three.js)

Integration:
- Load .obj or .gltf files converted from Nastran .bdf or .op2.
- Color Mapping: Overlay stress/displacement results on the mesh.
- Controls: Orbit, zoom, pan, section cuts.
- Comparison: Split-screen view for comparing baseline vs. optimized geometry.

3. Report Generation (Phase 5)

Goal: Automated, publication-ready reporting.

3.1 Dynamic Report Builder

Features:
- Markdown-based editor with live preview.
- Drag-and-drop charts from the dashboard into the report.
- LLM integration: "Explain this convergence plot" -> Generates text.

3.2 Export Options

Formats: PDF (via react-to-print or server-side generation), HTML, Markdown.
Content: Includes high-res charts, tables, and 3D snapshots.

4. UI/UX Polish (Scientific Theme)

Goal: Professional, "Dark Mode" scientific aesthetic.

Typography: Use a monospaced font for data (e.g., JetBrains Mono, Fira Code) and a clean sans-serif for UI (Inter).
Color Palette:
- Background: #0a0a0a (Deep black/gray).
- Accents: Neon cyan/blue for data, muted gray for UI.
- Status: Traffic light colors (Green/Yellow/Red) but desaturated/neon.
Layout:
- Collapsible sidebars for maximum data visibility.
- "Zen Mode" for focusing on specific visualizations.
- Dense data display (compact rows, small fonts) for information density.

Implementation Roadmap

Step 1: Advanced Visualizations
- Implement Parallel Coordinates.
- Implement Pareto Front Plot.
- Enhance Convergence Plot with confidence intervals (if available).
Step 2: Iteration Analysis
- Build the advanced data table with sorting/filtering.
- Create the "Compare Trials" view.
Step 3: 3D Viewer Foundation
- Set up Three.js canvas.
- Implement basic mesh loading (placeholder geometry first).
- Add color mapping logic.
Step 4: Reporting & Polish
- Build the report editor.
- Apply the strict "Scientific Dark" theme globally.

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