Atomizer/knowledge_base/lac/session_insights/success_pattern.jsonl

{"timestamp":"2025-12-22T11:05:00","category":"success_pattern","context":"Organized M1 Mirror documentation with parent-child README hierarchy","insight":"DOCUMENTATION PATTERN: Studies use a two-level README hierarchy. Parent README at studies/{geometry_type}/README.md contains project-wide context (optical specs, design variables catalog, objectives catalog, campaign history, sub-studies index). Child README at studies/{geometry_type}/{study_name}/README.md references parent and contains study-specific details (active variables, algorithm config, results). This eliminates duplication, maintains single source of truth for specs, and makes sub-study docs concise. Pattern documented in OP_01_CREATE_STUDY.md and study-creation-core.md.","confidence":0.95,"tags":["documentation","readme","hierarchy","study-creation","organization"],"rule":"When creating studies for a geometry type: (1) Create parent README with project context if first study, (2) Add reference banner to child README: '> See [../README.md](../README.md) for project overview', (3) Update parent's sub-studies index table when adding new sub-studies."}
{"timestamp":"2025-12-22T11:05:00","category":"success_pattern","context":"Created universal mirror optical specs extraction tool","insight":"TOOL PATTERN: Mirror optical specs (focal length, f-number, diameter) can be auto-estimated from FEA mesh geometry by fitting z = a*r² + b to node coordinates. Focal length = 1/(4*|a|). Tool at tools/extract_mirror_optical_specs.py works with any mirror study - just point it at an OP2 file or study directory. Reports fit quality to indicate if explicit focal length should be used instead. Use: python tools/extract_mirror_optical_specs.py path/to/study","confidence":0.9,"tags":["tools","mirror","optical-specs","zernike","opd","extraction"],"rule":"For mirror optimization: (1) Run extract_mirror_optical_specs.py to estimate optical prescription from mesh, (2) Validate against design specs, (3) Document in parent README, (4) Use explicit focal_length in ZernikeOPDExtractor if fit quality is poor."}
{"timestamp":"2025-12-22T11:05:00","category":"success_pattern","context":"Implemented OPD-based Zernike method for lateral support optimization","insight":"PHYSICS PATTERN: Standard Zernike WFE analysis uses Z-displacement at original (x,y) coordinates. This is INCORRECT for lateral support optimization where nodes shift in X,Y. The rigorous OPD method computes: surface_error = dz - delta_z_parabola where delta_z_parabola = -delta_r²/(4f) for concave mirrors. This accounts for the fact that laterally displaced nodes should be compared against parabola height at their NEW position. Implemented in extract_zernike_opd.py with ZernikeOPDExtractor class. Use extract_comparison() to see method difference. Threshold: >10µm lateral displacement = CRITICAL to use OPD.","confidence":1.0,"tags":["zernike","opd","lateral-support","mirror","wfe","physics"],"rule":"For mirror optimization with lateral supports or any case where X,Y displacement may be significant: (1) Use ZernikeOPDExtractor instead of ZernikeExtractor, (2) Run zernike_opd_comparison insight to check lateral displacement magnitude, (3) If max lateral >10µm, OPD method is CRITICAL."}