generated_hooks/weighted_objective_result.json

{
  "weighted_objective": 0.7169999999999999,
  "objective_type": "minimize",
  "inputs_used": {
    "norm_stress": 0.75,
    "norm_disp": 0.64
  },
  "formula": "0.7 * norm_stress + 0.3 * norm_disp"
}
feat: Complete Phase 3 - pyNastran Documentation Integration Phase 3 implements automated OP2 extraction code generation using pyNastran documentation research. This completes the zero-manual-coding pipeline for FEA optimization workflows. Key Features: - PyNastranResearchAgent for automated OP2 code generation - Documentation research via WebFetch integration - 3 core extraction patterns (displacement, stress, force) - Knowledge base architecture for learned patterns - Successfully tested on real OP2 files Phase 2.9 Integration: - Updated HookGenerator with lifecycle hook generation - Added POST_CALCULATION hook point to hooks.py - Created post_calculation/ plugin directory - Generated hooks integrate seamlessly with HookManager New Files: - optimization_engine/pynastran_research_agent.py (600+ lines) - optimization_engine/hook_generator.py (800+ lines) - optimization_engine/inline_code_generator.py - optimization_engine/plugins/post_calculation/ - tests/test_lifecycle_hook_integration.py - docs/SESSION_SUMMARY_PHASE_3.md - docs/SESSION_SUMMARY_PHASE_2_9.md - docs/SESSION_SUMMARY_PHASE_2_8.md - docs/HOOK_ARCHITECTURE.md Modified Files: - README.md - Added Phase 3 completion status - optimization_engine/plugins/hooks.py - Added POST_CALCULATION hook Test Results: - Phase 3 research agent: PASSED - Real OP2 extraction: PASSED (max_disp=0.362mm) - Lifecycle hook integration: PASSED Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com> 2025-11-16 16:33:48 -05:00			`{`
			`"weighted_objective": 0.7169999999999999,`
			`"objective_type": "minimize",`
			`"inputs_used": {`
			`"norm_stress": 0.75,`
			`"norm_disp": 0.64`
			`},`
			`"formula": "0.7 * norm_stress + 0.3 * norm_disp"`
			`}`