18 lines
7.5 KiB
JSON
18 lines
7.5 KiB
JSON
|
{
|
|||
|
|
"schemaVersion": "1.1",
|
|||
|
|
"runId": "orch-isogrid-test-02-techlead",
|
|||
|
|
"agent": "tech-lead",
|
|||
|
|
"status": "partial",
|
|||
|
|
"result": "## Review: P-Adaptive-Isogrid vs State-of-the-Art\n\n### CRITICAL NOTE\nWebster's research payload was **empty** — no external research was provided. This review is based on my own knowledge of isogrid optimization literature and the full technical spec (`docs/technical-spec.md`).\n\n---\n\n### (1) What We Already Implement vs What's Missing\n\n**Already Implemented (strengths):**\n- ✅ Spatially-varying density field with exponential kernels — this is solid and aligns with modern variable-density lattice approaches\n- ✅ Constrained Delaunay triangulation (Shewchuk's Triangle) — industry-standard for quality mesh generation\n- ✅ Manufacturing constraints embedded in geometry generation (min rib width, fillet radii, keepout zones, min pocket size) — this is ahead of many academic tools that ignore manufacturability\n- ✅ Reserved-region AFEM architecture — elegant solution to the load/BC persistence problem\n- ✅ TPE (Optuna) for 15-param optimization — appropriate for this dimensionality\n- ✅ JSON-only geometry transfer — eliminates CAD format drift\n- ✅ Hole weight classification system — practical for real engineering use\n- ✅ V2 stress-feedback roadmap — this is the right direction\n\n**Missing from State-of-the-Art:**\n- ❌ **No topology optimization seeding** — modern approaches (SIMP/LSM) generate optimal material layouts that could seed/validate the density field rather than relying purely on distance-based heuristics\n- ❌ **No buckling consideration** — isogrid pockets are buckling-critical; current objective only checks stress/displacement. SOL 105 eigenvalue buckling or local pocket buckling analytical checks are absent\n- ❌ **No multi-objective Pareto front** — single penalized objective conflates mass/stress/displacement; Optuna supports multi-objective (NSGA-II/MOTPE) natively\n- ❌ **No anisotropic density** — density field is isotropic (same in all directions). Real load paths are directional; ribs aligned with principal stress directions are more efficient\n- ❌ **No rib height variation** — current model assumes constant plate thickness with pocket depth = full thickness. Variable-depth pockets (partial machining) are common in aerospace isogrids\n- ❌ **No analytical validation benchmarks** — NASA CR-124075 isogrid handbook provides closed-form solutions for regular patterns; no comparison framework exists\n- ❌ **No surrogate model acceleration** — 2000 trials × 2 min = 67 hours. Gaussian process or neural network surrogates could cut this 5-10×\n\n---\n\n### (2) Top 5 Prioritized Improvements for Phase 1 (Python Brain Standalone)\n\n**P1: Local Pocket Buckling Check (HIGH PRIORITY)**\nAdd an analytical pocket buckling estimate during geometry generation. For each triangular pocket, compute the critical buckling stress using plate buckling theory (σ_cr = k·π²·E·t²/(12(1-ν²)·b²) where b = pocket inscribed diameter). Flag/penalize pockets where σ_cr < allowable. This is cheap (no FEA needed), catches the #1 failure mode of isogrids, and can be a geometry-phase reject criterion.\n\n**P2: Principal Stress Direction Alignment (MEDIUM-HIGH)**\nAdd an optional anisotropic term to the density field. Even without stress feedback, the user can specify a dominant load direction. Modify spacing to be anisotropic: s_along = s(x)·(1+ε), s_across = s(x)·(1-ε), where ε is a new optimization parameter. This biases triangles to elongate perpendicular to load paths, creating preferential rib alignment. Cheap to implement in Triangle via anisotropic area constraints.\n\n**P3: Multi-Objective Support (MEDIUM)**\nRefactor the objective function to return (mass, max_stress, max_displacement) as separate objectives. Use Optuna's `NSGAIISampler` or `MOTPESampler`. This gives the engineer a Pareto front to choose from rather than a single point that depends on arbitrary penalty weights. The penalty weights are currently hidden design decisions that bias the result.\n\n**P4: Analytical Benchmark Suite (MEDIUM)**\nImplement NASA CR-124075 close
|
|||
|
|
"deliverable": {
|
|||
|
|
"type": "review",
|
|||
|
|
"title": "P-Adaptive-Isogrid Technical Review — State-of-Art Gap Analysis",
|
|||
|
|
"path": null,
|
|||
|
|
"summary": "Gap analysis identifying 7 missing SOTA techniques, 5 prioritized Phase 1 improvements (buckling check, load alignment, multi-objective, benchmarks, smoothing), and 5 architecture risks"
|
|||
|
|
},
|
|||
|
|
"artifacts": [],
|
|||
|
|
"confidence": "medium",
|
|||
|
|
"notes": "Webster's research payload was EMPTY — no external research was provided for comparison. Review is based on internal knowledge of isogrid SOTA. Confidence would be HIGH with Webster's actual research to cross-reference. Recommend re-running with Webster's research populated.",
|
|||
|
|
"timestamp": "2026-02-16T08:37:00-05:00"
|
|||
|
|
}
|