# chunks

id: 6d5f3e90f3fbe0db0524722ba71f4fda90c8b6b02270ff2572913ce0250e7d1f
path: memory/reviews/2025-02-10_optimization_strategy_review.md
source: memory
hash: ae8332e6e2d8993b3f92dd2e6ea1aaa90ce9601e7eaacbc28baec40e042b685b
model: gemini-embedding-001
text:
Additionally, some KB files have DV baselines as round numbers (20, 20) while CONTEXT.md has precise values (21.504, 25.162). The Gen 002 KB files were NOT updated with the later introspection data.

**REQUIRED ACTION:** After Blocker 1 is resolved, update all KB files to use consistent, authoritative values. Single source of truth.

### 🟡 WARNING 3 — Baseline "Likely FAILS" Displacement is Poorly Sourced

Section 1.5 states: *"~22 mm (unverified — awaiting baseline re-run)"* and *"The baseline design likely violates the displacement constraint (~22 mm vs 10 mm limit)."*

The 22mm figure comes from Gen 001 intake when the mass was supposedly ~974 kg. Since the mass baseline is now disputed (11.33 vs 1,133.01 kg), the displacement estimate is even less reliable. The entire strategy narrative — "optimizer must first find the feasible region" — hinges on the baseline being infeasible.

If the baseline is actually feasible (displacement < 10mm), the strategy is still valid but the emphasis shifts from "find feasibility" to "minimize mass within feasible region." The Phase 1→2 gate criteria and risk mitigations are correctly written to handle either case — this is good planning. But the narrative framing should not over-commit to the infeasible-baseline scenario.

**REQUIRED ACTION:** Await baseline solve results before finalizing strategy narrative. The algorithmic approach is sound either way, but the gate criteria at §6.4 should explicitly handle the case where the baseline is feasible.

---

## Suggestions (Non-Blocking)

embedding:
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id: c260f1004c29a65c4c371d1dc735301e6d7337321a7c932ca312fc1bf61d96ff
path: memory/reviews/2025-02-10_optimization_strategy_review.md
source: memory
hash: 41a824f36bcf5c0bb13d0865acd6f13cd284250fcf18e9070c165c4966d4a35d
model: gemini-embedding-001
text:
If the baseline is actually feasible (displacement < 10mm), the strategy is still valid but the emphasis shifts from "find feasibility" to "minimize mass within feasible region." The Phase 1→2 gate criteria and risk mitigations are correctly written to handle either case — this is good planning. But the narrative framing should not over-commit to the infeasible-baseline scenario.

**REQUIRED ACTION:** Await baseline solve results before finalizing strategy narrative. The algorithmic approach is sound either way, but the gate criteria at §6.4 should explicitly handle the case where the baseline is feasible.

---

## Suggestions (Non-Blocking)

### 💡 SUGGESTION 1 — Add Pre-Flight Geometric Feasibility Filter

Before sending any trial to NX, compute:
1. `ligament = hole_span / (hole_count - 1) - holes_diameter` → must be ≥ 30mm
2. `web_clear = 2 * beam_half_height - 2 * beam_face_thickness - holes_diameter` → must be > 0

If either fails, skip the NX evaluation and record as infeasible with max constraint violation. This saves compute and avoids NX geometry crashes.

### 💡 SUGGESTION 2 — Constraint Margin vs. Hard Limits in Deb's Rules

Section 3.5 proposes using 9.5mm / 123.5 MPa as optimizer targets while keeping 10mm / 130 MPa as hard limits. This is fine, but the implementation needs care: Deb's rules should use the **margin targets** for constraint calculation, not the hard limits. Otherwise the margin has no effect on the optimization.

embedding:
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id: 2c1eaf8d207cdc6878e5e7f7ce2c610c8dfe4169f0d68faad312e77b493542a4
path: memory/reviews/2025-02-10_optimization_strategy_review.md
source: memory
hash: c556b1cb159a6a5236b3839114a010e8119950f8d463bd7880d556b0fd40f836
model: gemini-embedding-001
text:
### 💡 SUGGESTION 2 — Constraint Margin vs. Hard Limits in Deb's Rules

Section 3.5 proposes using 9.5mm / 123.5 MPa as optimizer targets while keeping 10mm / 130 MPa as hard limits. This is fine, but the implementation needs care: Deb's rules should use the **margin targets** for constraint calculation, not the hard limits. Otherwise the margin has no effect on the optimization.

Alternatively, run the optimization on hard limits and apply the margin only during final validation (re-run best design and confirm it has ≥5% margin). This is simpler.

### 💡 SUGGESTION 3 — Document `n_startup_trials=0` Risk

Setting `n_startup_trials=0` in Phase 2 TPE (warm-started from Phase 1) is correct and efficient, but it means TPE immediately starts modeling from trial 1. If the Phase 1 data has uneven coverage (e.g., many infeasible points clustered in one region), TPE may develop a biased model early. Consider keeping `n_startup_trials=5-10` as insurance, or at minimum document this decision and the reasoning.

### 💡 SUGGESTION 4 — Convergence Criteria Should Track Feasible-Only

Section 6.2 convergence criteria ("best feasible objective unchanged for 20 trials") are correct. But ensure the implementation tracks ONLY feasible trials for the improvement check. If 20 trials all land infeasible, that's not "no improvement" — that's "still searching for feasibility."

### 💡 SUGGESTION 5 — Phase 1 Corner Tests

embedding:
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id: 366e4ec5c4588699958c85d160439cfc3bb1486a42712918ea09ff4052ff8d73
path: memory/reviews/2025-02-10_optimization_strategy_review.md
source: memory
hash: 463c9ffc99bd58fe869c0f11fb996f4cf93f82de12f3e98a1f51e8e3790bb99f
model: gemini-embedding-001
text:
Section 6.2 convergence criteria ("best feasible objective unchanged for 20 trials") are correct. But ensure the implementation tracks ONLY feasible trials for the improvement check. If 20 trials all land infeasible, that's not "no improvement" — that's "still searching for feasibility."

### 💡 SUGGESTION 5 — Phase 1 Corner Tests

Section 7.2 proposes 16 corner tests (2⁴). With the corrected spacing formula, we know some corners are geometrically infeasible (e.g., DV3=450 + DV4=15). The corner tests should include the geometric pre-check so only physically possible corners are sent to NX. Expected: ~10-12 valid corners out of 16.

---

## Checklist Responses

| # | Question | Verdict | Notes |
|---|----------|---------|-------|
| 1 | Problem formulation correct? | ✅ **YES** | Objective, constraints, DVs are well-formulated. Minor: mass expression needs resolution (Blocker 1) |
| 2 | Algorithm choices justified? | ✅ **YES** | LHS → TPE is well-reasoned with strong LAC backing. CMA-ES/surrogate rejection is properly justified |
| 3 | Trial budgets reasonable? | ✅ **YES** | 50 LHS + 60-100 TPE is appropriate for 4 DVs with unknown landscape |
| 4 | Constraint handling sound? | ✅ **YES** | Deb's rules via Optuna is the right call for an infeasible baseline |
| 5 | Integer handling correct? | ✅ **YES** | True integer via `IntDistribution(5,15)` + stratified LHS is correct |
| 6 | Any gaps blocking Study Builder? | ⚠️ **YES** | Blockers 1-2 must be resolved. Warnings 1-3 should be addressed |

embedding:
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id: e540ec2c0136b70a3582653f8e3a1f89c71d4f15c3cfe12cd2fb637f9f679951
path: memory/reviews/2025-02-10_optimization_strategy_review.md
source: memory
hash: 04b49c66b2d123692beaecebccafc8202b8cd1f491f8ae0e1277deb734039776
model: gemini-embedding-001
text:
| 4 | Constraint handling sound? | ✅ **YES** | Deb's rules via Optuna is the right call for an infeasible baseline |
| 5 | Integer handling correct? | ✅ **YES** | True integer via `IntDistribution(5,15)` + stratified LHS is correct |
| 6 | Any gaps blocking Study Builder? | ⚠️ **YES** | Blockers 1-2 must be resolved. Warnings 1-3 should be addressed |
| 7 | Hole collision feasibility (G5)? | ⚠️ **PARTIALLY** | Recognized but spacing formula is wrong (Blocker 2). Web height interaction missed |
| 8 | LAC lessons applied? | ✅ **YES** | Excellent LAC application — surrogate avoidance, baseline enqueue, copy-not-rewrite, kPa→MPa |

---

## Summary

The Optimizer produced an excellent, thorough strategy. The algorithm selection, constraint handling, risk mitigation, and LAC integration are all strong. The two blockers are data-integrity issues (mass/expression conflict, spacing formula) not architectural problems — they're fixable without redesigning the strategy.

**Path forward:**
1. Resolve Blocker 1 (CEO confirms authoritative mass expression and DV baselines)
2. Fix Blocker 2 (correct spacing formula to `span / (count - 1)`)
3. Address Warning 1 (add web-height feasibility constraint)
4. Sync KB files (Warning 2)
5. Await baseline solve (Warning 3) — can proceed with code in parallel

Once blockers are cleared, the strategy is ready for Study Builder.

---

*Technical Lead 🔧 — The physics is the boss.*

embedding:
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