18 lines
3.7 KiB
JSON
18 lines
3.7 KiB
JSON
{
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"schemaVersion": "1.1",
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"runId": "orch-1771275609-d6136ddd",
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"agent": "tech-lead",
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"status": "complete",
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"result": "## Technical Readiness Assessment: Variable Density Lattice Structures\n\n### Research Quality\nWebster's research is solid at a survey level. The key insight — that 'Delaunay adaptive isogrid' maps to the well-established field of graded lattice structures — is correct and important. It means we're not chasing a niche technique; there's a mature body of work to draw from.\n\n### Our Readiness: MEDIUM-LOW\n\n**What we have:**\n- Strong FEA/optimization foundation (SOL 200, topology optimization experience)\n- Atomizer's LAC framework can handle parametric sweeps and result extraction\n- NX/Simcenter toolchain with lattice structure support in newer versions\n\n**What we lack:**\n1. **Homogenization expertise** — Mapping lattice unit cell properties to continuum-level material cards is non-trivial. We'd need to build or validate RVE models for each cell topology we want to use.\n2. **AM process knowledge** — Self-supporting constraints, overhang angles, minimum feature sizes are manufacturing-specific. Without a target AM process and machine, optimization is academic.\n3. **Lattice meshing pipeline** — Going from a density field to an actual lattice geometry that can be meshed and validated is a significant toolchain gap. NX has some capability here but we haven't exercised it.\n4. **Validation data** — No test specimens, no correlation between predicted and actual lattice performance.\n\n### Key Challenges\n1. **Computational cost** — Graded lattice optimization with homogenization is expensive. Our current compute setup (single workstation) may be a bottleneck for anything beyond small components.\n2. **Two-scale problem** — The macro-level optimization and micro-level lattice behavior are coupled. Getting this right requires careful methodology.\n3. **Post-processing** — Extracting meaningful stress/strain results from lattice structures requires different approaches than solid elements.\n\n### Recommended First Steps\n1. **Scope a pilot problem** — Pick a simple bracket or plate with known loading. Run standard topology optimization first, then attempt lattice infill using NX's built-in tools. This tests the toolchain without custom code.\n2. **Build one RVE model** — Take a single unit cell (e.g., BCC or octet-truss), model it in detail, extract effective properties via homogenization. This builds the foundational skill.\n3. **Define the AM target** — We cannot optimize for manufacturability without knowing the process (SLM, EBM, DLP?) and material. This is a business decision that gates technical work.\n4. **Literature deep-dive on homogenization** — Specifically Hashin-Shtrikman bounds and asymptotic homogenization for lattices. This is the theory we need.\n\n### Bottom Line\nThe technology is mature in academia but implementing it properly requires filling real gaps in our pipeline — especially homogenization, AM constraints, and lattice geometry generation. I recommend a 2-3 week pilot study on a simple component before committing to any client work involving graded lattices.",
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"deliverable": {
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"type": "analysis",
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"title": "Readiness Assessment: Variable Density Lattice Structures",
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"path": null,
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"summary": "Assessment of team readiness to implement graded lattice optimization, identifying gaps and recommending a pilot study approach."
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},
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"artifacts": [],
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"confidence": "high",
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"notes": "Assessment assumes current NX/Simcenter toolchain and single-workstation compute. Readiness level would change significantly if we partner with an AM shop or acquire lattice-specific software (e.g., nTopology).",
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"timestamp": "2026-02-16T16:00:45.000-05:00"
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}
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