Calculix Sizing Optimization

CalculiX Sizing Optimization

Two-stage sizing/parameter optimization: minimize mass subject to stress, displacement, or natural-frequency constraints by editing scalar design variables in place (shell thickness, beam section, material E/nu/density, load magnitude). The mesh and geometry never change — only scalar cards.

This is sizing optimization, not topology optimization. It thins sections; it does not redistribute material in space.

When to Use

Use when an agent must lighten a CalculiX shell or beam model while keeping von Mises stress and displacement within limits (static deck), or must lighten it while keeping a natural frequency above a resonance floor (modal deck). Driven by the optimize_structure_tool MCP tool.

Do NOT use for:

• Solid (C3D8 / C3D8R) models. Solids expose no scalar geometry card — their mass is set by node-defined volume x density, so there is no thickness to thin. Material/load variables on a solid are degenerate for mass minimization (density changes mass but not stiffness; E changes stiffness but not mass). Solid lightweighting needs shape or topology optimization, which is a different problem and is not covered here.
• Topology optimization (material distribution over a fixed mesh) — separate, future work.

Workflow

1. parse_inp / list_design_vars_tool — confirm the deck and find the shell.<elset>.thickness (or beam section) var_id and its current value.
2. Choose bounds {var_id: [lower, upper]} to bracket the search. Mass falls monotonically with shell/beam thickness.
3. optimize_structure_tool — run the two-stage loop (LHS sweep, then coordinate descent). Each evaluation is a real ccx solve, so set max_solves to bound wall time.
4. Inspect the result: best (vars, mass_kg, stress_vm, disp, feasible, mass_reduction_pct), converged / termination_reason, and history.
5. Optional: export_results_tool on the persisted <stem>.optimized.inp to render the optimized design in the viewer.

Rules

• Frame results as sizing/parameter optimization (section sizing), never topology.
• Defaults: minimize mass s.t. max von Mises < 250 MPa and max displacement < 1.5 mm; pass objective / constraints to override.
• Match the constraint set to the deck: a *STATIC deck reports max_stress_vm / max_disp; a *FREQUENCY deck reports freq_<N>_hz (mode N in Hz, from the .dat eigenvalue table) and nothing else. Mixing a stress constraint into a modal optimization makes every point infeasible — the run warns about missing metrics rather than failing opaquely.
• Avoid-resonance runs: on a modal deck pass e.g. constraints=[{"metric": "freq_1_hz", "op": ">", "value": 300.0}]; thinning stops where mode 1 sits just above the floor. Constraint metric names are validated (mass, max_stress_vm, max_disp, freq_<N>_hz).
• The acceptance rule assumes shell/beam thickness (mass-monotone). Material E and load magnitude are exposed as variables but are not validated for mass-minimization — prefer section thickness.
• Units follow the .inp (commonly mm-t-s-MPa); mass_kg is reported in kg.
• A converged=False result is not a failure: best is the lightest feasible point found, and bound_limited tells whether it already sits at the box optimum (widen the bounds to do better).

Example

MCP/CalculiX/examples/bracket.inp is a public S4 shell bracket (steel plate, clamped edge, transverse tip load). Starting from thickness 8 mm with bounds {"shell.PLATE.thickness": [2.0, 8.0]} and n_lhs=8, the optimizer converges to ~4.1 mm — about -48% mass — while keeping stress < 250 MPa and displacement < 1.5 mm.

MCP/CalculiX/examples/plate_modal.inp is the avoid-resonance counterpart: a public S4 shell cantilever plate with a 5-mode *FREQUENCY step. With constraints=[{"metric": "freq_1_hz", "op": ">", "value": 30.0}] the optimizer thins from 4 mm to ~3.23 mm — -19% mass, f1 = 30.4 Hz — matching the Euler-Bernoulli hand calc t* = 30 / 9.29 ≈ 3.23 mm for L = 300 steel (f1 ≈ (1.8751²/2π)(t/L²)√(E/12ρ)).