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28 GHz case study

examples/06_full_pipeline_case_study.py runs the whole chain for a 5G mmWave scenario: unit-cell full-wave simulation, coupling-aware 8x8 array patterns, a 200 m link budget at 400 MHz bandwidth, and a 40-point trade study over array size and transmit power. EdgeFEM is required for this one:

pip install "apab[edgefem]"    # needs CMake + Eigen3 (see README)
python examples/06_full_pipeline_case_study.py

What the pipeline computes

  1. Unit cell (EdgeFEM) — a grounded patch on a Rogers-class substrate, swept 26–30 GHz with Floquet ports. EdgeFEM excites the cell with a plane wave, so for a grounded patch the reflection magnitude stays near one across the band and resonance appears as a reflection-phase transition, not a magnitude dip. The example detects resonance from the maximum phase derivative.
  2. Feed-port model (analytical) — return loss and impedance bandwidth come from a cavity model of the probe-fed patch. The two models cross-validate: FEM phase resonance at 28.50 GHz vs the analytical 28.40 GHz, under 0.4 % apart.
  3. Scan behavior — Floquet reflection versus scan angle characterizes the element in its array environment, feeding the coupling-aware pattern computation.
  4. Array pattern — 8x8 with taper, steered cuts, directivity and sidelobe level.
  5. System trade study — Latin-hypercube sampling over array size (4–16 per axis) and per-element power (10–500 mW) against a 5G NR comms scenario, with Pareto extraction.

The run writes six figures to examples/output/ (reflection phase, feed-port S11, scan behavior, link budget, trade study, array layout).

Why the hybrid modeling approach

Floquet-port simulation answers array-environment questions (scan impedance, phase response, blindness onset) that a feed-port model cannot; the analytical feed model answers match-bandwidth questions that a plane-wave excitation cannot. The case study keeps both and checks one against the other — the same split you would use with a commercial solver before committing to a fabricated design.

Companion materials

The repository includes a LaTeX write-up of this study (examples/case_study_paper.tex) and the agent-driven variant of the same workflow in the quickstart, where the LLM sequences these steps from a natural-language request instead of a script.