Validated GPU Crowd Evacuation Simulation for Generative Design: IMO Tests, SFPE Flows, and 120 Buildings in NVIDIA Omniverse
GD–AI Loop 2.0 · Lab Notes #8 (rewritten) · validated crowd model → 20,947 buildings → AI The first version of this post trained a neural network on a crowd model that a fire engineer would call a toy: one person per 1.5 m cell, so the densest crowd it could form was 0.44 persons/m²; doors one cell wide; single-file stairs; no validation; three example buildings. This rewrite replaces the people model and shows the checks a practitioner would ask for before trusting any number — the IMO MSC.1/Circ.1533 test cases, SFPE flows and speed–density, and the same model run in JuPedSim. It then re-runs all 20,947 designs with occupant loads, pre-movement times and blocked-exit and blocked-stair scenarios, stages 120 of them at once in NVIDIA Omniverse, re-measures the Lab Notes #6 result, and retrains the network. Nov 6, 2026 — rewritten the same day after a practitioner's critique of v1 ("too elementary; why only two or three cases?") · Previous: Lab Notes #6 — evacuation sim...