No single algorithm fits every application. The art is matching the method to the physics, the data, and the deployment constraint. Here's how we decide — and the full toolkit we decide between.
Four cells — each is a class of problem we see often, paired with the method we use for it and the reason.
Three coherent layers across the OpSimTech stack — from first-principles solvers to system-level twin enablers.
Fluid dynamics, turbulence, heat transfer. RANS, LES, DES for steady & transient flows.
Smoothed particle hydrodynamics. Free-surface, slurry, mixing, multiphase.
Discrete element method. Granular mechanics & particle-level manufacturing.
Physics-residual-trained neural solvers. PDEs encoded directly in loss.
ROM, Gaussian processes, ML with physics constraints in architecture or loss.
Sweep thousands of designs against multi-objective constraints.
Couple low- and high-fidelity intelligently — speed where you can, accuracy where you must.
Sensor streams fused into simulation states. The twin stays current with the real asset.
Optimization & scenario analysis on top of the twin. Outputs are decisions, not numbers.