Simulation Cost & Surrogate ROI Calculator
Put a real number on what your CAE/CFD pipeline costs: compute, solver licenses, and engineer time. Then see the payback and throughput gain of a surrogate model that answers in milliseconds instead of hours.
Presets are illustrative starting points; adjust every number to your own.
Your simulation workload
Solves submitted across the team
Queue-to-result on a full solve
Cluster time + solver seats
Salary + overhead
Meshing, boundary conditions, watching the solve
Runs inside the trained design envelope
The surrogate model
Milliseconds-to-seconds per prediction
Sanity-check the prediction
Full solves used to build the training set
Data pipeline, training, validation
How the math works
Cost per full run = compute/license ($40) + engineer time (1.5 hrs × $90/hr) = $175
Current annual cost = 2,400 runs/yr × $175 = $420,000
With the surrogate, the 1,680 replaceable runs/yr drop to near-zero compute + 3 min review each; the remaining 720 runs stay at full fidelity.
Payback = one-time build cost ÷ monthly savings. Throughput gain = wall-clock hours ÷ inference seconds, for the replaceable share.
Annual results
Throughput gain on the replaceable share
43.2K× faster
6 hrs → 0.5 sec per prediction. Design sweeps that took a weekend now finish while you read the mesh report.
Where this breaks down: a surrogate is trustworthy for interpolation inside the design envelope it was trained on. You still need full simulation to validate the surrogate, to certify final designs, and for any point that falls outside the trained range. Treat it as a fast filter, not a replacement for your solver.
Frequently Asked Questions
What is a surrogate model in simulation?
A surrogate (or reduced-order) model is a fast approximation trained on a set of high-fidelity CAE/CFD runs. Once trained, it predicts the same outputs (drag, stress, temperature) in milliseconds instead of hours, so engineers can explore a design space far more widely before committing to a full solve.
How do you calculate the ROI of a surrogate model?
Add up your current annual simulation cost (compute plus solver licenses plus fully-loaded engineer time per run). Estimate the share of runs a surrogate can handle inside its trained envelope; those drop to near-zero marginal cost. Net annual savings is the difference. Payback is the one-time build cost divided by monthly savings; the calculator computes it from your own numbers.
Can a surrogate model replace full simulation?
No, and it should not. A surrogate is trustworthy for interpolation inside the design envelope it was trained on. You still need full simulation to build and validate the surrogate, to certify final designs, and for any operating point outside the trained range. It works best as a fast first-pass filter that reserves expensive solves for the cases that matter.
How much faster is a surrogate than a full CFD or FEA run?
A solve that takes six wall-clock hours becomes a prediction in a fraction of a second. The exact factor depends on the physics and the model, and the calculator shows the throughput math for your numbers. The practical effect: design sweeps that used to take a weekend finish in minutes, so teams evaluate far more iterations for the same budget.