Simulation vs Experiment
Simulation and experiment are complementary sources of truth; each checks and extends the reach of the other.
Two ways to know
An experiment measures what a physical system actually does. A simulation computes what a model of that system predicts. Neither is the whole truth. Experiments are limited by what can be built and instrumented; simulations are limited by the fidelity of their equations and inputs.
Where simulation leads
Before a machine exists, simulation is the only way to explore it. The breeder Hyperion and the D–³He burner are, today, design-and-simulation efforts — no net-gain claim is made from built hardware before first-of-a-kind operation. Simulation lets designers test regimes that would be slow, costly, or unsafe to reach experimentally, and to do so across thousands of parameter combinations.
Where experiment leads
Reality contains effects that no model fully captures: fabrication imperfections, unexpected instabilities, material behavior under real neutron flux. Experiments reveal these, and in doing so expose where models are wrong.
The validation handshake
- Simulation predicts a measurable quantity before the experiment runs.
- The experiment measures it.
- Agreement builds confidence; disagreement locates a modeling error.
- The model is corrected and the loop repeats.
Verification versus validation
Verification asks whether the code correctly solves its equations. Validation asks whether those equations correctly describe reality. A simulation can be perfectly verified and still invalid. Only comparison with experiment settles validity, which is why the two must be planned together rather than in sequence.