To assess the ability of the surrogate to make accurate predictions outside its the region of the minimization, we calculated objective functions with the surrogate produced in each 𝑁 = 10 optimization for the parameter sets produced from all other 𝑁 = 10 optimizations. If the surrogates were globally predictive, we would observe low prediction error for the other minima; with high error, surrogates are likely only locally predictive. Results are shown in Figure . This analysis indicates that surrogates produced as a part of a multi-fidelity optimization are usually only locally predictive, as many have very large prediction errors for objective functions at some of the other minima. The surrogate that performs best is the surrogate from run 1; which estimates the objective to within 20% of the simulation value for all cases besides the optima from run 3, which is far away from the region where other surrogates generally have samples.