> a Bayesian solution that, upon further examination with simulations, gives the wrong answer 90% of time on identical problems
If "with simulations" means either
"with simulations using a probability distribution different from the prior used in the Bayesian analysis"
or
"with simulations using a model different from the one used in the Bayesian analysis"
are we expected to conclude that there is something wrong with the Bayesian way?
Yes, in this case would should conclude there is something wrong with the Bayesian way. If you hand me a statistical method to e.g. estimate some parameter that frequently returns answers that are far from the truth, that is a problem. One cannot assume the prior exactly describes reality (or there would be no point in doing inference, because the prior already gives you the truth).
On the other hand, Frequentist methods do not claim anything concrete about reality. Only about long-run frequencies in hypothetical replications.
You may think that makes them better, it's your choice.