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Simulation to obtain reliability and availability estimates has been widely used by system designers to evaluate and compare alternative choices before making design decisions. However, traditionally that approach worked only if significant computer resources were available or designers accepted a significant time delay between design iterations. In this paper, we present an alternative approach to compute measures of interest for a family of models that represent alternative design choices that is significantly more efficient than the traditional approach. The new approach combines the existing single-clock multiple-system simulation with adaptive uniformization. We achieve the speedup by simulating all the alternative configurations of the discrete-event model simultaneously while amortizing the cost of enabled event set management. That allows us to explore and evaluate multiple configuration settings of a discrete-event model at the same time, significantly increasing the number of alternative versions of the model that are explored in a given amount of time.