Engineering workflow models are frequently used to optimize an engineering endeavor for some well-defined performance metrics, such as time-to-market or monetary costs. Static workflow analysis is often insufficient due to the complex interleavings of different activities and the interplay with limited resources. Simulation-based techniques provide a feasible alternative to static analysis. In this paper, we provide an automated translation from engineering workflow models to DEVS (Discrete Event System Specification) models, useful for simulation and subsequent performance evaluation. Our translation supports the vast majority of the essential workflow control patterns, previously identified by van der Aalst et al. Thanks to the use of simulation, our approach is able to deal with stochastically varying activity execution times and workflow decisions, potentially evolving between subsequent iterations of the workflow. Our approach is implemented in the Modelverse, where the mapping to and simulation of DEVS models remains completely hidden from the process modeler.