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Dynamic modeling of processes involving phase changes can be challenging due to changes in the model equations caused by appearance and disappearance of equilibrium phases. Dynamic simulation of these processes requires the ability to detect the change in the number of phases and adapt the model to the new phase regime on the fly. In this work, an easy‐to‐use nonsmooth model for dynamic simulation of processes with vapor‐liquid equilibrium is presented. The presented model does not introduce any auxiliary variables or equations, nor does it require solution of an optimization problem to determine the new phase regime during the dynamic simulation. It can therefore be used for comprehensive simulation of, e.g., distillation columns, where the number of phases present can change during startup and shutdown. The nonsmooth model is illustrated through examples of an evaporator and a distillation column. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3334–3351, 2016

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Campaign continuous manufacturing (CM), characterized by relatively short operational windows such as a few weeks, is being explored as an alternative to traditional batch-wise manufacturing in the pharmaceutical industry. However, optimal operation in campaign CM can be challenging because of the significance of startup and shutdown phases, which can negatively affect on-specification production and plant economy. In this paper, the effectiveness and computational tractability of several known optimization approaches when applied to campaign CM are investigated. Inspired by the turnpike property in optimal control, a new approach is then proposed, which aims to maximize on-specification production explicitly rather than minimizing the startup/shutdown times as commonly adopted in high-volume industries. A main contribution in the new approach is that the resulting optimization formulation is guaranteed to be differentiable, despite the underlying hybrid dynamic system. Thus, it can be solved reliably using gradient-based algorithms. Case studies are presented to demonstrate the effectiveness of the proposed approach.