Simulation is besides experimentation the major method for designing, analyzing and optimizing chemical processes. The ability of simulations to reflect real process behavior strongly depends on model quality. Validation and adaption of process models are usually based on available plant data. Using such a model in various simulation and optimization studies can support the process designer in his task. Beneath steady state models there is also a growing demand for dynamic models either to adapt faster to changing conditions or to reflect batch operation. In this contribution challenges of extending an existing decision support framework for steady state models to dynamic models will be discussed and the resulting opportunities will be demonstrated for distillation and reactor examples.

除了实验以外，仿真是设计，分析和优化化学过程的主要方法。仿真反映真实过程行为的能力在很大程度上取决于模型的质量。过程模型的验证和调整通常基于可用的工厂数据。在各种仿真和优化研究中使用这种模型可以为流程设计人员的工作提供支持。在稳态模型下，对动态模型的需求也在不断增长，以更快地适应变化的条件或反映批处理操作。在此贡献中，将讨论将稳态模型的现有决策支持框架扩展为动态模型的挑战，并将为蒸馏和反应器示例演示所产生的机会。