A versatile modeling strategy for Steady State Isotopic Transient Kinetic Analysis (SSITKA) data, acquired in a plug flow reactor, is elaborated with particular attention to complex reaction networks and Fischer-Tropsch Synthesis as example. A spatial discretization scheme optimizing accuracy and CPU time is developed. For low switch time constants, the van Leer and van Albada flux limiter functions used in conjunction with the DASPK solver yields the lowest CPU time for the integration of the resulting ordinary differential equations. For larger switch time constants, conventional central differencing can be applied. A network generation methodology is implemented accounting for the isotopic labeling. It reduces the exponential dependence of the number of considered species on the carbon number to a quadratic dependence. For a reaction network allowing a maximum chain length of 5 carbon atoms a gain in CPU time up to a factor of 10 can be achieved.

详细阐述了在活塞流反应器中获取的稳态同位素瞬态动力学分析（SSITKA）数据的通用建模策略，并特别注意复杂的反应网络和费-托合成法。开发了一种优化精度和CPU时间的空间离散方案。对于低开关时间常数，与DASPK求解器配合使用的van Leer和van Albada通量限制器功能可为集成所得的常微分方程提供最低的CPU时间。对于较大的开关时间常数，可以应用常规的中央差分。实现了一种网络生成方法，解决了同位素标记问题。它将考虑的物种数对碳原子数的指数依赖性降低到二次依赖性。