**4. Conclusion**

A multi-scale steam cracking model was established in this chapter. An elementary reaction network was generated to obtain a more accurate and robust model. The results showed that the established multi-scale model agrees well with the industrial data. A surrogate coke thickness model is thus proposed to make multi-period optimization with parallel simulation possible. A case study showed that multi-period optimization with parallel computing possesses an 8.55 x speedup compared to optimization with serial simulation. Parallel computing makes real-time optimization (RTO) possible in multi-period optimization. The average error of optimization using a parallel simulation model was 0.04% compared to optimization using a serial model. The error was deemed acceptable for the optimization of large-scale industrial steam cracking processes.

Optimization using the parallel computing method can also be used in other aspects of chemical processes. Due to the complexity of chemical processes, it is always difficult to conduct a simulation or optimization using a multi-scale model. The connections of different levels in a multi-scale model or different equipment in chemical process can be decoupled and transferred to a multiple sub-system model, which can be simulated in parallel. This method can bring powerful computing performance into play in chemical engineering.
