I had to come up with a fairly complex FT-based process in Aspen Plus. The task is to calculate plant efficiency for varying boundary conditions. Because the calculations take a very long time, I am trying to use random forrest regression to estimate plant efficiency. The approach is to use a python script to access Aspen Plus via the COM interface to generate a large data set. In order to limit machine time, I would like to have multiple instances of Aspen Plus running at the same time. To do so I am using the multiprocessing toolbox to generate a pool of asynchronous workers. While the script works flawlessly for a single instance and when multi-threaded calculations are limited to several hundred cases, it starts to drop threads for larger data sets. The number of cases returned is random, but always a multiple of the number of Jobs designated to a thread.

I had to come up with a fairly complex FT-based process in Aspen Plus. The task is to calculate plant efficiency for varying boundary conditions. Because the calculations take a very long time, I am trying to use random forrest regression to estimate plant efficiency. The approach is to use a python script to access Aspen Plus via the COM interface to generate a large data set. In order to limit machine time, I would like to have multiple instances of Aspen Plus running at the same time. To do so I am using the multiprocessing toolbox to generate a pool of asynchronous workers. While the script works flawlessly for a single instance and when multi-threaded calculations are limited to several hundred cases, it starts to drop threads for larger data sets. The number of cases returned is random, but always a multiple of the number of Jobs designated to a thread.