论文标题
通过增强学习的分离过程的合成
Synthesis of separation processes with reinforcement learning
论文作者
论文摘要
本文显示了用于设计和优化蒸馏序列的商业流程模拟器软件（Aspen Plus V12）中强化学习（RL）的实现。 SAC剂的目的是通过利用蒸馏将碳氢化合物混合物分开。在这样做的同时，它试图最大程度地提高蒸馏序列产生的利润。代理的所有动作均由SAC代理在Python设定，并通过API在Aspen Plus中进行了通信。在此，通过使用Build-In-In-In Radfrac列模拟了蒸馏柱。有了这一点，建立了用于Python和Aspen之间的数据传输的连接，而代理商成功地展示了学习行为，同时增加了利润。尽管产生了结果，但ASPEN的使用速度很慢（190小时），并且发现Aspen不适合并行化。这使得Aspen无法兼容解决RL问题。代码和论文可在https://github.com/lollcat/aspen-rl上获得
This paper shows the implementation of reinforcement learning (RL) in commercial flowsheet simulator software (Aspen Plus V12) for designing and optimising a distillation sequence. The aim of the SAC agent was to separate a hydrocarbon mixture in its individual components by utilising distillation. While doing so it tries to maximise the profit produced by the distillation sequence. All actions of the agent were set by the SAC agent in Python and communicated in Aspen Plus via an API. Here the distillation column was simulated by use of the build-in RADFRAC column. With this a connection was established for data transfer between Python and Aspen and the agent succeeded to show learning behaviour, while increasing profit. Although results were generated, the use of Aspen was slow (190 hours) and Aspen was found unsuitable for parallelisation. This makes that Aspen is incompatible for solving RL problems. Code and thesis are available at https://github.com/lollcat/Aspen-RL
