Abstract Catalyst bed dilution by mixing active and inert particles is common practice for highly exothermic gas phase reactions for balancing the heat generation and heat removal out of the reactor tubes. The predicted reactor performance is commonly calculated assuming a perfectly mixed bed. However, loading a particle mixture into a reactor tube is an inherently statistical process, and thus fluctuations in local activity cannot be avoided which can lead to the formation of local hotspots. We have analyzed the influence of non-uniform activity profiles on the reactor behavior by simulation studies using 1- and 2-dimensional reactor models. Based on the results, an a priori criterion using dimensionless numbers was derived for the prediction of maximum temperature variations. The general applicability has been successfully proven for several reaction systems and process conditions. The derived correlation allows for considering the non-idealities at an early stage of reactor and process development.

中文翻译：

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稀释催化剂床中统计活性变化对热反应器行为的影响：先验标准的推导

摘要 通过混合活性颗粒和惰性颗粒来稀释催化剂床是高放热气相反应的常用做法，以平衡反应器管的发热和排热。预测的反应器性能通常是假设一个完美的混合床来计算的。然而，将颗粒混合物加载到反应器管中是一个固有的统计过程，因此无法避免局部活动的波动，这可能导致局部热点的形成。我们通过使用一维和二维反应器模型的模拟研究分析了非均匀活性分布对反应器行为的影响。基于这些结果，推导出使用无量纲数的先验标准来预测最大温度变化。已成功证明其适用于多种反应系统和工艺条件。导出的相关性允许在反应器和工艺开发的早期阶段考虑非理想情况。