一种简单的ANNs-RSM耦合方法，通过使用Ru促进Co / Al2O3催化剂的微通道反应器对费托合成的产物分布进行建模,International Journal of Energy Research

当前位置： X-MOL 学术 › Int. J. Energy Res. › 论文详情

Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)

一种简单的ANNs-RSM耦合方法，通过使用Ru促进Co / Al2O3催化剂的微通道反应器对费托合成的产物分布进行建模
International Journal of Energy Research ( IF 4.3 ) Pub Date : 2019-11-22 , DOI: 10.1002/er.4990
Yong Sun _{1,

2} , Gang Yang ₃ , Mengxia Xu _{1,

4} , Jian Xu ₅ , Zhi Sun ₆

Affiliation

开发了一种使用混合人工神经网络（ANN）-响应面方法（RSM）的简单方法，以Ru促进的钴基催化剂和Al ₂ O ₃为载体在费托微通道反应器中对详细的产品分布进行建模。（FT）合成。使用独立的过程参数进行训练，所建立的模型能够预测碳氢化合物的产量分布，即石蜡形成率（C ₂ -C ₁₅）和烯烃与石蜡的比率（OPR C ₂ -C ₁₅）在可接受的不确定性范围内。对比了使用Langmuir-Hinshelwood-Hougen-Watson（LHHW）方法的ANNs-RSM模型和综合机制模型，以识别该模型在复杂FT合成建模中的一些固有优势。拟议的ANNs-RSM模型显示出其吸引人的优点，即收敛速度更快和准确性更高（ANNs-RSM模型的不确定度小于±10％，而LHHW模型的不确定度小于±15％，除了一些例外的高误差不确定度在某些实验条件下）。通过建立的ANNs-RSM模型可以轻松地识别并定量分析对FT合成过程中产物分布和烃形成速率的统计意义。

"点击查看英文标题和摘要"

A simple coupled ANNs‐RSM approach in modeling product distribution of Fischer‐Tropsch synthesis using a microchannel reactor with Ru‐promoted Co/Al2O3 catalyst

A simple approach using hybrid artificial neural networks (ANNs)‐response surface methodology (RSM) was developed to model the detailed product distribution using Ru‐promoted cobalt‐based catalyst with Al₂O₃ as the support in a microchannel reactor for Fischer‐Tropsch (FT) synthesis. Using the independent process parameters for training, the established model is capable of predicting hydrocarbon production distributions, ie, paraffin formation rate (C₂‐C₁₅) and olefin to paraffin ratio (OPR C₂‐C₁₅) within acceptable uncertainties. The ANNs‐RSM model and comprehensive mechanistic model using the Langmuir‐Hinshelwood‐Hougen‐Watson (LHHW) approach were compared to identify a few inherent advantages of the proposed model in modeling complex FT synthesis. The proposed ANNs‐RSM model shows its appealing merits, ie, faster converge and higher accuracy (less than ±10% uncertainties was achieved from ANNs‐RSM model, while LHHW model achieved less than ±15% uncertainties except a few exceptional high errors uncertainties at certain experimental conditions). The statistical significances to the product distributions and hydrocarbon formation rate during FT synthesis could be easily identified and quantitatively analyzed by the established ANNs‐RSM model. The future effective alternative of kinetic study of the complex system such as FT synthesis in the microstructured reactor might follow the methods of using empirical reliable approach for process optimization together with mechanistic kinetic study for detailed reaction pathway discrimination.

更新日期：2019-11-22

点击分享查看原文

点击收藏

阅读更多本刊新发论文本刊介绍/投稿指南