...
首页> 外文期刊>Journal of engineering for gas turbines and power: Transactions of the ASME >Control-Oriented Reduced-Order Modeling of Conversion Efficiency in Dual-Layer Washcoat Catalysts With Accumulation and Oxidation Functions
【24h】

Control-Oriented Reduced-Order Modeling of Conversion Efficiency in Dual-Layer Washcoat Catalysts With Accumulation and Oxidation Functions

机译:

获取原文
获取原文并翻译 | 示例

摘要

This work proposes a model for predicting conversion efficiency in multifunctional catalysts with dual-layer washcoat. The mass transfer is more relevant in these devices than in single-layer washcoats due to additional transport steps between the catalytic layers. In addition, the different reaction mechanisms between layers make the concentration of the chemical species differ in each layer. To deal with this boundary while considering the need for real-time computation, a reduced-order explicit solver for the convective diffusive reactive transport is presented for the case of dual-layer washcoats. Assuming one-dimensional quasi-steady flow, the solution procedure consisted of substituting the diffusive interfacial fluxes in the bulk gas and washcoat conservation equations by expressions that depend explicitly on the average concentration in the gas phase. The solution was then applied to model the performance of dual-layer oxidation catalysts with reductant accumulation in one washcoat layer, such as diesel oxidation catalyst (DOC) and ammonia slip catalyst (ASC) systems, during driving cycles. First, the response of these catalysts was analyzed by comparing them against experimental data and considering additional parameters provided by the model. Next, the importance of the mass transfer limitations was discussed to complete the analysis. The proposed model was compared with a simplified solver where the mass transfer steps were omitted, thus deteriorating the prediction capabilities in some driving cycle phases. Finally, a sensitivity study was performed to assess the impact of the mesh size on the prediction capabilities and computational requirements.

著录项

相似文献

  • 外文文献
  • 中文文献
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号