Method for calculating resistance of SCR denitration catalyst

Abstract

The invention discloses a method for calculating the resistance of an SCR denitration catalyst in the technical field of computer-aided engineering. The method comprises the following steps: establishing a mesoscopic three-dimensional model of the SCR denitration catalyst; performing grid division on the mesoscopic model; analyzing the model after grid division to obtain a resistance value of theSCR denitration catalyst under a mesoscopic condition; fitting the obtained resistance value to obtain a resistance calculation formula of the SCR denitration catalyst; establishing a macroscopic model of the SCR denitration catalyst, and obtaining an inertia resistance coefficient and a viscous resistance coefficient based on a resistance formula obtained through fitting; and carrying out numerical simulation analysis based on the macroscopic model to obtain the resistance value of the SCR denitration catalyst. Macroscopic and microscopic combined multi-scale numerical simulation is applied to the SCR denitration catalyst, so that the consumption of computer resources is greatly reduced, and the calculation efficiency is improved.

Description

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AI Technical Summary

Benefits of technology

This patented technique allows us to calculate resistances from different types of materials used in chemical reactions without having to use expensive equipment or complicated calculations. It involves simulating multiple steps at once during the reaction process, allowing researchers to study how these changes affect their performance over time. By doing this we aimed towards developing new methods that could improve industrial processes more efficiently.

Problems solved by technology

Technological Problem addressed in this patents relates to improving the performance and durability of selectively catalysed exhaust systems that use multiple layers or pores within an enclosed space called a tube. Current methods involve simulations based on computational fluiddynamics alone without considering any other factors like temperature and pressure distributions. Additionally, current models require expensive computing hardware and time-consumings, making their practicality limited. Therefore, new solutions must improve upon existing techniques while reducing costs associated with these issues.

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