Enhanced NOx reduction and byproduct removal by (HC+OHC)/SCR over multifunctional dual-bed monolith catalyst

2012 ◽  
Vol 184 (1) ◽  
pp. 95-106 ◽  
Author(s):  
Mun Kyu Kim ◽  
Pyung Soon Kim ◽  
Byong K. Cho ◽  
In-Sik Nam ◽  
Se H. Oh
2021 ◽  
Vol 228 ◽  
pp. 430-432
Author(s):  
Jinhoon Choe ◽  
Wenting Sun ◽  
Timothy Ombrello ◽  
Campbell Carter
Keyword(s):  

Author(s):  
Shubham Kinekar ◽  
Shital Mone ◽  
Adnan Taqi ◽  
Pravin Mane ◽  
Bajirao Gawali ◽  
...  
Keyword(s):  

2003 ◽  
Vol 132 (3) ◽  
pp. 374-386 ◽  
Author(s):  
Xiaohai Han ◽  
Xiaolin Wei ◽  
Uwe Schnell ◽  
Klaus R.G. Hein
Keyword(s):  

Processes ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 515
Author(s):  
Thomas Freudenmann ◽  
Hans-Joachim Gehrmann ◽  
Krasimir Aleksandrov ◽  
Mohanad El-Haji ◽  
Dieter Stapf

This paper describes a procedure and an IT product that combine numerical models, expert knowledge, and data-based models through artificial intelligence (AI)-based hybrid models to enable the integrated control, optimization, and monitoring of processes and plants. The working principle of the hybrid model is demonstrated by NOx reduction through guided oscillating combustion at the pulverized fuel boiler pilot incineration plant at the Institute for Technical Chemistry, Karlsruhe Institute of Technology. The presented example refers to coal firing, but the approach can be easily applied to any other type of nitrogen-containing solid fuel. The need for a reduction in operation and maintenance costs for biomass-fired plants is huge, especially in the frame of emission reductions and, in the case of Germany, the potential loss of funding as a result of the Renewable Energy Law (Erneuerbare-Energien-Gesetz) for plants older than 20 years. Other social aspects, such as the departure of experienced personnel may be another reason for the increasing demand for data mining and the use of artificial intelligence (AI).


Author(s):  
Igor S. Anufriev ◽  
Evgeny P. Kopyev ◽  
Ivan S. Sadkin ◽  
Mariia A. Mukhina

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