A Numerically Efficient Method for the Prediction of Nitrogen Oxide Emissions in Industrial Furnaces. Issue 12 (16th October 2020)

• Record Type: Journal Article
• Authors: Spijker, Christoph; Swaminathan, Senthilathiban; Raupenstrauch, Harald
• Other Names: Schenk Johannes guestEditor.; Bürgler Thomas guestEditor.
• Is Part Of: Steel research international. Volume 91:Issue 12(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-10-16
• Subjects: computational fluid dynamics (CFD) -- combustion -- NOX -- post-processor; Steel -- Periodicals; Steel -- Metallurgy -- Periodicals; 669.142
• DOI: 10.1002/srin.202000239
• Languages: English
• ISSNs: 1611-3683

Abstract

Abstract : Nitrogen oxides emissions are a concern in industrial furnaces, due to constantly increasing environmental requirements. A cost‐effective way to reduce emissions is an optimization of the burners in the furnace using computational fluid dynamics (CFD) methods. Still, state of the art approaches are computationally too expensive for real scale geometries such as industrial furnaces, or can not predict the nitrogen concentrations with sufficient accuracy. Therefore, the development of nitrogen oxides post‐processors was defined in K1‐Met projects in 2012. Currently, there are three different variations available, where the generation 2.0+ is the latest development. Abstract : Increasing environmental requirements request lower nitrogen oxides emissions for industrial furnaces. The computational fluid dynamics (CFD) methods are a cost‐effective way to reduce emissions by burner optimization, but state of the art approaches are computationally too expensive. Therefore, the development of nitrogen oxides post‐processors was started in 2012. This article explains the approaches of the current generation 2.0+.