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  • Summary & Details

Comprehensive Prediction of Deposit Formation in SCR Systems Using Integrated 1D Heat Transfer Model with Empirical Data from 3D CFD Simulations

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Author(E)1) Kazuma Sugimoto, 2) Ken Kawabe
Affiliation(E)1) Yanmar Power Technology Co., Ltd., 2) Yanmar Holdings Co., Ltd.
Abstract(E)Urea-based selective catalytic reduction (SCR) systems are widely used to meet stringent NOx emission standards in industrial diesel engines. However, suboptimal design of the urea-water solution (UWS) mixing pipes in SCR systems can lead to the formation of urea-derived solid deposits, which may adversely affect the system performance and reliability. Although recent advancements in deposit simulation technology using three-dimensional Computational Fluid Dynamics (3D CFD) have significantly improved the performance and compactness of mixing pipes, assessing deposit formation across all operating and environmental conditions remains challenging due to high simulation costs. This study introduces a novel computational method for predicting the formation and temperature of permanent liquid films from UWS injection which are closely related to deposit formation, along with new deposit evaluation criteria based on them. This proposed method integrates a one-dimensional heat transfer model with empirical thermal dissipation and film formation data derived from 3D CFD simulations, allowing for rapid prediction of film formation and temperature. By simplifying calculations to algebraic equations, this method enables rapid assessment of deposit formation across various operating conditions and provides a comprehensive evaluation of deposit formation in the SCR systems. The effectiveness of the proposed approach is validated through good correlations between simulation predictions and experimental results of deposit formation. In industrial machinery, versatile aftertreatment systems (ATS) are used across different applications and layouts. The proposed method enables speedy assessment of deposit formation by accounting for variations in ATS layouts, operating patterns, and environmental conditions during the design phase. It also supports the development of optimized insulation designs, balancing reliability, and cost-efficiency in product development.

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