Development of NOx removal process for LNG evaporation system: Comparative assessment between response surface methodology (RSM) and artificial neural network (ANN)

Kim, Ziehyun; Shin, Yeonju; Yu, Jihye; Kim, Geonjoong; Hwang, Sungwon

doi:10.1016/j.jiec.2019.02.020

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Development of NOx removal process for LNG evaporation system: Comparative assessment between response surface methodology (RSM) and artificial neural network (ANN)

Kim, Ziehyun;
Shin, Yeonju;
Yu, Jihye;
Kim, Geonjoong;
Hwang, Sungwon

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WEB OF SCIENCE

41

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43

초록

In this work, response surface methodology and artificial neural network were adopted to build a model of a NOx removal system in a LNG terminal that estimates the released amounts of NOx in flue gas from a submerged combustion vaporizer. A small-scale SCV setting was prepared for the experiment, and it was operated under various conditions (i.e., changes of residence time, flow rate of the air, water temperature, and pH of the water). The simulation results demonstrated good agreement between both models and the experimental data, although the ANN model showed a higher accuracy than that of the RSM model. (C) 2019 The Korean Society of Industrial and Engineering Chemistry. Published by Elsevier B.V. All rights reserved.

키워드

Response surface methodology (RSM); Artificial neural network (ANN); NOx reduction; Submerged combustion vaporizer (SCV); Modeling; Optimization; FUNCTIONALIZED SILICA; EXPERIMENTAL-DESIGN; AQUEOUS-SOLUTIONS; OPTIMIZATION; PREDICTION; ABSORPTION; NANOPARTICLES; TEMPERATURE; PERFORMANCE; COMBUSTION

제목: Development of NOx removal process for LNG evaporation system: Comparative assessment between response surface methodology (RSM) and artificial neural network (ANN)

저자: Kim, Ziehyun; Shin, Yeonju; Yu, Jihye; Kim, Geonjoong; Hwang, Sungwon

DOI: 10.1016/j.jiec.2019.02.020

발행일: 2019-06-25

유형: Article

저널명: Journal of Industrial and Engineering Chemistry

권: 74

페이지: 136 ~ 147