Optimal Design of an Ambient Air Vaporizer using Numerical Model and DIRECT Algorithm

Yongkyu Lee; Jonggeol Na; Wonbo Lee

doi:10.1016/B978-0-444-64241-7.50294-9

Optimal Design of an Ambient Air Vaporizer using Numerical Model and DIRECT Algorithm

Yongkyu Lee, Jonggeol Na, Wonbo Lee

Department of Chemical Engineering & Materials Science

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

4 Scopus citations

Abstract

The ambient air vaporizer (AAV) using ambient air as heat source was environment-friendly method to vaporize LNG. The main problem of the vaporizer is performance degradation caused by frost formation on surface of tube. Determining the appropriate value of design variables under given climate is a critical issue. In this paper, design optimization in the vaporizer is performed using DIRECT algorithm whose result is compared with the result obtained by GA. Time series dataset including temperature and relative humidity of air for a year is categorized using k-means clustering. Finally, the optimal design shows 23.4 % improved performance of AAV and defrosting time is drastically reduced.

Original language	English
Title of host publication	Computer Aided Chemical Engineering
Publisher	Elsevier B.V.
Pages	1795-1800
Number of pages	6
DOIs	https://doi.org/10.1016/B978-0-444-64241-7.50294-9
State	Published - 1 Jan 2018

Publication series

Name	Computer Aided Chemical Engineering
Volume	44
ISSN (Print)	1570-7946

Bibliographical note

Publisher Copyright:
© 2018 Elsevier B.V.

Keywords

Ambient air vaporizer
DIRECT algorithm
K-means clustering

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10.1016/B978-0-444-64241-7.50294-9

Cite this

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title = "Optimal Design of an Ambient Air Vaporizer using Numerical Model and DIRECT Algorithm",

abstract = "The ambient air vaporizer (AAV) using ambient air as heat source was environment-friendly method to vaporize LNG. The main problem of the vaporizer is performance degradation caused by frost formation on surface of tube. Determining the appropriate value of design variables under given climate is a critical issue. In this paper, design optimization in the vaporizer is performed using DIRECT algorithm whose result is compared with the result obtained by GA. Time series dataset including temperature and relative humidity of air for a year is categorized using k-means clustering. Finally, the optimal design shows 23.4 % improved performance of AAV and defrosting time is drastically reduced.",

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AB - The ambient air vaporizer (AAV) using ambient air as heat source was environment-friendly method to vaporize LNG. The main problem of the vaporizer is performance degradation caused by frost formation on surface of tube. Determining the appropriate value of design variables under given climate is a critical issue. In this paper, design optimization in the vaporizer is performed using DIRECT algorithm whose result is compared with the result obtained by GA. Time series dataset including temperature and relative humidity of air for a year is categorized using k-means clustering. Finally, the optimal design shows 23.4 % improved performance of AAV and defrosting time is drastically reduced.

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KW - DIRECT algorithm

KW - K-means clustering

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ER -

Optimal Design of an Ambient Air Vaporizer using Numerical Model and DIRECT Algorithm

Abstract

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Keywords

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