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

Yongkyu Lee, Jonggeol Na, Wonbo Lee

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

4 Scopus citations


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 languageEnglish
Title of host publicationComputer Aided Chemical Engineering
PublisherElsevier B.V.
Number of pages6
StatePublished - 1 Jan 2018

Publication series

NameComputer Aided Chemical Engineering
ISSN (Print)1570-7946

Bibliographical note

Publisher Copyright:
© 2018 Elsevier B.V.


  • Ambient air vaporizer
  • DIRECT algorithm
  • K-means clustering


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