@inbook{f1999e1d38294d0c8fddbf6aeb8186c1,
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.",
keywords = "Ambient air vaporizer, DIRECT algorithm, K-means clustering",
author = "Yongkyu Lee and Jonggeol Na and Wonbo Lee",
note = "Funding Information: Authors are thankful to Department of Science and Technology, New Delhi for the financial assistance in the form of project No. III-5(44)-97ET. One of the authors (MKM) is also thankful to University Grant Commission, New Delhi for SRF. Publisher Copyright: {\textcopyright} 2018 Elsevier B.V.",
year = "2018",
month = jan,
day = "1",
doi = "10.1016/B978-0-444-64241-7.50294-9",
language = "English",
series = "Computer Aided Chemical Engineering",
publisher = "Elsevier B.V.",
pages = "1795--1800",
booktitle = "Computer Aided Chemical Engineering",
}