A New Approach for Allocating Explosive Facilities in Order to Minimize the Domino Effect Using NLP

この論文にアクセスする

この論文をさがす

著者

    • Kim Ho Soo KIM Ho Soo
    • School of Chemical and Biological Engineering, Institute of Chemical Processes, Seoul National University
    • Yoon En Sup YOON En Sup
    • School of Chemical and Biological Engineering, Institute of Chemical Processes, Seoul National University

抄録

Accidents caused by the domino effect in chemical plants or the petrochemical industry are generally more serious than any other accidents. Although the factors or mechanisms that might cause the domino effect have been studied, it is difficult to examine the true factor because the domino effect is affected by many nonlinear factors. Hence, it is almost impossible to predict the result. The immediate causes of the domino effect are the peak overpressure, flying objects, and flame, and nonlinearity is inherent in all three causes. However, it is believed that a systematic and mathematical approach can minimize the incidence of the domino effect.<BR>This study considered the case where there were <I>N</I>-explosive facilities such as storage tanks, high temperature reactors in the given arbitrary rectangular facility site. This paper suggests the positions that can minimize the domino effect using a nonlinear approach. The well-known method of gradient or steepest descent was adopted in this work. The method initiated an arbitrary number of facilities in addition to the original position, and can search for the position to minimize the domino effect.<BR>This paper presents a new computer-aided module, MiniFFECT (MINImization of domino eFFECT), which can simulate the procedure for deciding the position of <I>N</I>-facilities for minimizing the domino effect.

収録刊行物

  • Journal of chemical engineering of Japan  

    Journal of chemical engineering of Japan 39(7), 731-745, 2006-07-01 

    公益社団法人 化学工学会

参考文献:  22件

参考文献を見るにはログインが必要です。ユーザIDをお持ちでない方は新規登録してください。

各種コード

  • NII論文ID(NAID)
    10018182778
  • NII書誌ID(NCID)
    AA00709658
  • 本文言語コード
    ENG
  • 資料種別
    ART
  • ISSN
    00219592
  • NDL 記事登録ID
    7987411
  • NDL 雑誌分類
    ZP1(科学技術--化学・化学工業)
  • NDL 請求記号
    Z53-R395
  • データ提供元
    CJP書誌  NDL  J-STAGE 
ページトップへ