Optimization for Allocating the Explosive Facilities in Order to Minimize the Domino Effect Using Nonlinear Programming

Joo Young Lee; Joong Won Lee; Jaewook Ko; En Sup Yoon

Korean Journal of Chemical Engineering, Vol.22, No.5, 649-656, September, 2005

DOI10.1007/BF02705777 Export Citation

Optimization for Allocating the Explosive Facilities in Order to Minimize the Domino Effect Using Nonlinear Programming

Joo Young Lee, Joong Won Lee, Jaewook Ko¹, and En Sup Yoon^†

School of Chemical Engineering, Institute of Chemical Processes, Seoul National University, San 56-1 Sillim-dong, Gwanak-gu, Seoul 151-742, Korea
¹Department of Chemical Engineering, Kwangwoon University, 447-1, Wolgye-dong, Nowon-gu, Seoul 139-701, Korea

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.Accidents caused by the domino effect in chemical plants or the petrochemical industry are generally more serious than any other accident. But it is difficult to examine the true factor because the domino effect is influenced by many nonlinear factors. The immediate causes of the domino effect are the peak overpressure, flying objects, and flame. 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. We considered the case where there were n-explosive facilities in a given arbitrary rectangular facility site. This paper suggests the positions that can minimize the domino effect using a nonlinear approach. 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. This paper presents a new computer-aided module, MiniFFECT (MINImization of domino eFFECT).

Keywords:Domino Effect;MiniFFECT;Nonlinear Approach;Gradient Method;Explosive Facility

[References]

AIChE CCPS, Guidelines for Chemical Process Quantitative Risk Analysis, 2nd ed., NY (1999)
Bagster DF, Pitblado RM, Trans IChemE, 69 (1991)
Birk AM, J. Loss Prev. Process Ind., 9(2), 173 (1996)
Cozzani V, Salzano E, J. Hazard. Mater., 107(3), 67 (2004)
Delvosalle C, Domino Effects Phenomena: Definition, Overview and Classification, European Seminar on Domino Effects, Leuven, Belgium, Federal Ministry of Employment, Safety Administration, Direction Chemical Risks, Brussels, Belgium, 5-15 (1996)
Delvosalle C, Fievez C, Brohez S, A Methodology and a Software(DOMINOXL) for Studying Domino Effects, Chisa 2002, 15th International Congress of Chemical and Process Engineering, pp. 25-29, Praha, Czech Republic (2002)
Dougal D, An Introduction to Fire Dynamics, 2nd ed., JOHN WILEY & SONS, pp. 52-63 (1998)
Hauptmanns, J. Loss Prevention, 14, 395 (2001)
Health and Safety Commission, The Control of Major Hazards, Third Report of the HSC Advisory Committee on Major Hazards, pp. A8-C2, HMSO (1984)
Holden PL, Reeves AB, IChemE Symp. Series, 93 (1985)
Khan FI, Abbasi SA, Environ. Modell. Softw., 13, 163 (1998)
Khan FI, Abbasi SA, Process Saf. Prog., 17(2), 107 (1998)
Khan FI, Iqbal A, Abbasi SA, J. Loss Prev. Process Ind., 14, 413 (2001)
Lees FP, Loss Prevention in the Process Industries, Butterworths, pp. 593-602 (1980)
Avriel M, Nonlinear Programming Analysis and Methods, Prentice-Hall, Englewood Cliffs, N. J. (1976)
Pietersen CM, J. Hazard. Mater., 20 (1988)
Renier G, Dullaert W, Soudan K, A Domino Effect Evaluation Model, EconPapers, Working Papers from Univ. of Antwerp., Faculty of Applied Economics (2004)
Spadoni G, Contini S, Ugoccioni G, Process Saf. Environ. Protect., 81(1), 19 (2003)
Uth HJ, Richter B, DISMA, PC-Tools for Implementing the Directive Seveso II, Seminar on 'Software Tools Relevant to Seveso II Directive', Turku, Finland, 13th October (1999)

[Related Articles]

[1] AIChE CCPS, Guidelines for Chemical Process Quantitative Risk Analysis, 2nd ed., NY (1999)

[2] Bagster DF, Pitblado RM, Trans IChemE, 69 (1991)

[3] Birk AM, J. Loss Prev. Process Ind., 9(2), 173 (1996)

[4] Cozzani V, Salzano E, J. Hazard. Mater., 107(3), 67 (2004)

[5] Delvosalle C, Domino Effects Phenomena: Definition, Overview and Classification, European Seminar on Domino Effects, Leuven, Belgium, Federal Ministry of Employment, Safety Administration, Direction Chemical Risks, Brussels, Belgium, 5-15 (1996)

[6] Delvosalle C, Fievez C, Brohez S, A Methodology and a Software(DOMINOXL) for Studying Domino Effects, Chisa 2002, 15th International Congress of Chemical and Process Engineering, pp. 25-29, Praha, Czech Republic (2002)

[7] Dougal D, An Introduction to Fire Dynamics, 2nd ed., JOHN WILEY & SONS, pp. 52-63 (1998)

[8] Hauptmanns, J. Loss Prevention, 14, 395 (2001)

[9] Health and Safety Commission, The Control of Major Hazards, Third Report of the HSC Advisory Committee on Major Hazards, pp. A8-C2, HMSO (1984)

[10] Holden PL, Reeves AB, IChemE Symp. Series, 93 (1985)

[11] Khan FI, Abbasi SA, Environ. Modell. Softw., 13, 163 (1998)

[12] Khan FI, Abbasi SA, Process Saf. Prog., 17(2), 107 (1998)

[13] Khan FI, Iqbal A, Abbasi SA, J. Loss Prev. Process Ind., 14, 413 (2001)

[14] Lees FP, Loss Prevention in the Process Industries, Butterworths, pp. 593-602 (1980)

[15] Avriel M, Nonlinear Programming Analysis and Methods, Prentice-Hall, Englewood Cliffs, N. J. (1976)

[16] Pietersen CM, J. Hazard. Mater., 20 (1988)

[17] Renier G, Dullaert W, Soudan K, A Domino Effect Evaluation Model, EconPapers, Working Papers from Univ. of Antwerp., Faculty of Applied Economics (2004)

[18] Spadoni G, Contini S, Ugoccioni G, Process Saf. Environ. Protect., 81(1), 19 (2003)

[19] Uth HJ, Richter B, DISMA, PC-Tools for Implementing the Directive Seveso II, Seminar on 'Software Tools Relevant to Seveso II Directive', Turku, Finland, 13th October (1999)