DOI: https://doi.org/10.15587/1729-4061.2019.163442

Construction of an integrated criterion for estimating the consequences of emergencies involving dangerous goods

Oleksandr Lavrukhin, Anton Kovalov, Vitaliy Schevcenko, Andrii Kyman, Daria Kulova

Abstract


The paper reports a method for estimating the consequences of emergencies involving dangerous cargoes when they are transported by railroad transport. The method is based on constructing an integrated criterion, which takes into consideration those factors that influence the magnitude of risk, which in turn depends on a specific arrangement of wagons in a freight train carrying dangerous cargoes.

The criterion chosen is a conditional confidence in the occurrence of greater consequences as a result of an emergency. The criterion depends on: the number of groups of wagons carrying dangerous goods in a train being formed; the total number of wagons with dangerous goods. The criterion is also affected by: the degree of danger in a group to which wagons with dangerous goods are assigned and the number of cases for the co-arrangement of wagons from various risk groups.

It was established that the factors' values are constantly changing, so they were described using an apparatus of fuzzy logic and fuzzy sets. The use of such an apparatus has made it possible to comprehensively identify the mutual influence of these factors on a safer option for train formation at marshalling yards.

Modeling of possible situations has led to a conclusion about correspondence of the magnitude of values for input fuzzy parameters to the magnitude of values for conditional confidence in the occurrence of greater consequences as a result of an emergency.

The obtained results logically indicate the occurrence of greater consequences when a train has the maximum values for fuzzy variables, the medium ones ‒ at medium values, and the minimal consequences at minimum values for fuzzy variables.

The relationships have been identified for fuzzy input data, whose analysis revealed that an increase in the value for any fuzzy parameters (and their combinations) leads to an increase in the total value for the magnitude of conditional confidence in the occurrence of greater consequences as a result of emergency

Keywords


dangerous goods; conditional confidence; fuzzy logic; emergency; risk assessment

References


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The Ministry of Infrastructure will expand rail connection with EU countries. Available at: https://mtu.gov.ua/en/news/30305.html

Bagheri, M., Saccomanno, F. F., Fu, L. (2010). Effective placement of dangerous goods cars in rail yard marshaling operation. Canadian Journal of Civil Engineering, 37 (5), 753–762. doi: https://doi.org/10.1139/l10-015

Bagheri, M., Saccomanno, F., Chenouri, S., Fu, L. (2011). Reducing the threat of in-transit derailments involving dangerous goods through effective placement along the train consist. Accident Analysis & Prevention, 43 (3), 613–620. doi: https://doi.org/10.1016/j.aap.2010.09.008

Conca, A., Ridella, C., Sapori, E. (2016). A Risk Assessment for Road Transportation of Dangerous Goods: A Routing Solution. Transportation Research Procedia, 14, 2890–2899. doi: https://doi.org/10.1016/j.trpro.2016.05.407

Luan, T., Guo, Z., Pang, L., Lü, P. (2017). Early warning model for risks in railway transportation of dangerous goods based on combination weight. Tiedao Xuebao/Journal of the China Railway Society, 39 (12), 1–7. doi: http://doi.org/10.3969/j.issn.1001-8360.2017.12.001

Giacone, M., Brattaa, F., Gandinib, P., Studerb, L. (2012). Dangerous goods transportation by road: a risk analysis model and a Global Integrated Information System to monitor hazardous materials land transportation in order to protect territory. Chemical Engineering Transaction, 26, 579–584. doi: http://doi.org/10.3303/CET1226097

Zhao, H., Zhang, N., Guan, Y. (2018). Safety Assessment Model for Dangerous Goods Transport by Air Carrier. Sustainability, 10 (5), 1306. doi: https://doi.org/10.3390/su10051306

Cebeci, U. (2009). Fuzzy AHP-based decision support system for selecting ERP systems in textile industry by using balanced scorecard. Expert Systems with Applications, 36 (5), 8900–8909. doi: https://doi.org/10.1016/j.eswa.2008.11.046

Shavranskyy, V. (2012). Using fuzzy logic in support systems decision complications during drilling. Technology audit and production reserves, 4 (1 (6)), 35–36. doi: https://doi.org/10.15587/2312-8372.2012.4782

Tymchuk, S. (2013). Definition of information uncertainty in energy. Technology audit and production reserves, 6 (5 (14)), 33–35. doi: https://doi.org/10.15587/2312-8372.2013.19648

Lomotko, D., Kovalov, A., Kovalova, O. (2015). Formation of fuzzy support system for decision-making on merchantability of rolling stock in its allocation. Eastern-European Journal of Enterprise Technologies, 6 (3 (78)), 11–17. doi: https://doi.org/10.15587/1729-4061.2015.54496

Lavrukhin, O. V. (2015). Intellectual model formation of railway station work during the train operation execution. Science and Transport Progress. Bulletin of Dnipropetrovsk National University of Railway Transport, 1, 43–53. doi: https://doi.org/10.15802/stp2015/38239

Panchenko, S., Lavrukhin, О., Shapatina, O. (2017). Creating a qualimetric criterion for the generalized level of vehicle. Eastern-European Journal of Enterprise Technologies, 1 (3 (85)), 39–45. doi: https://doi.org/10.15587/1729-4061.2017.92203

Lavrukhin, O., Kovalov, A., Kulova, D., Panchenko, A. (2019). Formation of a model for the rational placement of cars with dangerous goods in a freight train. Procedia Computer Science, 149, 28–35. doi: https://doi.org/10.1016/j.procs.2019.01.103

Lavrukhin, O. V., Bocharov, O. P., Horbachov, O. A. (2007). Metody udoskonalennia systemy zminno-dobovoho planuvannia na osnovi teoriyi neironnykh merezh. Sbornik nauchnyh trudov Doneckogo instituta zheleznodorozhnogo transporta, 12, 25–33.

DSTU 4500-3:2008. Vantazhi nebezpechni. Klasyfikatsiya (2010). Kyiv, 36.

"Pravyla perevezennia nebezpechnykh vantazhiv", zatverdzheni nakazom Ministerstva transportu ta zviazku Ukrainy vid 25.11.2008 za No. 1430 ta zareiestrovani v Ministerstvi yustytsiyi Ukrainy vid 26.02.2009 za No. 180/16196.

Baldzhy, M. D. (2015). Ekonomichnyi ryzyk ta metody yoho vymiriuvannia. Kharkiv: Promart, 300.

Astahov, A. M. (2010). Iskusstvo upravleniya informacionnymi riskami. Moscow: DMK Press, 312.


GOST Style Citations


Method of determining the loss of emergency situations dangerous goods / Kotenko A. M., Kozodoy D. S., Svetlichnaya A. V., Shilaev P. S. // Zbirnyk naukovykh prats Ukrainskoi derzhavnoi akademiyi zaliznychnoho transportu. 2013. Issue 141. P. 272–280.

The Ministry of Infrastructure will expand rail connection with EU countries. URL: https://mtu.gov.ua/en/news/30305.html

Bagheri M., Saccomanno F. F., Fu L. Effective placement of dangerous goods cars in rail yard marshaling operation // Canadian Journal of Civil Engineering. 2010. Vol. 37, Issue 5. P. 753–762. doi: https://doi.org/10.1139/l10-015 

Reducing the threat of in-transit derailments involving dangerous goods through effective placement along the train consist / Bagheri M., Saccomanno F., Chenouri S., Fu L. // Accident Analysis & Prevention. 2011. Vol. 43, Issue 3. P. 613–620. doi: https://doi.org/10.1016/j.aap.2010.09.008 

Conca A., Ridella C., Sapori E. A Risk Assessment for Road Transportation of Dangerous Goods: A Routing Solution // Transportation Research Procedia. 2016. Vol. 14. P. 2890–2899. doi: https://doi.org/10.1016/j.trpro.2016.05.407 

Early warning model for risks in railway transportation of dangerous goods based on combination weight / Luan T., Guo Z., Pang L., Lü P. // Tiedao Xuebao/Journal of the China Railway Society. 2017. Vol. 39, Issue 12. P. 1–7. doi: http://doi.org/10.3969/j.issn.1001-8360.2017.12.001

Dangerous goods transportation by road: a risk analysis model and a Global Integrated Information System to monitor hazardous materials land transportation in order to protect territory / Giacone M., Brattaa F., Gandinib P., Studerb L. // Chemical Engineering Transaction. 2012. Vol. 26. P. 579–584. doi: http://doi.org/10.3303/CET1226097

Zhao H., Zhang N., Guan Y. Safety Assessment Model for Dangerous Goods Transport by Air Carrier // Sustainability. 2018. Vol. 10, Issue 5. P. 1306. doi: https://doi.org/10.3390/su10051306 

Cebeci U. Fuzzy AHP-based decision support system for selecting ERP systems in textile industry by using balanced scorecard // Expert Systems with Applications. 2009. Vol. 36, Issue 5. P. 8900–8909. doi: https://doi.org/10.1016/j.eswa.2008.11.046 

Shavranskyy V. Using fuzzy logic in support systems decision complications during drilling // Technology audit and production reserves. 2012. Vol. 4, Issue 1 (6). P. 35–36. doi: https://doi.org/10.15587/2312-8372.2012.4782 

Tymchuk S. Definition of information uncertainty in energy // Technology audit and production reserves. 2013. Vol. 6, Issue 5 (14). P. 33–35. doi: https://doi.org/10.15587/2312-8372.2013.19648 

Lomotko D., Kovalov A., Kovalova O. Formation of fuzzy support system for decision-making on merchantability of rolling stock in its allocation // Eastern-European Journal of Enterprise Technologies. 2015. Vol. 6, Issue 3 (78). P. 11–17. doi: https://doi.org/10.15587/1729-4061.2015.54496 

Lavrukhin O. V. Intellectual model formation of railway station work during the train operation execution // Science and Transport Progress. Bulletin of Dnipropetrovsk National University of Railway Transport. 2015. Issue 1. P. 43–53. doi: https://doi.org/10.15802/stp2015/38239 

Panchenko S., Lavrukhin О., Shapatina O. Creating a qualimetric criterion for the generalized level of vehicle // Eastern-European Journal of Enterprise Technologies. 2017. Vol. 1, Issue 3 (85). P. 39–45. doi: https://doi.org/10.15587/1729-4061.2017.92203 

Formation of a model for the rational placement of cars with dangerous goods in a freight train / Lavrukhin O., Kovalov A., Kulova D., Panchenko A. // Procedia Computer Science. 2019. Vol. 149. P. 28–35. doi: https://doi.org/10.1016/j.procs.2019.01.103 

Lavrukhin O. V., Bocharov O. P., Horbachov O. A. Metody udoskonalennia systemy zminno-dobovoho planuvannia na osnovi teoriyi neironnykh merezh // Sbornik nauchnyh trudov Doneckogo instituta zheleznodorozhnogo transporta. 2007. Issue 12. P. 25–33.

DSTU 4500-3:2008. Vantazhi nebezpechni. Klasyfikatsiya. Kyiv, 2010. 36 p.

"Pravyla perevezennia nebezpechnykh vantazhiv", zatverdzheni nakazom Ministerstva transportu ta zviazku Ukrainy vid 25.11.2008 za No. 1430 ta zareiestrovani v Ministerstvi yustytsiyi Ukrainy vid 26.02.2009 za No. 180/16196.

Baldzhy M. D. Ekonomichnyi ryzyk ta metody yoho vymiriuvannia: navch. pos. Kharkiv: Promart, 2015. 300 p.

Astahov A. M. Iskusstvo upravleniya informacionnymi riskami. Moscow: DMK Press, 2010. 312 p.







Copyright (c) 2019 Anton Kovalov, Oleksandr Lavrukhin, Vitaliy Schevcenko, Andrii Kyman, Daria Kulova

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ISSN (print) 1729-3774, ISSN (on-line) 1729-4061