Simulation of the chemical damage zone in the conditions of emergency localization

 

Maksym Kustov

National University of Civil Protection of Ukraine

https://orcid.org/0000-0002-6960-6399

 

Oleksii Basmanov

National University of Civil Protection of Ukraine

https://orcid.org/0000-0002-6434-6575

 

Andrey Melnichenko

National University of Civil Protection of Ukraine

https://orcid.org/0000-0002-7229-6926

 

DOI: https://doi.org/10.5281/zenodo.4400185

 

Keywords: emissions, hazardous chemicals, contamination area, hazardous substance deposition, spray intensity

 

Abstract

A mathematical model of the distribution of gaseous hazardous chemicals has been developed, taking into account the factors of their active deposition on the distribution path. The conditions of dis-tribution of gaseous hazardous substance during depressurization of technological equipment during the localization of the accident by deposition of hazardous chemical substance by sprayed jets are analyzed. To simplify the modeling, a number of assumptions have been made regarding wind parameters, emis-sion and deposition conditions, which simplify the forecasting process and are within the permissible error limits. Based on Gaussian law and taking into account the parameters of the source of emission of hazardous chemical substance and its deposition, the differential equation of distribution of hazardous chemical substance under the conditions of emergency localization is obtained. By solving the differen-tial equation of diffusion, a mathematical model of the distribution of gaseous hazardous substances in the emergency zone is obtained, taking into account its active deposition by operational and rescue units. In modeling, the process of precipitation of hazardous chemicals by fine liquid flow was consid-ered as the process of gas sorption by spherical flow droplets, taking into account both the physico-chemical interaction of gas and liquid and the intensity of fine flow. The developed mathematical model allows to calculate the size of chemical pollution zones with determination of boundary safety condi-tions taking into account wind direction and speed, air temperature, degree of vertical stability of air, width of active deposition zone and chemical properties of both gas and liquid. Taking into account the process of localization of the accident zone when forecasting the development of an emergency situation allows the emergency response manager to make the right management decision, ensure safe working conditions for rescuers and optimize evacuation work from the affected area and property.

 

References

  1. Global Hazards Weekly Bulletin. Public Health England. London, (2020). Available at: http://www.met.reading.ac.uk/~sgs02rpa/extreme.html
  2. Malmén, Y., Nissila, M., Virolainen, K. and Repola, P. (2010). ‘Process chemicals – An ever present concern during plant shutdowns’, Journal of Loss Prevention in the Process Industries, 23, 249–252.
  3. Analytical review of the state of technogenic and natural security in Ukraine for 2018 Available at: http://cn.dsns.gov.ua.
  4. Andronov V.A., Divizinyuk М.М., Kalugin V.D., Tiutiunik V.V. (2016). Scientific and design bases of creation of complex system of monitoring of emergency situations in Ukraine: Monograph, Kharkiv, 319.
  5. Ernst S., LaDue D., and Gerard A. (2018). Understanding emergency manager forecast use in severe weather events. J. Operational Meteor., 6 (9), 95-105,
  6. Leelossy A., Jr F.M., Izsak F., Havasi A., Lagzi I., Meszaros R. (2014). Dispersion modeling of air pollutants in the atmosphere: a review. Central European Journal of Geosciences, 6, 257-278.
  7. Dahia, A., Merrouche, D., Merouani, D.R. et al. (2019). Numerical Study of Long-Term Radioactivity Impact on Foodstuff for Accidental Release Using Atmospheric Dispersion Model. Arab J Sci Eng., 44, 5233–5244.
  8. Hoinaski L., Franco D., Lisboa H. (2016). Comparison of plume lateral dispersion coefficients schemes: Effect of averaging time. Atmospheric Pollution Research, 7, 134-141.
  9. Govalenkov S.S., Basmanov A.E. (2010). Estimation of the intensity of leakage of hazardous chemicals from the emission source. Problems of emergencies. Kharkiv, 11, 39–44.
  10. Shiraiwa M., Pfrang C., Koop T., Pöschl U. (2012). Kinetic multi-layer model of gas-particle interactions in aerosols and clouds (KM-GAP): linking condensation, evaporation and chemical reactions of organics, oxidants and water. Atmos. Chem. Phys., 12, 2777–2794.
  11. Hollingsworth S.A., Dror R.O. (2018). Molecular Dynamics Simulation for All Neuron, 99, 1129–1143.
  12. Julin J., Shiraiwa M., Miles R., Reid J.P., Pöschl U., Riipinen I. (2013). Mass Accommodation of Water: Bridging the Gap Between Molecular Dynamics Simulations and Kinetic Condensation Models. J. Phys. Chem. A., 117, 410 − 420.
  13. Kustov M., Kalugin V., Levterov A. (2016). Rain scavenging of a radioactive aerosol atmospheric precipitation. Austrian Journal of Technical and Natural Sciences, Vienne, 3–4, 73–76.