Short-term forecast of fire in the premises based on modification of the Brown’s zero-order model

Authors

DOI:

https://doi.org/10.15587/1729-4061.2021.238555

Keywords:

fire forecast, Brown’s model modification, ignition, current recurrence measure, state vector increment

Abstract

This paper reports the rationale for the modification of Brown’s zero-order model, which ensures increased accuracy of the short-term fire forecast based on the use of the current measure of recurrence in the increments of the state of the air environment in the premises. A special feature of the proposed model modification is that the a priori model of the dynamics of the level of the time series of the measure of the current recurrence of increments in the air environment states determined by the dangerous factors of the fire has been modified. In this case, it is proposed that the new a priori model should take into consideration additionally the value of the current increments of the level of the studied time series. That makes it possible to negligibly reduce errors of the short-term forecast of fire in the premises without significantly complicating Brown’s zero-order model while retaining all its implementing advantages. The provided accuracy of the forecast for one step in advance on the basis of a time series of measures of the current recurrence of increments of the state of the air environment, determined from the experimental data during the ignition of alcohol and timber in a laboratory chamber, has been investigated. The considered quantitative indicators of forecast accuracy are the absolute and average errors exponentially smoothed with a parameter of 0.4. It has been established that for the proposed modification the value of the average absolute error does not exceed 0.02 %. That means that an error of the short-term forecast of a fire in the premises based on the proposed modification is an order of magnitude less than that in the case of using known Brown’s model at the smoothing parameter from an unclustered set. The results from the ignition of alcohol and timber in the laboratory chamber, in general, indicate significant advantages of using the proposed modification of Brown’s zero-order model for a short-term forecast of a fire in the premises.

Author Biographies

Boris Pospelov, Scientific-methodical Center of Educational Institutions in the Sphere of Civil Defence

Doctor of Technical Sciences, Professor

Department of Organization and Coordination of Research Activities

Evgenіy Rybka, National University of Civil Defence of Ukraine

Doctor of Technical Sciences, Senior Researcher

Research Center

Olekcii Krainiukov, V. N. Karazin Kharkiv National University

Doctor of Geographical Sciences, Associate Professor

Department of Environmental Safety and Environmental Education

Oleksandr Yashchenko, National University of Civil Defence of Ukraine

PhD, Associate Professor

Department of Management and Organization in the Field of Civil Protection

Yuliia Bezuhla, National University of Civil Defence of Ukraine

PhD, Associate Professor

Department of Prevention Activities and Monitoring

Serhii Bielai, National Academy of the National Guard of Ukraine

Doctor of Science in Public Administration, Professor

Research Center

Eduard Kochanov, V. N. Karazin Kharkiv National University

PhD

Department of Monitoring and Nature Management

Svitlana Hryshko, Bogdan Khmelnitsky Melitopol State Pedagogical University

PhD

Department of Physical Geography and Geology

Eduard Poltavski, National Academy of the National Guard of Ukraine

PhD

Department of Armored Vehicles

Oleksandr Nepsha, Bogdan Khmelnitsky Melitopol State Pedagogical University

Department of Physical Geography and Geology

References

Kustov, M. V., Kalugin, V. D., Tutunik, V. V., Tarakhno, E. V. (2019). Physicochemical principles of the technology of modified pyrotechnic compositions to reduce the chemical pollution of the atmosphere. Voprosy Khimii i Khimicheskoi Tekhnologii, 1, 92–99. doi: https://doi.org/10.32434/0321-4095-2019-122-1-92-99

Migalenko, K., Nuianzin, V., Zemlianskyi, A., Dominik, A., Pozdieiev, S. (2018). Development of the technique for restricting the propagation of fire in natural peat ecosystems. Eastern-European Journal of Enterprise Technologies, 1 (10 (91)), 31–37. doi: https://doi.org/10.15587/1729-4061.2018.121727

Vambol, S., Vambol, V., Kondratenko, O., Koloskov, V., Suchikova, Y. (2018). Substantiation of expedience of application of high-temperature utilization of used tires for liquefied methane production. Journal of Achievements in Materials and Manufacturing Engineering, 2 (87), 77–84. doi: https://doi.org/10.5604/01.3001.0012.2830

Vambol, S., Vambol, V., Sobyna, V., Koloskov, V., Poberezhna, L. (2018). Investigation of the energy efficiency of waste utilization technology, with considering the use of low-temperature separation of the resulting gas mixtures. Energetika, 64 (4). doi: https://doi.org/10.6001/energetika.v64i4.3893

Semko, A., Rusanova, O., Kazak, O., Beskrovnaya, M., Vinogradov, S., Gricina, I. (2015). The use of pulsed high-speed liquid jet for putting out gas blow-out. The International Journal of Multiphysics, 9 (1), 9–20. doi: https://doi.org/10.1260/1750-9548.9.1.9

Vambol, S., Vambol, V., Kondratenko, O., Suchikova, Y., Hurenko, O. (2017). Assessment of improvement of ecological safety of power plants by arranging the system of pollutant neutralization. Eastern-European Journal of Enterprise Technologies, 3 (10 (87)), 63–73. doi: https://doi.org/10.15587/1729-4061.2017.102314

Otrosh, Y., Kovalov, A., Semkiv, O., Rudeshko, I.,Diven, V. (2018). Methodology remaining lifetime determination of the building structures. MATEC Web of Conferences, 230, 02023. doi: https://doi.org/10.1051/matecconf/201823002023

Vasyukov, A., Loboichenko, V., Bushtec, S. (2016). Identification of bottled natural waters by using direct conductometry. Ecology, Environment and Conservation, 22 (3), 1171–1176.

Ahrens, M., Evarts, B. (2020). Fire loss in the United States during 2019. National Fire Protection Association, 11. Available at: https://www.nfpa.org/~/media/fd0144a044c84fc5baf90c05c04890b7.ashx

Koshmarov, Yu. A., Puzach, S. V., Andreev, V. V. (2012). Prognozirovanie opasnyh faktorov pozhara v pomeschenii. Moscow: AGPS MChS Rossii, 126.

Otrosh, Y., Semkiv, O., Rybka, E., Kovalov, A. (2019). About need of calculations for the steel framework building in temperature influences conditions. IOP Conference Series: Materials Science and Engineering, 708, 012065. doi: https://doi.org/10.1088/1757-899x/708/1/012065

Pospelov, B., Andronov, V., Rybka, E., Meleshchenko, R., Borodych, P. (2018). Studying the recurrent diagrams of carbon monoxide concentration at early ignitions in premises. Eastern-European Journal of Enterprise Technologies, 3 (9 (93)), 34–40. doi: https://doi.org/10.15587/1729-4061.2018.133127

Andronov, V., Pospelov, B., Rybka, E., Skliarov, S. (2017). Examining the learning fire detectors under real conditions of application. Eastern-European Journal of Enterprise Technologies, 3 (9 (87)), 53–59. doi: https://doi.org/10.15587/1729-4061.2017.101985

Ahn, C.-S., Kim, J.-Y. (2011). A study for a fire spread mechanism of residential buildings with numerical modeling. Safety and Security Engineering IV. doi: https://doi.org/10.2495/safe110171

Webber,, C. L., Ioana, C., Marwan, N. (Eds.) (2016). Recurrence plots and their quantifications: expanding horizons. International Symposium on Recurrence Plots. Grenoble, 380. doi: https://doi.org/10.1007/978-3-319-29922-8

Sadkovyi, V., Pospelov, B., Andronov, V., Rybka, E., Krainiukov, O., Rud, A. et. al. (2020). Construction of a method for detecting arbitrary hazard pollutants in the atmospheric air based on the structural function of the current pollutant concentrations. Eastern-European Journal of Enterprise Technologies, 6 (10 (108)), 14–22. doi: https://doi.org/10.15587/1729-4061.2020.218714

Turcotte, D. L. (1997). Fractals and chaos in geology and geophysics. Cambridge University Press. doi: https://doi.org/10.1017/cbo9781139174695

Poulsen, A., Jomaas, G. (2011). Experimental Study on the Burning Behavior of Pool Fires in Rooms with Different Wall Linings. Fire Technology, 48 (2), 419–439. doi: https://doi.org/10.1007/s10694-011-0230-0

Zhang, D., Xue, W. (2010). Effect of heat radiation on combustion heat release rate of larch. Journal of West China Forestry Science, 39, 148.

Ji, J., Yang, L., Fan, W. (2003). Experimental Study on Effects of Burning Behaviours of Materials Caused by External Heat Radiation. Journal of Combustion Science and Technology, 9, 139.

Peng, X., Liu, S., Lu, G. (2005). Experimental Analysis on Heat Release Rate of Materials. Journal of Chongqing University, 28, 122.

Andronov, V., Pospelov, B., Rybka, E. (2017). Development of a method to improve the performance speed of maximal fire detectors. Eastern-European Journal of Enterprise Technologies, 2 (9 (86)), 32–37. doi: https://doi.org/10.15587/1729-4061.2017.96694

Pospelov, B., Andronov, V., Rybka, E., Meleshchenko, R., Gornostal, S. (2018). Analysis of correlation dimensionality of the state of a gas medium at early ignition of materials. Eastern-European Journal of Enterprise Technologies, 5 (10 (95)), 25–30. doi: https://doi.org/10.15587/1729-4061.2018.142995

Pospelov, B., Andronov, V., Rybka, E., Skliarov, S. (2017). Design of fire detectors capable of self-adjusting by ignition. Eastern-European Journal of Enterprise Technologies, 4 (9 (88)), 53–59. doi: https://doi.org/10.15587/1729-4061.2017.108448

Pospelov, B., Rybka, E., Meleshchenko, R., Gornostal, S., Shcherbak, S. (2017). Results of experimental research into correlations between hazardous factors of ignition of materials in premises. Eastern-European Journal of Enterprise Technologies, 6 (10 (90)), 50–56. doi: https://doi.org/10.15587/1729-4061.2017.117789

Bendat, J. S., Piersol, A. G. (2010). Random data: analysis and measurement procedures. John Wiley & Sons. doi: https://doi.org/10.1002/9781118032428

Shafi, I., Ahmad, J., Shah, S. I., Kashif, F. M. (2009). Techniques to Obtain Good Resolution and Concentrated Time-Frequency Distributions: A Review. EURASIP Journal on Advances in Signal Processing, 2009 (1). doi: https://doi.org/10.1155/2009/673539

Singh, P. (2016). Time-frequency analysis via the fourier representation. HAL, 1–8. Available at: https://hal.archives-ouvertes.fr/hal-01303330/document

Pretrel, H., Querre, P., Forestier, M. (2005). Experimental Study Of Burning Rate Behaviour In Confined And Ventilated Fire Compartments. Fire Safety Science, 8, 1217–1228. doi: https://doi.org/10.3801/iafss.fss.8-1217

Pospelov, B., Andronov, V., Rybka, E., Popov, V., Romin, A. (2018). Experimental study of the fluctuations of gas medium parameters as early signs of fire. Eastern-European Journal of Enterprise Technologies, 1 (10 (91)), 50–55. doi: https://doi.org/10.15587/1729-4061.2018.122419

Stankovic, L., Dakovic, M., Thayaparan, T. (2014). Time-frequency signal analysis. Kindle edition, 655.

Avargel, Y., Cohen, I. (2010). Modeling and Identification of Nonlinear Systems in the Short-Time Fourier Transform Domain. IEEE Transactions on Signal Processing, 58 (1), 291–304. doi: https://doi.org/10.1109/tsp.2009.2028978

Giv, H. H. (2013). Directional short-time Fourier transform. Journal of Mathematical Analysis and Applications, 399 (1), 100–107. doi: https://doi.org/10.1016/j.jmaa.2012.09.053

Pospelov, B., Andronov, V., Rybka, E., Popov, V., Semkiv, O. (2018). Development of the method of frequency­temporal representation of fluctuations of gaseous medium parameters at fire. Eastern-European Journal of Enterprise Technologies, 2 (10 (92)), 44–49. doi: https://doi.org/10.15587/1729-4061.2018.125926

Pospelov, B., Andronov, V., Rybka, E., Samoilov, M., Krainiukov, O., Biryukov, I. et. al. (2021). Development of the method of operational forecasting of fire in the premises of objects under real conditions. Eastern-European Journal of Enterprise Technologies, 2 (10 (110)), 43–50. doi: https://doi.org/10.15587/1729-4061.2021.226692

Sinaga, H., Irawati, N. (2020). A Medical Disposable Supply Demand Forecasting By Moving Average And Exponential Smoothing Method. Proceedings of the Proceedings of the 2nd Workshop on Multidisciplinary and Applications (WMA) 2018, 24-25 January 2018, Padang, Indonesia. doi: https://doi.org/10.4108/eai.24-1-2018.2292378

Svetun'kov, S. G. (2002). O rasshirenii granits primeneniya metoda Brauna. Izvestiya Sankt-Peterburgskogo gosudarstvennogo universiteta ekonomiki i finansov, 3, 94–107.

Pospelov, B., Rybka, E., Meleshchenko, R., Krainiukov, O., Biryukov, I., Butenko, T. et. al. (2021). Short-term fire forecast based on air state gain recurrence and zero-order Brown model. Eastern-European Journal of Enterprise Technologies, 3 (10 (111)), 27–33. doi: https://doi.org/10.15587/1729-4061.2021.233606

Chetyrkin, E. M. (1977). Statisticheskie metody prognozirovaniya. Moscow: Statistika, 200.

Marwan, N. (2011). How to avoid potential pitfalls in recurrence plot based data analysis. International Journal of Bifurcation and Chaos, 21 (04), 1003–1017. doi: https://doi.org/10.1142/s0218127411029008

Webber, Jr. C. L., Zbilut, J. P.; Riley, M. A., Van Orden, G. C. (Eds.) (2005). Chapter 2. Recurrence quantification analysis of nonlinear dynamical systems. Tutorials in contemporary nonlinear methods for the behavioral sciences, 26–94. Available at: https://www.nsf.gov/pubs/2005/nsf05057/nmbs/nmbs.pdf

Orlova, I. V., Polovnikov, V. A. (2010). Ekonomiko-matematicheskie metody i modeli: komp'yuternoe modelirovanie. Moscow: INFRA-M, 366.

Pospelov, B., Rybka, E., Togobytska, V., Meleshchenko, R., Danchenko, Y., Butenko, T. et. al. (2019). Construction of the method for semi-adaptive threshold scaling transformation when computing recurrent plots. Eastern-European Journal of Enterprise Technologies, 4 (10 (100)), 22–29. doi: https://doi.org/10.15587/1729-4061.2019.176579

Pospelov, B., Andronov, V., Rybka, E., Krainiukov, O., Karpets, K., Pirohov, O. et. al. (2019). Development of the correlation method for operative detection of recurrent states. Eastern-European Journal of Enterprise Technologies, 6 (4 (102)), 39–46. doi: https://doi.org/10.15587/1729-4061.2019.187252

Published

2021-08-30

How to Cite

Pospelov, B., Rybka, E., Krainiukov, O., Yashchenko, O., Bezuhla, Y., Bielai, S., Kochanov, E., Hryshko, S., Poltavski, E., & Nepsha, O. (2021). Short-term forecast of fire in the premises based on modification of the Brown’s zero-order model . Eastern-European Journal of Enterprise Technologies, 4(10(112), 52–58. https://doi.org/10.15587/1729-4061.2021.238555