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Levente Tugyi István Sályi Doctoral School of Mechanical Engineering Sciences, Faculty of Mechanical Engineering and Informatics, University of Miskolc, Miskolc-Egyetemváros, Miskolc, Hungary

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Zoltán Siménfalvi Institute of Energy Engineering and Chemical Machinery, Faculty of Mechanical Engineering and Informatics, University of Miskolc, Miskolc-Egyetemváros, Miskolc, Hungary

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Gábor L. Szepesi Institute of Energy Engineering and Chemical Machinery, Faculty of Mechanical Engineering and Informatics, University of Miskolc, Miskolc-Egyetemváros, Miskolc, Hungary

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Csaba Kecskés Institute of Energy Engineering and Chemical Machinery, Faculty of Mechanical Engineering and Informatics, University of Miskolc, Miskolc-Egyetemváros, Miskolc, Hungary

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Zoltán Kerekes Institute of Energy Engineering and Chemical Machinery, Faculty of Mechanical Engineering and Informatics, University of Miskolc, Miskolc-Egyetemváros, Miskolc, Hungary

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Tamás Sári Institute of Energy Engineering and Chemical Machinery, Faculty of Mechanical Engineering and Informatics, University of Miskolc, Miskolc-Egyetemváros, Miskolc, Hungary

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Abstract

In the event of a flammable liquid, gas, or vapor release the first step is to identify the type of outflow, which can fall into two categories sonic or subsonic. The two types of outflows carry different flow characteristics, which effect on the extent of the potentially explosive areas. In case of subsonic outflow, a short jet is formed without turbulent flow conditions at low velocity, which appears more concentrated around the source of release. With sonic outflow, a high velocity jet is formed with turbulent flow properties, which can extend further away from the source of release. The simulations examine the lower explosion limit of the flammable medium around the vessel where LEL20% or LEL40%. In addition, high temperature methane gas release was also presented.

Abstract

In the event of a flammable liquid, gas, or vapor release the first step is to identify the type of outflow, which can fall into two categories sonic or subsonic. The two types of outflows carry different flow characteristics, which effect on the extent of the potentially explosive areas. In case of subsonic outflow, a short jet is formed without turbulent flow conditions at low velocity, which appears more concentrated around the source of release. With sonic outflow, a high velocity jet is formed with turbulent flow properties, which can extend further away from the source of release. The simulations examine the lower explosion limit of the flammable medium around the vessel where LEL20% or LEL40%. In addition, high temperature methane gas release was also presented.

1 Introduction

In industrial plants, where flammable materials are stored, produced, or processed, hazardous explosive atmospheres can occur, what could be one of most dangerous [1]. An analysis of chemical accidents between 1998 and 2015 showed that gas explosions are the most dangerous [2]. A gas explosion, which can be identified with the concept of explosion, Keller et al. [3] describes a process where a rapid rise in temperature and pressure occurs that causes an audible, spherically propagating pressure surge that results in oxidation or other exothermic reactions due to the explosion.

A distinction can be made between a continuous, voluminous gas cloud and an instantaneous accidental, volumetrically negligible release, where an explosion can only occur in the event of immediate ignition [4]. In these cases no gas explosion occurs, but rather only deflagration resulting in overpressurisation [5]. The severity of explosions depends on the position and strength of the ignition source, the volume and concentration of the gas or vapor cloud mixed with air [4]. In addition, the explosion is also influenced by the surrounding cascade and the combustion and explosive properties of the combustible material [6].

The possibilities of chemical plants accidents can be reduced by preliminary investigations HAZard and OPerability (HAZOP) [7], which include a detailed assessment of the potential consequences. Properly selected safety equipment and organizational measures also reduce the risk (explosion-proof equipment, fire and explosion protection regulations). Experimental assessments are instructive, however, such experimental predictive assessments are limited to small-scale accidents, as replicating large-scale explosions would be very costly, time-consuming and dangerous [8].

Cost and safety optimization [9] in mind have led to the rapid development of more practical theoretical models. The Computational Fluid Dynamics (CFD) and others software may include the following:

  • ANYSY (CFD simulation) [10–12];

  • Arial LOcation Hazardous Atmosphere (ALOHA) [13];

  • GEXCON FLame ACceleration Simulator (FLACS-CFD) [14, 15];

  • DNV PHAST [16];

  • TNO Effects [17].

The safe and effectively cheaply reproducible software environment provided by the simulations has great advantages, which is still extensively used nowadays for initial screening validation purposes [18]. Researchers typically validate their simulation results with investigations data or other experience [19–21]. Interesting and useful simulation studies were evaluated with the help of the CFD. Papanikolaou and Baraldi [20] study of high-pressure hydrogen gas propagation in an external environment. In a test space in an external environment, the different air flow speeds can also greatly influence the spread of explosive gases [21]. In the analyzes an important aspect is the relative density of the gas, based on which it can spread better upwards or downwards. This phenomenon can be investigated excellently with simulations [22]. Natural gas contains approximately 95% methane, one of the dangerous substances that can be present anywhere in everyday life. Its spread in the external environment in a large area Sebastian et al. was examined in his study [23].

2 Theoretical background

Literature and standards are available to identify these hazardous areas [24, 25]. The result of hazardous area classification reveals the type and extent of potentially explosive areas. In the event of a flammable liquid, gas or vapor release the first step is to identify the type of outflow, which can fall into two categories sonic or subsonic [26]. To determine the type of outflow the critical pressure of the medium must be calculated, however in case of unknown parameters 1.89 bar can be used as the average value of critical pressure. If the internal pressure is lower than the critical pressure it is classified as subsonic flow, otherwise it is sonic outflow.

The two types of outflows carry different flow characteristics, which affect the extent of the potentially explosive areas. In the case of subsonic outflow, a short jet is formed without turbulent flow conditions at low velocity, which appears more concentrated around the source of release.

With sonic outflow, a high velocity jet is formed with turbulent flow properties, which can extend further away from the source of release.

To decide the type of outflow, the critical pressure of the closed system must be determined. The expanding gas velocity is sonic (choked) if the internal pressure of the system is greater than the critical pressure, whereas it is subsonic (no choking) if the internal pressure of the system is less than the critical pressure. According to ILNAS-IEC 60079-10-1:2015 [25], the determination of the emission rate of gases or vapors is an important condition for proceeding with calculations, as different relationships have to be applied in the subsonic and sonic cases. The first step is to determine the adiabatic expansion polytrophic index of the gas or vapor according to Eq. (1):
γ=M·CpM·CpR,
where M is the molar mass [kg∙kmol−1]; Cp is the specific heat capacity [J∙kg−1∙K−1]; and R is the universal gas constant [J∙kmol−1∙K−1]. Eq. (1) gives γ = 1.3 for methane. The critical pressure value can be determined by Eq. (2):
pc=pa·γ+12γγ1,
where pa is the molar mass [Pa]; γ is the adiabatic expansion politropic index [-]. Eq. (2) gives pc = 185 904 Pa for methane.

3 Results and discussion

The ANSYS CFD were simulated the propagation of the two types of emission through a source of release located on a methane tank. The results were presented the outflow and spreading of the slower and more concentrated subsonic outflow and the high velocity, but less concentrated sonic outflow. Both subsonic and sonic transient state simulations were performed using a large vortex model k–ω Shear Stress Transport (SST) with polyhedral mesh. Material properties were determined using the Peng-Robinson correlation. There is no airflow both simulations. The rate of emissions was also determined using a mathematical model.

3.1 Subsonic release

The mathematical relationship proposed by ILNAS-IEC 60079-10-1:2015 [25] for the quantification of subsonic emissions given by Eq. (3), which also applies the adiabatic expansion politropic index of Eq. (1):
Wg=Cd·S·p·Mz·R·T·2·γγ11papγγ1·pap1γ,
where Cd is the discharge coefficient [-]; S is the hole cross section [m2], which represents a hole with a diameter of 0.01 m as the source of release; p is the internal pressure of medium [Pa]; z is the compressibility factor [-]; T is the temperature of medium [K]. According to the boundary conditions of the variables Cd = 1.0, S = 0.000078 m2, p = 180,000 Pa, z = 1.0, T = 298.15 K, the mass release rate of methane: Wg = 0.024 kg s−1.

The simulation duration examined was 4 s, which required 7.5 days of run time. Between the start and end points of the period under study, the level of gas emissions was monitored. As it is shown in Fig. 1 the gas emission rate decreases with time, as the pressure inside the tank decreases accordingly. Fig. 1 shows that the simulation proves a lower value.

Fig. 1.
Fig. 1.

Time series function of the subsonic emission

Citation: Pollack Periodica 18, 3; 10.1556/606.2023.00789

During the simulation, the methane gas propagation states are shown before the methane tank and between the operating building and other tank in Figs 24 at time instants of 0.5 and 4.0 s. The tested concentrations of the Lower Explosion Limit (LEL) are 20 and 40%.

Fig. 2.
Fig. 2.

Surfaces reaching LEL 20% in 0.5 s (left), 4.0 s (right)

Citation: Pollack Periodica 18, 3; 10.1556/606.2023.00789

Fig. 3.
Fig. 3.

Surfaces reaching LEL 40% in 0.5 s (left), 4.0 s (right)

Citation: Pollack Periodica 18, 3; 10.1556/606.2023.00789

Fig. 4.
Fig. 4.

Surfaces reaching LEL in 0.5 s (left), 4.0 s (right)

Citation: Pollack Periodica 18, 3; 10.1556/606.2023.00789

The LEL 20% value for methane is 0.88 volume percent (vol%). Initially a longer jet is visible, then after deceleration the gas volume spreads out and can penetrate into an area below ground level due to the effects of expansion. At LEL 40%–1.76 vol% a little thinner both cases. The length and extent of the LEL-4.4 vol% increases over time.

3.2 Sonic release

The mathematical relationship proposed by ILNAS-IEC 60079-10-1:2015 [25] for the quantification of sonic emissions is given by Eq. (4), which is almost identical to Eq. (3),
Wg=Cd·S·p·Mz·R·T·2·γγ+1γ+1γ1.

According to the boundary conditions of the variables almost same than subsonic, the internal pressure of the medium is higher, exactly p = 600,000 Pa. The mass release rate of methane: Wg = 0.08 kg∙s−1.

The simulation duration examined was 10.5 s, which required 18 days of run time. Based on preliminary calculations, it takes approximately this time and a little more to empty the tank. Between the start and end points of the period under study, the level of gas emissions was monitored. As it is shown in Fig. 5 the gas emission rate decreases with time, as the pressure inside the tank decreases accordingly. The figure shows that the simulation shows a lower value.

Fig. 5.
Fig. 5.

Time series function of the sonic emission

Citation: Pollack Periodica 18, 3; 10.1556/606.2023.00789

During the simulation, the methane gas propagation states are shown before the methane tank and between the operating building and other tank in Figs 68 at time instants of 0.5 and 8.0 s at the same concentrations as subsonic. At 8.0 s the gas emission is close to a steady state, it is not necessary to look at the last simulated moment.

Fig. 6.
Fig. 6.

Surfaces reaching LEL 20% in 0.5 s (left), 8.0 s (right)

Citation: Pollack Periodica 18, 3; 10.1556/606.2023.00789

Fig. 7.
Fig. 7.

Surfaces reaching LEL 40% in 0.5 s (left), 8.0 s (right)

Citation: Pollack Periodica 18, 3; 10.1556/606.2023.00789

Fig. 8.
Fig. 8.

Surfaces reaching LEL in 0.5 s (left), 8.0 s (right)

Citation: Pollack Periodica 18, 3; 10.1556/606.2023.00789

At LEL 20% - 0.88 vol% are the same effects when the methane can penetrate into an area below ground level due to the effects of expansion. At the LEL - 4.4 vol% in the sonic case the LEL volume decreases. The high velocity causes fresh air to flow in a vortex over the surface of the volumes, diluting the concentration of the medium. It is the eddy diffusion [27] (see Fig. 9). In both outflows, the distance and location of the objects affected the direction of propagation as obstacles. Different distances and positions would result in different propagation forms.

Fig. 9.
Fig. 9.

Eddy diffusion

Citation: Pollack Periodica 18, 3; 10.1556/606.2023.00789

3.3 High temperature medium release

In addition to investigating the propagation, the temperature variation of the outflow medium is simulated because of the lower explosion limit depends on the temperature of the medium [28] (the higher the lower). The results of the simulations shown in Fig. 10 indicate that a methane medium at 80 °C cools down very quickly in 1 s, both in subsonic and sonic outflow.

Fig. 10.
Fig. 10.

a) Subsonic, b) sonic outflow of 80 °C methane

Citation: Pollack Periodica 18, 3; 10.1556/606.2023.00789

4 Conclusion

The use of simulation is a more accurate approach but requires more time. Mathematical relationships make higher emission values and larger zone but it means deviate conservatively, towards safety. At 20% of the lower explosive limit for both releases, lighter-than-air gas can penetrate to lower ground levels. Long or flattened beams are observed at 40% of the lower explosion limit. In the case of the lower explosion limit, an interesting phenomenon is observed, at subsonic the volume increases with time, in the sonic case it decreases. The temperature of the medium in the external space drops to low temperatures very quickly, the danger of correlating the explosion temperature with the temperature is not really there, although it may be significant at very high temperatures. In the future the simulations with measurements is planed to validate.

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  • [1]

    J. Ge, Y. Zhang, K. Xu, J. Li, X. Yao, C. Wu, S. Li, F. Yan, J. Zhang, and Q. Xu, “A new accident causation theory based on systems thinking and its systemic accident analysis method of work systems,” Process Saf. Environ. Prot., vol. 158, pp. 644660, 2022.

    • Search Google Scholar
    • Export Citation
  • [2]

    K. G. Reddy and K. Yarrakula, “Analysis of accidents in chemical process industries in the period 1998-2015,” Int. J. Chem Tech Res., vol. 9, no. 4, pp. 177191, 2016.

    • Search Google Scholar
    • Export Citation
  • [3]

    J. O. Keller, M. Gresho, A. Harris, and A. V. Tchouvelev, “What is an explosion?Int. J. Hydrogen Energy, vol. 39, no. 35, pp. 2042620433, 2014.

    • Search Google Scholar
    • Export Citation
  • [4]

    D. P. Nolan, “Characteristics of hazardous material releases, fires, and explosions,” Handbook of Fire and Explosion Protection Engineering Principles for Oil, Gas, Chemical, and Related Facilities .4th ed., D. P. Nolan, Ed., Elsevier, 2019, pp. 89121.

    • Search Google Scholar
    • Export Citation
  • [5]

    E. S. Oran, G. Chamberlain, and A. Pekalski, “Mechanisms and occurrence of detonations in vapor cloud explosions,” Prog. Energy Combust. Sci., vol. 77, 2020, Paper no. 100804.

    • Search Google Scholar
    • Export Citation
  • [6]

    V. Mikaczo, Z. Simenfalvi, and G. L. Szepesi, “Practical extension of ideal gas model for propane explosion simulation,” Pollack Period., vol. 17, no. 3, pp. 6570, 2022.

    • Search Google Scholar
    • Export Citation
  • [7]

    P. Mocellin, J. De Tommaso, C. Vianello, G. Maschio, T. Saulnier-Bellemare, L. D. Virla, and G. S. Patience, “Experimental methods in chemical engineering: Hazard and operability analysis—HAZOP,” Can. J. Chem. Eng., vol. 100, no. 12, pp. 34503469, 2022.

    • Search Google Scholar
    • Export Citation
  • [8]

    D. S. N. Abg Shamsuddin, A. F. M. Fekeri, A. Muchtar, F. Khan, B. C. Khor, B. H. Lim, M. I. Rosli abd, and M. S. Takriff, “Computational fluid dynamics modeling approaches of gas explosion in the chemical process industry: A review,” Process Saf. Environ. Prot., vol. 170, pp. 112138, 2023.

    • Search Google Scholar
    • Export Citation
  • [9]

    M. Petrik, G. Szepesi, and K. Jármai, “Optimal design of double-pipe heat exchangers,” in World Congress of Structural and Multidisciplinary Optimization, Braunschweig, Germany, June 5–9, 2017, Advances in Structural and Multidisciplinary Optimization, A. Schumacher, T. Vietor, S. Fiebig, K. U. Bletzinger, and K. Maute, Eds, Springer, 2018, pp. 755764.

    • Search Google Scholar
    • Export Citation
  • [10]

    A. Chakrabarty, S. Mannan, and T. Cagin, “Computational fluid dynamics simulation in process safety,” in Multiscale Modeling for Process Safety Applications .A. Chakrabarty, S. Mannan, and T. Cagin, Eds, Elsevier, 2016, pp. 211274.

    • Search Google Scholar
    • Export Citation
  • [11]

    T. Pusztai and Z. Simenfalvi, “CFD analysis on a direct spring-loaded safety valve to determine flow forces,” Pollack Period., vol. 16, no. 1, pp. 109113, 2021.

    • Search Google Scholar
    • Export Citation
  • [12]

    J. Labovský and L. Jelemenský, “Verification of CFD pollution dispersion modelling based on experimental data,” J. Loss Prev. Process Ind., vol. 24, no. 2, pp. 166177, 2011.

    • Search Google Scholar
    • Export Citation
  • [13]

    L. Tugyi, Z. Siménfalvi, and L. G. Szepesi, “Explosive atmosphere analysis for simulation of acetone source of release using ALOHA software,” Multidiszciplináris Tudományok, vol. 12, no. 3, pp. 274282, 2022.

    • Search Google Scholar
    • Export Citation
  • [14]

    A. Dasgotra, G. V. V. V. Teja, A. Sharma, and K. B. Mishra, “CFD modeling of large-scale flammable cloud dispersion using FLACS,” J. Loss Prev. Process Ind., vol. 56, pp. 531536, 2018.

    • Search Google Scholar
    • Export Citation
  • [15]

    E. Vyazmina and S. Jallais, “Validation and recommendations for FLACS CFD and engineering approaches to model hydrogen vented explosions: Effects of concentration, obstruction vent area and ignition position,” Int. J. Hydrogen Energy, vol. 41, no. 33, pp. 1510115109, 2016.

    • Search Google Scholar
    • Export Citation
  • [16]

    H. Meysami, T. Ebadi, H. Zohdirad, and M. Minepur, “Worst-case identification of gas dispersion for gas detector mapping using dispersion modeling,” J. Loss Prev. Process Ind., vol. 26, no. 6, pp. 14071414, 2013.

    • Search Google Scholar
    • Export Citation
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    S. I. Suddle, J. Weerheijm, and A. C. van den Berg, “The cost-effectiveness of a steel tube or a buffer zone for mitigating blast effects on a building spanning an underpass with transport of LPG,” 10th International Conference on Probabilistic Safety Assessment and Management, vol. 4, Seattle, WA, USA, June 7–10, 2010, pp. 33173329.

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Senior editors

Editor(s)-in-Chief: Iványi, Amália

Editor(s)-in-Chief: Iványi, Péter

 

Scientific Secretary

Miklós M. Iványi

Editorial Board

  • Bálint Bachmann (Institute of Architecture, Faculty of Engineering and Information Technology, University of Pécs, Hungary)
  • Jeno Balogh (Department of Civil Engineering Technology, Metropolitan State University of Denver, Denver, Colorado, USA)
  • Radu Bancila (Department of Geotechnical Engineering and Terrestrial Communications Ways, Faculty of Civil Engineering and Architecture, “Politehnica” University Timisoara, Romania)
  • Charalambos C. Baniotopolous (Department of Civil Engineering, Chair of Sustainable Energy Systems, Director of Resilience Centre, School of Engineering, University of Birmingham, U.K.)
  • Oszkar Biro (Graz University of Technology, Institute of Fundamentals and Theory in Electrical Engineering, Austria)
  • Ágnes Borsos (Institute of Architecture, Department of Interior, Applied and Creative Design, Faculty of Engineering and Information Technology, University of Pécs, Hungary)
  • Matteo Bruggi (Dipartimento di Ingegneria Civile e Ambientale, Politecnico di Milano, Italy)
  • Petra Bujňáková (Department of Structures and Bridges, Faculty of Civil Engineering, University of Žilina, Slovakia)
  • Anikó Borbála Csébfalvi (Department of Civil Engineering, Institute of Smart Technology and Engineering, Faculty of Engineering and Information Technology, University of Pécs, Hungary)
  • Mirjana S. Devetaković (Faculty of Architecture, University of Belgrade, Serbia)
  • Szabolcs Fischer (Department of Transport Infrastructure and Water Resources Engineering, Faculty of Architerture, Civil Engineering and Transport Sciences Széchenyi István University, Győr, Hungary)
  • Radomir Folic (Department of Civil Engineering, Faculty of Technical Sciences, University of Novi Sad Serbia)
  • Jana Frankovská (Department of Geotechnics, Faculty of Civil Engineering, Slovak University of Technology in Bratislava, Slovakia)
  • János Gyergyák (Department of Architecture and Urban Planning, Institute of Architecture, Faculty of Engineering and Information Technology, University of Pécs, Hungary)
  • Kay Hameyer (Chair in Electromagnetic Energy Conversion, Institute of Electrical Machines, Faculty of Electrical Engineering and Information Technology, RWTH Aachen University, Germany)
  • Elena Helerea (Dept. of Electrical Engineering and Applied Physics, Faculty of Electrical Engineering and Computer Science, Transilvania University of Brasov, Romania)
  • Ákos Hutter (Department of Architecture and Urban Planning, Institute of Architecture, Faculty of Engineering and Information Technolgy, University of Pécs, Hungary)
  • Károly Jármai (Institute of Energy and Chemical Machinery, Faculty of Mechanical Engineering and Informatics, University of Miskolc, Hungary)
  • Teuta Jashari-Kajtazi (Department of Architecture, Faculty of Civil Engineering and Architecture, University of Prishtina, Kosovo)
  • Róbert Kersner (Department of Technical Informatics, Institute of Information and Electrical Technology, Faculty of Engineering and Information Technology, University of Pécs, Hungary)
  • Rita Kiss  (Biomechanical Cooperation Center, Faculty of Mechanical Engineering, Budapest University of Technology and Economics, Budapest, Hungary)
  • István Kistelegdi  (Department of Building Structures and Energy Design, Institute of Architecture, Faculty of Engineering and Information Technology, University of Pécs, Hungary)
  • Stanislav Kmeť (President of University Science Park TECHNICOM, Technical University of Kosice, Slovakia)
  • Imre Kocsis  (Department of Basic Engineering Research, Faculty of Engineering, University of Debrecen, Hungary)
  • László T. Kóczy (Department of Information Sciences, Faculty of Mechanical Engineering, Informatics and Electrical Engineering, University of Győr, Hungary)
  • Dražan Kozak (Faculty of Mechanical Engineering, Josip Juraj Strossmayer University of Osijek, Croatia)
  • György L. Kovács (Department of Technical Informatics, Institute of Information and Electrical Technology, Faculty of Engineering and Information Technology, University of Pécs, Hungary)
  • Balázs Géza Kövesdi (Department of Structural Engineering, Faculty of Civil Engineering, Budapest University of Engineering and Economics, Budapest, Hungary)
  • Tomáš Krejčí (Department of Mechanics, Faculty of Civil Engineering, Czech Technical University in Prague, Czech Republic)
  • Jaroslav Kruis (Department of Mechanics, Faculty of Civil Engineering, Czech Technical University in Prague, Czech Republic)
  • Miklós Kuczmann (Department of Automations, Faculty of Mechanical Engineering, Informatics and Electrical Engineering, Széchenyi István University, Győr, Hungary)
  • Tibor Kukai (Department of Engineering Studies, Institute of Smart Technology and Engineering, Faculty of Engineering and Information Technology, University of Pécs, Hungary)
  • Maria Jesus Lamela-Rey (Departamento de Construcción e Ingeniería de Fabricación, University of Oviedo, Spain)
  • János Lógó  (Department of Structural Mechanics, Faculty of Civil Engineering, Budapest University of Technology and Economics, Hungary)
  • Carmen Mihaela Lungoci (Faculty of Electrical Engineering and Computer Science, Universitatea Transilvania Brasov, Romania)
  • Frédéric Magoulés (Department of Mathematics and Informatics for Complex Systems, Centrale Supélec, Université Paris Saclay, France)
  • Gabriella Medvegy (Department of Interior, Applied and Creative Design, Institute of Architecture, Faculty of Engineering and Information Technology, University of Pécs, Hungary)
  • Tamás Molnár (Department of Visual Studies, Institute of Architecture, Faculty of Engineering and Information Technology, University of Pécs, Hungary)
  • Ferenc Orbán (Department of Mechanical Engineering, Institute of Smart Technology and Engineering, Faculty of Engineering and Information Technology, University of Pécs, Hungary)
  • Zoltán Orbán (Department of Civil Engineering, Institute of Smart Technology and Engineering, Faculty of Engineering and Information Technology, University of Pécs, Hungary)
  • Dmitrii Rachinskii (Department of Mathematical Sciences, The University of Texas at Dallas, Texas, USA)
  • Chro Radha (Chro Ali Hamaradha) (Sulaimani Polytechnic University, Technical College of Engineering, Department of City Planning, Kurdistan Region, Iraq)
  • Maurizio Repetto (Department of Energy “Galileo Ferraris”, Politecnico di Torino, Italy)
  • Zoltán Sári (Department of Technical Informatics, Institute of Information and Electrical Technology, Faculty of Engineering and Information Technology, University of Pécs, Hungary)
  • Grzegorz Sierpiński (Department of Transport Systems and Traffic Engineering, Faculty of Transport, Silesian University of Technology, Katowice, Poland)
  • Zoltán Siménfalvi (Institute of Energy and Chemical Machinery, Faculty of Mechanical Engineering and Informatics, University of Miskolc, Hungary)
  • Andrej Šoltész (Department of Hydrology, Faculty of Civil Engineering, Slovak University of Technology in Bratislava, Slovakia)
  • Zsolt Szabó (Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Hungary)
  • Mykola Sysyn (Chair of Planning and Design of Railway Infrastructure, Institute of Railway Systems and Public Transport, Technical University of Dresden, Germany)
  • András Timár (Faculty of Engineering and Information Technology, University of Pécs, Hungary)
  • Barry H. V. Topping (Heriot-Watt University, UK, Faculty of Engineering and Information Technology, University of Pécs, Hungary)

POLLACK PERIODICA
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or amalia.ivanyi@mik.pte.hu

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2023  
Scopus  
CiteScore 1.5
CiteScore rank Q3 (Civil and Structural Engineering)
SNIP 0.849
Scimago  
SJR index 0.288
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2023  
Scopus  
CiteScore 1.5
CiteScore rank Q3 (Civil and Structural Engineering)
SNIP 0.849
Scimago  
SJR index 0.288
SJR Q rank Q3

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