Authors:
Masoud Osfouri Institute of Ceramics and Polymer Engineering, Faculty of Materials Science and Engineering, University of Miskolc, Miskolc-Egyetemvaros, Hungary

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Andrea Simon Institute of Ceramics and Polymer Engineering, Faculty of Materials Science and Engineering, University of Miskolc, Miskolc-Egyetemvaros, Hungary

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Abstract

This paper focuses on the relationship between the composition of foam glass and its thermal conductivity and density. In this experimental research, three levels of glass particle size and foaming agent (SiC) quantity were tested. The results showed that the thermal conductivity increased by increasing the ratio of fine glass particles. On the contrary, the thermal conductivity was not affected by changing the foaming agent weight ratio. The density of foam glass increased by decreasing the foaming agent ratio, and there was no linear relation between the size of glass particles and the density of foam glass.

Abstract

This paper focuses on the relationship between the composition of foam glass and its thermal conductivity and density. In this experimental research, three levels of glass particle size and foaming agent (SiC) quantity were tested. The results showed that the thermal conductivity increased by increasing the ratio of fine glass particles. On the contrary, the thermal conductivity was not affected by changing the foaming agent weight ratio. The density of foam glass increased by decreasing the foaming agent ratio, and there was no linear relation between the size of glass particles and the density of foam glass.

1 Introduction

In many engineering applications, it is necessary to combine the properties of materials and it is difficult to find a material that proves all of the required properties. For example, in the building industries, materials are needed to have high strength, low density, good sound/heat insulation, high vibration damping, good wettability, and high adhesion capability. Many ceramic materials could be used for thermal insulation in the form of foams or bricks [1, 2]. Foam glass is one of the modern lightweight materials, which can withstand high temperatures, and provide outstanding sound and heat insulation at the same time. The main substances of foam glass are the glass powder and the foaming agent, while the most well-known processing method is the powder method which covers the mixing, pressing, and subsequently sintering of the mixture. The sintering temperature, which is also called foaming temperature, should exceed the glass softening point. [3–5].

In general, the glass powder is provided from waste glass. Consequently, foam glass has two advantages. Firstly, it is benefited both mechanical and thermal properties simultaneously. On the other hand, using waste glass causes less harm to the environment [6]. Foam glass is a hetero-phase material that consists of both solid and gaseous phases. The glass as a solid phase builds up the cell walls having micrometer scaled thickness. Additionally, the inside of the cells consists of one or more gaseous phases (for example CO2, O2, etc.,) originating mainly from the foaming agent.

Typically, foam glasses have a compressive strength in the range of 1.5–5.5 MPa, and the bulk density varies in the range of 120–400 kg m−3. Despite many natural foam materials, which consist of open-cell structures, the foam glass could consist of closed cells structures that made foam glass to be an efficient candidate in humid weather as an aggregate of concretes [7–11].

There are several materials suggested to use as a foaming agent in foam glass, like KNO3, commercial dolomite- and calcite-based sludge, MnO2 and carbon [12]. Ibrahim et al. [13] found that increasing the foaming temperature lead to the occurrence of amorphous phase and anorthite. By increasing further the temperature, the latter decomposed and an amorphous glassy phase appeared.

Regarding further researches, the glass particle size also affects the density of final foam glass. Generally, the finer glass particles lead to a lower density of foam glass. By decreasing particle size or increasing milling time the density of the foam glass decreases. Furthermore, decreasing the glass particle size leads to a decrease in the sintering temperature [14–16]. König et al. [15] studied the glass particle size effect on the foaming process, as well as the density, and the microstructure of the foam glass. The results showed that the foaming was mainly caused by the reduction of manganese. They obtained a very lightweight foam glass, with a density of around 150 kg m−3 when the glass particle size was less than 33 μm. They revealed that when the particle size was smaller than 13 μm, the pore size increased to 1–3 mm due to the faster coalescence process.

Research works revealed that the foaming agent to glass weight ratio and the glass particle size could be two critical parameters that affect the properties of the final material [9–11]. One of the most useful and high-demand materials to be employed as a foaming agent is SiC. However, there is a lack of knowledge about the relationship between foam glass particle sizes and foaming agent to glass ratio on the properties of foam glasses. This study aims to find the relationship between these parameters and the density and thermal conductivity of the produced foam glass.

2 Materials and methods

2.1 Design of experiments

In order to conduct the research work, first of all, the experiments were designed. As this study focuses on the effect of particle size and foaming agent to glass weight ratio, these parameters were considered as input variables.

To make three levels of particle size variables, two different ranges of particle sizes–between 125 and 160 μm and less than 90 μm, nominated as D1 and D2, respectively were chosen. The levels of particle sizes were defined as Level 1: 66 wt% D1–34 wt% D2, Level 2: 50 wt% D1–50 wt% D2 and Level 3: 34 wt% D1–66 wt% D2.

Based on previous experiments [17, 18] and a short literature review [5, 11, 19, 20], the weight ratio of the foaming agent was considered to change in three levels with a 0.5 wt% step as follows: 1 wt%, 1.5 wt%, and 2 wt%.

To obtain the optimal accuracy, five replications for each combination were prepared. The specimens were coded as Pn-m, where n stands for the level of particle sizes (could be 1, 2, or 3) and m represents the level of foaming agent ratio (could be 1, 2, or 3). Nine experimental groups were produced completely (overall 45 specimens by considering the iterations). Table 1 shows the groups and their detailed compositions.

Table 1.

The experimental groups and their related compositions (whereas D1 particle size is between 125 and 160 μm, D2 particle size is less than 90 μm)

Experimental groupsGlass particle size level wt%Foaming agent content, wt%
P1-1L1: 66 D1–34 D2L1: 1.0
P1-2L1: 66 D1–34 D2L2: 1.5
P1-3L1: 66 D1–34 D2L3: 2.0
P2-1L2: 50 D1–50 D2L1: 1.0
P2-2L2: 50 D1–50 D2L2: 1.5
P2-3L2: 50 D1–50 D2L3: 2.0
P3-1L3: 34 D1–66 D2L1: 1.0
P3-2L3: 34 D1–66 D2L2: 1.5
P3-3L3: 34 D1–66 D2L3: 2.0

Note that in experimental group code (Pn-m), “n” stands for the level of glass particle sizes (could be 1, 2, or 3) and “m” represents the level of foaming agent content (could be 1, 2, or 3).

2.2 Materials

The glass used in this study was waste Soda Lime Silicate (SLS) glass. The size of waste glass cullet was between 5 and 12.5 mm. The foaming agent used in this study was SiC provided by Ibiden Hungary Ltd.

The first step was to prepare the glass powder. The crushed glass was milled in a planetary ball mill (Retsch PM 400) with 200 rpm for 20 min with balls having a diameter of 20.15 mm. After the milling, the glass powder was sieved in a vibrator sieve to obtain the two fractions (D1 = 125–160 μm and D2< 90 μm) of particle size. The fractionated glass powders were mixed to obtain the three levels of particle size combinations:

  1. 34 wt% of glass with particle size less than 90 μm–66 wt% of glass with particle size between 125 and 160 μm;

  2. 50 wt% of glass with particle size less than 90 μm–50 wt% of glass with particle size between 125 and 160 μm;

  3. 66 wt% of glass with particle size less than 90 μm–34 wt% of glass with particle size between 125 and 160 μm.

Finally, the foaming agent (having a particle size less than 1 μm) was added to each particle size related combination. These groups contained 1 wt%, 1.5 wt%, or 2 wt% of SiC. The final compositions were homogenized in a laboratory mixer at 20 rpm for 18 min. The mixed powders were tested in a Camar Elettronica MicrOVis heating microscope to obtain the temperature where the specimens reach their maximum expansion. The ratio of the actual to the initial height of specimen was constantly recorded by software, and its maximum was considered as the maximum expansion. The homogenized powders were mixed with 1 wt% water to augment the consolidation of the composition. After this stage, five grams of each composition were placed into the pressing mold and exposed to a pressure of 5 tons.

The pressed specimens were placed into a drying chamber and heated to 50 °C for four hours to complete the drying step. After that, they were put on a ceramic sheet covered with alumina (Al2O3) powder to avoid the probable adhesion between the foam glass and the sheet, and placed into a laboratory furnace. Five iterations of each foam glass composition were placed at the center band of the sheet to decline the practical temperature gradient. The specimens were heated to the sintering temperature–set as the temperature obtained from the heating microscopy tests (Table 2)–with 10 °C min−1 heating rate and held at the peak temperature for 5 min. After the sintering, the specimens were left in the furnace to cool down to room temperature.

Table 2.

Foaming characteristics of the foam glass mixtures obtained by heating microscopy

Experimental groupsFoaming temperature (°C)Actual height/initial height (%)
P1-1986124
P1-2940132
P1-3930129
P2-1959124
P2-2941144
P2-3951130
P3-1946117
P3-2953122
P3-3928117

Note that in the experimental group code (Pn-m), “n” stands for the level of particle sizes (could be 1, 2, or 3) and “m” represents the level of foaming agent ratio (could be 1, 2, or 3).

Before performing the thermal conductivity tests, the top and bottom surfaces of the specimens were rubbed with sandpaper to make parallel with each other. After this step, the periphery parts of the specimens were eliminated with lathe machining. So the final shape of the specimens was cylindrical (Fig. 1).

Fig. 1.
Fig. 1.

a) Machining and forming the foam glass; b) the cylindrical foam glass specimen (background grid is 1 × 1 cm)

Citation: Pollack Periodica 18, 1; 10.1556/606.2022.00591

2.3 Tests methods

2.3.1 Density

First of all, the dry weight of the specimens was measured by using a 4 digits' laboratory balance. Subsequently, the specimens were put in a pot full of distilled water and boiled for four hours. Afterwards, a modified Archimedes method was used to measure the volume of each specimen. In this method, each porous specimen (Fig. 2a) was modeled as Fig. 2b.

Fig. 2.
Fig. 2.

a) Intersection sketch of the porous foam glass; b) the modeled foam glass containing open pores, closed pores, and cell walls; A represents the sum of the cells walls, B represents the sum of the open pores, and C area is equal to the total closed pore volume)

Citation: Pollack Periodica 18, 1; 10.1556/606.2022.00591

After all the open pours were saturated with water (see area B in Fig. 2b), the saturated specimen was put in the empty laboratory beaker and a weight was placed on that to avoid floating the foam glass. The pristine surface level of 100 ml water, containing the holder weight, was already marked on the beaker (Fig. 3a). After the specimen and the weight were placed in the beaker, the difference between the new and the pristine surface was photographed and measured using ImageJ image analysis software. Finally, the volume of saturated foam was calculated (Fig. 3b). Since the open pores were filled by water (at room temperature, 21 °C), the obtained density was considered as the apparent foam density.

Fig. 3.
Fig. 3.

a) The 100 ml + weight's water level; b) the foam glass and the weight in 100 ml of water

Citation: Pollack Periodica 18, 1; 10.1556/606.2022.00591

2.3.2 Thermal conductivity

The thermal conductivity of each specimen was measured at room temperature by using a C-Therm TCi laboratory instrument. Each specimen was tested five times and the mean of the measured data was calculated.

2.3.3 Open-pore volume

After the volume of specimens was measured, the water-saturated specimens were weighed. The difference between the weight of wet and dry specimens was considered as the absorbed water. By dividing absorbed water weight by the water's density, the total volume of open pores was obtained for each specimen. The microstructure of the specimens was visualized by a Canon EOS 70D camera.

2.3.4 Data analysis

After all the data was extracted from the experiments, they were analyzed by using a T-test to see if the changes in the density, volume, and thermal conductivity of groups are related to the input parameters.

3 Results and discussion

3.1 Density

The density of the foams was obtained from the modified Archimedes test. Every three groups of specimens' results were arranged in two categories. Figures 4 and 5 show the density of specimens containing the same foaming agent and the same particle size levels, respectively.

Fig. 4.
Fig. 4.

The density of foam glasses with different particle size levels (Particle size Level 1: 66 wt% D1–34 wt% D2; Level 2: 50 wt% D1–50 wt% D2 and Level 3: 34 wt% D1–66 wt% D2; D1 = 125–160 μm and D2< 90 μm

Citation: Pollack Periodica 18, 1; 10.1556/606.2022.00591

Fig. 5.
Fig. 5.

The density of foam glasses with different foaming agent content (particle size Level 1: 66 wt% D1–34 wt% D2; Level 2: 50 wt% D1–50 wt% D2 and Level 3: 34 wt% D1–66 wt% D2; D1 = 125–160 μm and D2< 90 μm)

Citation: Pollack Periodica 18, 1; 10.1556/606.2022.00591

In the categories, which contained the same particle sizes (Fig. 5), when the particle size is at Level 1 (coarse particles > fine particles) and at Level 2 (the amount of coarse and fine particles is equal) by increasing the foaming agent ratio from the 1 to 1.5 wt%, the density strongly increases, but in case of 1.5–2 wt% foaming agent, it slightly decreases. When the composition contained Level 3 of the particle sizes (there are more fine particles than coarse particles), the density of the foam glass increased by increasing the foaming agent ratio. It could be explained in a way that when the composition included larger particles, by increasing the foaming agent ratio from 1 to 1.5 wt%, some of the closed pores collapsed because the released gas from the reaction of the foaming agent passed out through the coarse non-melted glass particles. In the case of 1.5–2 wt% foaming agent, the released gas is trapped inside the structure of the foam glass. If the particle size decreases and the foaming agent ratio increases, when reaching the sintering temperature, the extra gas may find a way to release throughout the specimen. When the particle size is at Level 3 and the foaming agent ratio increases, the density also increases. Figure 6 shows the microstructure of these foam glass specimens. To investigate the level of confidence about changes in the results, a statistical T-test was performed on the results (results are shown in Tables 3 and 4).

Fig. 6.
Fig. 6.

The microstructure of foam glasses having different foaming agent content and different particle sizes

Citation: Pollack Periodica 18, 1; 10.1556/606.2022.00591

Table 3.

T-test results for density dependency of foaming agent content

NumberTested treatmentsT-value
1P1-1 and P1-24.22 × 10−9
2P1-2 and P1-30.002127
3P2-1 and P2-20.000123
4P2-2 and P2-30.005200
5P3-1 and P3-20.212955
6P3-2 and P3-33.07 × 10−5
Table 4.

T-test results for density dependency of particle size levels

NumberExperimental groupsT-value
1P1-1 and P2-10.030202
2P2-1 and P3-10.213090
3P1-2 and P2-20.001149
4P2-2 and P3-23.77 × 10−7
5P1-3 and P2-30.004937
6P2-3 and P3-30.003712

The results showed that when the foaming agent ratio was at Level 1 (1 wt%) the changes in particle sizes had significant effect on the density, while when the foaming agent ratio was at Level 2 and 3, the change in the particle size from Level 1 to 2 had no significant effect. Otherwise, by changing the particle size from Level 2 to Level 3, and having 1.5 and 2 wt% of foaming agent, there was a significant change in the density of specimen. Note that the probability value was considered as 5% for the T-test in this study. As it mentioned before the open pores volume ratio was calculated by dividing the difference of wet and dry sample's weight by the density of water. Figure 7 shows the average open pores ratio of each experimental group.

Fig. 7.
Fig. 7.

The open pores to total volume of specimens

Citation: Pollack Periodica 18, 1; 10.1556/606.2022.00591

3.2 Thermal conductivity

As it is shown in Fig. 8, when the foaming agent ratio is 1 wt%, there was no significant effect of changing the particle size from Level 1 to Level 2. When the particle size changes from Level 2 to Level 3, there was not a good correlation with the thermal conductivity. The changes in the thermal conductivity of the specimens containing 1.5 and 2 wt% foaming agents were the same when the particle size was in Level 3. Overall, by increasing the foaming agent ratio the thermal conductivity increases and the change in particle size has no significant effect on the thermal conductivity of foam glass.

Fig. 8.
Fig. 8.

Thermal conductivity of foam glasses with different foaming agent ratio (particle size Level 1: 66 wt% D1–34 wt% D2; Level 2: 50 wt% D1–50 wt% D2 and Level 3: 34 wt% D1–66 wt% D2; D1 = 125–160 μm and D2 < 90 μm)

Citation: Pollack Periodica 18, 1; 10.1556/606.2022.00591

4 Conclusion

In this study, the aim was to investigate the effect of the foaming agent ratio and glass particle sizes on the density and thermal conductivity of foam glass. Nine experimental groups with five specimens were tested and the results showed that by increasing foaming agent content the thermal conductivity increases. The microstructure observations revealed that by increasing foaming agent content, bigger cells are created and by decreasing the size of the glass particles the uniformity of the microstructure decreases.

References

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  • [1]

    S. I. A. Ali and Z. Szalay, “Overview and analysis of the overheating effect in modern Sudanese buildings,” Pollack Period., vol. 15, no. 3, pp. 208219, 2020.

    • Search Google Scholar
    • Export Citation
  • [2]

    J. E. F. M. Ibrahim, E. Kurovics, M. Tihtih, and L. A. Gömze, “Ceramic bricks with enhanced thermal insulation produced from natural zeolite,” Pollack Period., vol. 16, no. 3, pp. 101107, 2021.

    • Search Google Scholar
    • Export Citation
  • [3]

    A. Rincón, M. Marangoni, S. Cetin, and E. Bernardo, “Recycling of inorganic waste in monolithic and cellular glass‐based materials for structural and functional applications,” J. Chem. Technol. Biotechnol., vol. 91, no. 7, pp. 19461961, 2016.

    • Search Google Scholar
    • Export Citation
  • [4]

    M. T. Souza, B. G. O. Maia, L. B. Teixeira, K. G. de Oliveira, A. H. B. Teixeira, and A. P. N. de Oliveira, “Glass foams produced from glass bottles and eggshell wastes,” Process Saf. Environ. Prot., vol. 111, pp. 6064, 2017.

    • Search Google Scholar
    • Export Citation
  • [5]

    D. I. Saparuddin, N. A. N. Hisham, S. A. Aziz, K. A. Matori, S. Honda, Y. Iwamoto, and M. H. M. Zaid, “Effect of sintering temperature on the crystal growth, microstructure and mechanical strength of foam glass-ceramic from waste materials,” J. Mater. Res. Technol., vol. 9, no. 3, pp. 56405647, 2020.

    • Search Google Scholar
    • Export Citation
  • [6]

    D. D. Khamidulina, S. A. Nekrasova, and K. M. Voronin, “Foam glass production from waste glass by compression,” IOP Conf. Ser. Mater. Sci. Eng., vol. 262, 2017, Paper no. 012008.

    • Search Google Scholar
    • Export Citation
  • [7]

    M. A. Elrahman, S. Y. Chung, and D. StephanEffect of different expanded aggregates on the properties of lightweight concrete,” Mag. Concrete Res., vol. 71, no. 2, pp. 95107, 2019.

    • Search Google Scholar
    • Export Citation
  • [8]

    M. F. Dragoescu, S. M. Axinte, L. Paunescu, and A. Fiti, “Foam glass with low apparent density and thermal conductivity produced by microwave heating,” Eur. J. Eng. Technol., vol. 6, no. 2, pp. 19, 2018.

    • Search Google Scholar
    • Export Citation
  • [9]

    H. W. Guo, Z. X. Mo, P. Liu, and D. N. Gao, “Improved mechanical property of foam glass composites toughened by mullite fiber,” Appl. Mech. Mater., vols 357–360, pp. 13701373, 2013.

    • Search Google Scholar
    • Export Citation
  • [10]

    E. Kim, K. Kim, and O. Song, “Properties of basalt-fiber reinforced foam glass,” J. Asian Ceram. Societies, vol. 8, no. 1, pp. 170175, 2019.

    • Search Google Scholar
    • Export Citation
  • [11]

    Y. Liu, J. Xie, P. Hao, Y. Shi, Y. Xu, and X. Ding, “Study on factors affecting properties of foam glass Made from waste glass,” J. Renew. Mater., vol. 9, no. 2, pp. 237253, 2021.

    • Search Google Scholar
    • Export Citation
  • [12]

    X. Wang, D. Feng, B. Zhang, Z. Li, C. Li, and Y. Zhu, “Effect of KNO3 on the microstructure and physical properties of glass foam from solid waste glass and SiC powder,” Mater. Lett., vol. 169, pp. 2123, 2016.

    • Search Google Scholar
    • Export Citation
  • [13]

    J. E. F. M. Ibrahim, L. A. Gömze, D. Koncz-Horvath, Á. Filep, and I. Kocserha, “Preparation, characterization, and physicomechanical properties of glass-ceramic foams based on alkali-activation and sintering of zeolite-poor rock and eggshell,” Ceramics Int., vol. 48, no. 18, pp. 2590525917, 2022.

    • Search Google Scholar
    • Export Citation
  • [14]

    J. König, R. R. Petersen, and Y. Yue, “Influence of the glass-calcium carbonate mixture's characteristics on the foaming process and the properties of the foam glass,” J. Eur. Ceram. Soc., vol. 34, no. 6, pp. 15911598, 2014.

    • Search Google Scholar
    • Export Citation
  • [15]

    J. König, R. R. Petersen, and Y. Yue, “Influence of the glass particle size on the foaming process and physical characteristics of foam glasses,” J. Non-Crystalline Sol., vol. 447, pp. 190197, 2016.

    • Search Google Scholar
    • Export Citation
  • [16]

    E Saakyan, A. Arzumanyan, and G. Galstyan, “Chemical technology of cellular glass production,” in E3S Web of Conferences, vol. 97, 2019, Paper no. 02012.

    • Search Google Scholar
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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)

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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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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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