Authors:
Ákos Levente Kókai Antal Kerpely Doctoral School of Materials Science and Technology, University of Miskolc, Miskolc, Hungary

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Maria Berkes Maros Faculty Research Organization Center, Bánki Donát Faculty of Mechanical and Safety Engineering, Óbuda University, Budapest, Hungary

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Abstract

Cylinder bore coatings are widely used in automotive internal combustion engines to replace cylinder liners. During the atmospheric plasma spraying process, the coatings are oxidized and controlled by the Si content of the steel powder used as the coating raw material. This phenomenon affects the technological process, the microstructure, and the properties of the formed coatings. The research aims to investigate how the Si content of two commercial grades of steel powder commonly used in industry affects the undesirable consequences observed in practice, such as clogging of powder nozzles or large variations in coating hardness. The analyses and industrial experiments show that increasing the Si content can contribute significantly to these undesirable phenomena.

Abstract

Cylinder bore coatings are widely used in automotive internal combustion engines to replace cylinder liners. During the atmospheric plasma spraying process, the coatings are oxidized and controlled by the Si content of the steel powder used as the coating raw material. This phenomenon affects the technological process, the microstructure, and the properties of the formed coatings. The research aims to investigate how the Si content of two commercial grades of steel powder commonly used in industry affects the undesirable consequences observed in practice, such as clogging of powder nozzles or large variations in coating hardness. The analyses and industrial experiments show that increasing the Si content can contribute significantly to these undesirable phenomena.

1 Introduction

Global climate change is a constant development pressure on the automotive industry. For this reason, reducing fuel consumption is a priority for developing internal combustion engines. Thermal plasma spray coatings are advanced substitutes for the cylinder liners that were widely used in the past [1, 2]. Cylinder liner coatings have porous surfaces with improved tribological properties, which also serve as lubricant reservoirs, thus reducing friction and wear between the piston rings and cylinder bores [3–6].

Atmospheric Plasma Spraying (APS) is one of the most widely used technologies and has a wide range of applications, for example, in the automotive, aerospace, and aeronautical industries. Furthermore, a wide range of materials is available, suitable for the development of heat-resistant and wear-resistant coatings as well as for the reconditioning of components [7–9].

As coatings are formed under atmospheric conditions, they oxidize in extremely high-temperature spaces, as the turbulence of the argon plasma used in the coating process can cause the surrounding atmospheric constituents, such as oxygen, to mix into the plasma. The metal droplets in the molten state are thus oxidized, and these oxide compounds are transported by convection flow to the front surface of the melt droplets in the direction of flow [10–15]. The oxide compounds formed significantly influence the fabric structure of the resulting coatings and their tribological properties. Deshpande et al. [16] described that the oxide compounds formed shell-like layers on the surface of the melt droplets during their flight and then bent upon impact, thus creating a lamellar structure in the cross-section of the coatings.

Vencl et al. [17] have shown that steel coatings with different oxide contents applied to cylinder bores can reduce wear compared to grey cast iron cylinder liners. For example, the wear rate of APS steel coatings was reduced by 30% at 13% magnetite content and by 49% at 41% wüstite content during abrasion wear tests.

To protect the coatings from oxidation, silicon is added to the base material to form oxides due to its stronger affinity to oxygen, and the atmosphere does not oxidize the iron-based matrix. For this reason, different automotive suppliers have developed coating materials with varying silicon contents.

Lukács et al. [18] and Paniti [19] investigated a model for producing an automotive part by plastic forming using tribological simulation. In these works, the authors point out that the workpiece is exposed to severe wear due to the friction onset during the forming process, leading to an uncertain part quality.

Detailed knowledge of the properties of the coatings is essential to maintain the stability of the production and the required quality of the product. The current research aims to understand the relationship between silicon content and the microstructure and properties of the produced APS coatings and to investigate the effect of silicon on the technological processes involved in the coating process.

2 Materials and methods

2.1 Test samples

Experimental coatings have been prepared on cylinder bores of mechanically roughened four-cylinder crankshafts using two commercial grades of steel powders commonly used in industry for coating. The crankcases were made of AlSi9Cu3 alloy.

The experiments were carried out using an Oerlikon RotaCouplerTM Centerline F210 CL S310/74/40/-10°/R2.0 type coating head [20]. During the experiments, coatings were formed on cylinder bores of six to six crankshafts using powder feedstock purchased from two suppliers.

The chemical composition of the raw materials designated as Powder 1 and 2 (P1 and P2) used for coating preparation is shown in Table 1. The nominal composition represents the technological specifications of the automotive company, while Powder 1 and 2 show the composition of the commercially available grades used in the experiment. The main differences between the powders are in the silicon, oxygen, and nitrogen contents. Comparing the oxygen contents, it can be seen that Powder 1 was produced in an inert atmosphere, while Powder 2 was produced in a normal atmosphere.

Table 1.

Chemical composition of the raw powders in weight%

Raw materialCMnSiCrO, ppmN, ppm
Nominal composition1.301.401.40
Powder 11.071.340.411.3415133
Powder 21.111.250.871.2953855

The technological parameters used during the coating process and kept constant for each experiment are summarized in Table 2.

Table 2.

Technological parameters of the coating head set constant during the experiment

VoltageCurrentPower of the coating headPowder feed rateArgon flowHydrogen flowRate of suctionRevolution of the coating head
40 V360 A14.5 kW120 g min−140 L min−16 L min−117 m s−1600 min−1

Samples of 20 × 150 mm were cut from a selected cylinder of the finished crankcases and subjected to the qualitative and quantitative tests described in the following.

2.2 Investigation of the chemical composition

The chemical composition of the coatings was determined by the wet analytical method. The coatings were prepared for analysis by bouncing them off the cylinder bores using an electro-hydraulic press and then cleaning them in alcohol. The measured compositional characteristics are valid for the total volume of the coatings.

2.3 XRD analysis

The tests were carried out on the Bruker D8 Discover XRD SAXS XRR system [21] at the 3D Laboratory of the University of Miskolc. Due to the surface curvature of the specimens, the measurements were performed in parallel beam geometry produced by a Göbel mirror using Cu Kα(1+2) radiation with an accelerating voltage of 40 kV and a current of 40 mA. After recording the full spectra, the crystalline phases were identified from the International Center for Diffraction Data (ICDD) PDF database, and the austenite, martensite, and ferrite phase structures were calculated by Rietveld fitting for each sample.

2.4 Scanning electron microscopy

The tests were conducted at the Complex Image Analysis and Microstructural Testing Laboratory of the Institute of Metallurgy, Metal Forming and Nanotechnology, University of Miskolc. The analyses were performed on the ground, polished, and etched samples using Zeiss EVOMa10 equipment, complemented by selective area elemental analysis with Energy Dispersive X-ray (EDX) microprobe.

2.5 Morphological analysis and microhardness tests

Morphological analyses were performed by Optical Microscopy (OM) on a Zeiss AXIO Observer D1m microscope, and the hardness measurements on a MITUTOYO MVK-H1 type microhardness tester at the Laboratory of Metallography and Surface Testing of the Institute of Materials Science and Technology of the University of Miskolc. For the tests, shorter pieces were cut from the long samples described above and embedded in resin. Thus, the coatings' cross-sectional plane coincided with the samples' surface. The samples were ground and polished. To determine the Vickers Hardness (HV), a series of tests were carried out with different F = 0.5, 3, 5, and 10 N loading forces, and the values obtained were denoted HV0.05, HV0.3, HV0.5, and HV1, respectively. The minimum number of tests performed was five valid impressions for a given load.

2.6 Profilometry

The 2D roughness and 3D surface topography investigations were carried out on the AltiSurf 520 3D profilometer at the Institute of Manufacturing Science, University of Miskolc, using a CL2 optical confocal head (vertical resolution 0.012 μm). Surface topography measurements were performed on each sample at two locations, at the bottom of the top quarter and the top of the bottom quarter of the sample, by scanning an area of 4 × 4 mm. The 2D roughness was measured over a section length of 18 mm in the middle of the samples, parallel to the longitudinal axis of the samples.

3 Results and discussion

3.1 Chemical analysis

The results of the wet chemical analysis are summarized in Table 3. It can be observed that the carbon content of both coatings decreased slightly compared to the values measured in the base powder (Table 2). While the manganese, chromium, and silicon contents remained unchanged, the oxygen and nitrogen contents increased by two and three orders of magnitude, respectively. The nitrogen content also showed an increase. Molybdenum and titanium were not detectable in the coatings. It is worth noting that while the oxygen content of P1 base powder was one order of magnitude lower than that of P2 base powder, the situation was different in the produced coatings, with P2 coating having lower oxygen content, supposedly due to the higher Si content. Nevertheless, the difference was slight as the oxygen content of both coatings fell into the order of magnitude of 104 ppm.

Table 3.

Chemical composition of the formed coatings, weight%

SampleCMnSiPSCrNiCuAlVCoO, ppmN, ppm
P1 coating0.851.080.430.0110.0101.460.080.0800.0040.0050.01213443516
P2 coating0.931.250.980.0100.0061.540.130.0160.0020.0050.01411807394

3.2 X-ray diffraction investigations

The phase ratio of the formed coatings is depicted in Fig. 1. Based on the X-ray diffraction (XRD) analyses, it was established that the coatings have a very heterogeneous microstructure.

Fig. 1.
Fig. 1.

Phase ratios of the formed coatings

Citation: Pollack Periodica 19, 3; 10.1556/606.2024.01076

Different iron oxides and chromium carbides, consisting of ferrite, austenite, and martensite, were also detected in the metallic matrix of the coatings. There are two types of wüstite; into one of them, the Mn is dissolved, and two phases of austenite have been identified. The difference between the two phases could be a texture (but this would have required a flat surface to measure accurately) or different alloying and carbon content, which could have a thermal effect.

The main differences between the investigated coatings were represented by the significantly higher oxide content and the lower amount of metallic matrix, especially the lower residual austenite content of the coating produced from the P1 raw material. Due to the higher silicon content in P2, the coating is better protected from oxidation, which results in a lower oxide content in this coating. The phase analysis results agree with those of the chemical analysis.

3.3 Scanning electron microscopy

The microstructure of the coatings can be compared by analyzing their Scanning Electron Microscopic (SEM) images shown in Fig. 2.

Fig. 2.
Fig. 2.

The SEM BackScattered Electron (BSE) images of the microstructure of a) P1 and b) P2 coatings

Citation: Pollack Periodica 19, 3; 10.1556/606.2024.01076

Scanning electron microscopy studies revealed that the coatings have a highly inhomogeneous layer architecture and heterogeneous microstructure, which is a general feature of APS coatings. High porosity and separation between the layers decorated with oxides between them is also observed. Slag-like inclusions are characteristic in both coatings. However, its amount is significantly higher in the microstructure of the P2 coating due to its twice higher Si content, which hinders the oxidation of the iron but promotes the formation of the complex-oxides and a higher amount of slag-type phases.

The dark black areas in the microstructure are marks of slag items left from the oxidation mechanism and trapped in the metallic substrate during the coating process. The high porosity associated with the slag inclusions may be caused by the high oxygen content of the coatings, which leaves it after the metal solidifies. Thus, the cavities seen in the micrographs often had slag inclusions removed during sample preparation (i.e., grinding and polishing), so these material deficiencies can often be interpreted as porosity. Still, in fact, they were present in the form of complex oxide compound phases in the matrix.

While the XRD analyses showed a higher iron-oxide content of the P1 coating, the higher porosity in the P2 coating is associated with the higher amount of silicon content and the related higher amount of slag and porosity connected to these slag-containing regions. In addition, several spherical particles, which are base powder grains that were not melted into the slurry during the coating process, are also visible.

Altogether, it can be established that the P1 coating has a more homogeneous and continuous structure with fewer slag-like inclusions. In contrast, a highly porous structure with a higher amount of slaggy regions is characteristic of the P2 coating, where the separation between layers is much more expressed.

3.4 Microhardness tests and microstructural analyses by optical microscopy

The aim of the hardness tests was multi-directional. Characterizing the hardness of a multiphase porous material, which is highly heterogeneous in both microstructure and properties, strongly depends on the extension of the region of investigation, i.e., the size of the indentation. Therefore, a lower loading force was used to characterize the local hardness, i.e., the hardness of the individual phases, and a higher loading force was used to characterize the average hardness of the larger regions of the heterogeneous structure in the hardness tests with four different loading forces described in section 2.5.

The numerical hardness values are illustrated in Fig. 3. At the same time, the indentations generated by each loading force are shown in Fig. 4 also indicating the range of the typical size (average diagonal d) of the indentations.

Fig. 3.
Fig. 3.

The microhardness of the two coatings measured by different loading forces

Citation: Pollack Periodica 19, 3; 10.1556/606.2024.01076

Fig. 4.
Fig. 4.

Microhardness indentations from different loading force tests

Citation: Pollack Periodica 19, 3; 10.1556/606.2024.01076

The hardness values shown in Fig. 3 indicate slight force dependence. On the one hand, it may be because the metallic matrix contains a high amount of ferrite and austenite, which have a high hardening component, and therefore, the phenomenon may be related to the microstructural changes of the coating.

On the other hand, it can also play a role that the smaller size (d = 10÷55 µm) indentations obtained with lower (F = 0.5…, 5 N) loadings were always tried to place in an intact, relatively homogeneous area of the matrix (Fig. 4) so that they mainly provide information on the hardness of the metallic matrix.

As the load force increases, the indenter hits more and more hard grains, so it may also cause the rise in measured hardness. Still, overall, in the applied F = 0.5…, 5 N load range, the effect of the metallic matrix dominates the test results, which is confirmed by the microphotographs presented in Fig. 4. The decrease in hardness observed for both coatings at 10 N load is explained by the effect of the significant amount of pores falling into the area of the larger indentations and in the deeper regions below them, which the test results can no longer be independent of, and an apparent lower hardness is measured due to porosity.

By comparing the hardness of the P1 and P2 coatings, a systematically higher hardness for the P1 coating can be seen at each loading. This is consistent with the phase composition results presented in Fig. 1, which show a much higher amount of hard phase in this coating. The relative standard deviation of the measured hardness values for HV0.05, HV0.3, HV0.5, and HV1 was found to be 12, 9, 14 and 20% for the P1 coating, respectively, and 13, 6, 15 and 11% for the P2 coating, respectively. In other words, the variation coefficient at a given load was almost the same for both coatings and was the lowest at F = 3 N.

One important characteristic of the machinability of coatings is the hardness index, which is directly influenced by the quality, quantity, and distribution of the phases that make up the coating. The optical microscope images shown in Fig. 5 explain the significant variation in hardness values and the phase differences that can be detected.

Fig. 5.
Fig. 5.

MicroVickers indentations and the related HV0.05 hardness values characterizing the soft and hard phases of a) P1 and b) P2 coating

Citation: Pollack Periodica 19, 3; 10.1556/606.2024.01076

The spherical grains shown in the figure are unmelted metal powder grains with a martensitic structure. Their surface is covered by a thin oxide film, which strongly prevents the metal powder particles from melting into the liquid phase. In addition to the theoretical knowledge in the literature [1016] that can also be inferred from the fact that a thin oxide layer always appears between the layers of the coating, as can be seen in the microscopic images (Fig. 2).

Among the hardness values measured in both the matrix and the spherical phases, on the one hand, there can be found very small (243-352 HV0.05) hardness values. On the other hand, one of the indentations in the matrix of the P1 coating shows a significantly higher hardness (408 HV0.05) than that of the P2 coating (537 HV0.05). This is due to the widely differing oxidation processes occurring during the coating, which result in significantly different metallurgical processes (different alloy content of the grains, their influence on the critical cooling rate, type, and size of the oxide inclusions formed, their hardness, etc.), which can be closely related to the significantly different Si content of the coatings.

Where the hardness of the spherical grains is lower, the grains are embedded in a larger amount of grey phase, which XRD studies show to be mostly wüstite. This is an iron oxide with a porous structure, which surrounds the spherical unmelted metallic powder grains in the molten state. From these grains, by diffusion, a large proportion of the alloying elements can be transferred to the slag, thus reducing its hardness. The more they retain their original composition, the more the critical cooling rate of the base metal decreases, and the higher the probability of non-equilibrium, higher hardness phases, e.g., martensite, in these grains containing predominantly base metal. This can also be concluded from the fact that grains with a higher hardness are covered by a thinner, more uniform oxide film and are embedded mainly in a metallic environment. Examples are the 392 HV0.05 and 404 HV0.05 grains in the P1 coating or the 413 HV0.05 and 537 HV0.05 grains in the P2 coating.

Identifying the higher hardness phases found in the matrix is a much more complex task since, in a thermal/metallurgical process such as atmospheric plasma spraying, the precipitates formed in the metallic matrix can have a very diverse composition depending on the dissolution and diffusion of other elements - alloying elements and impurities - present in the steel. For example, the iron-silicate compounds formed at higher Si contents may strongly inhibit the diffusion of Fe atoms, which changes the type of iron oxides formed, replacing the lower hardness wüstite with, among others, the higher hardness magnetite. This is confirmed by the XRD analysis of the P2 coating (Fig. 1). The measured hardness values can be closely related to the XRD test results. If the phase composition results shown in Fig. 1 are rearranged as it is illustrated in Fig. 6 and compared with the total amount of soft and high hardness phases in P1 and P2 coatings, the higher hardness of P1 coatings can be attributed to the much higher amount of non-metallic phases in P1 coatings. However, the difference in hardness between the two coatings is much smaller than the amount of oxides. The reason is that the P2 coating, with its significantly higher porosity and coarser structure, considerably reduces the hardness measured on the bulk material, as described earlier.

Fig. 6.
Fig. 6.

Soft and hard phases in the P1 and P2 coatings

Citation: Pollack Periodica 19, 3; 10.1556/606.2024.01076

3.5 Profilometry

Profilometry analysis of the raw, unmachined surface of the coatings revealed several differences between the two coatings, which could be related to the different alloy content of the powders. During the production of the experimental workpieces, when using the P2 raw material, the powder nozzles of the coating machine head became clogged in many cases, and the nozzle could not continuously deliver the adjusted amount of powder. The fluctuating powder feed resulted in small droplet-like deposits on the surface (Fig. 7). In similar cases, the coating process had to be interrupted, and production could only be continued by installing a new nozzle.

Fig. 7.
Fig. 7.

A small splash on the surface of the P2 coating

Citation: Pollack Periodica 19, 3; 10.1556/606.2024.01076

Detectable differences can also be found in the characteristics of the two coatings as determined by 2D and 3D profilometric analysis. In the topographic images (Fig. 8), the P1 coating shows a much more uniform relief than the P2 coating.

Fig. 8.
Fig. 8.

Surface topography of a) P1 and b) P2 coatings obtained by profilometry

Citation: Pollack Periodica 19, 3; 10.1556/606.2024.01076

Among the numerical characteristics, the Spatial average (Sa) roughness and the Spatial material ratio (Smr) were compared (Fig. 9).

Fig. 9.
Fig. 9.

Comparison of the coatings based on the spatial roughness characteristics

Citation: Pollack Periodica 19, 3; 10.1556/606.2024.01076

It can be seen that while there is hardly any measurable difference in the Sa values, which were 10.4 and 11.6 μm for P1 and P2 coatings, respectively, there is a significant difference - 71.4% and 10.4%, respectively - in the Smr values measured at a depth of 100 µm from the highest peak, which is important for the operation of these surfaces.

4 Conclusion

APS coating experiments were carried out on the surface of engine block cylinders using different silicon-containing hypoeutectic steel powder raw materials.

The chemical analyses showed that the silicon content in the P1 raw material (0.41%) is half that of P2 (0.87%). In contrast, their oxygen content falls in the order of magnitude of 101 and 102 ppm, respectively. During the APS coating process performed at atmospheric conditions, the oxygen content of the coatings increased to 104 ppm of order of magnitude. These findings agree with the results of the XRD phase analyses, revealing a significant amount of different iron-oxides in the metallic matrix, namely 43.5% in the P1 coating and 29.6% in the P2 coating.

Microstructural analysis of thermally sprayed cylinder wall coatings indicated slag-like (highly probable silicon dioxide) inclusions within both coatings, with a higher amount in the P2 coating, explained by its higher silicon content. These inclusions are characteristically connected to pores, resulting in a higher porosity of the P2 coatings. MicroVickers hardness tests performed by four different loadings showed slight force dependence but systematically higher hardness of the P1 coating for all applied loadings, which is in harmony with the higher iron-oxide content of this coating. The hardness values obtained with F = 3 N, the measurement with the lowest relative scattering, were 341 HV0.3 and 287 HV0.3 for P1 and P2 coatings, respectively.

In the very inhomogeneous structure of the coatings, a unique inherent feature of APS coatings, a large number of spherical particles, identified as unmelted powder particles of the raw materials, were found during the optical microscopic investigations. The low load (F = 0.05 N) hardness test showed very different hardness for these items, referring to the varying cooling conditions and diffusion rates, resulting in different compositions of the particular martensitic grains formed during the non-equilibrium cooling.

During the experiments aimed at modeling the industrial coating processes, an important shortcoming was observed in the case of the P2 raw material. P2 powder possessing the higher Si content melts prematurely in the zone affected by the heat from plasma, leading to clogging of the nozzles, which is undesirable for the stability of the coating process. This fluctuating powder feed rate results in small splashes on the coating's surface, leading to a slightly higher average surface roughness (Ra = 11.6 μm vs. Ra = 10.4 μm) but a significantly lower spatial material ratio (Smr = 10.4% vs. Smr = 71.4%) of the P2 coating vs. P1 coating, which is unfavorable regarding the manufacturing process (honing operation), as well as the operational characteristics of the coating's surfaces.

In the OM and SEM micrographs of the coatings, several slag-like inclusions - in higher amounts for P2 coating - that felt out of the investigated surfaces during surface preparations were observed. These coarse particles also fall out of the coating during rough machining, leaving considerable material discontinuities in the metallic matrix, resulting in considerably higher dynamic loading during fine machining, e.g., honing.

The research provided useful information for understanding the microstructural and machinability differences of the investigated coatings.

Based on the results obtained, the application of the lower Si content powder in manufacturing cylinder wall coatings is recommended for serial production compared to higher Si content powder from the point of view of manufacturing time, tool cost, and application properties of the coatings.

Acknowledgment

The research work was carried out with the support of the European Union and the Hungarian Government, co-financed by the European Regional Development Fund, in the framework of the project GINOP-2.3.4-15-2016-00004, with the aim of promoting cooperation between higher education and industry. The authors would like to thank all the support provided by the University of Miskolc, namely Prof. Dr. János Lukács (FIEK; Institute of Materials Science and Technology) for providing the financial conditions for the research work, Prof. Dr. Valeria Mertinger and colleagues (Institute of Metals Forming and Nanotechnology) for their significant help in the phase analyses, Dr. Tibor Kulcsár (Institute of Casting) for his help in the in-depth analysis of the metallurgical issues of oxidation processes, Dr. Olivér Bánhidi (Institute of Chemistry) for his consultations on chemical composition studies, Dr. Csaba Felhő and Dr. Zsolt Maros (Institute of Manufacturing Sciences) for the profilometry measurements and analyses, furthemore the staff of the Institute of Materials Science and Technology, namely Ágnes Csurilláné Balogh and Nóra Nagy, for their assistance in hardness measurement and metallographic preparations, András Bartók and Géza Csukás for their help in the preparation of test specimens.

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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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