Enhancing thermal performance of phase change materials in building envelopes

Ammar Saliby; Béla Kovács

doi:10.1556/606.2024.01153

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Pollack Periodica

Volume/Issue:: Volume 20: Issue 1

Enhancing thermal performance of phase change materials in building envelopes

Authors:

Ammar Saliby

Ammar Saliby Department of Mathematics Analysis, Institute of Mathematics, Faculty of Mechanical Engineering and Informatics, University of Miskolc, Miskolc, Hungary

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saliby.ammar@student.uni-miskolc.hu https://orcid.org/0009-0006-2555-022X

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Béla Kovács

Béla Kovács Department of Mathematics Analysis, Institute of Mathematics, Faculty of Mechanical Engineering and Informatics, University of Miskolc, Miskolc, Hungary

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Pages:: 87–94

Online Publication Date:: 14 Nov 2024

Publication Date:: 26 Mar 2025

Article Category:: Research Article

DOI:: https://doi.org/10.1556/606.2024.01153

Keywords:: phase change materials; thermal energy storage; latent heat storage; building envelope; computational fluid dynamics

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Abstract

Phase change material in conjunction with a passive latent heat thermal energy storage approach is a potentially effective way to solve the growing concerns about building energy usage. This research examines the thermal performance of building envelopes in Miskolc, Hungary. The factors impacting the thermal performance of phase change material integrated into the building envelope were assessed. The findings indicate that the enthalpy and melting temperature of the phase change material significantly impact the effectiveness of phase change material-based walls. It was determined the optimal location of the phase change material layer is possible. This determination is intricately related to the thermal properties of the phase change material and the prevailing environmental conditions.

Abstract

1 Introduction

The rise of global energy consumption in buildings has become a pressing issue in many countries. According to the International Energy Agency (IEA), there has been a recent 40% increase in energy demand for commercial buildings and a 61% increase for residential buildings worldwide. The predominant energy usage in these buildings is attributed to Heating, Ventilation, and Air Conditioning (HVAC) systems. If this trajectory continues, energy consumption in these buildings is expected to escalate by as much as 37% by the year 2050 [1]. Ensuring a comfortable environment remains a primary consideration for commercial and residential buildings, irrespective of weather conditions, placing distinct requirements on the energy needed for heating and cooling. The energy consumption of a building contributes to 20–40% of the total energy demand [2–5]. Hence, enhancing system efficiency would yield significant advantages in managing energy consumption. Effective thermal management is crucial for ensuring system efficiency. Thermal Energy Storage (TES) systems represent a recent advancement in thermal management technology, allowing the storage of thermal energy rather than its wasteful dissipation. This technology can be implemented through various methods, including storing energy through thermochemical processes and sensible and latent heat storage [6, 7]. The utilization of Phase Change Materials (PCMs) is observed in systems employing Latent Heat Storage (LHS) [8]. PCMs can absorb and release heat throughout phase transitions characterized by constant temperature. These materials exhibit high heat absorption and release capacities within a compact unit volume. Heat is stored during the melting and charging phases and released during the solidification and discharge phases. In numerous applications, PCMs effectively regulate energy, allowing precise control of the required amount of energy. Moreover, PCMs shift peak energy demand to off-peak hours, improving building efficiency [9–11]. PCMs can transform solid and liquid states, absorbing the latent heat of fusion and its reverse process. Similarly, they can transition from liquid to gaseous states by absorbing the latent heat of vaporization and its reverse process. Additionally, PCMs can shift from solid to gaseous states by absorbing latent sublimation heat and its reverse process while maintaining a constant temperature. The solid-to-liquid phase change method is commonly employed in LHS [12]. Figure 1 visually represents the phase change phenomena from solid to liquid. The shaded area in the figure represents the cumulative heat energy stored when a substance transforms from solid to liquid. The calculation includes sensible heat in the solid state, latent heat generated by phase changes at a constant temperature, and sensible heat in the liquid state to determine the overall stored energy.

Fig. 1.

Heat retained as a substance changes phases (Source: Author's)

Citation: Pollack Periodica 20, 1; 10.1556/606.2024.01153

PCMs are commonly classified into organic, inorganic, and eutectic categories based on their chemical composition, as depicted in Fig. 2. Each category exhibits a spectrum of melting temperatures and thermo-physical properties, rendering some more suitable for specific applications than others [13, 14].

Fig. 2.

Categorization of PCMs (Source: Author's)

Citation: Pollack Periodica 20, 1; 10.1556/606.2024.01153

Integrating PCM into the building envelope can decrease peak temperatures by as much as 4 °C, ensuring consistent thermal comfort in summer daytime conditions [15]. The efficacy of PCM thermal performance is influenced by various parameters (positions, thicknesses, and melting temperatures), some of which may adversely affect its functionality. It is advisable to address these parameters to optimize PCM performance and efficiently harness its full potential.

This study investigates the impact of incorporating PCMs into the building envelope in Miskolc, Hungary. The building envelope in Miskolc comprises cement 3 cm, brick 15 cm, and plaster 2 cm. The core question is: to what extent do these three parameters play a role in minimizing heat transfer? This study is dedicated to examining the thermophysical properties of PCMs and explaining the crucial parameters that have an impact.

2 Model characteristics

A visual representation of the simulated external wall is illustrated in Fig. 3. This depiction mirrors the construction of walls commonly found in buildings in Miskolc, the location of this study. The simulated wall is composed of layers of cement 3 cm, brick 15 cm, and plaster 2 cm. As a result, the total thickness of the wall, excluding the consideration of the PCM, is 20 cm, and its height is 20 cm. Table 1 outlines the properties of the construction materials used in the simulation.

Fig. 3.

Wall schematic without PCM (Source: Author's)

Citation: Pollack Periodica 20, 1; 10.1556/606.2024.01153

Table 1.

Properties of building envelope materials [16]

Property		Cement	Brick	Plaster
Density (kg m⁻³)	ρ	2,300	880	1,680
Specific heat (J kg⁻¹∙K)	C_p	2,000	880	1,085
Thermal conductivity (W m⁻¹∙K)	k	1.40	1.30	0.22

To model the PCM-based wall, the following assumptions were considered:

Adequate coverage and isolation for the upper and lower surfaces of the wall;
Uniform layers, including plaster, brick, concrete, and PCM;
Convection for the liquid phase of PCM should be included within the solid phase;
Neglect the PCM's volumetric expansion.

For the assessment of PCM performance, layers with thicknesses of 1 cm, 3 cm, 5 cm, and 0.5 cm were introduced to the envelope. The PCM was positioned in four locations to examine the impact of its placement. Further details regarding the properties of the PCMs utilized in the simulation are shown in Table 2.

Table 2.

Thermo-physical properties of PCM [17]

Property			Organic PCM		Inorganic PCM
Property			RT-27	RT-21	SP-25E2	SP-21EK
Density (kg m⁻³)	ρ	solid phase (°C)	880 at 15	880 at 15	1,600 at 15	1,600 at 15
Density (kg m⁻³)	ρ	liquid phase (°C)	760 at 40	770 at 25	1,500 at 35	1,500 at 35
Specific heat (J kg⁻¹∙K)	C_p	Solid+liquid	2,000	2,000	2,000	2,000
Thermal conductivity (W m⁻¹∙K)	k	Solid+liquid	0.2	0.2	0.5	0.5
Latent heat (J kg⁻¹)	L_H	–	189,000	165,000	180,000	170,000
Solidus temperature (°C)	T_S	–	24.5	19	24	20
Liquidus temperature (°C)	T_L	–	26.5	24	26	22

3 Mathematical model

The phase transition occurrence is a boundary value issue in which the changing border is represented as a time function. Only scenarios with one-dimensional, infinite, or semi-infinite geometries can have analytical solutions for melting PCM. These scenarios assume constant temperature boundary conditions coupled with the consistent thermal properties of the PCM [18]. The enthalpy-porosity method is employed to approximate the solid-liquid interface. As it can be seen in Fig. 4, this approach does not specifically follow the melting contact. Within the PCM area, each cell is assigned a value known as the liquid fraction, representing the cell volume percentage in a liquid state. Following each iteration the liquid fraction is calculated through an enthalpy balance. This method visualizes the phase transition interface as a mushy zone characterized by a varying liquid fraction from 0 to 1. The mushy zone exhibits a declining porosity from 1 to 0, like a pseudo-porous zone. Both porosity and velocity are zero in the region where material solidification occurs [19].

Fig. 4.

Enthalpy-porosity technique (Source: Author's)

Citation: Pollack Periodica 20, 1; 10.1556/606.2024.01153

The liquid-fraction (f) can be distinguished as:

f = {\begin{array}{c} 0, & T < T_{S} (Solidification), \\ \frac{T - T_{S}}{T_{L} - T_{S}}, & T < T_{L} (Mushy zone), \\ 1, & T > T_{L} (Melting), \end{array}

(1)

where T_S (°C) is the solidus temperatures of PCM; T_L (°C) is the liquids temperatures of PCM.

A substance's sensible and latent heat are combined to determine its enthalpy

H = h + Δ H,

(2)

where H (J kg⁻¹) is the enthalpy of substance; h (J kg⁻¹) is the sensible heat; ΔH (J kg⁻¹) is the latent heat content.

The sensible temperature is calculated according to the following:

h = h_{r e f} + \int_{T_{r e f}}^{T} C_{p} . d T,

(3)

where h_ref (J kg⁻¹) is the reference enthalpy; T_ref (°C) is the reference temperature; C_p (J kg⁻¹∙K) is the specific heat at a constant pressure of PCM.

In terms of the latent heat of material, the latent heat content is expressed as follows:

Δ H = f \cdot L,

(4)

whereas the latent heat content of a liquid is L (J kg⁻¹), it might range from zero for a solid. Equation (5) represents the energy equation for solidification/melting situations, is provided [19]:

\frac{\partial}{\partial t} (ρ H) + \nabla \cdot (ρ v H) = \nabla \cdot (k \nabla T) + S,

(5)

where ρ (kg m⁻³) is the density of material; v (m s⁻¹) is the velocity of fluid; S refers to additional terms that are added to the governing equations such as continuity (kg m⁻³), momentum (N m⁻³), energy (W m⁻³).

The convective components in momentum equations are discretized using a second-order upwind interpolation approach. In energy equations, discretization of the convective components is achieved through first-order upwind interpolation. The coupling of pressure and velocity is implemented using the Semi-Implicit Method for Pressure-Linked Equations (SIMPLE) method, and pressure interpolation is carried out using PRESTO in ANSYS Fluent code. The energy, continuity, and momentum equations converge when residuals fall below 10⁻¹⁰, 10⁻⁸, and 10⁻⁵.

This study maintained a constant room temperature of T_in = 22 °C (thermal comfort temperature) [20]. For all wall analyses, the convective heat transfer coefficients for the outdoor and indoor surfaces were set at h_out = 25 W m⁻²∙K and h_in = 10 W m⁻²∙K, respectively [21]. The research assumed that the wall's top and bottom surfaces included in the analysis were isolated q = 0 W m⁻². The distribution of outdoor ambient temperature over time in the city of Miskolc, Hungary, during three days in mid-July is depicted in Fig. 5. The mean outdoor temperature for 2020 to 2023 was calculated for this period [22].

Fig. 5.

Mean temperature variations over time in July for Miskolc, Hungary (Source: Author's)

Citation: Pollack Periodica 20, 1; 10.1556/606.2024.01153

Selecting an optimal time step (Δt) influences the solution runtime. For transient problems, the appropriateness of the time step can be determined by the problem's convergence rate over a series of iterations. In this context, the simulation utilized a Δt value of 10 s, and the solution consistently converged within 10 iterations for the specified time interval.

The Fourier equation determines the heat transfer flux, considering the initial temperature variation inside the wall, as it can be seen in Fig. 6 [23],

\ddot{q} = \frac{(T_{o u t} - T_{i n})}{\frac{1}{h_{o u t}} + \frac{δ_{1}}{k_{1}} + \frac{δ_{2}}{k_{2}} + \frac{δ_{3}}{k_{3}} + \frac{δ_{4}}{k_{4}} + \frac{1}{h_{i n}}},

(6)

where T_out (°C) is the outdoor temperature; k_i (W m⁻¹∙K), i = 1,2,3,4 is the thermal conductivity for each section, δ_i (m), i = 1,2,3,4 is the thickness for each section.

Fig. 6.

Wall sections (Source: Author's)

Citation: Pollack Periodica 20, 1; 10.1556/606.2024.01153

However, to find the temperature at each wall section's boundary locations, utilize the following equations:

T_{1} = T_{i n} + \ddot{q} (\frac{δ_{1}}{k_{1}} + \frac{δ_{2}}{k_{2}} + \frac{δ_{3}}{k_{3}} + \frac{δ_{4}}{k_{4}} + \frac{1}{h_{i n}}),

(7)

T_{2} = T_{i n} + \ddot{q} (\frac{δ_{2}}{k_{2}} + \frac{δ_{3}}{k_{3}} + \frac{δ_{4}}{k_{4}} + \frac{1}{h_{i n}}),

(8)

T_{3} = T_{i n} + \ddot{q} (\frac{δ_{3}}{k_{3}} + \frac{δ_{4}}{k_{4}} + \frac{1}{h_{i n}}),

(9)

T_{4} = T_{i n} + \ddot{q} (\frac{δ_{4}}{k_{4}} + \frac{1}{h_{i n}}),

(10)

T_{5} = T_{i n} + \frac{\ddot{q}}{h_{i n}} .

(11)

4 Validation

The numerical approach described in this study was validated experimentally by A. Pasupathy et al. [24]. They constructed an experimental test room measuring 1.22 × 1.22 × 2.44 m³ to assess the impact of PCM panels on the building's roof. Their experimentation employed inorganic salt hydrate (48% CaCl₂ + 4.3% NaCl + 0.4% KCl + 47.3% H₂O) as the PCM. All walls, except the ceiling, were insulated with 6 mm thick plywood to isolate the particular impact of the PCM panel on the roof. Throughout the experiment, the room temperature is preserved at 27 °C, with convective heat transfer on both the inside h_in = 1 W m⁻²∙K and outside surfaces h_out = 5 W m⁻²∙K. The temperature fluctuations, both experimentally and numerically, on the underneath surface of the ceiling are depicted in Fig. 7. Additionally, the ambient temperature is included in the figure to enhance comprehension.

Fig. 7.

Evaluating numerical results compared to prior experimental outcomes under consistent ambient temperature conditions (Source: Author's)

Citation: Pollack Periodica 20, 1; 10.1556/606.2024.01153

As it is illustrated in the figure, the outcomes derived from the numerical way align well with the experimental findings documented by A. Pasupathy et al. [24]. The good agreement between the experimental data and the numerical method makes it easier to investigate the thermal properties of PCM-based envelopes.

5 Results

5.1 Effect of integrating PCM in the building envelope

The study examines the impact of incorporating PCM (RT-27) with a 1 cm thickness. Figure 8 illustrates the indoor surface temperature for the wall with and without PCM. As evident, the wall incorporated with PCM has a lower temperature fluctuation than the one without PCM. This is explained by the fact that the PCM in the wall acts as a heat sink, lowering the amount of energy that is transported from the outside to the interior surface. Consequently, the increase in the temperature of the inner surface is less pronounced.

Fig. 8.

Indoor surface temperature distribution with and without PCM (RT-27) (Source: Author's)

Citation: Pollack Periodica 20, 1; 10.1556/606.2024.01153

Heat transmission to the room is decreased when the temperature differential between the interior surface and the room is less. Without PCM, the total heat transmission to the room is 2.25 W, while with PCM incorporated, it is 1.74 W. Calculations show that incorporating PCM into the wall reduces energy transfer into the room by 23%.

5.2 Effect of relocating the PCM in the building envelope

The computations from the previous section were particularly applied to the wall shown in Fig. 9b, where PCM was layered between brick and cement. The PCM was installed in close proximity to the wall's external surface. This section looks at the effects of relocating the PCM in four locations on decreasing or increasing the total heat transmission through the wall, as it is shown in Fig. 9.

Fig. 9.

Schematic of building envelope with PCM (Source: Author's)

Citation: Pollack Periodica 20, 1; 10.1556/606.2024.01153

These locations are outlined below:

a)The outside of the building envelope;
b)Proximity to the outer surface of the building envelope, incorporated between the cement and bricklayers;
c)Close to the inner surface of the building envelope, incorporated between the brick and plaster layers;
d)The inner surface of the building envelope.

To achieve this goal, PCM type RT-27 with a thickness of 1 cm was considered at the specified locations. Figure 10 presents the reduction in heat transfer concerning the incorporation position. It is apparent from Table 3 that as the PCM is placed closer to the exterior; there is a more significant reduction in heat transfer. As a result, the investigations were specifically focused on this position.

Fig. 10.

Heat transmission into the room when the PCM is relocated (Source: Author's)

Citation: Pollack Periodica 20, 1; 10.1556/606.2024.01153

Table 3.

Total heat flux to the room when the PCM is relocated

Location	Heat flux to the room (W)		Reduction (%)
Location	Building envelope without PCM	Building envelope with PCM	Reduction (%)
a)	2.5	1.90	15
b)	2.5	1.74	23
c)	2.5	1.86	17
d)	2.5	1.86	17

5.3 Effect of PCM thickness on the building envelope

The optimal location b) was chosen from the previous section. The thickness of PCM was changed systematically, initially from 1 to 3 cm, later, to 5 cm, as it is shown in Fig. 11.

Fig. 11.

Schematic of building envelope with multi-thickness PCM (Source: Author's)

Citation: Pollack Periodica 20, 1; 10.1556/606.2024.01153

The amount of energy stored within the PCM shows a significant increase corresponding to the increase in thickness. As a result, it should take less energy to transfer to the room. Figure 12 displays the temperature distribution over the wall's indoor surface for three different thicknesses. The fluctuations of temperature changes across the indoor surface diminish with increasing PCM thickness.

Fig. 12.

Indoor surface temperature distribution with different thicknesses of PCM (RT-27) (Source: Author's)

Citation: Pollack Periodica 20, 1; 10.1556/606.2024.01153

However, as heat flux depends on temperature, the heat transferred into the room reduces as thickness increases. Table 4 presents the calculated total heat transmission to the room for three different thicknesses.

Table 4.

Total amount of heat flux to the room when changing the thickness of the PCM

Thickness [cm]	Heat transfer to the room (W)		Reduction (%)
Thickness [cm]	Building envelope without PCM	Building envelope with PCM	Reduction (%)
1	2.5	1.74	23
3	2.5	1.47	34
5	2.5	1.30	42

5.4 Effect of PCM thermo-physical properties

The impact of using various PCM types is examined in this section. Distinct PCMs have varying thermal characteristics. As a result, thermal property changes cause changes in the quantity of melted PCM and, in turn, the stored energy. Figure 13 illustrates the temperature distribution over the wall's indoor surface for different types of PCM.

Fig. 13.

Indoor surface temperature distribution with different types of PCM (Source: Author's)

Citation: Pollack Periodica 20, 1; 10.1556/606.2024.01153

Table 5 shows the total quantity of heat transmission to the room for each type. SP-21EK has the least amount of heat transmission of any kind among the materials that are being studied. Consequently, this substance has the biggest impact on lowering the quantity of heat flow into the room.

Table 5.

Total amount of heat flux to the room for different types of PCM

PCM Type	Heat flux to the room (W)		Reduction (%)
PCM Type	Building envelope without PCM	Building envelope with PCM	Reduction (%)
RT-27	2.5	1.74	23
RT-21	2.5	1.82	19
SP-25E2	2.5	1.67	26
SP-21EK	2.5	2.09	7

6 Conclusion

This investigation employed numerical models to assess the engineering implications of integrating phase change materials into building envelopes in Miskolc, Hungary's urban setting. The examined wall configuration comprised layers of cement 3 cm, brick 15 cm, and plaster 2 cm. The effect of PCM positioning within the wall on heat transfer was systematically analyzed at four designated locations. The first two positions were closer to the outdoor surface, while the last two were closer to the indoor surface, allowing for a comprehensive evaluation of the heat transfer dynamics. The following conclusions were drawn from the numerical analysis of the wall's thermal performance: Incorporating PCMs reduces heat transfer into the room. The magnitude of this reduction is intricately tied to factors such as ambient temperature and the specific characteristics of the PCM employed in the building envelope configuration:

Temperature variations are usually reduced when PCMs are incorporated;
The critical criterion for selecting an appropriate PCM is its thermal conductivity. A lower conductivity coefficient is indicative of reduced heat flux to the room;
Achieving optimal performance of PCM in mitigating heat transfer entails positioning it closer to the outdoor surface;
More energy is stored in the building envelope when the proportion of PCM is higher.

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Pollack Periodica

Print ISSN:: 1788-1994

Online ISSN:: 1788-3911

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
Pollack Mihály Faculty of Engineering
Institute: University of Pécs
Address: Boszorkány utca 2. H–7624 Pécs, Hungary
Phone/Fax: (36 72) 503 650

E-mail: peter.ivanyi@mik.pte.hu

or amalia.ivanyi@mik.pte.hu

Indexing and Abstracting Services:

SCOPUS
CABELLS Journalytics

2024
Scopus
CiteScore
CiteScore rank
SNIP
Scimago
SJR index	0.385
SJR Q rank	Q3

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

Pollack Periodica
Publication Model	Hybrid
Submission Fee	none
Article Processing Charge	900 EUR/article
Printed Color Illustrations	40 EUR (or 10 000 HUF) + VAT / piece
Regional discounts on country of the funding agency	World Bank Lower-middle-income economies: 50% World Bank Low-income economies: 100%
Further Discounts	Editorial Board / Advisory Board members: 50% Corresponding authors, affiliated to an EISZ member institution subscribing to the journal package of Akadémiai Kiadó: 100%
Subscription fee 2025	Online subsscription: 381 EUR / 420 USD Print + online subscription: 456 EUR / 520 USD
Subscription Information	Online subscribers are entitled access to all back issues published by Akadémiai Kiadó for each title for the duration of the subscription, as well as Online First content for the subscribed content.
Purchase per Title	Individual articles are sold on the displayed price.

Pollack Periodica
Language	English
Size	A4
Year of Foundation	2006
Volumes per Year	1
Issues per Year	3
Founder	Faculty of Engineering and Information Technology, University of Pécs
Founder's Address	H–7624 Pécs, Hungary, Boszorkány utca 2.
Publisher	Akadémiai Kiadó
Publisher's Address	H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
Responsible Publisher	Chief Executive Officer, Akadémiai Kiadó
ISSN	1788-1994 (Print)
ISSN	1788-3911 (Online)