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  • 1 Marcel Breuer Doctoral School, Department of Building Structures and Energy Design, Institute of Architecture, Faculty of Engineering and Information Technology, University of Pécs, , Boszorkány u. 2, H-7624Pécs, , Hungary
  • | 2 Institute of Architecture, University Mohamed Khider Biskra, , BP 145 RP, 07000, Biskra, , Algeria
  • | 3 Department of Building Structures and Energy Design, Institute of Architecture, Faculty of Engineering and Information Technology, , Boszorkány u. 2, and János Szentágothai Research Center, Ifjúság u. 20, University of Pécs, H-7624Pécs, , Hungary
Open access

Abstract

As it is clear, worldwide buildings are the largest consumer of the final energy consumption. In Algeria, it has been reported that 33% of the overall energy consumption was attributed to buildings. This is due to the design and constructional techniques of the residential buildings, which do not address the local climatic condition. To assess this situation, the study is focused on analyzing the existing residential buildings in Algeria, in terms of energy, thermal, daylight, and indoor air quality performance, using a dynamic simulation software. Typical building design in a hot and dry climate was selected. The results revealed that the existing residential buildings do not comply with the energy-efficient design standards. It was concluded that further strategies should be applied in this sector, in terms of building design, materials, and façade configuration.

Abstract

As it is clear, worldwide buildings are the largest consumer of the final energy consumption. In Algeria, it has been reported that 33% of the overall energy consumption was attributed to buildings. This is due to the design and constructional techniques of the residential buildings, which do not address the local climatic condition. To assess this situation, the study is focused on analyzing the existing residential buildings in Algeria, in terms of energy, thermal, daylight, and indoor air quality performance, using a dynamic simulation software. Typical building design in a hot and dry climate was selected. The results revealed that the existing residential buildings do not comply with the energy-efficient design standards. It was concluded that further strategies should be applied in this sector, in terms of building design, materials, and façade configuration.

1 Introduction

Preserving the environment is the most important issue of today's world in which human beings must reduce energy consumption. As it is clear, worldwide buildings are the largest consumer of the final energy consumption, it accounts for more than 40% [1]. In Algeria, it has been reported that 33% of the overall energy consumption was attributed to buildings; this value has increased awfully between 2016 and 2017 by 5.3% [2]. During the last decade, housing construction issues became one of the development priorities in Algeria. Policies and strategies were set up in order to tackle the housing demand and to reorganize the sprawling slum areas, providing social houses for these low-income families who live there [3]. The design and constructional techniques of these buildings are operated with over-shorter project planning time, and it is always striving to minimize design costs, neglecting the climate conditions in the different regions of the country. However, performing buildings that maintain occupant's comfort with less energy consumption requires an architectural design that uses appropriate technologies and design principles which respond accurately to the local climatic conditions [4–6]. According to the literature, several research studies revealed that building façade elements have the most influential impact on building energy consumption and thermal performance [7]. In addition, the building façade should behave as an energy-efficient passive or active mechanical system. For instance, the wall material, the thermal insulation type, and its thickness have a significant impact on minimizing the heats transfer, therefore, enhancing thermal comfort [8, 9]. Furthermore, the window to wall ratio is an important factor to balance the heat flow and natural light by choosing the appropriate size, orientation, glazing, and shading type. The analysis should be concluded by accounting for the interaction between natural lighting and the Heating, Ventilation and Air Conditioning (HVAC) system [10]. The amount of incident solar radiation (insolation) admitted through the glazed surfaces in the façade may show severe thermal and visual discomfort issues, in order to avoid excessive solar gain and reduce energy consumption it is necessary to adopt suitable shading device design [11]. The building façade design also plays an important role in providing effective ventilation configuration and strategies, in order to provide efficient Indoor Air Quality (IQA), which usually expressed by the CO2 concentration in the space and the air ventilation rate [12]. This study presents the evaluation of a typical existing social house design in Algerian hot and dry climate region, which represent the major part of the country, through a Diagnostic of Energy Performance (DEP) of the building, estimating the energy demand related to the thermal comfort, day-lighting and air quality, which mainly depends on the façade component design.

2 Diagnosis of energy performance methodology

2.1 Case study location and climate

The study context is located in Algeria, in a hot and dry climate region, because it represents the major part of the country depending on the Köppen-Geiger climate classification, this climate is characterized by very hot summers and mild winters [13]. The city of Biskra was selected as a representative city of this climate, it is located in north-eastern of Algeria on the northern edge of the Sahara Desert at latitude of 34°48′ North and a longitude of 5°44′ east, it rises to an altitude of 86 m. Based on the climatic data of Biskra city, which obtained from the weather file “Meteonorm 7”; during the year, the average temperatures vary by 22.7 °C. The warmest month is July with an average temperature of 40.2 °C. Moreover, January has the lowest average temperature of the year at 16.7 °C. Furthermore, the highest relative humidity average is in December 60.7%, while July represents the lowest relative humidity average, it is 26.5%.

2.2 Typical social housing

This study is focused on the collective residential building type in Algeria called Social housing. An existing building in Biskra city was selected as a referential model; it characterizes the typical design used in all over the country. The building reference is located in an urban area; the implementation is oriented within the axis North-east and South-west. This building is a multiple-dwelling unit, that contains 8 apartments and all the apartments have a similar spatial distribution; living room, two rooms, kitchen, laundry room, toilet, and bathroom. The total area of one apartment is 92.13 m2, with a ceiling height of 2.70 m, Fig. 1. The materials applied for the façades are concrete blocks and plasterboard, the plaster is used for the coating. Currently, these materials are less used in the Algerian residential building factory, therefore the concrete blocks were replaced by double hollow brick in this study because it is the most commonly used in the last years. Table 1 shows the detailed thermal properties of the material used in the diagnosis.

Fig. 1.
Fig. 1.

Plan and section of the social house reference

Citation: Pollack Periodica 16, 2; 10.1556/606.2020.00204

Table 1.

Conventional wall thermal properties

Material (mm)Conductivity (W/m·K)Thickness (mm)Specific heat capacity (J/kg∙K)Density (kg/m3)
Cement mortar1.4201,0802,200
Hollow brick0.48150936589
Air gap0.026501,0001
Hollow brick0.48100936625
Plaster0.3520936875

2.3 Input data and boundary conditions for the simulation process

The current study methodology is based on a quantitative diagnosis of the DEP, it provides information on the amount of energy consumed in terms of heating and cooling together, with thermal comfort, daylight, and indoor air quality. The diagnosis is carried out by using dynamic simulation with Blender 3D software for modeling and building information has been included by the plugin VI-suite that controls the external applications radiance, energy plus [14].

The inputs of the climate data used in the simulation are based on “Biskra” climate station from the weather file “Meteonorm 7”.

The assessment of the energy consumption is conducted by insertion of the HVAC; and it is applied to the upper apartment in the selected block. The simulation period has been carried out in the whole year (from January 1 to December 31). To analyze each space in the apartment, the building boundary is specified in sixteen, 16 zones; six, 6 zones with an HVAC system (hall, 2 bedrooms, living room, kitchen, and bathroom/WC) and eight, 8 zones without HVAC (laundry, entrance and the seven, 7 other apartments in the building). The analysis is carried out for the 6 zones that have a HVAC system. The balconies' setting was inserted as shading elements. Additionally, the building cooling-heating service system setting was inserted based on the Algerian Regulatory technical document, the cooling system turns on if the temperature is above 25 °C, while the heating system turns on when the temperature is less than 20 °C [15].

Meanwhile, the analytical methodology adopted for thermal comfort is based upon the model of Fanger, Predicted Mean Vote/Predicted Percentage of Dissatisfied (PMV/PPD), which defines the thermal sensation of the occupants [16]. In the thermal assessment phase of the analysis, 2 zones (living room, Room 1) in the upper apartment were specified in the upper apartment to be analyzed; assuming two occupants and one occupant respectively, and no mechanical system has been applied in the zones.

Furthermore, the diagnosis is concerning also the daylight comfort, which is related to the Window to Wall Ratio (WWR), it focuses on the assessment of the illuminance levels and the light uniformity. The analysis is applied for the living room and the Room 1 in two design days (December 21 and June 21) form the sunrise to the sunset for both days. The results are compared with the standard of Building Research Establishment Environment Assessment Method (BREEAM) that provides information about the required illuminance level (the average over interspace and the minimum at the worst point) as well as the daylight uniformity [17].

Finally, the analysis of the InDdoor air Quality (IDQ) is focused on evaluating the amount of the CO2 concentration, it has been set up in two zones (the living and the Room 1), assuming 2 occupants in the living room and 1 occupant in the Room 1, and the windows opening/closing was set up based on a normal family house activities. Those are open on weekdays between 7.00 and 8.00 and from 16.00 to 17.00 at 10%, as well as the un-occupancy time are defined between 8:00 to 16:00. On the weekends, it is assumed that the occupants are staying all the time in the apartment and the windows are opened between (7:00 to 8:00, 12:00 to 13:00 and 17:00 to 17:00 at the same opening rate).

3 Results and discussion

The simulation results of the energy consumption showed that 89% of the total energy consumption was used on cooling, while 11% was used on heating, Fig. 2.

Fig. 2.
Fig. 2.

The energy consumption of the upper apartment in a whole year

Citation: Pollack Periodica 16, 2; 10.1556/606.2020.00204

The comparison of the energy consumed in heating and cooling shows a variation in each different zone, this is due to the zone's position in the apartment, regarding its orientation and different surface areas that have direct contact with the outside.

The bathroom has the highest cooling energy consumption, followed by the kitchen, the living room, the hall, Room 1, Room 2, which includes the balcony has less consumed energy. The cooling consumption in the bathroom reached 287.19 kW/m2, it has direct contact with the entrance hall that has a fully glazed façade, which increased the greenhouse effect in the entrance hall and impacts directly the bathroom. In the kitchen, the assumed energy is 183.16 kWh/m2, the main façade of this zone is oriented to the south-west which has a higher solar gain. The living room has 173.01 kWh/m 2, it has 2 façades one oriented to the south-east, and the other is oriented to the south-west. The cooling consumption in the hall reached 172.37 kWh/m2 because it is surrounded by the different spaces, during the day the heat is accumulated, which means there is no effective air circulation furthermore it has direct contact with the entrance zone. The bedrooms are both oriented to the north-west façade but the energy consumption in Room 1 is higher than Room 2, 158.09 kW/m2, 155.29 kW/m2 respectively, this is revealed that the balcony as a shading element has an impact on minimizing the solar heat gain.

For the heating consumption, the kitchen has the highest heating energy consumption 49.49 kWh/m2, followed by the Room 1; 23.02 kWh/m2, and the Room 2; 22.92 kWh/m2, the bathroom 19.53 kWh/m2, the hall 18.61 kWh/m2, and the living room that has less heating consumption 8.96 kWh/m2. The heating and cooling consumption show partial reversed results according to orientation and solar gain; the more exposed zone to solar gain, the less heating, and more cooling it consumes, Fig. 3.

Fig. 3.
Fig. 3.

The cooling and heating consumption of all the simulated zones

Citation: Pollack Periodica 16, 2; 10.1556/606.2020.00204

The diagnosis of thermal comfort is also applied in the living room and the Room 1. The resulting analysis of the PMV/PPD indices for the given zones shows that; based on the PMV people are feeling very hot almost all the summer period (June, July, August), in the winter (January, February, and December) they are feeling cold to be very cold, the feelings are approached the comfort zone in some days of the mouths (March, April, May, and October). Furthermore, the comfort range is defined between -1< PMV <+1, and the feelings above this range are uncomfortable, the comfort hours for the whole year are reached 1,437 hours and 1,219 hours for the living room and Room 1 respectively. The discomfort hours are attained 7,323 hours in the living room and 7,541 hours in Room 1, Fig. 4. Illustrate the scale of occupant's sensation from very cold feelings +6 to very hot -6, while zero expresses neutral feelings.

Fig. 4.
Fig. 4.

PMV results for the living room and Room 1

Citation: Pollack Periodica 16, 2; 10.1556/606.2020.00204

Moreover, the PPD indicates that more than 90% of people are not satisfied almost all the summer and winter periods, while in March and April it varied between 10 and 70% for both the living room and Room 1, Fig. 5.

Fig. 5.
Fig. 5.

PPD results for the living room and Room 1

Citation: Pollack Periodica 16, 2; 10.1556/606.2020.00204

The daylight analysis, which carried out in the Room 1 and the living room in the winter and the summer shows that the minimum illuminance for the living room reached maximum 20 lux in the summer and 10 lux in the winter, and the Room 1 reached in the summer 10 lux, while in the winter 5 lux, both zones have less than the minimum illuminance required by the BREEAM standard, which is 30 lux at the worst point. Meanwhile, the optimal average daylight illuminance in the BREEAM standard is 100 lux, both zones have more illuminance levels than the standard, in summer, the living room reached 160 lux and the Room 1 reached 125 lux, while in winter both zones have less than the standard illuminance, the living room 87.5 lux, and the Room 1 62.5 lux, Fig. 6. Also, the results revealed that there is a daylight uniformity problem in the zones as is illustrated in the graphs of Fig. 7, which indicates that the uniformity of both zones in summer and in winter is less than the uniformity value 0.3, which is required by the BREEAM standard.

Fig. 6.
Fig. 6.

Daylight illuminance comparison between bream standard and the living room and Room 1 a) illuminance in the summer (June); b) illuminance in the winter (December)

Citation: Pollack Periodica 16, 2; 10.1556/606.2020.00204

Fig. 7.
Fig. 7.

Daylight uniformity comparison between bream standard and the living room and the Room 1 results, a) uniformity in June; b) uniformity in December

Citation: Pollack Periodica 16, 2; 10.1556/606.2020.00204

The CO2 concentration analysis is applied in Room 1 and the living room and the simulation results are compared with the American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE) standard that determined the optimal level 1,000 ppm of CO2 concentration [18]. The results show that the living room has higher CO2 concentration levels than the Room 1. The levels are varied between 500 and 4,000 ppm as a maximum level for the whole year.

A reduction of the CO2 concentration is presented during windows were open, it reached 1,000–2,500 ppm, while when the windows were closed, the concentration exceeded the recommended value of 1,000 ppm as it is indicated by the ASHRAE standard. Fig. 8a illustrates the variation of the CO2 concentration in the whole year. The best hours of CO2 concentration is reached 3,647 hours and 4,009 hours in the living room and the Room 1 respectively in the whole year, while the CO2 concentration that is above the standard 1,000 ppm is reached 5,113 hours and 4,751 hours in the living room and the Room 1. Figure 8 shows the CO2 concentration in the whole year together with the hours of comfort/discomfort.

Fig. 8.
Fig. 8.

The CO2 concentration in the living room and Room 1 for the whole year

Citation: Pollack Periodica 16, 2; 10.1556/606.2020.00204

4 Conclusion

The comprehensive analysis of the residential building selected for representative case study in Algeria demonstrated that the building does not comply with the building energy design standards; there are many weaknesses in terms of building energy consumption, thermal comfort, visual comfort, and indoor air quality.

This study revealed what kind of further design strategies are needed, including materials of the external wall structure to optimize the thermal comfort and to reduce the energy consumption, the window configuration, and its orientation with an accurate design that responds to the climate to ensure the best practice in visual performance and minimize the penetration of direct solar irradiation. Furthermore, it is demonstrated that mechanical and natural ventilation should be integrated into the design strategy in order to improve indoor air quality. This study shows clearly that the energy efficiency strategy should be accounted for during the early design stage. Additionally, these design strategies should be developed for the hottest period which represents the longer period in the year when 89% of cooling consumption is estimated.

Acknowledgements

The authors would like to thank Dr. Ryan Southall researcher and developer of VI-suite Add-on Blender 3D software, University of Brighton, for his help and great support.

References

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    • Search Google Scholar
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    H. Shen and A. Tzempelikos, “Daylighting and energy analysis of private offices with automated interior roller shades”, Solar Energy, vol. 86, no. 2, pp. 681704, 2012.

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    • Search Google Scholar
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    M. Rais, A. Boumerzoug, M. Halada, and L. Sriti, “Optimizing the cooling energy consumption by the passive traditional façade strategies in hot dry climate”, Pollack Period., vol. 14, no. 1, pp. 177188, 2019.

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    • Search Google Scholar
    • Export Citation
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    C. Xiaohui, G. B. M. Reza, R. R. L. Shih, and B. Baranyai, “Comfort and energy performance analysis of a heritage residential building in Shanghai”, Pollack Period., vol. 14, no. 1, pp. 189200, 2019.

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    • Search Google Scholar
    • Export Citation
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    • Crossref
    • Search Google Scholar
    • Export Citation
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    R. Southall, F. Biljecki, “The VI-Suite: A set of environmental analysis tools with geospatial data applications”, Open Geospatial Data Softw. Stand., vol. 2, no. 23, pp. 113, 2017.

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    • Search Google Scholar
    • Export Citation
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    The regulatory technical document. Residential-Rules of calculation of the heat supply in the buildings (in French). DTR C3-2, 1997.

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    K. E. Charles, Fanger’s Thermal Comfort, and Draught Models. Institute for Research in Construction National Research Council of Canada, pp. 130, 2003.

    • Search Google Scholar
    • Export Citation
  • [17]

    BREEAM UK New construction: Non-domestic buildings, Bre Global Ltd, SD5076:5.0-2014, CreateSpace Independent Publishing Platform, 2017.

  • [18]

    ASHRAE Standard 62.1-2010, Ventilation for acceptable indoor air quality, American Society of Heating Refrigerating, and Air Conditioning Engineers, 2016.

  • [1]

    X. Cao, X. Dai, and J. Liu, “Building energy-consumption status worldwide and the state-of-the-art technologies for zero-energy buildings during the past decade”, Energ. Build., vol. 128, pp. 198213, 2016.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • [2]

    Bilan_Energetique_National_2016_edition. Ministry of Energy and Mining, Algeria, [Online], Available: http://www.energy.gov.dz/francais/uploads/2017/Bilans_ et_statistiques_du_secteur/Bilan-Energetique/Bilan_Energetique_National_2016_ edition_2017.pdf. Accessed: Mar. 15, 2018.

  • [3]

    R. Djafri, M. M. Osman, N. S. Rabe, and S. Shuid, “Algerian housing policies”, Asian J. Environ.-Behavior Stud., vol. 4, no. 13, pp. 114, 2019.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • [4]

    I. Oropeza-Perez and P. A. Østergaard, “Active and passive cooling methods for dwellings: a review”, Renew. Sustain. Energ. Rev., vol. 82, part 1, pp. 531544, 2018.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • [5]

    S. Elhadad, B. Baranyai, J. Gyergyak, I. Kistelegdi, and A. Salem, “Passive design strategies for residential buildings in a hot desert climate in upper Egypt”, in Proceeding of 20th International Multidisciplinary Scientific Geoconference, Varna, Bulgaria, June 28–July 7, 2019, 2019, pp. 495501.

    • Search Google Scholar
    • Export Citation
  • [6]

    S. Elhadad, M. Rais, A. Boumerzoug, and B. Baranyai, “Assessing the impact of local climate on the building energy design: Case study Algeria-Egypt in hot and dry regions”, in Proceeding of 172nd International Conference on Science, Engineering and Technology, Istanbul, Turkey, Nov. 20–21, 2019, 2019, pp. 2124.

    • Search Google Scholar
    • Export Citation
  • [7]

    D. Aelenei, L. Aelenei, and C. P. Vieira, “Adaptive façade: Concept, applications, research questions”, Energ. Proced., vol. 91, pp. 269275, 2016.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • [8]

    M. Ozel, “Thermal performance and optimum insulation thickness of building walls with different structure materials”, Appl. Therm. Eng., vol. 31, no. 17-18, pp. 38543863, 2011.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • [9]

    C. H. Radha and I. Kistelegdi, “Thermal performance analysis of Sabunkaran residential buildings typology”, Pollack Period., vol. 12, no. 2, pp. 151162, 2017.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • [10]

    H. Shen and A. Tzempelikos, “Daylighting and energy analysis of private offices with automated interior roller shades”, Solar Energy, vol. 86, no. 2, pp. 681704, 2012.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • [11]

    M. Rais, A. Boumerzoug, M. Halada, and L. Sriti, “Optimizing the cooling energy consumption by the passive traditional façade strategies in hot dry climate”, Pollack Period., vol. 14, no. 1, pp. 177188, 2019.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • [12]

    C. Xiaohui, G. B. M. Reza, R. R. L. Shih, and B. Baranyai, “Comfort and energy performance analysis of a heritage residential building in Shanghai”, Pollack Period., vol. 14, no. 1, pp. 189200, 2019.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • [13]

    M. Kottek, J. Grieser, C. Beck, B. Rudolf, and F. Rubel, “World map of the Köppen-Geiger climate classification updated”, Meteorologische Z., vol. 15, no. 3, pp. 259263, 2006.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • [14]

    R. Southall, F. Biljecki, “The VI-Suite: A set of environmental analysis tools with geospatial data applications”, Open Geospatial Data Softw. Stand., vol. 2, no. 23, pp. 113, 2017.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • [15]

    The regulatory technical document. Residential-Rules of calculation of the heat supply in the buildings (in French). DTR C3-2, 1997.

  • [16]

    K. E. Charles, Fanger’s Thermal Comfort, and Draught Models. Institute for Research in Construction National Research Council of Canada, pp. 130, 2003.

    • Search Google Scholar
    • Export Citation
  • [17]

    BREEAM UK New construction: Non-domestic buildings, Bre Global Ltd, SD5076:5.0-2014, CreateSpace Independent Publishing Platform, 2017.

  • [18]

    ASHRAE Standard 62.1-2010, Ventilation for acceptable indoor air quality, American Society of Heating Refrigerating, and Air Conditioning Engineers, 2016.

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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)
  • Ján Bujňák (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

 

2020  
Scimago
H-index
11
Scimago
Journal Rank
0,257
Scimago
Quartile Score
Civil and Structural Engineering Q3
Computer Science Applications Q3
Materials Science (miscellaneous) Q3
Modeling and Simulation Q3
Software Q3
Scopus
Cite Score
340/243=1,4
Scopus
Cite Score Rank
Civil and Structural Engineering 219/318 (Q3)
Computer Science Applications 487/693 (Q3)
General Materials Science 316/455 (Q3)
Modeling and Simulation 217/290 (Q4)
Software 307/389 (Q4)
Scopus
SNIP
1,09
Scopus
Cites
321
Scopus
Documents
67
Days from submission to acceptance 136
Days from acceptance to publication 239
Acceptance
Rate
48%

 

2019  
Scimago
H-index
10
Scimago
Journal Rank
0,262
Scimago
Quartile Score
Civil and Structural Engineering Q3
Computer Science Applications Q3
Materials Science (miscellaneous) Q3
Modeling and Simulation Q3
Software Q3
Scopus
Cite Score
269/220=1,2
Scopus
Cite Score Rank
Civil and Structural Engineering 206/310 (Q3)
Computer Science Applications 445/636 (Q3)
General Materials Science 295/460 (Q3)
Modeling and Simulation 212/274 (Q4)
Software 304/373 (Q4)
Scopus
SNIP
0,933
Scopus
Cites
290
Scopus
Documents
68
Acceptance
Rate
67%

 

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 2021 Online subsscription: 321  EUR / 402 USD
Print + online subscription: 384 EUR / 480 USD
Subscription fee 2022 Online subsscription: 327 EUR / 411 USD 321
Print + online subscription: 393 EUR / 492 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.
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Pollack Periodica
Language English
Size A4
Year of
Foundation
2006
Publication
Programme
2021 Volume 16
Volumes
per Year
1
Issues
per Year
3
Founder Akadémiai Kiadó
Founder's
Address
H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
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)

Monthly Content Usage

Abstract Views Full Text Views PDF Downloads
Jun 2021 0 11 2
Jul 2021 0 199 9
Aug 2021 0 105 18
Sep 2021 0 31 24
Oct 2021 0 42 22
Nov 2021 0 27 17
Dec 2021 0 2 2