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Suha I. A. Ali Department of Construction Materials and Technologies, Faculty of Civil Engineering Budapest University of Technology and Economics, Műegyetem rkp. 3., H-1111 Budapest, Hungary

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Zsuzsa Szalay Department of Construction Materials and Technologies, Faculty of Civil Engineering Budapest University of Technology and Economics, Műegyetem rkp. 3., H-1111 Budapest, Hungary

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Sudan is suffering from harsh summers, but most of the modern buildings in urban areas are not compatible with the recent and future climate phenomena. Application of cooling devices is relatively expensive and therefore beyond reach. The main objective of this research is to give an overview on the overheating problem and the thermal comfort in buildings. A dynamic energy simulation has been performed for a selected case study using Design Builder Code. The results show that the share of discomfort hours for a typical modern building is 78% and 33% above 26 °C and 32 °C per year, respectively, but after using a combination of different ventilation, shading and building materials options the discomfort hours can be reduced to 77% and 26%, respectively.

Abstract

Sudan is suffering from harsh summers, but most of the modern buildings in urban areas are not compatible with the recent and future climate phenomena. Application of cooling devices is relatively expensive and therefore beyond reach. The main objective of this research is to give an overview on the overheating problem and the thermal comfort in buildings. A dynamic energy simulation has been performed for a selected case study using Design Builder Code. The results show that the share of discomfort hours for a typical modern building is 78% and 33% above 26 °C and 32 °C per year, respectively, but after using a combination of different ventilation, shading and building materials options the discomfort hours can be reduced to 77% and 26%, respectively.

1 Introduction

With climate change, overheating is likely to occur more frequently [1]. According to the Stern Report on climate change, overheating problems need to be highlighted and tackled now [2]. The primary function of buildings and building services engineering is to create and maintain a comfortable environment for people. Overheating is increasing during warm weather in buildings without air-conditioning, especially in homes in temperate climates where the retention of winter heat has been the major focus of thermal design [3]-[5].

Thermal comfort is the point of satisfaction with the thermal environment, i.e. when the great majority of people are not feeling either too hot or too cold. Thermal discomfort is where people start to feel uncomfortable, i.e. they are feeling hot or cold, but they are not experiencing any health effects [6]. There are many factors that affect thermal comfort. For overheating discomfort, temperature is probably the primary factor but there are other factors that affect the feeling of comfort or discomfort in both hot and cold conditions. The other factors are humidity, air movement, radiation and radiation asymmetry [7], [8].

There is no internationally accepted definition of ‘overheating’ because it depends on local climatic conditions. The WHO guidance on thermal comfort states that temperatures above 24 oC cause discomfort in temperate zones [9]. Factors like the rate of increase in temperature, the temperature reached, the length of time for which the temperature stays high and individual tolerance are all important factors [10].

As a result of climate change, the summer overheating phenomenon occurs in different climate zones. The effect is the worst in the hot arid climate zone because it is very far from the comfort zone on the psychrometric chart [11] and it is difficult to achieve the comfort level by applying simple solutions [12], [13]. Also, there are gaps in the knowledge on the thermal performance of buildings in developing countries. The main objective of this paper is to analyze the overheating level in modern Sudanese buildings and study the effect of applying passive techniques, such as shading, ventilation and choice of building materials using dynamic building energy simulation.

2 Methodology

The thermal performance of a building and the internal comfort can be assessed using dynamic building simulation. For dynamic simulation, a lot of data are required as location, weather, building geometry and building materials, etc., which are described in the following sections.

2.1 Description of the case study

A first building typology matrix for Sudan has been compiled by Ali and Szalay [14]. In this paper, one type from the typology is selected, which is representative of modern buildings in a warm semi-arid climate zone. The building is a single-family house with a floor area of 96 m2 (Fig. 1). There were no architectural plans available, but a common arrangement and typical dimensions were assumed based on expert estimations. The building has a single floor with two bedrooms, kitchen, living area, toilet and bathroom. There is a wall made out of bricks surrounding the building, which is very typical due to security and privacy reasons.

Fig. 1
Fig. 1

Plan and photo of the building

Citation: Pollack Periodica 15, 3; 10.1556/606.2020.15.3.20

2.2 Location and weather file (Sudan, Khartoum)

Sudan is located in North-East Africa. Sudan is classified into three climatic zones (Zone I: warm desert climate, Zone II: warm semi-arid climate and Zone III: tropical savanna climate) as it is shown in Fig. 2 [15], [16]. Sudan’s weather is characterized by three seasons: the hot season from March-May (summer), the wet rainy season between June and October (autumn) and the dry season from November until February (winter).

Fig. 2
Fig. 2

Sudan climate zones (Source: S. I. A. Ali on the basis of Koppen, and Sudan Meteorological Authority (SMA) [16], [15])

Citation: Pollack Periodica 15, 3; 10.1556/606.2020.15.3.20

The northern part of Sudan (zone I) has a harsh climate compared to the other regions. Here summer temperatures exceed 43.3 °C in the desert zones and rainfall is negligible, except in the center, where rainfall is common between June and September. Zone II has moderate summer and winter temperatures, high rainfall and relative humidity values, because it is close to the tropical savannah region [17], [18].

The greatest amount of solar radiation in Sudan is between 15 and 35 latitude north. Wind speed and direction vary with seasons. In winter, the wind speed ranges between 0.54 m/s to 1.54 m/s in N and NW direction, while in the summer season winds are in the direction of NW to SW.

The case study is located in the capital city Khartoum, with latitude N15.550 o, longitude E32.530 o, altitude 366 m and climate zone 1 B according to the Meteonorm database [18]. In Khartoum, the average annual temperature is about 26.7 °C; and the annual rainfall is about 254 mm. Energy simulation tools need hourly ambient conditions (temperature, humidity, wind velocity, solar radiation, etc.) at the building location. This information is available in weather files. For this simulation, the weather file from Meteonorm was used [18].

2.3 Building energy simulation tool

The simulation was performed with Design Builder Code, v6. Design Builder provides a range of environmental performance data like energy consumption, comfort conditions, maximum summertime temperatures and Heating, Ventilation and Air Conditioning (HVAC) component sizes [19].

2.4 Base case model

As the first step for the simulation process, a base case model was created that is typical for Sudanese buildings and can be compared with different design alternatives. The base case has solid brick walls with concrete slab, natural ventilation and no shading system.

Orientation. The typical orientation of the building allowing maximum natural ventilation and daylight is shown in Fig. 1. In selecting suitable building orientation in hot dry regions, reduction of the internal daytime temperatures must be the main objective, and thus minimization of solar load is a primary concern [20].

Zoning. Zones are used in thermal simulations to divide the building into separate areas with different energy/thermal characteristics [19]. As the selected case study is a small single-storey building where internal doors would be frequently left open, a single zone is used in the calculations. Additional thermal mass was included in the simulation using hanging partitions.

Building components. It is necessary to have construction details, for instance the thickness and thermo-physical properties of materials used in each layer of the building envelope (Table I). The floor consists of 4 layers, which are plain concrete, sand layer, cement mortar and ceramic tiles. External walls are 0.3 m solid brick walls with mortar and plaster layer inside and outside the wall, while internal walls and partitions are 20 cm thick and have a loadbearing function with a similar composition to external walls. The flat roof is most common in the urban parts of Sudan. Usually a mixture of crush bricks, sand and stabilizer is applied on the top of the flat roof as a kind of waterproofing, and this was modeled as a lightweight plaster material in Design Builder. This case study has a reinforced concrete flat roof with a 2 cm plaster layer in the top and 1 cm base plaster on the bottom of the roof (Fig. 3). The thermal properties were taken from the database of Design Builder. Thermal bridges were neglected in this study.

Table I

Description of the wall and roof buildings materials options

Table I
Fig. 3
Fig. 3

Construction details (cross-section)

Citation: Pollack Periodica 15, 3; 10.1556/606.2020.15.3.20

Openings (Doors and Windows) Doors are usually made of wood or aluminum, while windows have single glazing with a wooden, aluminum or metallic frame.

Shading. In Sudan, usually there are two types of shading: a permanent one, which is aluminum fencing for windows (mostly for security purposes) and curtains. Due to the high solar altitude, roofs with an overhang also shade the windows. For the base case, no shading was applied.

Usage of building. The hourly schedules of occupancy, lighting, equipment, thermostat set-point, and HVAC operation are required for the simulation. Internal gains are calculated according to the occupants’ density, activity, and equipment. Sudanese single family houses are normally occupied by an average of 5 persons [21], so the occupant density is 0.05 person/m2. Metabolic activity is assumed as light manual work, 150 W household equipment is calculated as the absolute zone power and 24 oC is the indoor temperature ventilation set-point.

Ventilation and infiltration. There are two general approaches to model natural ventilation and infiltration in Design Builder: ‘scheduled’, where fixed air change rates are set manually by users or ‘calculated’, where natural ventilation and infiltration rates are modeled based on window opening, cracks, buoyancy and wind-driven pressure differences. In the case study, the calculated model option is used for more accuracy. For infiltration, ‘poor airtightness’ from the crack template of Design Builder was assumed according to Sudanese building envelope characteristics. Due to the high cost of mechanical ventilation installations, natural ventilation is mainly used in Sudanese buildings. Simple fans are used in some parts of the buildings. Windows were assumed to be open if the internal temperature is above 24 oC and the external temperature is lower than the internal temperature. External doors were assumed to be closed 24 hours a day.

Cooling system. In Sudan, mechanical cooling is usually not applied due to the high cost. Sometimes simple air conditioners are used. Here, no cooling system was assumed.

2.5 Applied options

In order to analyze the effect of certain parameters on the thermal comfort, different options for ventilation, shading and building materials were examined. For natural ventilation, the different tested options are temperature controlled ventilation, no ventilation and constant ventilation option (Table II). For shading, closed weave inside and outside, and cantilever of 0.5 m and 1 m from the flat slab have been applied (Table II). The options for the wall are solid bricks, hollow red bricks, cement block, lightweight concrete block and solid bricks + 5 or 10 cm polystyrene insulation. The options for roof are concrete slab, jack arch roof, corrugated iron sheets with or without insulation and concrete slab with 5 or 10 cm polystyrene insulation (Table I).

Table II

Description of the ventilation and shading options

VentilationShading
Control Mode Temperature (base case) Windows and doors are opened if Tzone >Tout and Tzone > Tset Tset= 24 oCConstant Windows and doors are open all the time.Control Mode Drapes-close weave light inside: Outdoor air temperature + Horizontal solar Solar setpoint=150 (W/m2) Tset= 24 oCOverhang 0.5 m
No Ventilation Drapes-close weave light outside Overhang 1.0 m
Windows and doors are closed at all times.Outdoor air temperature + Horizontal solar Solar setpoint=150 (W/m2) Outside air temperatre setpoint = 24 oC

3 Results and discussion

3.1 Base case results

The annual, seasonal and weekly temperatures have been extracted and compared for the base case and the different options. Fig. 4 shows the annual internal Operative (Op) and the Outside Dry-Bulb (ODB) temperatures for the base case. Generally, there is a big difference between the day and night temperatures. During the summer hot season, the maximum ODB temperature difference between day and night is 16 oC, while the minimum is 7 oC. The maximum range for the ODB and Op temperatures are between 34-46 and 26- 38 oC during the daytime, and 17-24 and 23-30 oC during the night, respectively.

Fig. 4
Fig. 4

Annual operative and outside dry-bulb temperatures (oC) for the base case

Citation: Pollack Periodica 15, 3; 10.1556/606.2020.15.3.20

In the wet autumn, the maximum difference between day and night ODB temperatures is 13 oC, while the minimum is 3 oC. The maximum range for the ODB and Op temperatures are between 35-44 and 29-38 oC during the daytime, and 21-26 and 26-30 oC during the night. In the dry winter season, the maximum ODB temperature difference between day and night is 15 oC, while the minimum is 10 oC. The maximum range for the ODB and Op temperatures are between 30-39 and 24-33 oC during the daytime and 24-14 and 22-32 oC during the night.

In order to compare the total discomfort hours between the different seasons, the hottest week in the hot, wet and dry season was selected. As of now there is no standard discomfort level for the hot arid climate or especially for Sudan. According to the discomfort baseline, the number of Discomfort Hours (DH) above 26 oC, which is a standard value in Europe was counted, and also 28, 30 and 32 oC Op and ODB temperatures. Fig. 5 illustrates the indoor and outdoor total DH percentage for the hottest week in the summer, autumn and winter seasons. In the summer week, the operative temperature is always above 32 oC, while for the ODB all the hours are above 28 oC, and 95 and 81% of the hours are above 30 and 32 oC, respectively. The autumn week is even hotter, 89% of the hours are above 32 oC for the ODB. In the winter season, the percentage of discomfort hours is much lower than in the summer and autumn, only 13% of the hours are above 26 oC for the operative temperature.

Fig. 5
Fig. 5

Percent of hours above a certain temperature limit for the summer, autumn and winter design week

Citation: Pollack Periodica 15, 3; 10.1556/606.2020.15.3.20

3.2 Different options results

As it is shown in Fig. 6 and Table III the annual discomfort hours (above 26, 28, 30 and 32 oC) are calculated for the different ventilation, shading, and material options. In the calculations, only one parameter was changed at a time compared to the base case.

Fig. 6
Fig. 6

Percent of the annual discomfort hours for the different selected options compared to the total hours of the year

Citation: Pollack Periodica 15, 3; 10.1556/606.2020.15.3.20

Table III

Total discomfort hours per year for the different studied options

Annual (hours)
OptionsAboveAboveAboveAbove
26 oC28 oC30 oC32 oC
Base case (temperature controlled ventilation, no shading, solid brick wall, concrete roof)6806568643142903
Vent.No Ventilation Constant ventilation

Closed weave inside
8082 69767307 60836281 49315085 3721
6811564142132799
ShadingClosed weave outside

Overhang 0,5 m

Overhang 1,0 m

Cement block

Hollow red brick
6622538439762510
6761559842082784
6685549040932690
6808566742782848
6803566342722844
Materials (Wall)Aerated concrete block

Solid brick + 5 cm insulation

Solid brick + 10 cm insulation

CISs + Airgap+ Gypsum board
6797565342562830
6802563142192787
6798560941882759
6969601748053517
Materials

(Roof)
CISs + polys+ Gypsum board

Jack arch (plaster, bricks, plaster)

Concrete + 5 cm ins.

Concrete + 10 cm ins.
6953590845543154
6864579144403028
6881569242612795
6892569642602788
Combined case (temperature controlled

ventilation, overhang 1.0 m, solid brick wall + 5 cm insulation, reinf. concrete roof +10

cm insulation
6734535538682243

In the ventilation options, the lowest discomfort hours are registered for the temperature control model option, which represents the base case, with 6806 hours above 26 oC, while both the no ventilation option and the constant ventilation have higher values. For the shading options, DH results for the closed weave outside are better than the other shading options, but applying an overhang shading has the benefit of allowing more daylight into the room.

Regarding the applied material options, there is no big change in the discomfort values for the walling and roofing material. Applying an insulation layer of 10 cm to the base case wall and roof showed discomfort hours of about 5609 and 5696 above 30 oC and 6798 and 6892 above 26 oC, respectively.

Finally, in order to decrease the discomfort hour values, a combination of different options is used (Table III). The combined model uses the temperature control ventilation option with a 1 m overhang for shading and an insulation layer of 5 cm for the solid brick wall and 10 cm for the concrete roof slab. After applying these, the annual discomfort hours decreased by 660 hours above 32 oC, that represent 23% improvement compared to the base case (Fig. 6).

3.3 Temperature in the different seasons

For more details through the different seasons, a temperature comparison between the base case and the combined model was added. In the summer, there is some difference for the operative temperature between the base case and the modified combined case, the highest temperature for the base case is 40.3 oC while for the combined case 37.04 oC (Fig. 7a).

Fig. 7
Fig. 7

Hourly (design week) operative temperatures for the base case and combined case during a) summer b) autumn c) winter

Citation: Pollack Periodica 15, 3; 10.1556/606.2020.15.3.20

During the autumn, a reduction in operative temperature can be observed throughout the whole week period. The highest temperature registered for the base case is 38.35 oC and 36.07 oC for the combined case (Fig. 7b). In the winter season, there is no big difference in the operative temperatures between the base and combined case, so the highest operative temperature was 27.83 oC for the base case and 26.32 oC for the combined case (Fig. 7c).

Fig. 8 illustrates the difference in temperatures between the base case and the combined case during the summer, autumn and winter seasons. The maximum temperature decrease occurs during the summer by 3.66 oC, followed by the autumn season where the difference in the operative temperature for the combined case was 2.53 oC. In the winter season, the difference is less and temperatures in the combined case are slightly higher than in the base case but still in the comfort range.

Fig. 8
Fig. 8

Difference in the internal operative temperatures between the combined and the base case for the summer, autumn and winter design week

Citation: Pollack Periodica 15, 3; 10.1556/606.2020.15.3.20

4 Conclusion

In this paper, the internal temperatures in a typical modern Sudanese building were analyzed. Based on the dynamic simulation modeling the following can be concluded:

  • In the base case the simulation results showed that 78% and 33% of the year is above 26 oC and 32 oC, respectively;

  •  Most of the comfort period is in the winter dry season (Nov to Feb), while the rest of the year (March to Oct) was in the discomfort level;

  •  If no natural ventilation is applied when the outside temperatures are lower than inside, the annual discomfort hours increase by 14% and 25% above 26 oC and 32 oC over the year, respectively;

  •  It is difficult to achieve 100% comfort level for the base case without using a mechanical ventilation or cooling system, but by using a combination of different passive solutions, an improvement of 10% above 30 oC and 23% above 32 oC compared to the base case can be achieved;

  •  There is no specific benchmark for the discomfort level in the hot arid climate zone. In this research the temperatures above 26, 28, 30 and 32 oC were checked;

  •  Only the internal operative temperatures were analyzed as a first indicator of overheating. As thermal comfort is a function of various parameters, further research will focus on complex thermal indices.

Acknowledgements

‘Optimization of buildings and building elements from life cycle and building physics perspective based on complex numeric modeling” (Project FK 128663) has been implemented with the support provided from the National Research, Development and Innovation Fund of Hungary, financed under the FK_18 funding scheme. This research was also supported by the FIKP grant of EMMI in the frame of the Water sciences & Disaster Prevention research area of the Budapest University of Technology and Economics FIKP-VÍZ.

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    Lomas K. J., Porritt S.M. Overheating in buildings: Lessons from research, Building Research & Information, Vol. 45, No. 1-2, 2017, pp. 118

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    Rapp D. Assessing climate change temperatures, solar radiation, and heat balance, Praxis Publishing, Chichester, UK, 2013.

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    TM52: The limits of thermal comfort: avoiding overheating in European buildings, The Chartered Institution of Building Services Engineers, London,, 2013.

    • Search Google Scholar
    • Export Citation
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    Robertson G. Passive design toolkit, City of Vancouver 2009.

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    Albdour M. S., Baranyai B. Numerical evaluation of outdoor thermal comfort and weather parameters in summertime at Széchenyi square, Pollack Periodica, Vol. 14, No. 2, 2019, pp. 131142.

    • Search Google Scholar
    • Export Citation
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    Indoor environment: Health aspects of air quality, thermal environment, light and noise, WHO, 1990.

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    Dengel A., Swainson M., Ormandy D., Ezratty V. Overheating in dwellings guidance document, The BRE Centre for Resilience, 2011.

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    ASHRAE Standard 55-2010, Thermal environmental conditions for human occupancy, 2010.

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    • Crossref
    • Search Google Scholar
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  • [13]

    Szkordilisz F, Kiss M. Passive cooling potential of alley trees and their impact on indoor comfort, Pollack Periodica, Vol. 11, No. 1, 2016, pp. 101112.

    • Crossref
    • Search Google Scholar
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  • [14]

    Ali S. I. A., Szalay Zs. Towards developing a building typology for Sudan, IOP Conference Series: Earth and Environmental Science, Vol. 323, Paper No. 012012.

    • Search Google Scholar
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    Sudan Meteorological Authority, Maximum Temperature Forcast, Sudan, 2018.

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    Köppen Climate Classification, Sudan map of Köppen climate classification, 2019.

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    World Weather and Climate, Sudan Metrological Authority World Weather Information Service, 2019.

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    Meteonorm v7.1, weather data of Khartoum, 2019.

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    DesignBuilder, https://designbuilder.co.uk/helpv6.0, (last visited 2 March 2020).

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    Ahmed M. H. A. Solutions to low income urban housing problems in the Sudan, PhD Thesis, University of Sheffield, England, 1978.

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    Central Bureau of Statistics Census, Sudan, 2008.

  • [1]

    Global Warming of 1.5°C, An IPCC Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty, IPCC, 2018.

    • Search Google Scholar
    • Export Citation
  • [2]

    Stern N. The economics of climate change, The Stern review, Cambridg University, 2007.

  • [3]

    Race G. How to manage overheating in buildings: a practical guide to improving summertime comfort in buildings. The Chartered Institution of Building Services Engineers, London, 2010.

    • Search Google Scholar
    • Export Citation
  • [4]

    Lomas K. J., Porritt S.M. Overheating in buildings: Lessons from research, Building Research & Information, Vol. 45, No. 1-2, 2017, pp. 118

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

    Rapp D. Assessing climate change temperatures, solar radiation, and heat balance, Praxis Publishing, Chichester, UK, 2013.

  • [6]

    TM52: The limits of thermal comfort: avoiding overheating in European buildings, The Chartered Institution of Building Services Engineers, London,, 2013.

    • Search Google Scholar
    • Export Citation
  • [7]

    Robertson G. Passive design toolkit, City of Vancouver 2009.

  • [8]

    Albdour M. S., Baranyai B. Numerical evaluation of outdoor thermal comfort and weather parameters in summertime at Széchenyi square, Pollack Periodica, Vol. 14, No. 2, 2019, pp. 131142.

    • Search Google Scholar
    • Export Citation
  • [9]

    Indoor environment: Health aspects of air quality, thermal environment, light and noise, WHO, 1990.

  • [10]

    Dengel A., Swainson M., Ormandy D., Ezratty V. Overheating in dwellings guidance document, The BRE Centre for Resilience, 2011.

  • [11]

    ASHRAE Standard 55-2010, Thermal environmental conditions for human occupancy, 2010.

  • [12]

    Osman M. M., Sevinc H. Adaptation of climate-responsive building design strategies and resilience to climate change in the hot/arid region of Khartoum, Sudan, Sustainable Cities and Society, Vol. 47, 2019, Paper No. 101429.

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

    Szkordilisz F, Kiss M. Passive cooling potential of alley trees and their impact on indoor comfort, Pollack Periodica, Vol. 11, No. 1, 2016, pp. 101112.

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

    Ali S. I. A., Szalay Zs. Towards developing a building typology for Sudan, IOP Conference Series: Earth and Environmental Science, Vol. 323, Paper No. 012012.

    • Search Google Scholar
    • Export Citation
  • [15]

    Sudan Meteorological Authority, Maximum Temperature Forcast, Sudan, 2018.

  • [16]

    Köppen Climate Classification, Sudan map of Köppen climate classification, 2019.

  • [17]

    World Weather and Climate, Sudan Metrological Authority World Weather Information Service, 2019.

  • [18]

    Meteonorm v7.1, weather data of Khartoum, 2019.

  • [19]

    DesignBuilder, https://designbuilder.co.uk/helpv6.0, (last visited 2 March 2020).

  • [20]

    Ahmed M. H. A. Solutions to low income urban housing problems in the Sudan, PhD Thesis, University of Sheffield, England, 1978.

  • [21]

    Central Bureau of Statistics Census, Sudan, 2008.

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Senior editors

Editor(s)-in-Chief: Iványi, Amália

Editor(s)-in-Chief: Iványi, Péter

 

Scientific Secretary

Miklós M. Iványi

Editorial Board

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

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

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

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