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Influence of Solar Radiation to the Temperature Inside a Three-Layer Partition in Winter Season

Influence of Solar Radiation to the Temperature Inside a Three-Layer Partition in Winter Season Acta Sci. Pol. Architectura 20 (2) 2021, 75–82 content.sciendo.com/aspa ISSN 1644-0633 eISSN 2544-1760 DOI: 10.22630/ASPA.2021.20.2.16 ORIGINAL P APER Received: 27.12.2020 Accepted: 31.05.2021 INFLUENCE OF SOLAR RADIATION TO THE TEMPERATURE INSIDE A THREE-LAYER PARTITION IN WINTER SEASON Patrycja Antonik-Popiołek Faculty of Materials, Civil and Environmental Engineering, University of Bielsko-Biala, Bielsko-Biała, Poland ABSTRACT The article presents an analysis of the impact of solar radiation on the temperature changes in the external three-layer partition of a smart building. Data for analysis were taken from temperature sensors located in individual layers of the wall and from a weather station on the roof of a building. The data were recorded 24 h in 5- and 15-minute intervals. The analysis period was one month in a winter season. The purpose of the analysis was to determine the correlation between the solar radiation measured as the illuminance and the temperature inside the wall. In the analysed period of one month the correlation was very weak. Also, con- sidering only the illuminance over 10,000 lx, the correlation was noticeable, but still very weak. The use of innovative fiber optic technology with fibre Bragg grating was proposed to avoid incorrect measurements. Key words: outside wall, solar radiation, temperature, smart building external temperature fluctuations. Temperature distri- INTRODUCTION bution in a wall may be also studied using a thermal Speed of wind, external temperature, solar radiation, imaging camera, as described in Kong et al. (2017). air humidity and precipitation are the basic meteoro- Other method involves installation of sensors in the logical climate-forming factors. All those factors can wall during its production or conservation works, as influence on the temperature inside the wall. Is there presented by Marino, Muńoz and Thomas (2017). a correlation between the solar radiation and tem- Influence of evaporation and wind speed to the ther- perature in the external wall? The paper presents an mal transmittance were considered by Cui et al. (2019). analysis of solar radiation impact on temperature in Results indicated that there is a function expression an external wall. There are a few publications which between thermal transmittance and wind speed and it describe methods used to investigate the temperature was validated to be reliable. Authors also compared distribution and changes in walls or at their surface. thermal transmittance with the radiation heat transfer Climate-forming factors were analysed in many other coefficients and the thermal transmittance had a wider papers. The influence of wind and evaporation to the changing range, owing to rainfall effects. Gayo, De thermal transmittance was considered by Cui, Xie and Frutos, Palomo and Massa (1996) considered humid- Xue (2019). Ahola and Lahdensivu (2017) presented ity in different building materials. Research shows that an analysis of the temperature inside a building where the porosity is the most important feature which in- the internal temperature is not regulated. The analysis creases level of humidity inside the material. Świrska- was conducted by means of numerical methods and -Perkowska, Kucharczyk and Wyrwał (2020) analysed concerned the heat flow within the wall affected by a numerical model of solar wall with transparent in- Patrycja Antonik-Popiołek https://orcid.org/0000-0001-5949-8112 pantonik@ath.bielsko.pl © Copyright by Wydawnictwo SGGW Antonik-Popiołek, P. (2021). Infl uence of solar radiation to the temperature inside a three-layer partition in winter season. Acta Sci. Pol. Architectura, 20 (2), 75–82. doi: 10.22630/ASPA.2021.20.2.16 sulation. They considered different configurations of data are fixed in two rows 1.6 m above the floor. Precise the insulation and different orientations and analysed location of the sensors presents Figure 2. Data from the temperature distribution for the envelopes and monthly temperature sensors located in certain layers of the wall energy balances. Yu, Cui, Shao and Han (2019) re- were used for the analysis. Information was supplied ported an influence of temperature and heat transfer in from the sensors fixed in the following locations: the building envelopes on the cooling and heating en- – “I” half-way of the thickness of the thermal insula- ergy consumption and the indoor thermal and humid- tion, ity environment. The results showed that humidity also – “II” between the thermal insulation layer and the should be included in thermal calculations. cellular concrete wall, The innovative technology of monitoring of the – “III” half way of the thickness of the cellular con- temperature, strain, humidity and loads on tested en- crete wall. gineering objects, especially in civil engineering, uses Based on the data obtained, the correlation between the fiber Bragg grating (FBG) and is being developed the temperatures recorded by the certain weather sen- in Department of Civil Engineering of the Univer- sors and the speed of wind was calculated. The sample sity of Bielsko-Biala (Juraszek, 2019a, 2019b, 2020; consisted of the measurements performed in January Juraszek & Antonik-Popiołek, 2021). 2015, in 15-minute intervals. The total number of the Research can help to get to know which climate- records per sensor was 2,974. -forming factors are important in the design of an ex- Due to sensor failures, especially in the winter ternal wall. Additionally it could help to design better period, it was impossible to collect full data in Janu- configuration of wall layers and materials which are ary 2016 and 2017. In this period, there was a lot of used to it. incorrect measurements or no measurements for a few hours. For this reason, the analysis was based on the most representative data of the full month in 2015 MATERIAL AND METHODS (1–31 January 2015). The analysis was based on the data provided by sen- Numerous errors and failed measurements can be sors located inside the wall and a metrological station removed by replacing the existing sensors with fiber on the building. Weather data, obtained from the main external meteorological station located on the roof of the building, as well as temperature data from the sen- sors in the wall, were analysed. The wall is located on the north-east side of the building. The study covered data from full month. The measuring instru- ments of the external weather station register data in 5-minute intervals, whereas the measurements within the wall are recorded every 15 min. Then, the time intervals were unified and data obtained in 15-minute intervals were used for the analysis. The wall was a cavity wall made of cellular con- –3 crete (with the density of 700 kg·m ), insulated with expanded polystyrene and finished with face bricks. The cross-section of the wall is presented in Figure 1. The thermal transmittance equals to –2 –1 U = 0.14 W·m ·K ). The wall is located on the north-west side of the building, on the fifth floor. The sensors providing the Fig. 1. Cross-section of the external wall 76 architectura.actapol.net Antonik-Popiołek, P. (2021). Infl uence of solar radiation to the temperature inside a three-layer partition in winter season. Acta Sci. Pol. Architectura, 20 (2), 75–82. doi: 10.22630/ASPA.2021.20.2.16 Fig. 2. Location of temperature sensors optic devices based on Bragg’s grating. Those sensors – day-hour measurements (from sunrise to sunset); have many advantages: greater reliability, resistance – measurements including illumination above to external interferences, small sizes − and they can be 10,000 lx. built into the existing structures. Table 1 presents the basic statistical characteristics Publications by Juraszek (2019a, 2019b, 2019c, of the weather factors and the temperature measured 2020) and Juraszek and Antonik-Popiołek (2021) by particular sensors. Table 2 presents the basic sta- present the advantages and the use of new generation tistical characteristics of the weather factors and the of FBG and magnetic sensors. temperature measured by particular sensors only in the period from sunrise to sunset each day in January. Table 3 presents the basic statistical characteristics of RESULTS AND DISCUSSION the weather factors and the temperature measured by During January 2015 the temperatures were both posi- particular sensors only in the period when the solar tive and negative, between −9.5 and 17.5°C. The solar radiation was above 10,000 lx in January 2015. radiation measured as illuminance was between 405 In January the sunrise occurred between 7:17 and and 65,535 lx, with the average of 2,953 lx. 7:39, while the sunset was between 15:47 and 16:30. The analysis was divided into three parts: Taking into account only a period between sunrise and – 24-hour measurements (day and night); sunset, the average illuminance was 6,982 lx. Table 1. Basic statistical characteristics for weather conditions and the wall temperature for 24-hour measurements (day and night) Variable Mean Minimum Maximum SD External temperature [°C] 3.88 –9.5 17.5 3.7 Air humidity [%] 73.89 34.0 91.0 11.5 –1 Speed of wind [m·s ] 0.95 0.2 7.0 1.1 Solar radiation [lx] 2 953.0 405.0 65 535.0 8 276.4 Sensor III 15.953 13.9650 17.13 0.769 Temperature inside the wall [°C] Sensor II 15.953 13.9650 17.13 0.769 Sensor I 10.634 5.2950 14.24 1.486 architectura.actapol.net 77 Antonik-Popiołek, P. (2021). Infl uence of solar radiation to the temperature inside a three-layer partition in winter season. Acta Sci. Pol. Architectura, 20 (2), 75–82. doi: 10.22630/ASPA.2021.20.2.16 Table 2. Basic statistical characteristics for weather conditions and the wall temperature for day-hour measurements (from sunrise to sunset) Variable Mean Minimum Maximum SD External temperature [°C] 4.710 –9.0000 17.50 4.05 Air humidity [%] 71.599 34.0000 91.00 13.09 –1 Speed of wind [m·s ] 0.954 0.2000 6.40 1.03 Solar radiation [lx] 6 981.787 405.0000 65 535.00 12 257.11 Sensor III 17.353 15.8950 18.28 0.65 Temperature inside the wall [°C] Sensor II 15.925 13.9650 17.07 0.76 Sensor I 10.529 5.2950 14.14 1.41 Table 3. Basic statistical characteristics for weather conditions and the wall temperature measurements in the periods with the illumination above 10,000 lx Variable Mean Minimum Maximum SD External temperature [°C] 7.76 –1.50 17.50 5.19 Air humidity [%] 56.28 43.00 74.00 7.65 –1 Speed of wind [m·s ] 1.13 0.20 4.70 1.11 Solar radiation [lx] 34 718.63 10 005.00 65 535.00 18360.05 Sensor III 17.13 15.93 17.72 0.50 Temperature inside the wall [°C] Sensor II 15.73 14.14 16.46 0.63 Sensor I 10.44 7.89 12.18 1.29 Illuminance from 400 to 500 lx corresponds to the even at night what was caused by lighting of the area sunrise and sunset on a clear day. The illuminance close surrounding the building. Figure 3 presents the tem- to 0 lx can be measured in undeveloped areas at night. perature distribution in the selected layers of the wall Due to the location of the building in the city and Figure 4 and 5 present the illumination (solar ra- centre, sensors recorded illuminance above 400 lx diation) in January 2015. Time Sensor I Sensor II Sensor III Fig. 3. Temperature inside the wall 78 architectura.actapol.net Temperature [°C] Antonik-Popiołek, P. (2021). Infl uence of solar radiation to the temperature inside a three-layer partition in winter season. Acta Sci. Pol. Architectura, 20 (2), 75–82. doi: 10.22630/ASPA.2021.20.2.16 Fig. 4. Solar radiation in January 2015 (24-hour measurement) Fig. 5. Solar radiation in January 2015 at day architectura.actapol.net 79 Antonik-Popiołek, P. (2021). Infl uence of solar radiation to the temperature inside a three-layer partition in winter season. Acta Sci. Pol. Architectura, 20 (2), 75–82. doi: 10.22630/ASPA.2021.20.2.16 Correlations were analysed between the solar radi- Analysis during the whole month (Tables 5 and ation – illuminance and the temperature inside the wall 6) shows that there is a weak correlation between the (selected layers) as well as between solar radiation and temperature inside the wall and the solar radiation (all external temperature. three correlation coefficients show values lower than The analysis was performed using MS Excel and 0.3). Even the correlation between the outside temper- Statistica software for Pearson’s correlation, which ature and the solar radiation is weak. shows the linear correlation between two variables, and Analysis during the whole month including only the Spearman’s correlation concerning any monotonic day-hours (Table 7 and 8) also shows that there is very relationship, including the non-linear one, between the week correlation between the temperature inside the two variables. In both cases, a significant positive cor- wall and the solar radiation (correlation coefficients relation means that with a growth of the value of one lower than 0.3). The correlation between the outside characteristics, there is a growth of the value of other temperature and the solar radiation is also weak. feature. A significant negative correlation means that Analysis during the periods with solar radiation when one value increases, the other decreases. greater than 10,000 lx (Table 9 and 10) shows that the The strength of the correlations and correspond- correlation between the temperature inside the wall and ing ranges of correlation coefficients are presented in Table 4. The analysis of the correlations between Table 4. Strength of correlations and their interpretation certain variables is presented in Tables 5–10. Tables Strength of correlation Interpretation 4 and 5 show the results of correlation analysis dur- ing one whole month, Tables 6 and 7 show the results < 0.3 weak correlation from sunrise-to-sunset periods and Tables 8 and 9 for ≤ 0.3–0.7 moderate correlation the periods when the solar radiation was more than ≥ 0.7 strong correlation 10,000 lx. Table 5. Pearson’s correlations between solar radiation and temperature (inside the wall and external) for 24-hour meas- urements; correlations are significant at p < 0.05 (N = 2,974) Temperature inside the wall Variable External temperature Sensor III Sensor II Sensor I Correlation coefficients 0.065897 0.059411 0.043619 0.207004 Table 6. Spearman’s rank order correlations between solar radiation and temperature (inside the wall and external) for 24-hour measurements; correlations are significant at p < 0.05 (N = 1,131) Temperature inside the wall Variable External temperature Sensor III Sensor II Sensor I Correlation coefficients 0.119425 0.128949 0.061621 0.222455 Table 7. Pearson’s correlation between solar radiation and temperature (inside the wall and external); day hours only (from sunrise to sunset); correlations are significant at p < 0.05 (N = 1,131) Temperature inside the wall Variable External temperature Sensor III Sensor II Sensor I Correlation coefficients 0.111228 0.083658 0.038555 0.224269 80 architectura.actapol.net Antonik-Popiołek, P. (2021). Infl uence of solar radiation to the temperature inside a three-layer partition in winter season. Acta Sci. Pol. Architectura, 20 (2), 75–82. doi: 10.22630/ASPA.2021.20.2.16 Table 8. Spearman`s rank order correlations between solar radiation and temperature; day hours only (from surmise to sunset); correlations are significant at p < 0.05 (N = 1,131) Temperature inside the wall Variable External temperature Sensor III Sensor II Sensor I Correlation coefficients 0.189246 0.130261 0.018287 0.110764 Table 9. Pearson’s correlation between solar radiation and temperature (inside the wall and external) at solar radiation greater than 10,000 lx; correlations are significant at p < 0.05 (N = 123) Temperature inside the wall Variable External temperature Sensor III Sensor II Sensor I Solar radiation 0.224537 0.209426 0.169249 0.116059 Table 10. Spearman’s rank order correlations between solar radiation and temperature (inside the wall and external) at solar radiation greater than 10,000 lx; correlations are significant at p < 0.05 (N = 1,131) Temperature inside the wall Variable External temperature Sensor III Sensor II Sensor I Solar radiation 0.229177 0.226831 0.157319 0.217422 the solar radiation is higher than in previous analyses – one can observe that during the periods when (Tables 5–8), but it is still weak (correlation coefficients the solar radiation was higher, that is, more than lower than 0.3). The correlation between the outside 10,000 lx (up to 65,535 lx, average 34,617 lx), temperature and the solar radiation is also very weak. the strength of correlation between the variables Results can be different when we analyse differ- grows, but is still weak; ent sides of the building. Such analysis can be done – the greater illumination does not increase the tem- for other climate-forming factors. It could be useful to perature inside the wall; decide which factors are important and which does not – no correlation can be affected by the location of the matter while designing an external wall. wall and the location of the weather station (north- There is one limitation of analysis. The location -east wall) – if one analysed the correlation between of the building in the city centre may distort results the weather conditions measured on the different a little. walls and during other seasons the results could be different – the research will be continued; – there are numerous errors and failed measurements CONCLUSIONS while using classical temperature sensors. Errors The solar radiation does not affect the temperature can be removed by replacing the existing tradi tional recorded by sensors located in the wall. The analysis sensors with fiber optic devices based on Bragg’s of the effect of solar radiation on the temperature in grating which are more reliable and durable; the external wall during winter leads to the following – there is no reason to use materials which are more conclusions: solar radiation resistant or solar radiation absorb- – there is a very weak correlation between the solar ing because the correlation is to week on north and radiation and the temperature inside the wall, east sides of the building in the winter season. architectura.actapol.net 81 Antonik-Popiołek, P. (2021). Infl uence of solar radiation to the temperature inside a three-layer partition in winter season. Acta Sci. Pol. Architectura, 20 (2), 75–82. doi: 10.22630/ASPA.2021.20.2.16 Juraszek, J. (2020). Fiber Bragg sensors on strain analysis REFERENCES of power transmission lines. Materials, 13 (7), 1559. Ahola, S. & Lahdensivu, J. (2017). Long term monitoring of https://doi.org/10.3390/ma13071559 repaired external wall assembly. Energy Procedia, 132, Juraszek, J. & Antonik-Popiołek, P. (2021). Fibre optic 375–380. FBG sensors for monitoring of the temperature of the Cui, Y., Xie, J., Liu, J., & Xue, P. (2019). Experimental and building envelope. Materials, 14 (5), 1207. https://doi. Theoretical Study on the Heat Transfer Coefficients of org/10.3390/ma14051207 Building External Surfaces in the Tropical Island Re- Kong, Q., He, X., Cao, Y., Sun, Y., Chen, K. & Feng, J. gion. Applied Sciences, 9, 1063. https://doi.org/10.3390/ (2017). Numerical Analysis of the Dynamic Heat Trans- app9061063 fer through an External Wall under Different Outside Gayo, E., Frutos, J. De, Palomo, A. & Massa, S. (1996). Temperatures. Energy Procedia, 105, 2818–2824. A mathematical model simulating the evaporation proc- Marino, B. M., Muńoz, N. & Thomas, L. P. (2018). Calcula- esses in building materials: Experimental checking tion of the external surface temperature of a multi-layer through infrared thermography. Building and Environ- wall considering solar radiation effects. Energy & Build- ment, 31 (5), 469–475. ings, 174, 452–463. Juraszek, J. (2019a). The influence of the spatial structure Świrska-Perkowska, J., Kucharczyk, A. & Wyrwał, J. of carbon fibers on the strength properties of a carbon (2020). Energy Efficiency of a Solar Wall with Transpar- composite. Fibres & Textiles in Eastern Europe, 27 (3), ent Insulation in Polish Climatic Conditions. Energies, 111–117. 13 (4), 859. https://www.mdpi.com/1996-1073/13/4/859/ Juraszek, J. (2019b). Residual Magnetic Field for Identifica- pdf tion of Damage in Steel Wire Rope. Archives of Mining Yu, S., Cui, Y., Shao, Y. & Han, F. (2019). Simulation Re- Science, 64 (1), 79–92. search on the Effect of Coupled Heat and Moisture Juraszek, J. (2019c). Residual Magnetic Field Non-destruc- Transfer on the Energy Consumption and Indoor En- tive Testing of Gantry Cranes. Materials, 12 (4), 564. vironment of Public Buildings. Energies, 12 (1), 141. https://doi.org/10.3390/ma12040564 https://doi.org/10.3390/en12010141 WPŁYW PROMIENIOWANIA SŁONECZNEGO NA TEMPERATURĘ WEWNĄTRZ PRZEGRODY TRÓJWARSTWOWEJ W OKRESIE ZIMOWYM STRESZCZENIE Artykuł przedstawia analizę wpływu promieniowania słonecznego na temperaturę w zewnętrznej przegro- dzie trójwarstwowej w budynku inteligentnym. Dane do analizy pobrano z czujników temperaturowych zlo- kalizowanych w poszczególnych warstwach przegrody oraz ze stacji pogodowej zlokalizowanej na dachu budynku. Dane są rejestrowane 24 h w 5- i 15-minutowych odstępach. Okresem do analizy objęto jeden miesiąc w sezonie zimowym. Celem analiz było określenie korelacji między promieniowaniem słonecznym mierzonym jako natężenie promieniowania świetlnego i temperaturą wewnątrz przegrody. W analizowanym okresie korelacja wystąpiła, ale była bardzo słaba. Kiedy uwzględniono natężenie promieniowania świet- lnego na poziomie powyżej 10 000 lx, korelacja była zauważalna, jednak nadal na bardzo niskim poziomie. W trakcie badań zaproponowano wykorzystanie technologii z zastosowaniem siatki Bragga, które pozwoli- łoby na uniknięcie błędnych pomiarów. Słowa kluczowe: przegroda zewnętrzna, promieniowanie słoneczne, temperatura, budynek inteligentny 82 architectura.actapol.net http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Acta Scientiarum Polonorum Architectura de Gruyter

Influence of Solar Radiation to the Temperature Inside a Three-Layer Partition in Winter Season

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Acta Sci. Pol. Architectura 20 (2) 2021, 75–82 content.sciendo.com/aspa ISSN 1644-0633 eISSN 2544-1760 DOI: 10.22630/ASPA.2021.20.2.16 ORIGINAL P APER Received: 27.12.2020 Accepted: 31.05.2021 INFLUENCE OF SOLAR RADIATION TO THE TEMPERATURE INSIDE A THREE-LAYER PARTITION IN WINTER SEASON Patrycja Antonik-Popiołek Faculty of Materials, Civil and Environmental Engineering, University of Bielsko-Biala, Bielsko-Biała, Poland ABSTRACT The article presents an analysis of the impact of solar radiation on the temperature changes in the external three-layer partition of a smart building. Data for analysis were taken from temperature sensors located in individual layers of the wall and from a weather station on the roof of a building. The data were recorded 24 h in 5- and 15-minute intervals. The analysis period was one month in a winter season. The purpose of the analysis was to determine the correlation between the solar radiation measured as the illuminance and the temperature inside the wall. In the analysed period of one month the correlation was very weak. Also, con- sidering only the illuminance over 10,000 lx, the correlation was noticeable, but still very weak. The use of innovative fiber optic technology with fibre Bragg grating was proposed to avoid incorrect measurements. Key words: outside wall, solar radiation, temperature, smart building external temperature fluctuations. Temperature distri- INTRODUCTION bution in a wall may be also studied using a thermal Speed of wind, external temperature, solar radiation, imaging camera, as described in Kong et al. (2017). air humidity and precipitation are the basic meteoro- Other method involves installation of sensors in the logical climate-forming factors. All those factors can wall during its production or conservation works, as influence on the temperature inside the wall. Is there presented by Marino, Muńoz and Thomas (2017). a correlation between the solar radiation and tem- Influence of evaporation and wind speed to the ther- perature in the external wall? The paper presents an mal transmittance were considered by Cui et al. (2019). analysis of solar radiation impact on temperature in Results indicated that there is a function expression an external wall. There are a few publications which between thermal transmittance and wind speed and it describe methods used to investigate the temperature was validated to be reliable. Authors also compared distribution and changes in walls or at their surface. thermal transmittance with the radiation heat transfer Climate-forming factors were analysed in many other coefficients and the thermal transmittance had a wider papers. The influence of wind and evaporation to the changing range, owing to rainfall effects. Gayo, De thermal transmittance was considered by Cui, Xie and Frutos, Palomo and Massa (1996) considered humid- Xue (2019). Ahola and Lahdensivu (2017) presented ity in different building materials. Research shows that an analysis of the temperature inside a building where the porosity is the most important feature which in- the internal temperature is not regulated. The analysis creases level of humidity inside the material. Świrska- was conducted by means of numerical methods and -Perkowska, Kucharczyk and Wyrwał (2020) analysed concerned the heat flow within the wall affected by a numerical model of solar wall with transparent in- Patrycja Antonik-Popiołek https://orcid.org/0000-0001-5949-8112 pantonik@ath.bielsko.pl © Copyright by Wydawnictwo SGGW Antonik-Popiołek, P. (2021). Infl uence of solar radiation to the temperature inside a three-layer partition in winter season. Acta Sci. Pol. Architectura, 20 (2), 75–82. doi: 10.22630/ASPA.2021.20.2.16 sulation. They considered different configurations of data are fixed in two rows 1.6 m above the floor. Precise the insulation and different orientations and analysed location of the sensors presents Figure 2. Data from the temperature distribution for the envelopes and monthly temperature sensors located in certain layers of the wall energy balances. Yu, Cui, Shao and Han (2019) re- were used for the analysis. Information was supplied ported an influence of temperature and heat transfer in from the sensors fixed in the following locations: the building envelopes on the cooling and heating en- – “I” half-way of the thickness of the thermal insula- ergy consumption and the indoor thermal and humid- tion, ity environment. The results showed that humidity also – “II” between the thermal insulation layer and the should be included in thermal calculations. cellular concrete wall, The innovative technology of monitoring of the – “III” half way of the thickness of the cellular con- temperature, strain, humidity and loads on tested en- crete wall. gineering objects, especially in civil engineering, uses Based on the data obtained, the correlation between the fiber Bragg grating (FBG) and is being developed the temperatures recorded by the certain weather sen- in Department of Civil Engineering of the Univer- sors and the speed of wind was calculated. The sample sity of Bielsko-Biala (Juraszek, 2019a, 2019b, 2020; consisted of the measurements performed in January Juraszek & Antonik-Popiołek, 2021). 2015, in 15-minute intervals. The total number of the Research can help to get to know which climate- records per sensor was 2,974. -forming factors are important in the design of an ex- Due to sensor failures, especially in the winter ternal wall. Additionally it could help to design better period, it was impossible to collect full data in Janu- configuration of wall layers and materials which are ary 2016 and 2017. In this period, there was a lot of used to it. incorrect measurements or no measurements for a few hours. For this reason, the analysis was based on the most representative data of the full month in 2015 MATERIAL AND METHODS (1–31 January 2015). The analysis was based on the data provided by sen- Numerous errors and failed measurements can be sors located inside the wall and a metrological station removed by replacing the existing sensors with fiber on the building. Weather data, obtained from the main external meteorological station located on the roof of the building, as well as temperature data from the sen- sors in the wall, were analysed. The wall is located on the north-east side of the building. The study covered data from full month. The measuring instru- ments of the external weather station register data in 5-minute intervals, whereas the measurements within the wall are recorded every 15 min. Then, the time intervals were unified and data obtained in 15-minute intervals were used for the analysis. The wall was a cavity wall made of cellular con- –3 crete (with the density of 700 kg·m ), insulated with expanded polystyrene and finished with face bricks. The cross-section of the wall is presented in Figure 1. The thermal transmittance equals to –2 –1 U = 0.14 W·m ·K ). The wall is located on the north-west side of the building, on the fifth floor. The sensors providing the Fig. 1. Cross-section of the external wall 76 architectura.actapol.net Antonik-Popiołek, P. (2021). Infl uence of solar radiation to the temperature inside a three-layer partition in winter season. Acta Sci. Pol. Architectura, 20 (2), 75–82. doi: 10.22630/ASPA.2021.20.2.16 Fig. 2. Location of temperature sensors optic devices based on Bragg’s grating. Those sensors – day-hour measurements (from sunrise to sunset); have many advantages: greater reliability, resistance – measurements including illumination above to external interferences, small sizes − and they can be 10,000 lx. built into the existing structures. Table 1 presents the basic statistical characteristics Publications by Juraszek (2019a, 2019b, 2019c, of the weather factors and the temperature measured 2020) and Juraszek and Antonik-Popiołek (2021) by particular sensors. Table 2 presents the basic sta- present the advantages and the use of new generation tistical characteristics of the weather factors and the of FBG and magnetic sensors. temperature measured by particular sensors only in the period from sunrise to sunset each day in January. Table 3 presents the basic statistical characteristics of RESULTS AND DISCUSSION the weather factors and the temperature measured by During January 2015 the temperatures were both posi- particular sensors only in the period when the solar tive and negative, between −9.5 and 17.5°C. The solar radiation was above 10,000 lx in January 2015. radiation measured as illuminance was between 405 In January the sunrise occurred between 7:17 and and 65,535 lx, with the average of 2,953 lx. 7:39, while the sunset was between 15:47 and 16:30. The analysis was divided into three parts: Taking into account only a period between sunrise and – 24-hour measurements (day and night); sunset, the average illuminance was 6,982 lx. Table 1. Basic statistical characteristics for weather conditions and the wall temperature for 24-hour measurements (day and night) Variable Mean Minimum Maximum SD External temperature [°C] 3.88 –9.5 17.5 3.7 Air humidity [%] 73.89 34.0 91.0 11.5 –1 Speed of wind [m·s ] 0.95 0.2 7.0 1.1 Solar radiation [lx] 2 953.0 405.0 65 535.0 8 276.4 Sensor III 15.953 13.9650 17.13 0.769 Temperature inside the wall [°C] Sensor II 15.953 13.9650 17.13 0.769 Sensor I 10.634 5.2950 14.24 1.486 architectura.actapol.net 77 Antonik-Popiołek, P. (2021). Infl uence of solar radiation to the temperature inside a three-layer partition in winter season. Acta Sci. Pol. Architectura, 20 (2), 75–82. doi: 10.22630/ASPA.2021.20.2.16 Table 2. Basic statistical characteristics for weather conditions and the wall temperature for day-hour measurements (from sunrise to sunset) Variable Mean Minimum Maximum SD External temperature [°C] 4.710 –9.0000 17.50 4.05 Air humidity [%] 71.599 34.0000 91.00 13.09 –1 Speed of wind [m·s ] 0.954 0.2000 6.40 1.03 Solar radiation [lx] 6 981.787 405.0000 65 535.00 12 257.11 Sensor III 17.353 15.8950 18.28 0.65 Temperature inside the wall [°C] Sensor II 15.925 13.9650 17.07 0.76 Sensor I 10.529 5.2950 14.14 1.41 Table 3. Basic statistical characteristics for weather conditions and the wall temperature measurements in the periods with the illumination above 10,000 lx Variable Mean Minimum Maximum SD External temperature [°C] 7.76 –1.50 17.50 5.19 Air humidity [%] 56.28 43.00 74.00 7.65 –1 Speed of wind [m·s ] 1.13 0.20 4.70 1.11 Solar radiation [lx] 34 718.63 10 005.00 65 535.00 18360.05 Sensor III 17.13 15.93 17.72 0.50 Temperature inside the wall [°C] Sensor II 15.73 14.14 16.46 0.63 Sensor I 10.44 7.89 12.18 1.29 Illuminance from 400 to 500 lx corresponds to the even at night what was caused by lighting of the area sunrise and sunset on a clear day. The illuminance close surrounding the building. Figure 3 presents the tem- to 0 lx can be measured in undeveloped areas at night. perature distribution in the selected layers of the wall Due to the location of the building in the city and Figure 4 and 5 present the illumination (solar ra- centre, sensors recorded illuminance above 400 lx diation) in January 2015. Time Sensor I Sensor II Sensor III Fig. 3. Temperature inside the wall 78 architectura.actapol.net Temperature [°C] Antonik-Popiołek, P. (2021). Infl uence of solar radiation to the temperature inside a three-layer partition in winter season. Acta Sci. Pol. Architectura, 20 (2), 75–82. doi: 10.22630/ASPA.2021.20.2.16 Fig. 4. Solar radiation in January 2015 (24-hour measurement) Fig. 5. Solar radiation in January 2015 at day architectura.actapol.net 79 Antonik-Popiołek, P. (2021). Infl uence of solar radiation to the temperature inside a three-layer partition in winter season. Acta Sci. Pol. Architectura, 20 (2), 75–82. doi: 10.22630/ASPA.2021.20.2.16 Correlations were analysed between the solar radi- Analysis during the whole month (Tables 5 and ation – illuminance and the temperature inside the wall 6) shows that there is a weak correlation between the (selected layers) as well as between solar radiation and temperature inside the wall and the solar radiation (all external temperature. three correlation coefficients show values lower than The analysis was performed using MS Excel and 0.3). Even the correlation between the outside temper- Statistica software for Pearson’s correlation, which ature and the solar radiation is weak. shows the linear correlation between two variables, and Analysis during the whole month including only the Spearman’s correlation concerning any monotonic day-hours (Table 7 and 8) also shows that there is very relationship, including the non-linear one, between the week correlation between the temperature inside the two variables. In both cases, a significant positive cor- wall and the solar radiation (correlation coefficients relation means that with a growth of the value of one lower than 0.3). The correlation between the outside characteristics, there is a growth of the value of other temperature and the solar radiation is also weak. feature. A significant negative correlation means that Analysis during the periods with solar radiation when one value increases, the other decreases. greater than 10,000 lx (Table 9 and 10) shows that the The strength of the correlations and correspond- correlation between the temperature inside the wall and ing ranges of correlation coefficients are presented in Table 4. The analysis of the correlations between Table 4. Strength of correlations and their interpretation certain variables is presented in Tables 5–10. Tables Strength of correlation Interpretation 4 and 5 show the results of correlation analysis dur- ing one whole month, Tables 6 and 7 show the results < 0.3 weak correlation from sunrise-to-sunset periods and Tables 8 and 9 for ≤ 0.3–0.7 moderate correlation the periods when the solar radiation was more than ≥ 0.7 strong correlation 10,000 lx. Table 5. Pearson’s correlations between solar radiation and temperature (inside the wall and external) for 24-hour meas- urements; correlations are significant at p < 0.05 (N = 2,974) Temperature inside the wall Variable External temperature Sensor III Sensor II Sensor I Correlation coefficients 0.065897 0.059411 0.043619 0.207004 Table 6. Spearman’s rank order correlations between solar radiation and temperature (inside the wall and external) for 24-hour measurements; correlations are significant at p < 0.05 (N = 1,131) Temperature inside the wall Variable External temperature Sensor III Sensor II Sensor I Correlation coefficients 0.119425 0.128949 0.061621 0.222455 Table 7. Pearson’s correlation between solar radiation and temperature (inside the wall and external); day hours only (from sunrise to sunset); correlations are significant at p < 0.05 (N = 1,131) Temperature inside the wall Variable External temperature Sensor III Sensor II Sensor I Correlation coefficients 0.111228 0.083658 0.038555 0.224269 80 architectura.actapol.net Antonik-Popiołek, P. (2021). Infl uence of solar radiation to the temperature inside a three-layer partition in winter season. Acta Sci. Pol. Architectura, 20 (2), 75–82. doi: 10.22630/ASPA.2021.20.2.16 Table 8. Spearman`s rank order correlations between solar radiation and temperature; day hours only (from surmise to sunset); correlations are significant at p < 0.05 (N = 1,131) Temperature inside the wall Variable External temperature Sensor III Sensor II Sensor I Correlation coefficients 0.189246 0.130261 0.018287 0.110764 Table 9. Pearson’s correlation between solar radiation and temperature (inside the wall and external) at solar radiation greater than 10,000 lx; correlations are significant at p < 0.05 (N = 123) Temperature inside the wall Variable External temperature Sensor III Sensor II Sensor I Solar radiation 0.224537 0.209426 0.169249 0.116059 Table 10. Spearman’s rank order correlations between solar radiation and temperature (inside the wall and external) at solar radiation greater than 10,000 lx; correlations are significant at p < 0.05 (N = 1,131) Temperature inside the wall Variable External temperature Sensor III Sensor II Sensor I Solar radiation 0.229177 0.226831 0.157319 0.217422 the solar radiation is higher than in previous analyses – one can observe that during the periods when (Tables 5–8), but it is still weak (correlation coefficients the solar radiation was higher, that is, more than lower than 0.3). The correlation between the outside 10,000 lx (up to 65,535 lx, average 34,617 lx), temperature and the solar radiation is also very weak. the strength of correlation between the variables Results can be different when we analyse differ- grows, but is still weak; ent sides of the building. Such analysis can be done – the greater illumination does not increase the tem- for other climate-forming factors. It could be useful to perature inside the wall; decide which factors are important and which does not – no correlation can be affected by the location of the matter while designing an external wall. wall and the location of the weather station (north- There is one limitation of analysis. The location -east wall) – if one analysed the correlation between of the building in the city centre may distort results the weather conditions measured on the different a little. walls and during other seasons the results could be different – the research will be continued; – there are numerous errors and failed measurements CONCLUSIONS while using classical temperature sensors. Errors The solar radiation does not affect the temperature can be removed by replacing the existing tradi tional recorded by sensors located in the wall. The analysis sensors with fiber optic devices based on Bragg’s of the effect of solar radiation on the temperature in grating which are more reliable and durable; the external wall during winter leads to the following – there is no reason to use materials which are more conclusions: solar radiation resistant or solar radiation absorb- – there is a very weak correlation between the solar ing because the correlation is to week on north and radiation and the temperature inside the wall, east sides of the building in the winter season. architectura.actapol.net 81 Antonik-Popiołek, P. (2021). Infl uence of solar radiation to the temperature inside a three-layer partition in winter season. Acta Sci. Pol. Architectura, 20 (2), 75–82. doi: 10.22630/ASPA.2021.20.2.16 Juraszek, J. (2020). Fiber Bragg sensors on strain analysis REFERENCES of power transmission lines. Materials, 13 (7), 1559. Ahola, S. & Lahdensivu, J. (2017). 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Residual Magnetic Field Non-destruc- Transfer on the Energy Consumption and Indoor En- tive Testing of Gantry Cranes. Materials, 12 (4), 564. vironment of Public Buildings. Energies, 12 (1), 141. https://doi.org/10.3390/ma12040564 https://doi.org/10.3390/en12010141 WPŁYW PROMIENIOWANIA SŁONECZNEGO NA TEMPERATURĘ WEWNĄTRZ PRZEGRODY TRÓJWARSTWOWEJ W OKRESIE ZIMOWYM STRESZCZENIE Artykuł przedstawia analizę wpływu promieniowania słonecznego na temperaturę w zewnętrznej przegro- dzie trójwarstwowej w budynku inteligentnym. Dane do analizy pobrano z czujników temperaturowych zlo- kalizowanych w poszczególnych warstwach przegrody oraz ze stacji pogodowej zlokalizowanej na dachu budynku. Dane są rejestrowane 24 h w 5- i 15-minutowych odstępach. Okresem do analizy objęto jeden miesiąc w sezonie zimowym. Celem analiz było określenie korelacji między promieniowaniem słonecznym mierzonym jako natężenie promieniowania świetlnego i temperaturą wewnątrz przegrody. W analizowanym okresie korelacja wystąpiła, ale była bardzo słaba. Kiedy uwzględniono natężenie promieniowania świet- lnego na poziomie powyżej 10 000 lx, korelacja była zauważalna, jednak nadal na bardzo niskim poziomie. W trakcie badań zaproponowano wykorzystanie technologii z zastosowaniem siatki Bragga, które pozwoli- łoby na uniknięcie błędnych pomiarów. Słowa kluczowe: przegroda zewnętrzna, promieniowanie słoneczne, temperatura, budynek inteligentny 82 architectura.actapol.net

Journal

Acta Scientiarum Polonorum Architecturade Gruyter

Published: Jun 1, 2021

Keywords: outside wall; solar radiation; temperature; smart building

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