Thermal performance of windows and doors. Determination of solar heat gain coefficient using solar simulator

2017 ◽  
Keyword(s):  
Thermal Performance ◽  
Gain Coefficient ◽  
Solar Simulator ◽  
Heat Gain ◽  
Solar Heat ◽  
Solar Heat Gain

Hot-cool box calorimetric determination of the solar heat gain coefficient and the U-value of internal shading devices

2017 ◽  
Vol 10 (6) ◽  
pp. 1553-1571 ◽  
Author(s):  
Ayelén Villalba ◽  
Erica Correa ◽  
Andrea Pattini ◽  
Daniel Vicare
Keyword(s):  
Gain Coefficient ◽  
Heat Gain ◽  
Solar Heat ◽  
U Value ◽  
Solar Heat Gain ◽  
Shading Devices ◽  
Calorimetric Determination

Experimental determination of the solar heat gain coefficient of inside blinds

2002 ◽  
Vol 34 (1) ◽  
pp. 117-125
Author(s):  
Ingo Haug ◽  
Andreas Beck ◽  
Jochen Fricke
Keyword(s):  
Experimental Determination ◽  
Gain Coefficient ◽  
Heat Gain ◽  
Solar Heat ◽  
Solar Heat Gain

scholarly journals Establishment of Passive Energy Conservation Measure and Economic Evaluation of Fenestration System in Nonresidential Building of Korea

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Bo-Eun Choi ◽  
Ji-Hyun Shin ◽  
Jin-Hyun Lee ◽  
Sun-Sook Kim ◽  
Young-Hum Cho
Keyword(s):  
Energy Efficiency ◽  
Economic Evaluation ◽  
Energy Consumption ◽  
Energy Conservation ◽  
Gain Coefficient ◽  
Building Energy Efficiency ◽  
Basic Study ◽  
Heat Gain ◽  
Solar Heat ◽  
Solar Heat Gain

ECO2 (building energy efficiency rating program) and passive energy conservation measures (ECMs) were established as a basic study for targeted methodologies and decision support systems development in Korea to meet national regulations. The primary energy consumption and economic evaluation of nonresidential buildings was performed. Passive ECMs were classified as planning and performance elements. The planning elements are the window-to-wall ratio (WWR) and horizontal shading angle. The performance elements are the thermal transmittance (U-value) of the walls, roof, and floor and the U-value and solar heat gain coefficient (SHGC) of windows. This study focused on the window-to-wall ratio and the U-value and solar heat gain coefficient of windows. An economic efficiency database for the constructed alternatives was built; the target building was set and the Passive ECM List for the target building was derived. The energy consumption evaluation and economic evaluation were performed for each of the constructed alternatives, and a methodology for guiding energy efficiency decisions was proposed based on the performance evaluation results, and the optimal Passive ECM List for the target building was derived.

scholarly journals Simulation Analysis of Daylight Characteristics and Cooling Load Based on Performance Test of Covering Materials Used in Smart Farms

Energies ◽  
2021 ◽  
Vol 14 (19) ◽  
pp. 6331
Author(s):  
Doo-Yong Park ◽  
Hyun-Je Lee ◽  
Su-In Yun ◽  
Sang-Min Choi
Keyword(s):  
Double Layer ◽  
Optimal Growth ◽  
Gain Coefficient ◽  
Cooling Load ◽  
Heat Transmission ◽  
Rigid Plastic ◽  
Heat Gain ◽  
Solar Heat ◽  
Covering Material ◽  
Solar Heat Gain

In this study, seven of the most commonly applied covering materials in smart farms are selected as the representative samples for analysis, namely, glass, soft film (polyethylene, PE), soft film (polyolefin, PO), rigid plastic film (ethylene tetra fluoro ethylene, ETFE), rigid plastic sheet (poly methyl methacrylate, PMMA), rigid plastic sheet (polycarbonate, PC double layer), and woven film. For each covering material, visible light transmittance and reflectivity, solar radiation transmittance and reflectivity, thickness, solar heat gain coefficient, and the coefficient of heat transmission are measured according to the test methods in the Korean Industrial Standards (KS) to derive input data for the respective materials. In addition, using the optical and thermal input data as derived above, simulations are performed on the cooling load and daylight characteristics of smart farms to derive basic reference data for the selection of adequate covering materials for the design. Based on the analysis result of the daylight characteristics for each covering material, for a shading rate of 60%, the average values of indoor illuminance were 19,879 lux, 20,012 lux, 19,393 lux, 19,555 lux, 16,560 lux, 16,228 lux, and 11,173 lux for glass, PE film, PO film, ETFE, woven film, PMMA, and PC double layer, respectively, between 6 am and 8 pm, which correspond to the hours when daylight enters indoor spaces. Considering the target light intensity for strawberry growth at 10,000–40,000 lux, the above results confirm that all the sample covering materials had an indoor illuminance level above the lower limit range of the target light intensity. For the cooling load evaluation, the PC double layer had the lowest value of 482.8 W/m2, and PO film had the highest value of 633.8 W/m2. The difference between the cooling loads of the PC double layer and the PO film is 151 W/㎡, which amounts to 23.8%, thus indicating that the selected covering material significantly impacts the cooling load. The cooling load exhibited a pattern similar to that of the coefficient of heat transmission and solar heat gain coefficient, which are key influencing factors for most of the sample materials. However, for PMMA, the cooling load was low because it had a higher coefficient of heat transmission than other materials, but its solar heat gain coefficient was relatively low. Another possible reason for the difference is that the solar heat gain coefficient impacts the cooling load. When the cooling set temperature was controlled from Case 1-1 to Case 1-2, the cooling load decreased by 10.7% on average. In addition, when the cooling set temperature changed from Case 1-1 to Case 1-3, the cooling load decreased by 26.1% on average. For cooling set temperature control, maintaining the temperature around the lower temperature range of the optimal growth temperature of the plants increases the yield, but it also incurs increased cooling load and cost. In terms of cost only, while maintaining the cooling temperature for 24 h at 30 °C, which is the upper limit of the optimal growth temperature, would be advantageous, it will lead to a deterioration of the quality and reductions in yield. Therefore, as follow-up studies for further investigation of the findings of this research, there is the need for an evaluation of the yield and quality with respect to the range of cooling set temperatures. When the internal shading rate was increased to 40% (Case 2-2) with reference to Case 2-1, which was a greenhouse without the application of internal shading, the cooling load decreased by 27.4% on average. Furthermore, when the internal shading rate increased to 50% (Case 2-3) with reference to Case 2-1, the cooling load decreased by 29.3% on average. When the internal shading rate increased to 60% (Case 2-4), the cooling load decreased by 31.5% on average.

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