Abstract
Physical or virtual models are commonly employed to visualize the conceptual ideas of architects, lighting designers and daylighting researchers. The models are also used to assess the daylighting performance of their buildings, particularly when Complex Fenestration Systems (CFS) are considered. Recent studies have revealed a general tendency of physical models to over- estimate the performance, usually expressed through work plane illuminance and daylight factor profiles, when compared to that of the real building. These discrepancies can be attributed to several experimental errors. To analyze the main sources of error, a set of comparisons between a real building, a virtual model and a physical model was undertaken. The real building in our case consisted of a full scale test module with a south-facing windows designed for experimentation on daylighting systems. A virtual model was a computed model created in Radiance program while the physical model was a scale model (1:10) of the real case. The fenestration systems considered in this study were a simple window (double glazing) and two CFS (Laser-cut panel and Prismatic film). The physical model was placed in outdoor conditions similar to that of the real building as well as under a scanning sky simulator (for both real sky luminance distribution and CIE standard sky); the virtual model simulations were carried out with the program Radiance using the GenSky function (for CIE standard sky) and the Partial Daylight Factor (PDF) method, the later using the real sky luminance distribution acquired by a digital sky scanner at the same time as the real building's daylight performance was assessed. The daylighting performances of the building, daylight factor (DF) for overcast sky and illuminance ratio (IR) for clear sky, were monitored using illuminance meters: a set of sensors for exterior illuminance and another set of equally spaced 7 sensors placed at 1m intervals starting from the window plane for the interior space were used for that purpose. The interior surface luminance of both real building and physical model was measured using a luminance meter and a High Dynamic Range (HDR) imaging technique (within the Photosphere program). The Radiance program was used to determine the interior surface luminance within the virtual model. The measured performance of the real case, physical models and virtual models were compared, the causes of discrepancies between the real building and models were analyzed. The causes of errors that were evaluated were modeling of building details and dimensions, CFS modeling, mocking-up of the photometric properties (surface reflectance and window transmittance), model location as well as photometer features. To study the impact of these error sources on daylighting performance assessment, virtual models created using the Radiance program were used to achieve a sensitivity analysis of modeling errors. The significant factors were considered, leading to a set of modeling guidelines. The experimental study shows that large discrepancies can occur in daylighting performance figures. For example if glazings are omitted from the model's window, a relative divergence of 25% to 40% can be found at different points in the room, suggesting more light entering than actually measured in the real building. Inaccuracy in window transmittance inaccuracy is a major cause of errors commonly found in daylight modeling. In addition, significant discrepancies can be caused by even slight error in surface reflectance values. Only 10% overestimation of surface reflectance modeling leads up to 80% relative errors in work plane illuminance for a simple window and up to 90% for the assessment of CFS. Continuous sky distribution presented more accurate results than 145 sky sectors simulation, particularly when CFS were evaluated. These discrepancies can be reduced by making an effort to mock up the geometric and photometric features including the daylight simulation of the models carefully. A checklist presented in this thesis can be used as a guideline to help the daylight designers to estimate and avoid errors when assessing daylighting performance.
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