Modeling specular transmission of complex fenestration systems with data-driven BSDFs
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32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
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Daylight simulation workflows incorporating measured bidirectional scattering distribution functions
Daylight predictions of architectural spaces depend on good estimates of light transfer through skylights, windows and other fenestration systems. For clear glazing and painted surfaces, parametric transmission and reflection models have proven adequate, but there are many cases where light-scattering, semi-specular shading and daylighting materials defy simple characterization. Something as commonplace as fabric roller shades and venetian blinds may turn daylight prediction into guesswork, and numerous advanced systems on the market tuned specifically to enhance daylight are not sufficiently characterized to distinguish their performance. In this paper, we describe new tools available to handle novel and specialized fabrics, materials, and devices using data-driven modelling of bi-directional scattering distribution functions (BSDFs). These representations are usually tabulated at constant or adjustable angular resolution for efficient point-in-time and annual daylight simulations. We describe a variety of BSDF simulation workflows, including some of the tools and methods that make advanced analysis possible, and highlight some of the current challenges. We conclude with a discussion of future work and how such data might be created and shared worldwide.
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Field validation of isotropic analytical models for simulating fabric shades
Fabric roller shades are common shading materials used in commercial and residential buildings. Accurately characterizing and modeling shades helps practitioners select the appropriate product and its control strategy based on climate and occupants' priorities, such as visual comfort and view to outdoors. Previous studies established a generalized method for modeling complex fenestration systems using data-driven tabulated bidirectional scattering distribution functions. However, deploying such a method at scale to all fabric shading products on the market is too costly and time-consuming. Analytical models that are based on a limited set of measurements (e.g., normal-normal and normal-hemispherical visible transmittance and reflectance, and directional cut-off angles) can be used to model the wide variety of shading products on the market. This study evaluates the performance of two isotropic analytical models, Roos-Wienold and Modified-Kotey, for modeling fabric roller shades, with a focus on the model's ability to predict occupant visual comfort. The performance evaluation was conducted through laboratory and field measurements and simulations. The results showed that both models are sufficient for predicting vertical illuminance at seated eye-level. Roos-Wienold model was able to predict binary visual comfort classification (glare/no-glare) under a wide range of luminance conditions, while Modified-Kotey model did not perform as well under high-contrast low-adaptation conditions. Both models are insufficient in predicting visual comfort at a four-point scale (e.g., imperceptible, perceptible, disturbing, intolerable). The two isotropic models become less accurate when the fabric exhibits high anisotropy.
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Field validation of data-driven BSDF and peak extraction models for light-scattering fabric shades
Shading and daylighting systems affect cooling, heating, and lighting energy use by modulating solar radiation through the building façade. Characterizing shading systems holistically and accurately helps designers and engineers evaluate shading systems to achieve energy and non-energy performance goals. These complex fenestration systems can be modeled using Bidirectional Scattering Distribution Functions (BSDF), which map incident radiation to hemispherical distributions of outgoing radiation. Data-driven, tabulated BSDFs are derived from interpolated goniophotometer measured data, then sampled during the raytracing calculation. A peak extraction (PE) algorithm was developed to circumvent limits in BSDF angular resolution, where the specular peak is extracted during simulation by evaluating the BSDF in the through direction and surrounding region. The objective of this study was to validate this measurement and modeling workflow using field monitored data from a full scale testbed with eleven installed fabrics of different weaves, openness factors, and colors and assess the accuracy of the workflow under different adaptation and contrast conditions. Test conditions were limited to clear sky conditions with the sun in the field of view. Results showed that, for tensor tree datasets, vertical illuminance, solar luminance (2.5° apex), and daylight glare probability (DGP) were predicted to within a mean bias error (MBE) error of -456 lx (-12.3%), -3.46e5 (-38.4%), and -0.042 (-7.8%) when full PE occurred. With a binary classification of glare/ no glare, DGP was predicted accurately with a true positive rate of 0.98 and true negative rate of 1.0 using tensor tree data and less accurately with Klems BSDF data, particularly for cases of no glare. The workflow may be of insufficient accuracy to distinguish borderline performance between fabrics using the four-point glare scale, particularly under low adaptation, high contrast daylit conditions. Errors were due to reductions in peak shape and intensity across the BSDF interpolation and data reduction workflow. Future work is needed to better preserve measurement fidelity during interpolation and sampling, which in turn will improve PE performance.
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Automated Production of Optimization-Based Control Logics for Dynamic Facade Systems, with Experimental Application to Two-Zone External Venetian Blinds
The primary goal of this research is to devise a system that produces controllers for complex fenestration systems that perform nearly as well as Model Predictive Control but at a level of cost and implementation complexity that rivals simple heuristic controls. To this end, a cloud-based automated controller production system has been set up for a motorized external Venetian blind device, with a simple web interface that can be used by non-experts. The computation cost per controller is in the range of a few dollars, and the control logic is simple enough to be implemented on small and cheap distributed controllers. The web interface allows the user to specify some details of their particular building and window configuration, including orientation, latitude, interior geometries, and lighting and HVAC system parameters. Upon submittal, a cloud-based system configures the necessary files and commands, and then runs thousands of optimizations with them. Once the calculations are finished, the system produces a lookup table and interpolation-based controller scripts that can be used on a simple and cheap distributed controller. This paper describes the underlying models and optimization processes. It also describes the resulting control logics for two cases tested at Lawrence Berkeley National Laboratory’s Advanced Windows Testbed Facility: illuminance maximization subject to glare constraints; and lighting + HVAC energy minimization. The performance of the model-based controllers produced by the automated web-based system are compared to a heuristic ‘block beam’ controller in physical experiments at the Testbed. The experimental results are supplemented by simulation experiments with the same configuration as the Testbed. The results show the illuminance maximizing controller significantly outperforms the heuristic controller in terms of glare avoidance, and also outperforms it in terms of hours of daylight autonomy. The energy minimizing controller also outperforms the heuristic controller. This paper also discusses how the web-based system may be extended to consider other configurations, such as electrochromic windows and thermally massive HVAC systems. Potential roles for this type of system within the building design and construction industry are discussed.
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Experimental demonstration and performance evaluation of a complex fenestration system for daylighting and thermal harvesting
Two significant design strategies for mitigating building energy consumption are daylight redirection and solar energy harvesting. Effective daylighting implementation enhances the amount of useful natural light within a space and offsets the need for electric lighting. Solar energy harvesting systems can mitigate energy costs from mechanical systems by managing incoming thermal loads or capturing solar energy that can be used to supplement thermal systems in the building. While there are many available façade-based technologies that can perform daylighting or solar thermal energy harvesting, there remains a limitation in available systems that can perform both of them simultaneously. This paper, describes the design and experimental demonstration of a Liquid Filled Prismatic Louver (LFPL) system, which combines both energy-saving strategies. The LFPL system was installed in a south-facing room in New York City and evaluated for indoor daylight penetration and potential for thermal energy harvesting. Daylight redirection is achieved through the prismatic louver geometry and proper orientation, whereas thermal energy harvesting is achieved through IR absorption from the liquid (e.g., water) within the prisms. Daylighting performance was evaluated by illuminance measurements at key locations within the space, whereas thermal harvesting performance was evaluated through temperature measurements and thermal imaging analysis. We show that the LFPL system, with all prismatic elements oriented at the same angle, achieve a 2-fold and 8-fold enhancement in daylight redirection to the ceiling, for prism orientations of 10° and 20°, respectively. We also demonstrate the system’s capability to adjust to specific lighting needs, within the space, through the dynamic individual orientation of prismatic elements; thus, achieving a concentrated ceiling illuminance enhancement of ~100 times and ~200 times at 2.5 and 4.3 m away from the window sill, providing workplane illuminance enhancement of 6 and 2 times more than in the case of the control room with regular windows. Furthermore, we illustrate a reduction of potential heating loads at locations close to the window from the combination of infrared absorption in the water volume and the redirection of the incoming solar radiation, leading to a reduction of the workplane temperature by an average of 7–10 °C.
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