Field validation of data-driven BSDF and peak extraction models for light-scattering fabric shades

Shading and daylighting systems affect cooling, heating, lighting energy use by modulating solar radiation through the building façade. Characterizing shading holistically accurately helps designers engineers evaluate to achieve non-energy performance goals. These complex fenestration can be modeled using Bidirectional Scattering Distribution Functions (BSDF), which map incident hemispherical distributions of outgoing radiation. Data-driven, tabulated BSDFs are derived from interpolated goniophotometer measured data, then sampled during raytracing calculation. A peak extraction (PE) algorithm was developed circumvent limits in BSDF angular resolution, where specular is extracted simulation evaluating direction surrounding region. The objective this study validate measurement modeling workflow field monitored data a full scale testbed with eleven installed fabrics different weaves, openness factors, colors assess accuracy under adaptation contrast conditions. Test conditions were limited clear sky sun view. Results showed that, for tensor tree datasets, vertical illuminance, luminance (2.5° apex), daylight glare probability (DGP) predicted within mean bias error (MBE) ?456 lx (?12.3%), ?3.46e5 (?38.4%), ?0.042 (?7.8%) when PE occurred. With binary classification glare/ no glare, DGP true positive rate 0.98 negative 1.0 less Klems particularly cases glare. may insufficient distinguish borderline between four-point scale, low adaptation, high daylit Errors due reductions shape intensity across interpolation reduction workflow. Future work needed better preserve fidelity sampling, turn will improve performance.