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Modeling specular transmission of complex fenestration systems with data-driven BSDFs

  • Author(s): Ward, GJ;
  • Wang, T;
  • Geisler-Moroder, D;
  • Lee, ES;
  • Grobe, LO;
  • Wienold, J;
  • Jonsson, JC
  • et al.
Abstract

A Bidirectional Scattering Distribution Function (BSDF) describes how light from each incident direction is scattered (reflected and transmitted) by a simple or composite surface, such as a window shade. Compact, tabular BSDFs may be derived via interpolation, discretization and/or compression from goniophotometer measurements. These data-driven BSDFs can represent any measurable distribution to the limits of their tabulated resolution, making them more general than parametric or analytical BSDFs, which are restricted to a particular class of materials. However, tabulated BSDFs present a trade-off between higher sampling loads versus lower directional accuracy during simulation. Low-resolution BSDFs (e.g., Klems basis) may be adequate for calculating solar heat gains but fall short when applied to daylight glare predictions. The tensor-tree representation moderates this trade-off using a variable-resolution basis, providing detail where needed at an acceptable cost. Independently, a peak extraction algorithm isolates direct transmission from any tabular BSDF, enabling high-resolution beam radiation and glare analysis through transmitting systems with a “vision” component. Our data-driven BSDF methods were validated with a pilot study of a fabric shade installed in an outdoor, full-scale office testbed. Comparisons between measurement and simulation were made for vertical illuminance, specular and near-specular transmission, and daylight glare probability. Models based on high resolution BSDF measurements yielded superior results when accounting for anisotropy compared to isotropic models. Models with higher resolution produced more accurate source luminance data than low-resolution models. Further validation work is needed to better characterize generality of observed trends from this pilot study.

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