E3S Web Conf.
Volume 362, 2022BuildSim Nordic 2022
|Number of page(s)||7|
|Section||Daylighting in Simulation|
|Published online||01 December 2022|
- Amundadottir, M. L. (2016). Light-driven model for identifying indicators of non-visual health potential in the built environment. Ph. D. thesis, EPFL. [Google Scholar]
- Balakrishnan, P. and A. Jakubiec (2019). Spectral rendering with daylight: a comparison of two spectral daylight simulation platforms. In Building Simulation 2019, Rome, Italy. [Google Scholar]
- Bourgeois, D., C. F. Reinhart, and G. Ward (2008). Standard daylight coefficient model for dynamic day- lighting simulations. Building Research and Information 36(1), 68–82. [CrossRef] [Google Scholar]
- Brown, T., G. Brainard, C. Cajochen, C. Czeisler, J. Han-Ifin, S. Lockley, R. Lucas, M. Munch, J. O’Hagan, S. Peirson, L. Price, T. Roenneberg, L. Schlangen, D. Skene, M. Spitschan, C. Vetter, P. Zee, and K. Wright (2022). Recommendations for daytime, evening, and nighttime indoor light exposure to best support physiology, sleep, and wakefulness in healthy adults. PLoS biology 20(3). [Google Scholar]
- Hattar, S., H. W. Liao, M. Takao, D. M. Berson, and K. W. Yau (2002). Melanopsin-containing retinal ganglion cells: Architecture, projections, and intrinsic photosensitivity. Science 295(5557), 1065–1070. [Google Scholar]
- Inanici, M., M. Brennan, and E. Clark (2015). Spectral daylighting simulations: Computing circadian light. In Building Simulation 2015, Hyderabad, India. [Google Scholar]
- Inanici, M. and Z.G.F. Architects (2015). Lark Spectral Lighting. [Google Scholar]
- International Commission on Illumination (2018). System for Metrology of Optical Radiation for ipRGC- Influenced Responses to Light (CIE S 026/E:2018). [Google Scholar]
- International WELL Building Institute (2021). WELL v2. [Google Scholar]
- Khademagha, P. (2021). Light directionality in design of healthy offices. Ph. D. thesis, Eindhoven University of Technology. [Google Scholar]
- Khademagha, P., M. B. Aries, A. L. Rosemann, and E. J. van Loenen (2016). Implementing non-image-forming effects of light in the built environment: A review on what we need. Building and Environment 108, 263–272. [CrossRef] [Google Scholar]
- Lucas, R., S. Peirson, D. Berson, T. Brown, H. Cooper, C. Czeisler, M. Figueiro, P. Gamlin, S. Lockley, J. O’Hagan, L. Price, I. Provencio, D. Skene, and G. Brainard (2014, 1). Measuring and using light in the melanopsin age. Trends in Neurosciences 37(1), 1–9. [Google Scholar]
- Pierson, C., M. Aarts, and M. Andersen (2021). Validation of Spectral Simulation Tools for the Prediction of Indoor Daylight Exposure. In Building Simulation 2021, Bruges, Belgium. [Google Scholar]
- Subramaniam, S. (2017). Daylighting Simulations with Radiance using Matrix-based Methods. LBNL. [Google Scholar]
- Vetter, C., P. M. Pattison, K. Houser, M. Herf, A. J. Phillips, K. P. Wright, D. J. Skene, G. C. Brainard, D. B. Boivin, and G. Glickman (2021). A Review of Human Physiological Responses to Light: Implications for the Development of Integrative Lighting Solutions. LEUKOS. [Google Scholar]
- Walkenhorst, O., J. Luther, C. Reinhart, and J. Timmer (2002). Dynamic annual daylight simulations based on one-hour and one-minute means of irradiance data. Solar Energy 72(5), 385–395. [Google Scholar]
- Ward, G. and R. Shaskespeare (1998). Rendering with Radiance: The Art and Science of Lighting Visualization. San Francisco: Morgan Kaufmann Publishers, Inc. [Google Scholar]
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