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, J. L. M. (2012). State of the art in lighting simulation for building science : a literature review. Journal of Building Performance Simulation, 5(4), 209-233. DOI: 10.1080209-233. DOI: 10. /19401493.2011 General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.• Users may download and print one copy of any publication from the public portal for the purpose of private study or research.• You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal ? Take down policyIf you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. This paper examines the current state of the art in lighting simulation related to building science research. Discussion on historical developments and main modelling approaches is followed by describing lighting simulation within the design process, where it is applied beyond presentation renderings. Works are grouped using the main aspects of a program (input, modelling, and output). Lighting simulation currently focuses on representing accurately a large number of common situations encountered by building designers and researchers. Existing models apply roughly the same theoretical algorithms and calculation aids, limiting representation of certain physical phenomena. Although some models can be used for element design, they are not practical enough to develop or prototype new, untested elements. Elaborate building components require separate analysis through complex simulation aids. Few tools support the early architectural design process. Simplification applies when integrating lighting simulation to whole-building simulation. Input quality affects accuracy, while output needs careful expert interpretation.

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