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- W1971072263 abstract "Repeated modifications of multiple design parameters are required to optimize daylighting system design. However, a large number of optional design parameters increase the computation time. This research developed a simulation-based model to evaluate daylighting system design based on system daylighting and thermal performance. The model utilized the prediction methods to speed up computation. The methods that predict the daylight levels and energy usage were developed based on sample simulation results using Radiance and EnergyPlus software. A prominent multiobjective optimization technique, strength Pareto evolutionary approach II, was applied to optimize four main design parameters (window dimensions and position, glazing transmittance, and blind reflectance). A patch division scheme was proposed to limit the maximum number of daylighting simulations if there was a larger number of window dimensions and positions. A case study was conducted to illustrate the application of the model and to validate the accuracy of the prediction methods. The percentage errors between the predicted and simulation results for both energy and daylighting performances were less than 5%. The research contribution is the development of a new faster approach for predicting building energy consumption and daylight levels as well as the development of an integrated simulation environment for the daylighting system design." @default.
- W1971072263 created "2016-06-24" @default.
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- W1971072263 date "2014-09-01" @default.
- W1971072263 modified "2023-09-27" @default.
- W1971072263 title "Simulation-Based Model for Integrated Daylighting System Design" @default.
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- W1971072263 doi "https://doi.org/10.1061/(asce)cp.1943-5487.0000336" @default.
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