Abstract
This study perceives the developing process of Simulation-based Optimization (SBO), using Octopus® for Grasshopper®. This investigation aimed to optimize an Origami-inspired canopy designed to admit solar radiation and daylight in transitional spaces. As optimization objectives, we employed the maximization of Physiological Equivalent Temperature (PET) and Useful Daylight Illuminance (UDI). The method consists of shape optimization, considering the exclusion of non-robust parameters according to factorial analysis. The second step regards computational simulations for the admission of solar radiation and daylight performance within transitional spaces, followed by a comparative evaluation of the best solutions generated through the simulation process. We ran the simulations using Ladybug® and Honeybee® plugins. We simulated the canopy in three different transitional zones, which resulted in distinct shapes and performances. We adopted transitional spaces because they are neither indoor nor outdoor, and comfort standards are rarely evaluated. As the main results, the optimization generated maximum comfort of 93.75% for PET Percentage Time Comfortable and 93.8% for UDI for naturally conditioned spaces. These results denote that users are in thermal comfort for 93.75% of the time. For 93.8% of the evaluated time, illuminance levels are between 100 and 2000lx, and therefore in agreement with the recommended levels.
Highlights
Research on thermal comfort often concentrates on indoors (CHUN; KWOK; TAMURA, 2004)
We organized the method according to the following steps, based on Cartana (2018) and Fang (2017): (a) Shape optimization considering the exclusion of non-robust parameters dismissed through factorial analysis in previous work (LUCARELLI; CARLO, 2020); (b) computational simulations on the admission of solar radiation and daylight performance in transitional spaces; (c) comparative evaluation of the best solutions generated in the simulation process
For the sake of optimization, we adopted Octopus® because it enables the user to work with Multicriteria Design Optimization (MCDO) and the diversify parameters option, which increases the chances of algorithm exploration in the entire search field of solutions
Summary
Research on thermal comfort often concentrates on indoors (CHUN; KWOK; TAMURA, 2004). Notwithstanding, in the last two decades, there has been substantial research on outdoor thermal comfort (PENG; FENG; TIMMERMANS, 2019). Building simulations have been steadily established as a part of computational applications for the design process over the last two decades. The primary objective of their use is to run a performance analysis that informs, for instance, more efficient design alternatives that satisfy multiple criteria (YIGIT; OZORHON, 2018). They help speed up the design process and increase building efficiency, which leads to more optimal designs
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