Robustness Assessment of a Low Poly Modeling Strategy for Performance Simulation of Double-Skin Green Facades

Performance simulation of building vegetal envelope can be very resource intensive and time consuming when made with a high number of polygons. The aim of this study is to assess the robustness of a low poly modeling strategy based on raster image sampling, with the scope of reducing the simulation burden of natural illumination performance, in several scenarios of operation. The image-based approach is implemented for the geometric reconstruction of vegetation, starting from an ivy (Hedera Helix L.) leaf, to model a double skin green facade. Due to the high influence of foliage density on natural lighting performance of green walls and its variability in real cases, the strategy behavior is evaluated for the variation of this parameter, addressed as Wall Coverage Ratio (WCR). Five scenarios of WCR are taken into account to perform the analysis of several levels of detail of the low poly mesh geometries, obtained with different sample densities of the raster image. The strategy appears to be reliable and delivers a 21% decrease of the simulation time, compared to the duration of a high level of detail simulation, with an acceptable performance deviation and the result is robust across the analyzed scenarios. A peak 39% decrease is obtained too, but with a considerable performance deviation. The outcomes also show a high dependency of the performance deviation on WCR, especially for simulations with very few polygons. Useful insights on calibration of green modeling accuracy for lighting performance simulation can be drawn from the results of this work.