Sungmin Yoon

Recent advancements in Urban Building Energy Modeling (UBEM) highlight the critical role of shading, yet the trade-off between explicit terrain modeling and computational feasibility remains underexplored. To address this gap, this study conducts a systematic comparative analysis of shading simulation strategies to identify the optimal level of geometric abstraction. Utilizing a polygon clipping-based process, diverse scenarios—ranging from detailed terrain meshing to simplified approximations—were evaluated within a topographically complex, high-density urban district. The empirical analysis yielded three key findings. First, excluding surrounding buildings causes severe underestimation, confirming building-to-building occlusion as the dominant shading determinant. Second, the conventional "flat earth" assumption introduces complex bidirectional structural biases, underestimating shading in valleys and overestimating it on hilltops by distorting the geometry between solar vectors and building facades. Third, an "indirect topography" approach—accounting for relative elevation differences via base adjustments and skirt extensions without explicit terrain polygons—emerged as the most practical solution. This method demonstrated exceptional fidelity to the ground truth while effectively mitigating the computational burden of processing massive terrain meshes. These findings prove that high-fidelity shading assessment does not necessitate high-complexity geometric modeling. The proposed approach offers a scalable, efficient guideline for developing Digital Twins and UBEMs, bridging the gap between rigorous physical representation and practical computational feasibility.

Urban Building Energy Modeling (UBEM) underscores the critical role of shading effects in assessing energy performance and solar potential. However, the trade-off between explicit terrain modeling and computational feasibility remains largely underexplored. To address this, this study systematically compares various shading simulation strategies to identify the optimal level of geometric abstraction. Using a polygon clipping-based geometric process, diverse modeling scenarios—ranging from detailed terrain meshing to simplified approximations—were evaluated within a high-density, topographically complex urban district comprising over 22,000 buildings. The empirical analysis yielded critical insights. First, excluding surrounding buildings causes significant simulation error, confirming that building-to-building occlusion is the dominant shading factor in dense environments. Second, the conventional "flat earth" assumption introduces severe structural biases rather than simple inaccuracies. Ignoring ground elevation differences causes complex bidirectional discrepancies—underestimating shading in valleys and overestimating it on hilltops—thereby distorting the geometric relationship between solar vectors and building facades. Through this rigorous comparison, the "indirect topography" approach—which accounts for relative elevation differences via base adjustments and skirt extensions without explicit terrain polygon modeling—emerged as the most practical solution. This method demonstrated exceptional fidelity to the detailed ground truth while effectively alleviating the computational burden, reducing simulation runtime by 15% compared to explicit mesh models. These findings suggest that high-fidelity shading simulation does not necessitate high-complexity geometric modeling, offering scalable, efficient guidelines for developing Digital Twins and UBEMs that bridge urban climatology and architectural engineering.