Numerical simulations of contaminant dispersion, as after a gas leakage incident on a chemical plant, can provide valuable insights for both emergency response and preparedness. Simulation approaches combine incompressible Navier-Stokes (INS) equations with advection-diffusion (AD) processes to model wind and concentration field. However, the computational cost of such high-fidelity simulations increases rapidly for complex geometries like urban environments, making them unfeasible in time-critical or multi-query "what-if" scenarios. Therefore, this study focuses on the application of model order reduction (MOR) techniques enabling fast yet accurate predictions. To this end, a thorough comparison of intrusive and non-intrusive MOR methods is performed for the computationally more demanding parametric INS problem with varying wind velocities. Based on these insights, a non-intrusive reduced-order model (ROM) is constructed accounting for both wind velocity and direction. The study is conducted on a two-dimensional domain derived from real-world building footprints, preserving key features for analyzing the dispersion of, for instance, denser contaminants. The resulting ROM enables faster than real-time predictions of spatio-temporal contaminant dispersion from an instantaneous source under varying wind conditions. This capability allows assessing wind measurement uncertainties through a Monte Carlo analysis. To demonstrate the practical applicability, an interactive dashboard provides intuitive access to simulation results.

翻译：污染物扩散的数值模拟，例如化工厂气体泄漏事故后的模拟，可为应急响应与预案制定提供重要参考。模拟方法将不可压缩Navier-Stokes（INS）方程与对流-扩散（AD）过程相结合，以模拟风场与浓度场。然而，针对城市环境等复杂几何结构，此类高保真模拟的计算成本急剧增加，使其难以应用于时间敏感或多查询的"假设分析"场景。因此，本研究聚焦于应用模型降阶（MOR）技术以实现快速而准确的预测。为此，本文针对计算要求更高的参数化INS问题（风速可变），对侵入式与非侵入式MOR方法进行了全面比较。基于这些研究结果，构建了一个同时考虑风速与风向的非侵入式降阶模型（ROM）。研究采用基于真实建筑足迹的二维计算域，保留了分析（例如）高密度污染物扩散的关键特征。所构建的ROM能够以快于实时计算的速度，预测瞬时污染源在不同风条件下的时空扩散过程。该能力使得通过蒙特卡罗分析评估风测量不确定性成为可能。为展示实际应用价值，开发了一个交互式仪表板以提供对模拟结果的直观访问。