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This study aims to estimate the location and emission rate of an unknown air pollutant source within the complex geometry of an urban-like environment. The RANS and LES CFD modelling approaches are implemented separately for calculating wind field, turbulence parameters, and passive scalar transport using the open-source CFD tool OpenFOAM. The presented inverse modelling technique utilizes an STE algorithm that correlates, via a cost function, the estimated concentrations provided by the CFD model with the concentration observed by the corresponding measurement network to predict the unknown source location. The emission rate is calculated for the estimated location using a quadratic cost function. The methodology is applied in the Michelstadt wind tunnel experiment case, investigating two different release scenarios for evaluation purposes. The results highlight the high agreement between the modelled and the corresponding experiment’s source parameters from both models in the second release scenario. An acceptable solution is determined in the first scenario from both RANS and LES applications.

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Unknown Source Parameters Estimation in an Urban-Like Domain Using RANS and LES Approaches

  • 会议论文

  • 发表日期：

    2025年

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  • Panagiotis Gkirmpas,
  • Fotios Barmpas,
  • George Tsegas,
  • Nicolas Moussiopoulos,
  • Christos Vlachokostas

摘要

This study aims to estimate the location and emission rate of an unknown air pollutant source within the complex geometry of an urban-like environment. The RANS and LES CFD modelling approaches are implemented separately for calculating wind field, turbulence parameters, and passive scalar transport using the open-source CFD tool OpenFOAM. The presented inverse modelling technique utilizes an STE algorithm that correlates, via a cost function, the estimated concentrations provided by the CFD model with the concentration observed by the corresponding measurement network to predict the unknown source location. The emission rate is calculated for the estimated location using a quadratic cost function. The methodology is applied in the Michelstadt wind tunnel experiment case, investigating two different release scenarios for evaluation purposes. The results highlight the high agreement between the modelled and the corresponding experiment’s source parameters from both models in the second release scenario. An acceptable solution is determined in the first scenario from both RANS and LES applications.