Bayesian inference of environmental pollutant source in urban environment using adjoint equation simulated by LES

Abstract

This research proposed a source term estimation method embedding the unsteady adjoint equation, simulated by largeeddy simulation (LES), into the Bayesian inference frame. The performance of the proposed method was evaluated by the dispersion measurements in the wind tunnel experiment for a regular block-arrayed building group model. The difference between the measurements and the adjoint concentrations was formulated according to Bayesian theorem to estimate the source parameters stochastically. The estimations results were compared with that of existing method, which applies the steady simulation of adjoint equation based on mean flow field of LES. According to the results, the proposed method significantly improved the modeling accuracy of the adjoint equation and estimations of source parameters.