Quantitatively identify unsteady gas pollutant releases by inverse CFD modeling

This study proposed the Tikhonov regularization strategy coupled with the least-squares optimization to identify unsteady gas release processes from a fixed spot. The Tikhonov regularization adds a regularized term to the optimizing objective function and imposes a bound to solution. To accelerate the solving procedure, the unsteady gas concentration is calculated as the convolution integral between the concentration response by a unit impulse release and the arbitrary unsteady release. It finds the developed inverse model can accurately and efficiently quantify the unsteady gas release either in a constant or sinusoidal form for a while in a square ventilation cavity.