Inverse Atmospheric Dispersion Modeling in Complex Geometries

Sammanfattning: In the event of a radioactive release in an urban environment the consequent response mustbe swift and precise. As soon as first responders have correct information, they can make anaccurate risk assessment. However, if the position, release rate and time of the radioactiverelease is unknown it is hard to know how the pollutant will spread. This thesis aims to testa model which approximates these three unknowns using weather data (wind and rain) as wellas measurement data collected at sensors placed around an urban environment. An atmospheric dispersion model based on an existing Reynolds Averaged Navier-Stokes modelis set up in two geometries of different complexity to create forward mode synthetic depositiondata and adjoint mode concentration fields resulting from a fixed dry deposition velocity andscavenging effect for wet deposition. Variations of time- and space-dependent rainfall is simu-lated. The resulting data is used in an existing optimization model, where a parameter studyis conducted regarding regularization coefficients. This thesis shows that the optimization model accurately estimates position and its approximaterelease rate of a 2D geometry of radioactive releases using a logarithmic optimization approach,and fail to do so using a linear optimization approach. The logarithmic optimization model alsoapproximately estimates position and release rate in a 3D geometry. Regularization parametersshould be within the range of 0.1 and 1.2 depending on rain. More rain requires smallerparameters and will estimate a lower release rate. Time-dependent rainfall is shown to have amajor negative effect on simulation time.iii