Lead: Turbulent mixing of streams with different temperature may result in significant temperature fluctuations in the walls of pipes and other components of power plants or other industrial installations. These fluctuations may cause thermal fatigue in the wall material and pose the risk of a failure of the component. Method: The proposed project is focused on the prediction of temperature fluctuations in a T-junction. It is planned to apply Reynolds Averaged Navier-Stokes (RANS) modeling as an alternative to very computational expensive LES simulations. RANS modeling will be extended by temperature fluctuation transport equations. It is based on a second averaging of the scalar transport equation, which results in additional transport equations for the RMS of the temperature, and turbulent heat fluxes. This approach reduces computational costs compared to LES by orders of magnitude. Still, it is possible to obtain distributions of the RMS of the fluid temperature. For a subsequent fatigue analysis, estimates of the temperature fluctuations in the wall and their frequency range are needed. The feasibility of methods for an approximate determination of the time scale of turbulent mixing patterns found in the fluid and a simplified modeling of the response of the temperature field in the wall will be explored. For the experimental part, a co-operation with the Laboratory of Nuclear Power (IKE) of the University of Stuttgart will be established. IKE has started to construct a T-junction experiment operating parameters of an original nuclear power plant. We will construct a second test facility to perform complementary mixing experiments at room temperature respecting fluid dynamic similarity. Mesh sensor techniques provide two-dimensional distributions of the transport scalar with a time resolution of up to 10 kHz for the support of the model development. Aim: The main outcome of the project is an efficient method for the prediction of temperature fluctuations in components, where fluid streams of different temperature are mixed. This phenomenon has a relevant impact to the lifetime of components of nuclear power plants and other industrial installations. The results will therefore contribute to economy and safety of these plants. The fast-running RANS simulations aim at performing preliminary screenings of components to identify locations of critical amplitudes of temperature fluctuations, especially in complex, large-scale geometries. Locations with critical amplitudes of temperature fluctuations can be identified and a more detailed research using time-consuming LES methods or dedicated experiments can be focused to relevant cases.