Abstract. Flood risk analysis and management plans mostly neglect groundwater flooding, i.e. high groundwater levels. However, rising groundwater may cause considerable damage to buildings and infrastructure. To improve the knowledge about groundwater flooding and support risk management, a survey was undertaken in the city of Dresden (Saxony, Germany), resulting in 605 completed interviews with private households endangered by high groundwater levels. The reported relatively low flood impact and damage of groundwater floods in comparison with mixed floods was reflected by its scarce perception: Hardly anybody thinks about the risk of groundwater flooding. The interviewees thought that public authorities and not themselves, should be mainly responsible for preparedness and emergency response. Up to now, people do not include groundwater risk in their decision processes on self protection. The implementation of precautionary measures does not differ between households with groundwater or with mixed flood experience. However, less households undertake emergency measures when expecting a groundwater flood only. The state of preparedness should be further improved via an intensified risk communication about groundwater flooding by the authorities. Conditions to reach the endangered population are good, since 70% of the interviewed people are willing to inform themselves about groundwater floods. Recommendations for an improved risk communication are given.

Recent experimental and direct numerical simulation data of two-dimensional, isothermal wall-bounded incompressible turbulent flows indicate that Reynolds-number effects are not only present in the outer layer but are also quite noticeable in the inner layer. The effects are most apparent when the turbulence statistics are plotted in terms of inner variables. With recent advances made in Reynolds-stress and near-wall modeling, a near-wall Reynolds-stress closure based on a recently proposed quasi-linear model for the pressure strain tensor is used to analyse wall-bounded flows over a wide range of Reynolds numbers. The Reynolds number varies from a low of 180, based on the friction velocity and pipe radius/channel half-width, to 15406, based on momentum thickness and free stream velocity. In all the flow cases examined, the model replicates the turbulence statistics, including the Reynolds-number effects observed in the inner and outer layers, quite well. Furthermore, the model reproduces the correlation proposed for the location of the peak shear stress and an appropriately defined Reynolds number, and the variations of the near-wall asymptotes with Reynolds numbers. It is conjectured that the ability of the model to replicate the asymptotic behavior of the near-wall flow is most responsible for the correct prediction of the Reynolds-number effects.

Abstract. The analysis and management of flood risk commonly focuses on surface water floods, because these types are often associated with high economic losses due to damage to buildings and settlements. The rising groundwater as a secondary effect of these floods induces additional damage, particularly in the basements of buildings. Mostly, these losses remain underestimated, because they are difficult to assess, especially for the entire building stock of flood-prone urban areas. For this purpose an appropriate methodology has been developed and lead to a groundwater damage simulation model named GRUWAD. The overall methodology combines various engineering and geoinformatic methods to calculate major damage processes by high groundwater levels. It considers a classification of buildings by building types, synthetic depth-damage functions for groundwater inundation as well as the results of a groundwater-flow model. The modular structure of this procedure can be adapted in the level of detail. Hence, the model allows damage calculations from the local to the regional scale. Among others it can be used to prepare risk maps, for ex-ante analysis of future risks, and to simulate the effects of mitigation measures. Therefore, the model is a multifarious tool for determining urban resilience with respect to high groundwater levels.

Underplatform friction dampers are possible solutions for minimizing vibrations of rotating turbine blades. Solid dampers, characterized by their compact dimensions, are frequently used in real applications and often appear in patents in different forms. A different type of the friction damper is a thin-walled structure, which has larger dimensions and smaller contact stresses on a wider contact area in relation to the solid damper. The damping performance of a thin-walled damper, mounted under the platforms of two rotating, freestanding high pressure turbine blades, is investigated numerically and experimentally in this paper. The tangential and normal contact stiffness that are crucial parameters in optimal design of any friction damper are determined from three-dimensional finite element computations of the contact behavior of the damper on the platform including friction and centrifugal effects. The computed contact stiffness values are applied to nonlinear dynamic simulations of the analyzed blades coupled by the friction damper of a specified mass. These numerical analyses are performed in the modal frequency domain, which is based on the harmonic balance method for the complex linearization of friction forces. The numerical dynamic results are in good agreement with the measured data of the real mistuned system. In the analyzed excitation range, the numerical performance curve of the thin-walled damper is obtained within the scatter band of the experimental results. For the known friction coefficients and available finite element and harmonic balance tools, the described numerical process confirms its usability in the design process of turbine blades with underplatform dampers.

A near-wall variable-Prandtl-number turbulence model is developed for the calculations of high-speed compressible turbulent boundary layers. The model is based on the k-e and the 0 2 -e bk = coefficients in the expansion for k + in the near-wall region <*uv»b uv = coefficients in the expansion for ~uv + in the near-wall region _ #v0> bve = coefficients in the expansion for vO + in the near-wall region a 2 , b 2 = coefficients in the expansion for 6 + 2 in the near-wall region #e0> b eQ = coefficients in the expansion for e# + in the near-wall region B-constant in law of the wall Qx = model constant taken to be 0.1 C d i = model constant taken to be 1.8 for boundary layers and 2.0 for internal flows Cd2 = model constant taken to be 0 Qo = model constant taken to be 0.72 Q 4 = model constant taken to be 2.2 C ds = model constant taken to be 0.8 Cf = skin-friction coefficient, 2r w /(pU 2 X) ) Ch = heat transfer coefficient, /[(poot/ooC^ -e r )] C d = model constant taken to be 1.5 C e2 = model constant taken to be 1.83 C M = model constant taken to be 0.096 C x = model constant taken to be 0.11 f Wt 2 = near-wall damping function for e equation f Wtf e = near-wall damping function for e e equation fp = near-wall damping function for turbulent momentum diffusivity /x = near-wall damping function for turbulent heat diffusivity H = instantaneous total enthalpy, C P T + l /2U k U k h = half-channel width or pipe radius k = turbulent kinetic energy k + = normalized k, k/u 2 M = Mach number M t = local Mach number, u r /(yRT w ) y2 P$ = production due to mean temperature, defined as -(ue)(d(Q)/dx) Pr = molecular Prandtl number *Pr t = turbulent Prandtl number p -instantaneous pressure q w = heat flux at the wall R = univer...