We determine the size of argon clusters generated with a planar nozzle, based on the optical measurements in conjunction with theoretical modelling. Using a quasi-one dimensional model for the moments of the cluster size distribution, we determine the influence of critical physical assumptions. These refer to the surface tension depending on the presence of thermal equilibrium, the mass density of clusters, and different methods to model the growth rate of the cluster radius. We show that, despite strong variation in the predicted cluster size, 〈N〉, the liquid mass ratio, g, can be determined with high trustworthiness, because g is predicted as being almost independent of the specific model assumptions. Exploiting this observation, we use the calculated value for g to retrieve the cluster size from optical measurements, i.e., calibrated Rayleigh scattering and interferometry. Based on the measurements of the cluster size vs. the nozzle stagnation pressure, we provide a new power law for the prediction of the cluster size in experiments with higher values of the Hagena parameter (Γ*>104). This range is of relevance for experiments on high-intensity laser matter interactions.

This study provides a comparison between an Eulerian and a Lagrangian approach for simulation of ice crystal trajectories and impact in a generic turbofan compressor. The engine-like geometry consists of a one-and-a-half stage (stator-rotor-stator) compressor in which the computed air flow is steady and inviscid. Both methods apply the same models to evaluate ice crystal dynamics, mass and heat transfer, and phase change along ice crystal trajectories. The impingement of the crystals on the blade surfaces is modeled assuming full deposition for comparison and validation purposes. Moreover, the effect of ice crystal diameter and sphericity variations on impinging mass flux and a

A smoothness-increasing accuracy conserving filtering approach to the regularization of discontinuities is presented for single domain spectral collocation approximations of hyperbolic conservation laws. The filter is based on convolution of a polynomial kernel that approximates a delta-sequence. The kernel combines a k th order smoothness with an arbitrary number of m zero moments. The zero moments ensure a m th order accurate approximation of the delta-sequence to the delta function. Through exact quadrature the projection error of the polynomial kernel on the spectral basis is ensured to be less than the moment error. A number of test cases on the advection equation, Burger's equation and Euler equations in 1D and 2D shown that the filter regularizes discontinuities while preserving high-order resolution.

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