A crucial component in the statistical simulation of a computationally expensive model is a good design of experiments. In this paper we compare the efficiency of the columnwise-pairwise (CP) and genetic algorithms for the optimization of Latin hypercubes (LH) for the purpose of sampling in statistical investigations. The performed experiments indicate, among other results, that CP methods are most efficient for small and medium size LH while an adopted genetic algorithm performs better for large LH.Two optimality criteria suggested in the literature are evaluated with respect to statistical properties and efficiency. The obtained results lead us to favor a criterion based on the physical analogy of minimization of forces between charged particles suggested in [1] over a 'maximin distance' criterion from [9].
The effect of grid resolution on large eddy simulation (LES) of wall-bounded turbulent flow is investigated. A channel flow simulation campaign involving systematic variation of the streamwise (∆x) and spanwise (∆z) grid resolution is used for this purpose. The main friction-velocity based Reynolds number investigated is 300. Near the walls, the grid cell size is determined by the frictional scaling, ∆x + and ∆z + , and strongly anisotropic cells, with first ∆y + ∼ 1, thus aiming for wallresolving LES. Results are compared to direct numerical simulations (DNS) and several quality measures are investigated, including the error in the predicted mean friction velocity and the error in cross-channel profiles of flow statistics. To reduce the total number of channel flow simulations, techniques from the framework of uncertainty quantification (UQ) are employed. In particular, generalized polynomial chaos expansion (gPCE) is used to create meta models for the errors over the allowed parameter ranges. The differing behavior of the different quality measures is demonstrated and analyzed. It is shown that friction velocity, and profiles of velocity and the Reynolds stress tensor, are most sensitive to ∆z + , while the error in the turbulent kinetic energy is mostly influenced by ∆x + . Recommendations for grid resolution requirements are given, together with quantification of the resulting predictive accuracy. The sensitivity of the results to subgrid-scale (SGS) model and varying Reynolds number is also investigated. All simulations are carried out with second-order accurate finite-volume based solver OpenFOAM. It is shown, the choice of numerical scheme for the convective term significantly influences the error portraits. It is emphasized that the proposed methodology, involving gPCE, can be applied to other modeling approaches, i.e. other numerical methods and choice of SGS model.
Abstract. In this paper, a methodology is presented for modelling underwater noise emissions from ships based on realistic vessel activity in the Baltic Sea region. This paper combines the Wittekind noise source model with the Ship Traffic Emission Assessment Model (STEAM) in order to produce regular updates for underwater noise from ships. This approach allows the construction of noise source maps, but requires parameters which are not commonly available from commercial ship technical databases. For this reason, alternative methods were necessary to fill in the required information. Most of the parameters needed contain information that is available during the STEAM model runs, but features describing propeller cavitation are not easily recovered for the world fleet. Baltic Sea ship activity data were used to generate noise source maps for commercial shipping. Container ships were recognized as the most significant source of underwater noise, and the significant potential for an increase in their contribution to future noise emissions was identified.
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