Exploitable results Report on code development (D19) Within the EU-funded 5FP project, Leading Edge, Helsinki University of Technology (HUT) has implemented an Explicit Algebraic Reynolds Stress Model in its Reynolds-Averaged Navier-Stokes equation solver FINFLO. The EARSM is linked with the k-omega turbulence model. Two test cases are presented, the flow over a flate plate and the flow in a rectangular duct. Finally a comparison is made between the three turbulence models, k-epsilon, k-omega and the EARSM on the calculation of the flow patterns of a highly skewed propeller in open water conditions at model scale. While the k-omega model and the EARSM gives satifactory results, it is found that the k-epsilon model gives more accurate results concerning both the torque and the thrust coefficients compared with experimental values. State-of-the-art on water quality and cavitation inception (D6) State-of-the-art on water quality and cavitation inception (D6): A guideline is given by this deliverable for the performance of cavitation inception experiments within the Leading Edge Project. This guideline is based on a state-of-the-art survey and is in line with the report of the Committee on Water Quality and Cavitation to the 23rd International Towing Tank Conference. Following these guidelines will lead to comparable model test results for cavitation inception at different model basins involved in Leading Edge. To achieve this, the deliverable deals with the definition of cavitation inception, the handling of water quality effects as well as viscosity effects on cavitation inception. PIV performance in a towing tank (D5) The underwater 3-D PIV system developed for Leading Edge project has been described. The deliverable describes the system characteristics and a list of applications. The system was delivered by an European company DANTECThis system is available for measurements in maritime facilities on a rental basis. Enhanced volume grid methods (D2-2) Grid generation is a significant part of a CFD application, and much of the time is spent on grid generation. Moreover, the quality and the density of the grid are important parameters regarding the reliability of the final CFD results. - A system for grid generation can be evaluated from its ability to: - Model the shape of a complex geometry - Make grids elements of good quality - Ease of grid modification and grid refinement - Make grids that perform well in the CFD solver A grid can roughly be divided into two types, structured and unstructured. In a structured grid, every point has the same number of neighbouring points while in an unstructured grid the number of neighbours will vary. Finite element methods generally use unstructured grids. These methods take no particular advantage in using structured grids. An unstructured grid can model very complex geometrical shapes and it is easy to use local grid refinement to achieve a denser grid. The storage of the grid, however, is not very effective compared to a structured grid. A structured grid is able to take advantage of factored and directional solvers. They are normally used in computations utilizing finite differences. In general structured grids are less computation intensive than the unstructured ones. It is not necessary to store the topology of the grid points since this is obvious from the structure. On the other hand, complex geometries cannot always be represented using one mapping from a rectangular computational domain. The resulting grid could be very skewed. When the geometry gets too complex for a single structured grid, a multiblock approach may be used. The physical region is broken up into pieces or blocks that have a simple mapping from a rectangular grid. Several regular blocks are fitted together with some degree of continuity. Often adjacent blocks are required to have identical grid nodes at the common boundary, and the grid spacing should vary gradually over a block boundary. Orthogonality of the grid towards the boundary can also be desired. Block structured grids provide additional flexibility regarding representation of a complex geometry while maintaining simple storage of grid points for most points. The block creation is often a manual process while the grid generation once the blocks are defined, is easier to automate. Common for all types of grids is that high density of the grid points gives more accuracy, but the computations using this grid will take longer. Moreover, large variations in the grid density can lead to inaccurate results or instability. Non- orthogonality or skew elements in the physical grid increase the truncation error. Especially, at boundaries, skewed elements should be avoided. Propellers have a complex geometrical shape. In leading edge, we are considering propellers of three different types, a conventional propeller, a highly skewed propeller, and an end plate propeller. All propellers are four bladed. Already the conventional propeller has a complex shape and the two others even more so. There is also a strong twisting of the blade central plane. In Leading Edge, a number of partners are making grids for one or more of the benchmark propellers. A general conclusion from all grid generations in the project is that a multi grid approach seems to meet the requirements of representing a complex propeller geometry and at the same time maintain a good grid quality. Enhanced surface grid methods (D2-1) Surface gridding for the three benchmark propellers, the conventional one, the skewed one and the tip plated one. Several partners have been doing gridding of these propellers, both in house and commercial software is used. Some software development has been performed. Improved turbulence model and investigation of transition (D11-2) A transition model has been established and tested for a prolate spheroid and a conventional propeller. The calculations for the propeller show that the model captures centrifugal forcing of the laminar boundary layer. Transition has impact on both KT and KQ by increasing the former and reducing the latter Searching for OpenAIRE data... There was an error trying to search data from OpenAIRE No results available
