The present paper addresses a non-deterministic CFD simulation of a high-pressure compressor (HPC) stage. The investigation focuses on the determination of the influence of the manufacturing scatter of compressor blades on the aerodynamic performance of the analyzed HPC stage. A set of 150 blades was scanned using an optical 3D digitizer to obtain a three-dimensional point cloud representing the surface of the blades. Classical profile parameters were identified at several sections of constant spanwise coordinate. The radial stacking of these parameters forms a parameter vector that constructs the airfoil model of each scanned blade. Consequently these parameters were used to define the geometric variability of the entire measured blade set. A statistical analysis of the distribution of these parameters defines the input data of the probabilistic 3D CFD simulation. The Monte-Carlo method is used to identify the scatter of the performance values of the HPC stage and their sensitivity to the geometric variability of profile parameters.

This paper introduces an approach for considering manufacturing variability leading to a nonaxisymmetric blading in the computational fluid dynamics simulation of a high-pressure compressor stage. A set of 150 rotor blades from a high-pressure compressor stage was 3D scanned in order to obtain the manufacturing variability. The obtained point clouds were parameterized using a parametric blade model, which uses typical profile parameters to translate the geometric variability into a numerical model. Probabilistic simulation methods allow for the generation of a sampled set of blades that statistically corresponds to the measured one. This technique was applied to generate 4000 sampled blades in order to investigate the influence of a nonaxisymmetric blading. It was found that the aerodynamic performance is considerably influenced by a variation of the passage cross section. Nevertheless, this influence decreases with an increasing number of independently sampled blades and, thus, independently shaped passage cross sections. Due to its more accurate consideration of the geometric variability, the presented methodology allows for a more realistic performance analysis of a high-pressure compressor stage.

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Carica papaya L. does not contain wood, according to the botanical definition of wood as lignified secondary xylem. Despite its parenchymatous secondary xylem, these plants are able to grow up to 10-m high. This is surprising, as wooden structural elements are the ubiquitous strategy for supporting height growth in plants. Proposed possible alternative principles to explain the compensation for lack of wood in C. papaya are turgor pressure of the parenchyma, lignified phloem fibres in the bark, or a combination of the two. Interestingly, lignified tissue comprises only 5-8% of the entire stem mass. Furthermore, the phloem fibres do not form a compact tube enclosing the xylem, but instead form a mesh tubular structure. To investigate the mechanism of papaya's unusually high mechanical strength, a set of mechanical measurements were undertaken on whole stems and tissue sections of secondary phloem and xylem. The structural Young's modulus of mature stems reached 2.5 GPa. Since this is low compared to woody plants, the flexural rigidity of papaya stem construction may mainly be based on a higher second moment of inertia. Additionally, stem turgor pressure was determined indirectly by immersing specimens in sucrose solutions of different osmolalities, followed by mechanical tests; turgor pressure was between 0.82 and 1.25 MPa, indicating that turgor is essential for flexural rigidity of the entire stem.

The present paper introduces a novel approach for considering manufacturing variability in the numerical simulation of a multistage high-pressure compressor (HPC). The manufacturing process is investigated by analyzing three of a total of ten rotor rows. Therefore, ¡50 blades of each of the three rows were 3D scanned to obtain surface meshes of real blades. The deviation of a scanned blade to the design intent is quantified by a vector of 14 geometric parameters. Interpolating the statistical properties of these parameters provides the manufacturing scatter for all ten rotor rows expressed by 140 probability density functions. The probabilistic simulation utilizes the parametric scatter information for generating 200 virtual compressors. The CED analysis provides the performance of these compressors by calculating speed lines. Postprocessing methods are applied to statistically analyze the obtained results. It was found that the global performance parameters show a significantly wider scatter range for higher back pressure levels. The correlation coefficient and the coefficient of importance are utilized to identify the sensitivity of the results to the geometric parameters. It turned out that the sensitivities strongly shift for different operating points. While the leading edge geometry of all rotor rows dominantly influences the overall performance at maximum efficiency, the camber line parameters of the front stages become more important for higher back pressure levels. The analysis of the individual stage perfotmance confirms the determining importance of the front stages-especially for highly throttled operating conditions. This leads to conclusions regarding the robustness of the overall HPC, which is principally determined by the efficiency and pressure rise of the front stages.