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As the next generation of turbomachinery components becomes more sensitive to instrumentation intrusiveness, a reduction of the number of measurement devices required for the evaluation of performance is a possible and cost-effective way to mitigate the arising of non-mastered experimental errors. A first approach to a data assimilation methodology based on Bayesian inference is developed with the aim of reducing the instrumentation effort. A numerical model is employed to provide an initial belief of the flow, that is then updated based on experimental observations, using an ensemble Kalman filter algorithm for inverse problems. Validation of the algorithm is achieved with the usage of experimental measurements not used in the data assimilation process. The methodology is tested for a low aspect ratio axial compressor stage, showing a good prediction of the corrected compressor map, as well as a promising prediction of the inter-row radial pressure distribution and 2D flow field.

Purpose The present paper aims at evaluating the lattice Boltzmann method (LBM) on a high-subsonic high-pressure compressor stage at nominal regime. Design/methodology/approach The studied configuration corresponds to the H25 compressor operated in a closed-loop test rig at the von Karman Institute. Several operating points are simulated with LBM for two grids of successive refinements. A detailed analysis is performed on the time-averaged flow predicted by LBM, using a comparison with experimental and existing RANS data. Findings The finest grid is found to correctly predict the mean flow across the machine, as well as the influence of the rotor tip gap size. Going beyond time-averaged data, some flow analysis is performed to show the relevance of such a high-fidelity method applied to a compressor configuration. In particular, vortical structures and their evolution with the operating points are clearly highlighted. Spectral analyses finally hint at a proper prediction of tonal and broadband contents by LBM. Originality/value The application of LBM to high-speed turbomachinery flows is very recent. This paper validates one of the first LBM simulations of a high-subsonic high-pressure compressor stage.

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The quest for greener, more efficient aircraft engines is the main driver for the development of innovative compression system designs. Reduced order design tools rely nevertheless on semi-empirical loss models, whose validity range is often not net or in general not verified. The present work aims at defining a set of loss correlations, which could readily be employed in the analysis and design process of modern transonic axial compressors. In Part I, various loss correlations were deeply described and, in some cases, updated to enhance both their generality and their prediction capability. In Part II, the effectiveness of both original and updated models will be tested for one specific low aspect ratio axial compressor stage. Experimental and numerical data will be used at such extent.