Publications

@article{nokey,

title = {Analysis of the Loss Production Mechanism Due to Cavity–Main Flow Interaction in a Low-Pressure Turbine Stage},

author = {Dario Barsi, Davide Lengani, Daniele Simoni, Giulio Venturino, Francesco Bertini, Matteo Giovannini, Filippo Rubechini},

url = {https://asmedigitalcollection.asme.org/turbomachinery/article/144/9/091004/1134931/Analysis-of-the-Loss-Production-Mechanism-Due-to},

doi = {10.1115/1.4053745},

year  = {2022},

date = {2022-09-01},

journal = {Journal of Turbomachinery},

volume = {144},

number = {9},

pages = {091004},

abstract = {In the present work, URANS simulations are presented to describe the unsteady interaction process between the flow ingested/ejected from a cavity system and the main flow evolving into a low-pressure turbine stage. Particular care is posed on the analysis of the loss generation mechanisms acting outside the stator row and in the rear part of the axial gap separating the cavity flow ejection section and the leading edge plane of the downstream rotor row. The simulated geometry reproduces a typical engine cavity configuration, with upstream and downstream rotor rows reproduced by means of moving bars. Experimental results have been used to validate the simulations. These experimental data cannot explain and quantify alone the overall interaction process between the cavity flows and the main flow. The results of a simulation made by removing the domain of the cavity have been employed in order to better highlight and quantify the effects due to main flow and cavity flows interaction on total pressure loss. A deep inspection of the loss amount along the axial direction makes evident that losses generated in the vane row are basically increased prior to entering into the downstream rotor bars, due to cavity main flow interaction.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Towards the development of an advanced wind turbine rotor design tool integrating full CFD and FEM},

author = {Cozzi L, Bellucci J, Giovannini M, Papi F, Bianchini A},

doi = {10.1088/1742-6596/2265/4/042050},

year  = {2022},

date = {2022-06-01},

journal = {Journal of Physics: Conference Series: Torque 2022},

number = {Conf. Ser. 2265 042050},

abstract = {Large, highly flexible wind turbines of the new generation will make designers face un-precedent challenges, mainly connected to their huge dimensions. To tackle these challenges, it is commonly acknowledged that design tools must evolve in the direction of both improving their accuracy and turning into holistic, multiphysics tools. Furthermore, the wind turbine industry is reaching a high level of maturity, and ever more accurate and reliable design tools are required to further optimise these machines. Within this framework, the study shows the development of an integrated platform for blade design integrating 3D CFD flow simulations and 3D-FEM structural analysis. Artificial intelligence techniques are applied to develop an optimization procedure based on the proposed tool. The potential of the new platform has been tested on the well-known test case of the MEXICO rotor, for which an optimization of the blade design has been carried out. Exploring a design space sampled with 2000 CFD and FEM computations, increases in blade torque have been obtained at each of the three tip-speed ratios (TSR) investigated, ranging from 6% at the nominal TSR to 14% at the lowest one, while stresses on the blade are kept almost unaltered.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{1023,

title = {Reducing Secondary Flow Losses in Low-Pressure Turbines: The Snaked Blade},

author = {Matteo Giovannini and Filippo Rubechini and Michele Marconcini and Andrea Arnone and Francesco Bertini},

editor = {MDPI},

url = {https://www.mdpi.com/2504-186X/4/3/28/htm},

doi = {10.3390/ijtpp4030028},

year  = {2019},

date = {2019-08-21},

journal = {Int. J. Turbomachinery Propulsion and Power},

volume = {4},

number = {3},

address = {Lausanne (CH), 8-12 April 2019},

abstract = {This paper presents an innovative design for reducing the impact of secondary flows on the aerodynamics of low-pressure turbine (LPT) stages. Starting from a state-of-the-art LPT stage, a local reshaping of the stator blade was introduced in the end-wall region in order to oppose the flow turning deviation. This resulted in an optimal stator shape, able to provide a more uniform exit flow angle. The detailed comparison between the baseline stator and the redesigned one allowed for pointing out that the rotor row performance increased thanks to the more uniform inlet flow, while the stator losses were not significantly affected. Moreover, it was possible to derive some design rules and to devise a general blade shape, named ‘snaked’, able to ensure such results. This generalization translated in an effective parametric description of the ‘snaked’ shape, in which few parameters are sufficient to describe the optimal shape modification starting from a conventional design. The “snaked” blade concept and its design have been patented by Avio Aero. The stator redesign was then applied to a whole LPT module in order to evaluate the potential benefit of the ‘snaked’ design on the overall turbine performance. Finally, the design was validated by means of an experimental campaign concerning the stator blade. The spanwise distributions of the flow angle and pressure loss coefficient at the stator exit proved the effectiveness of the redesign in providing a more uniform flow to the successive row, while preserving the original stator losses.},

note = {This paper is an extended version of the paper published in Proceedings of the European Turbomachinery Conference, ETC13, Lausanne, Switzerland, 8–12 April 2019; Paper No. 338},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{1020,

title = {Capturing Radial Mixing in Axial Compressors With Computational Fluid Dynamics},

author = {Lorenzo Cozzi and Filippo Rubechini and Matteo Giovannini and Michele Marconcini and Andrea Arnone and Andrea Schneider and Pio Astrua},

url = {https://asmedigitalcollection.asme.org/turbomachinery/article/141/3/031012/475779/Capturing-Radial-Mixing-in-Axial-Compressors-With},

doi = {10.1115/1.4041738},

isbn = {0889-504X},

year  = {2019},

date = {2019-01-21},

journal = {ASME Journal of Turbomachinery},

volume = {141},

number = {3},

pages = {9},

abstract = {The current industrial standard for numerical simulations of axial compressors is the steady Reynolds-averaged Navier–Stokes (RANS) approach. Besides the well-known limitations of mixing planes, namely their inherent inability to capture the potential interaction and the wakes from the upstream blades, there is another flow feature which is lost, and which is a major accountable for the radial mixing: the transport of streamwise vorticity. Streamwise vorticity is generated for various reasons, mainly associated with secondary and tip-clearance flows. A strong link exists between the strain field associated with the vortices and the mixing augmentation: the strain field increases both the area available for mixing and the local gradients in fluid properties, which provide the driving potential for the mixing. In the rear compressor stages, due to high clearances and low aspect ratios, only accounting for the development of secondary and clearance flow structures, it is possible to properly predict the spanwise mixing. In this work, the results of steady and unsteady simulations on a heavy-duty axial compressor are compared with experimental data. Adopting an unsteady framework, the enhanced mixing in the rear stages is properly captured, in remarkable agreement with experimental distributions. On the contrary, steady analyses strongly underestimate the radial transport. It is inferred that the streamwise vorticity associated with clearance flows is a major driver of radial mixing, and restraining it by pitch-averaging the flow at mixing planes is the reason why the steady approach cannot predict the radial transport in the rear part of the compressor.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{986,

title = {Support Vector Machine Classification Applied to the Parametric Design of Centrifugal Pumps},

author = {Elisa Riccietti and Juri Bellucci and Matteo Checcucci and Michele Marconcini and Andrea Arnone},

url = {http://www.tandfonline.com/doi/full/10.1080/0305215X.2017.1391801},

doi = {dx.doi.org/10.1080/0305215X.2017.1391801},

issn = {1029-0273},

year  = {2018},

date = {2018-11-01},

journal = {Engineering Optimization},

volume = {50},

pages = {1304-1324},

abstract = {In this article the parametric design of centrifugal pumps is addressed. To deal with thisproblem, an approach based on coupling expensive Computational Fluid Dynamics (CFD) computations with Artificial Neural Networks (ANN) as a regression meta-model had been proposed in Checcucci et al. (2015), "A Novel Approach to Parametric Design of Centrifugal Pumps for a Wide Range of Specific Speeds."; ISAIF 12 paper n.121. Here, the previously proposed approach is improved by including also the use of Support Vector Machines (SVM) as a classification tool. The classification process is aimed at identifying parameters combinations corresponding to manufacturable machines among the much larger number of unfeasible ones. A binary classification problem on an unbalanced dataset has to be faced. Numerical tests show that the addition of this classification tool helps to considerably reduce the number of CFD computations required for the design, providing large savings in computational time.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{1019,

title = {Secondary Flows in Low-Pressure Turbines Cascades: Numerical and Experimental Investigation of the Impact of the Inner Part of the Boundary Layer},

author = {Matteo Giovannini and Filippo Rubechini and Michele Marconcini and Daniele Simoni and Vianney Yepmo and Francesco Bertini},

url = {http://turbomachinery.asmedigitalcollection.asme.org/article.aspx?articleid=2702055&resultClick=3},

doi = {10.1115/1.4041378},

issn = {0889-504X},

year  = {2018},

date = {2018-10-01},

journal = {ASME Journal of Turbomachinery},

volume = {140},

number = {11},

pages = {111002 (12 pages)},

abstract = {Due to the low level of profile losses reached in low-pressure turbines (LPT) for turbofan applications, a renewed interest is devoted to other sources of loss, e.g., secondary losses. At the same time, the adoption of high-lift profiles has reinforced the importance of these losses. A great attention, therefore, is dedicated to reliable prediction methods and to the understanding of the mechanisms that drive the secondary flows. In this context, a numerical and experimental campaign on a state-of-the-art LPT cascade was carried out focusing on the impact of different inlet boundary layer (BL) profiles. First of all, detailed Reynolds Averaged Navier-Stokes (RANS) analyzes were carried out in order to establish dependable guidelines for the computational setup. Such analyzes also underlined the importance of the shape of the inlet BL very close to the endwall, suggesting tight requirements for the characterization of the experimental environment. The impact of the inlet BL on the secondary flow was experimentally investigated by varying the inlet profile very close to the endwall as well as on the external part of the BL. The effects on the cascade performance were evaluated by measuring the span-wise distributions of flow angle and total pressure losses. For all the inlet conditions, comparisons between Computational Fluid Dynamics (CFD) and experimental results are discussed. Besides providing guidelines for a proper numerical and experimental setup, the present paper underlines the importance of a detailed characterization of the inlet BL for an accurate assessment of the secondary flows.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}