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Research

Dr Sergio Campobasso

Senior Lecturer

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  1. Published

    Low-speed preconditioning for strongly coupled integration of Reynolds-averaged Navier–Stokes equations and two-equation turbulence models

    Campobasso, M. S., Yan, M., Bonfiglioli, A., Gigante, F. A., Ferrari, L., Balduzzi, F. & Bianchini, A., 06/2018, In: Aerospace Science and Technology. 77, p. 286-298 13 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  2. Published

    Compressible Navier-Stokes Analysis of Floating Wind Turbine Rotor Aerodynamics

    Campobasso, M. S., Sanvito, A. G., Drofelnik, J., Jackson, A., Zhou, Y., Xiao, Q. & Croce, A., 4/11/2018, ASME 2018 1st International Offshore Wind Technical Conference: 4-7 November 2018, San Francisco, California, USA. The American Society of Mechanical Engineers, 12 p. IOWTC2018-1059

    Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

  3. Published

    Rapid Estimate of Wind Turbine Energy Loss due to Blade Leading Edge Delamination Using Artificial Neural Networks

    Campobasso, S., Cavazzini, A. & Minisci, E., 26/06/2020, In: Journal of Turbomachinery. 142, 7, 11 p., 071002.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  4. Published

    Experimentally validated three-dimensional computational aerodynamics of wind turbine blade sections featuring leading edge erosion cavities

    Campobasso, S., Castorrini, A., Cappugi, L. & Bonfiglioli, A., 31/01/2022, In: Wind Energy. 25, 1, p. 168-189 22 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  5. Published

    Probabilistic analysis of wind turbine performance degradation due to blade erosion accounting for uncertainty of damage geometry

    Campobasso, S., Castorrini, A., Ortolani, A. & Minisci, E., 31/05/2023, In: Renewable and Sustainable Energy Reviews. 178, 16 p., 113254.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  6. Published

    Machine learning-enabled prediction of wind turbine energy yield losses due to general blade leading edge erosion

    Cappugi, L., Castorrini, A., Bonfiglioli, A., Minisci, E. & Campobasso, S., 1/10/2021, In: Energy Conversion and Management. 245, 17 p., 114567.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  7. Published

    Assessing wind turbine energy losses due to blade leading edge erosion cavities with parametric CAD and 3D CFD

    Castorrini, A., Cappugi, L., Bonfiglioli, A. & Campobasso, S., 28/09/2020, In: Journal of Physics: Conference Series. 1618, 11 p., 052015.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  8. Published

    Assessing the progression of wind turbine energy yield losses due to blade erosion by resolving damage geometries from lab tests and field observations

    Castorrini, A., Ortolani, A. & Campobasso, M. S., 31/12/2023, In: Renewable Energy. 218, 119256.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  9. E-pub ahead of print

    Impact of meteorological data factors and material characterization method on the predictions of leading edge erosion of wind turbine blades

    Castorrini, A., Barnabei, V. F., Domenech, L., Šakalytė, A., Sánchez, F. & Campobasso, M. S., 30/06/2024, In: Renewable Energy. 227, 120549.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  10. Published

    Opensource machine learning metamodels for assessing blade performance impairment due to general leading edge degradation

    Castorrini, A., Ortolani, A., Minisci, E. & Campobasso, M. S., 1/06/2024, In: Journal of Physics: Conference Series. 2767, 5, 10 p., 052055.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

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