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Uncertainty Quantification Analysis of Exhaust Gas Plume in a Crosswind

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  • Carlo Cravero

    (Dipartimento di Ingegneria Meccanica, Energetica, Gestionale e dei Trasporti (DIME), Università degli Studi di Genova, Via Montallegro 1, 16145 Genoa, Italy)

  • Davide De Domenico

    (Dipartimento di Ingegneria Meccanica, Energetica, Gestionale e dei Trasporti (DIME), Università degli Studi di Genova, Via Montallegro 1, 16145 Genoa, Italy)

  • Davide Marsano

    (Dipartimento di Ingegneria Meccanica, Energetica, Gestionale e dei Trasporti (DIME), Università degli Studi di Genova, Via Montallegro 1, 16145 Genoa, Italy)

Abstract

The design of naval exhaust funnels has to take into account the interaction between the hot gases and topside structures, which usually includes critical electronic devices. Being able to predict the propagation trajectory, shape and temperature distribution of an exhaust gas plume is highly strategic in different industrial sectors. The propagation of a stack plume can be affected by different uncertainty factors, such as those related to the wind flow and gas flow conditions at the funnel exit. The constant growth of computational resources has allowed simulations to gain a key role in the early design phase. However, it is still difficult to model all the aspects of real physical problems in actual applications and, therefore, to completely rely upon the quantitative results of numerical simulations. One of the most important aspects is related to input variable uncertainty, which can significantly affect the simulation result. With this aim, the discipline of Uncertainty Quantification provides several methods to evaluate uncertainty propagation in numerical simulations. In this paper, UQ procedures are applied to a CFD simulation of a single plume in a crossflow. The authors test the influence of the uncertainty propagation of the chimney exit velocity and the main flow angle on the plume flow development. Two different UQ methods are applied to the analysis: the surrogate-based approach and the polynomial chaos expansion method. A comparison of the two methods is performed in order to find their pros and cons, focusing on the different and detailed quantities of interest.

Suggested Citation

  • Carlo Cravero & Davide De Domenico & Davide Marsano, 2023. "Uncertainty Quantification Analysis of Exhaust Gas Plume in a Crosswind," Energies, MDPI, vol. 16(8), pages 1-22, April.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:8:p:3549-:d:1127765
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    References listed on IDEAS

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    1. Liu, ZhiYi & Wang, XiaoDong & Kang, Shun, 2014. "Stochastic performance evaluation of horizontal axis wind turbine blades using non-deterministic CFD simulations," Energy, Elsevier, vol. 73(C), pages 126-136.
    2. Shubin Bai & Yuanqiao Wen & Li He & Yiming Liu & Yan Zhang & Qi Yu & Weichun Ma, 2020. "Single-Vessel Plume Dispersion Simulation: Method and a Case Study Using CALPUFF in the Yantian Port Area, Shenzhen (China)," IJERPH, MDPI, vol. 17(21), pages 1-29, October.
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    Cited by:

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    2. Michał Frant & Stanisław Kachel & Wojciech Maślanka, 2023. "Gust Modeling with State-of-the-Art Computational Fluid Dynamics (CFD) Software and Its Influence on the Aerodynamic Characteristics of an Unmanned Aerial Vehicle," Energies, MDPI, vol. 16(19), pages 1-19, September.
    3. Alberto Savino & Andrea Ferreri & Alex Zanotti, 2024. "Validation of a Mid-Fidelity Numerical Approach for Wind Turbine Aerodynamics Characterization," Energies, MDPI, vol. 17(7), pages 1-23, March.
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    5. Maria Hurnik & Piotr Ciuman & Zbigniew Popiolek, 2024. "Eddy–Viscosity Reynolds-Averaged Navier–Stokes Modeling of Air Distribution in a Sidewall Jet Supplied into a Room," Energies, MDPI, vol. 17(5), pages 1-19, March.

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