IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i8p3549-d1127765.html
   My bibliography  Save this article

Uncertainty Quantification Analysis of Exhaust Gas Plume in a Crosswind

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/8/3549/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/16/8/3549/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hyunjun Jang & Junho Suh, 2024. "Flow Characteristic Analysis of the Impeller Inlet Diameter in a Double-Suction Pump," Energies, MDPI, vol. 17(9), pages 1-18, April.
    2. Yinghua Chai & Yuansheng Lin & Qi Xiao & Chonghai Huang & Hanbing Ke & Bangming Li, 2024. "Numerical Simulation on Two-Phase Ejector with Non-Condensable Gas," Energies, MDPI, vol. 17(6), pages 1-19, March.
    3. 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.
    4. 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.
    5. Mingjun Liu & Zhenjiu Zhang & Zhuoming Liang & Haibing Xiao & Huanlong Chen & Xianqing Yang & Changxiao Shao, 2023. "New Insights into Flow for a Low-Bypass-Ratio Transonic Fan with Optimized Rotor," Energies, MDPI, vol. 16(21), pages 1-19, October.
    6. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Rocha, P. A. Costa & Rocha, H. H. Barbosa & Carneiro, F. O. Moura & da Silva, M. E. Vieira & de Andrade, C. Freitas, 2016. "A case study on the calibration of the k–ω SST (shear stress transport) turbulence model for small scale wind turbines designed with cambered and symmetrical airfoils," Energy, Elsevier, vol. 97(C), pages 144-150.
    2. Li, Jinxing & Liu, Tianyuan & Zhu, Guangya & Li, Yunzhu & Xie, Yonghui, 2023. "Uncertainty quantification and aerodynamic robust optimization of turbomachinery based on graph learning methods," Energy, Elsevier, vol. 273(C).
    3. Salehi, Saeed & Nilsson, Håkan, 2022. "Effects of uncertainties in positioning of PIV plane on validation of CFD results of a high-head Francis turbine model," Renewable Energy, Elsevier, vol. 193(C), pages 57-75.
    4. Wang, Xiaojing & Zou, Zhengping, 2019. "Uncertainty analysis of impact of geometric variations on turbine blade performance," Energy, Elsevier, vol. 176(C), pages 67-80.
    5. Daróczy, László & Janiga, Gábor & Thévenin, Dominique, 2016. "Analysis of the performance of a H-Darrieus rotor under uncertainty using Polynomial Chaos Expansion," Energy, Elsevier, vol. 113(C), pages 399-412.
    6. Wang, Haipeng & Zhang, Bo & Qiu, Qinggang & Xu, Xiang, 2017. "Flow control on the NREL S809 wind turbine airfoil using vortex generators," Energy, Elsevier, vol. 118(C), pages 1210-1221.
    7. Bai, Chi-Jeng & Wang, Wei-Cheng, 2016. "Review of computational and experimental approaches to analysis of aerodynamic performance in horizontal-axis wind turbines (HAWTs)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 63(C), pages 506-519.
    8. Kun, Wang & Fu, Chen & Jianyang, Yu & Yanping, Song, 2020. "Nested sparse-grid Stochastic Collocation Method for uncertainty quantification of blade stagger angle," Energy, Elsevier, vol. 201(C).
    9. Daróczy, László & Janiga, Gábor & Petrasch, Klaus & Webner, Michael & Thévenin, Dominique, 2015. "Comparative analysis of turbulence models for the aerodynamic simulation of H-Darrieus rotors," Energy, Elsevier, vol. 90(P1), pages 680-690.
    10. Xia, Zhiheng & Luo, Jiaqi & Liu, Feng, 2019. "Statistical evaluation of performance impact of flow variations for a transonic compressor rotor blade," Energy, Elsevier, vol. 189(C).
    11. Arteaga-López, Ernesto & Ángeles-Camacho, Cesar & Bañuelos-Ruedas, Francisco, 2019. "Advanced methodology for feasibility studies on building-mounted wind turbines installation in urban environment: Applying CFD analysis," Energy, Elsevier, vol. 167(C), pages 181-188.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:16:y:2023:i:8:p:3549-:d:1127765. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.