Conjugate Heat Transfer Simulations over ice characterized rough surfaces

ORAL

Abstract

Accurate modeling of ice accretion is important for the safe and efficient design of aircraft and propulsion systems. Heat transfer predictions obtained from the fluid flow solvers are used as input in ice accretion codes. In glaze ice conditions, the freezing rates and resulting ice shapes are highly sensitive to the input values of the heat-transfer coefficient. An accurate prediction of heat transfer on iced airfoils is crucial for correctly predicting the ice accretion process. In this work, we present wall-modeled large-eddy simulations of conjugate heat transfer (CHT) over a developing boundary layer on a surface characterized by ice roughness. Results from these simulations show that WMLES with CHT can represent temperature profiles and heat fluxes on surfaces characterized by ice roughness. The smooth to rough transition on the iced surface leads to a high increase in heat-transfer. Distributions of friction coefficient and Stanton number show that the Reynolds Analogy is less accurate with increasing roughness height. For surfaces with low conductivity, overall heat transfer is reduced. Additionally, the temperature distribution becomes more heterogeneous. These results can be used to further improve heat-transfer models used for ice accretion predictions.

*This investigation was funded by The Boeing Co. under grant \#2023-UI-PA-070, NASA's Transformational Tools and Technologies (T3) Project, and the DoD SMART Fellowship. This research used resources of the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC05-00OR22725.

Presenters

  • Federico Zabaleta

    • Stanford University

Authors

  • Federico Zabaleta

    • Stanford University
  • Brett Bornhoft

    • Air Force Research Laboratory
    • Stanford University
  • Suhas Jain

    • Woodruff School of Mechanical Engineering, Georgia Institute of Technology, USA. Center for Turbulence Research, Stanford Universty, USA
    • Georgia Institute of Technology, Flow Physics and Computational Sciences Lab
    • Woodruff School of Mechanical Engineering, Georgia Tech
    • Flow Physics and Computational Science Lab, Georgia Institute of Technology, Atlanta, Georgia, 30332, USA
    • Woodruff School of Mechanical Engineering, Georgia Institute of Technology; Center for Turbulence Research, Stanford University
    • George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
  • Sanjeeb T Bose

    • Cadence Design Systems, Inc and Institute for Computational and Mathematical Engineering, Stanford University
    • Cascade Technologies, Inc.
  • Parviz Moin

    • Center for Turbulence Research, Stanford University
    • Stanford University