Scaling and statistics in three-dimensional compressible turbulence

ORAL

Abstract

The scaling and statistical properties of three-dimensional (3D) compressible turbulence are studied using high resolution numerical simulation. The two-point statistics of solenoidal component of velocity field are found to be no significant difference from those in the incompressible turbulence, while scaling exponents for compressive component of velocity structure functions are saturated at high orders, similar to one-dimensional (1D) Burgers turbulence. Both numerical results and theoretical analysis based on the probability density function (PDF) equation reveal that the power law exponent in the PDF of 3D velocity divergence is different from that in the Burgers turbulence. The effect of various terms in the dynamic equation on PDF will also be presented.

–

Authors

  • Jianchun Wang

    • State Key Laboratory for Turbulence and Complex System, College of Engineering, Peking University, China
    • SKLTCS and CAPT, College of Engineering, Peking University, China
    • Center for Applied Physics and Technology and SKLTCS, College of Engineering, Peking University, Beijing, China

  • Xiantu He

    • SKLTCS and CAPT, College of Engineering, Peking University, China

  • Yipeng Shi

    • State Key Laboratory for Turbulence and Complex System, College of Engineering, Peking University, China
    • SKLTCS and CAPT, College of Engineering, Peking University, China

  • Lian-Ping Wang

    • University of Delaware
    • Department of Mechanical Engineering, University of Delaware, Newark, DE 19716, USA

  • Zuoli Xiao

    • State Key Laboratory for Turbulence and Complex System, College of Engineering, Peking University, China
    • SKLTCS and CAPT, College of Engineering, Peking University, China

  • Shiyi Chen

    • State Key Laboratory for Turbulence and Complex System, College of Engineering, Peking University, China
    • SKLTCS and CAPT, College of Engineering, Peking University, China
    • Center for Applied Physics and Technology and SKLTCS, College of Engineering, Peking University, Beijing, China