Day: September 4, 2016

Machine Learning in Fluid Dynamics (To be updated)

I have considerable interest in the application of machine learning techniques to (computational) fluid dynamics. I’ll collect the related information and enhance the following links.

News
Turbulence Modeling

Karthik Duraisamy, A Framework for Turbulence Modeling using Big Data

Anand Pratap Singh et al., Machine Learning-augmented Predictive Modeling of Turbulent Separated Flows over Airfoils

Computer Graphics

Lubor Ladicky et al., Data-driven Fluid Simulations using Regression Forests

  • Convolutional Network (ConvNet)

Jonathan Tompson et al., Accelerating Eulerian Fluid Simulation With Convolutional Networks

Impinging Jet part1

Jet flows can be classified in terms of

  • the flow conditions (laminar and turbulent)
  • the existence of objects: free jet and impinging jet
  • the differences of physical properties between a projected fluid and an ambient fluid: submerged jet and unsubmerged jet
  • the geometry of a nozzle: round jet and slot jet

and so on.

Free Jet

The following video visualizes the flow pattern of a submerged free jet (created by Bjarke Ove Andersen and Mathies Hjorth Jensen of Technical University of Denmark):

Flow Regions of Impinging Jet [1, 2]

impinging_jet_regions

  • Region Ⅰ is the region of flow establishment. It extends from the nozzle exit to the apex of the potential core. The so-called potential core is the central portion of the flow in which the velocity remains constant and equal to the velocity at the nozzle exit.
  • Region Ⅱ is a region of established flow in the direction of the jet beyond the apex of the potential core; it is characterized by a dissipation of the centerline jet velocity and by a spreading of the jet in the transverse direction.
  • Region Ⅲ is that region in which the jet is deflected from the axial direction.
  • Region Ⅳ is known as the wall jet region, where the directed flow increases in thickness as the boundary layer builds up along the solid surface.

– Gauntner et al. [1]

References

[1] J. W. Gauntner et al., SURVEY OF LITERATURE ON FLOW CHARACTERISTICS OF A SINGLE TURBULENT JET IMPINGING ON A FLAT’PLATE (accessed 2016-09-04)
[2] T. Dairay, DNS of a turbulent jet impinging on a heated wall (accessed 2016-09-04)
[3] N. ZUCKERMAN and N. LIOR, Jet Impingement Heat Transfer: Physics, Correlations, and Numerical Modeling (accessed 2016-09-04)
[4] Y. M. Chung and K. H. Luo, Unsteady Heat Transfer Analysis of an Impinging Jet (accessed 2016-09-04)
[5] ERCOFTAC Classic Database: Normally-Impinging Jet from a Circular Nozzle

Computational Aeroacoustics (CAA) part3

I’ve looked for some benchmark problems in the computational aeroacoustics (CAA) and found the eight problem categories that the BANC (Benchmark Problems for Airframe Noise Computations) workshop has addressed. This workshop is sponsored by the Aeroacoustics Technical Committee.

  • Inline Tandem Cylinders
  • Minimal 4-wheel Landing Gear (Rudimentary Landing Gear)
  • Partially-Dressed Cavity-Closed Nose Landing Gear (PDCC-NLG)
  • NASA Slat Noise Configuration (30P30N)

We can access the documents that describe the problem statement by clicking on the link at the bottom of each page:

I’ll try some problems using iconCFD and introduce my results.

Related Links