Wavelet adaptive proper orthogonal decomposition for large-scale flow data

HIGHLIGHTS

  • who: Philipp Krah from the (UNIVERSITY) have published the research work: Wavelet adaptive proper orthogonal decomposition for large-scale flow data, in the Journal: (JOURNAL)
  • what: The authors propose a wavelet-based adaptive version of the POD (the wPOD) to overcome this limitation. Using a synthetic academic test case the authors compare the algorithm with the randomized singular value decomposition. The authors demonstrate the ability of the method analyzing data of a two-dimensional wake flow and a three-dimensional flow generated by a flapping insect computed with direct numerical simulation. The authors aim at . . .

     

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