Repairing occluded data for a Mach 0.6 jet via data fusion

Christopher J. Ruscher, John Francis Dannenhoffer, Mark N Glauser

Research output: Contribution to journalArticle

5 Scopus citations

Abstract

Particle image velocimetry and near-field pressure were collected for an axisymmetric, Mach 0.6 jet. Some of the pressure sensors were in between the laser sheet and camera, causing occlusions in the particle image velocimetry data. Using ideas from the data fusion community, these occluded regions could be repaired. In this case, the particle image velocimetry data could be fused with the knowledge that the velocity field was symmetric about the center axis using a new technique called fused proper orthogonal decomposition, which is inspired by gappy proper orthogonal decomposition and image/wavelet fusion. Using this technique, 90% of the missing data could be estimated with 10% error.

Original languageEnglish (US)
Pages (from-to)255-264
Number of pages10
JournalAIAA Journal
Volume55
Issue number1
DOIs
StatePublished - 2017

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ASJC Scopus subject areas

  • Aerospace Engineering

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