A robust virtual-camera 3D shape reconstruction of deforming bubbles/droplets with additional physical constraints. (November 2019)

• Record Type: Journal Article
• Authors: Masuk, Ashik Ullah Mohammad; Salibindla, Ashwanth; Ni, Rui
• Is Part Of: International journal of multiphase flow. Volume 120(2019)
• Publication Date: 2019-11
• Subjects: Bubbly flow -- Non-affine deformation -- 3D shape reconstruction -- Visual hull -- Virtual camera; Multiphase flow -- Periodicals; Écoulement polyphasique -- Périodiques; Multiphase flow; Periodicals; 620.1064
• DOI: 10.1016/j.ijmultiphaseflow.2019.103088
• Languages: English
• ISSNs: 0301-9322

Abstract

Highlights: A robust virtual-camera method is introduced to reconstruct the 3D geometry of the non-affine deformation of bubbles or droplets in strong turbulence. The method provides a framework to incorporate an additional physical constraint into the images of virtual cameras to reduce the uncertainty of the limited-angle reconstruction. The reconstruction uncertainty of each bubble is quantified based on its aspect ratio and orientation. Abstract: Bubbles and droplets in strong turbulence exhibit non-affine deformation, especially near a breakup event when the strong necking and interfacial instability begin to play roles. The virtual-camera (VC) method was designed and implemented to mitigate the limited-angle reconstruction problem for complex bubble/droplet geometries. The VC method incorporates the additional physical constraint of minimum surface curvature into reconstruction. This framework helps to reduce the reconstruction uncertainty for experiments studying multiphase flows that use a limited number of cameras, non-ideal camera positions, or the combination of both. The method was tested with three synthetic geometries– sphere, ellipsoid, and dumbbell–that represent the undeformed, gently-deformed, and severely-deformed bubbles. In addition, a DNS dataset of bubbles with a 2% void fraction in turbulent channel flow was also utilized to generate a synthetic dataset for tests, and the volume overestimation was found to decrease from over 20% to about 10% after implementing the VC method. Finally, the method was applied to the experimental dataset of bubble-turbulence interaction, and the result shows over 20% improvement in volume estimation. An indirect uncertainty quantification that relies on the bubble aspect ratio and orientation has also been developed to estimate the bubble reconstruction uncertainty in each frame. This allows a more selective postprocessing step to obtain the statistics of deformation and breakup based on the quality of reconstruction.