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Jun Chen

Researcher at Purdue University

Publications -  73
Citations -  1806

Jun Chen is an academic researcher from Purdue University. The author has contributed to research in topics: Turbulence & Holography. The author has an hindex of 24, co-authored 70 publications receiving 1475 citations. Previous affiliations of Jun Chen include Johns Hopkins University & Indiana University – Purdue University Indianapolis.

Papers
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Cavopulmonary assist for the univentricular Fontan circulation: von Kármán viscous impeller pump.

TL;DR: A single viscous impeller pump stabilizes and augments cavopulmonary flow in 4 directions, in the desired pressure range, without venous pathway obstruction.
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Experimental statistics of droplet trajectory and air flow during aerodynamic fragmentation of liquid drops

TL;DR: In this paper, the deformation and fragmentation of single ethyl alcohol drops injected into a continuous air-jet is experimentally investigated, where high speed shadowgraphy coupled with image contour recognition is used to record the instantaneous droplet shape, trajectory, velocity and acceleration, while particle image velocimetry captures the gas-phase flow field around the drop.
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Accurate estimate of turbulent dissipation rate using PIV data

TL;DR: In this article, two modified methods were proposed to estimate turbulent dissipation rate and Kolmogorov scale at different interrogation window sizes, and they were applied to experimental PIV data acquired from a turbulent jet experiment.
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Digital in-line holography to quantify secondary droplets from the impact of a single drop on a thin film

TL;DR: In this paper, a hybrid method of particle detection and digital in-line holography (DIH) is applied to quantify the secondary droplets generated by the impact of a single drop on a thin film.
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Digital holography simulations and experiments to quantify the accuracy of 3D particle location and 2D sizing using a proposed hybrid method

TL;DR: The accuracy of digital in-line holography to detect particle position and size within a 3D domain is evaluated with particular focus placed on detection of nonspherical particles and a new hybrid method is proposed.