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Dong Liu

Researcher at Nanjing University of Science and Technology

Publications -  499
Citations -  9899

Dong Liu is an academic researcher from Nanjing University of Science and Technology. The author has contributed to research in topics: Chemistry & Combustion. The author has an hindex of 39, co-authored 412 publications receiving 7618 citations. Previous affiliations of Dong Liu include Indian Ministry of Environment and Forests & Purdue University.

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Random two-frame phase-shifting interferometry via minimization of coefficient of variation

TL;DR: Sufficient numerical simulations and experimental data demonstrate the high accuracy and high efficiency of this CV minimization (CVM) method, which is not limited by the number of fringes in interferograms, in contrast to existing state-of-the-art approaches.
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Effects of self-absorption on simultaneous estimation of temperature distribution and concentration fields of soot and metal-oxide nanoparticles in nanofluid fuel flames using a spectrometer

TL;DR: An improved inverse reconstruction model with consideration of self-absorption effect for the temperature distribution and concentration fields of soot and metal-oxide nanoparticles in nanofluid fuel flames was proposed based on the flame emission spectrometry as mentioned in this paper.
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Analysis of montmorillonite affecting coke formation during the thermal conversion of heavy oil

TL;DR: In this paper, a fixed-bed reactor was used to conduct the thermal conversion experiments of heavy oil and model compounds to reveal the mechanism of montmorillonite affecting the coke formation.
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Theoretical investigations on heat transfer to H 2 O/CO 2 mixtures in supercritical region

TL;DR: In this article, the authors show that supercritical mixtures with H2O being one of the components, have similar convection heat transfer behavior to supercritical pure fluids for temperatures and pressures above the critical point of H 2O.
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Noncontact direct temperature and concentration profiles measurement of soot and metal-oxide nanoparticles in optically thin/thick nanofluid fuel flames

TL;DR: In this article, a novel inverse reconstruction model was presented to simultaneously estimate temperature and concentration distributions of soot and metal-oxide nanoparticles in optically thin/thick nanofluid fuel flames from the knowledge of flame emission radiation intensities received by a CCD camera.