The Experts below are selected from a list of 282 Experts worldwide ranked by ideXlab platform
Xingyu Liang - One of the best experts on this subject based on the ideXlab platform.
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effect of lubricating oil on the Particle Size Distribution and total number concentration in a diesel engine
Fuel Processing Technology, 2013Co-Authors: Lihui Dong, Xingyu LiangAbstract:Abstract In this paper, the characteristics of Particle Size Distribution in the exhaust gas of a diesel engine lubricated by two kinds of lubricating oil are investigated. The experiments are conducted in a turbocharged direct-injection diesel engine with Fast Particulate Spectrometer DMS 500 connected to the exhaust pipe. Two kinds of commonly used commercial lubricating oil, Kunlun API CF-4 15W40 and Mobil API CI-4 15W40, are chosen for the experiments. Particle Size Distribution and total number concentration are measured under medium load (100 Nm) and full load. Barring a few exceptions, the results indicate that total Particle number concentration is almost the same, while Particle Size Distribution shows great difference.
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effect of lubricating oil additives on Particle Size Distribution and total number concentration in diesel engine
Lubrication Science, 2012Co-Authors: Lihui Dong, Xingyu Liang, Yuesen WangAbstract:This paper investigates the characteristics of Particle Size Distribution in exhaust gas of engine fuelled with pure diesel and with diesel mixed with base oil or with oil additives. The experiments are conducted on a turbocharged diesel engine with fast particulate spectrometer DMS 500 connected to the exhaust pipe. Base oil and two kinds of commonly used lubricating oil additives, antioxidant additives and antifoaming additives, are chosen to be added into the fuel, with the concentrations being 0.5%, 1.0% and 1.5% of fuel weight individually. The Particle Size Distribution is measured under medium load (100 Nm) and full load at different speeds. The results indicate that the existence of base oil or oil additives shows great influence on Particle Size Distribution. Copyright © 2012 John Wiley & Sons, Ltd.
Lihui Dong - One of the best experts on this subject based on the ideXlab platform.
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effect of lubricating oil on the Particle Size Distribution and total number concentration in a diesel engine
Fuel Processing Technology, 2013Co-Authors: Lihui Dong, Xingyu LiangAbstract:Abstract In this paper, the characteristics of Particle Size Distribution in the exhaust gas of a diesel engine lubricated by two kinds of lubricating oil are investigated. The experiments are conducted in a turbocharged direct-injection diesel engine with Fast Particulate Spectrometer DMS 500 connected to the exhaust pipe. Two kinds of commonly used commercial lubricating oil, Kunlun API CF-4 15W40 and Mobil API CI-4 15W40, are chosen for the experiments. Particle Size Distribution and total number concentration are measured under medium load (100 Nm) and full load. Barring a few exceptions, the results indicate that total Particle number concentration is almost the same, while Particle Size Distribution shows great difference.
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effect of lubricating oil additives on Particle Size Distribution and total number concentration in diesel engine
Lubrication Science, 2012Co-Authors: Lihui Dong, Xingyu Liang, Yuesen WangAbstract:This paper investigates the characteristics of Particle Size Distribution in exhaust gas of engine fuelled with pure diesel and with diesel mixed with base oil or with oil additives. The experiments are conducted on a turbocharged diesel engine with fast particulate spectrometer DMS 500 connected to the exhaust pipe. Base oil and two kinds of commonly used lubricating oil additives, antioxidant additives and antifoaming additives, are chosen to be added into the fuel, with the concentrations being 0.5%, 1.0% and 1.5% of fuel weight individually. The Particle Size Distribution is measured under medium load (100 Nm) and full load at different speeds. The results indicate that the existence of base oil or oil additives shows great influence on Particle Size Distribution. Copyright © 2012 John Wiley & Sons, Ltd.
Helen Shang - One of the best experts on this subject based on the ideXlab platform.
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a neural network based soft sensor for Particle Size Distribution using image analysis
Powder Technology, 2011Co-Authors: Youngdon Ko, Helen ShangAbstract:Abstract Many industrial processes require on-line measurement of Particle Size and Particle Size Distribution for process monitoring and control. The available techniques for reliable on-line measurement are, however, limited. In this paper, based on the captured surface images of randomly disarranged ore Particles, the image uniformity was characterized. Particle Size Distribution was then investigated by applying a neural network-based modeling with the obtained image uniformity. The proposed soft sensor provides an improved prediction model and can be used for real time measurement of Particle Size Distribution in the industrial operations.
Fabian Mauss - One of the best experts on this subject based on the ideXlab platform.
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calculating the soot Particle Size Distribution function in turbulent diffusion flames using a sectional method
Proceedings of the Combustion Institute; 31 pp 667-674 (2007), 2007Co-Authors: Karl Netzell, Harry Lehtiniemi, Fabian MaussAbstract:Soot formation in a turbulent jet diffusion flame is modeled using an unsteady flamelet approach in post-process. In the present work, we apply a detailed kinetic soot model with a sectional method, and study the evolution of the Particle Size Distribution. Detailed information on the evolution of the soot Particle Size Distribution function is acquired. It is found that the Particle Size Distribution function is bimodal throughout the flame. The transition from the small to large Particle Size Distributions is strongly influenced by surface growth and oxidation reactions. We find that large Particles are most likely to be emitted from the flame. (c) 2006 The Combustion Institute. Published by Elsevier Inc. All rights reserved.
Youngdon Ko - One of the best experts on this subject based on the ideXlab platform.
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a neural network based soft sensor for Particle Size Distribution using image analysis
Powder Technology, 2011Co-Authors: Youngdon Ko, Helen ShangAbstract:Abstract Many industrial processes require on-line measurement of Particle Size and Particle Size Distribution for process monitoring and control. The available techniques for reliable on-line measurement are, however, limited. In this paper, based on the captured surface images of randomly disarranged ore Particles, the image uniformity was characterized. Particle Size Distribution was then investigated by applying a neural network-based modeling with the obtained image uniformity. The proposed soft sensor provides an improved prediction model and can be used for real time measurement of Particle Size Distribution in the industrial operations.
