The Experts below are selected from a list of 68109 Experts worldwide ranked by ideXlab platform
David L S Hung - One of the best experts on this subject based on the ideXlab platform.
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time sequenced Flow field prediction in an optical spark ignition direct injection engine using bidirectional recurrent neural network bi rnn with long short term memory
Applied Thermal Engineering, 2020Co-Authors: Fengnian Zhao, Zhiming Ruan, Zongyu Yue, David L S Hung, Sibendu SomAbstract:Abstract To further improve the energy conversion efficiency of internal combustion engine, the transient and complex air Flow movement inside the Cylinder needs to be better understood and controlled. Although the in-Cylinder Flow fields are highly stochastic with strong cycle-to-cycle fluctuations, machine learning can still provide an efficient way to learn and regress the complex Flow movement process inside the Cylinder. In this work, a bidirectional recurrent neural network (bi-RNN) model with long short-term memory was applied to predict the in-Cylinder Flow fields at different time steps using training data from multi-cycle particle image velocimetry (PIV) measurements. To evaluate the agreement between the true and predicted Flow fields, structure and magnitude comparison indices are calculated both globally and locally. The comparison results show that the bi-RNN model can accurately predict the bulk Flow and vortex motions from early intake stroke to compression stroke. This work demonstrates that the machine learning model has the potential to predict the underlying dynamics of the interaction between in-Cylinder Flows and provides a reliable way to improve temporal resolution in PIV Flow data to better reveal transient in-Cylinder Flow features.
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Investigation of Swirl Ratio Impact on In-Cylinder Flow in an SIDI Optical Engine
2020Co-Authors: Hanyang Zhuang, David L S Hung, Jie Yang, Shaoxiong TianAbstract:Advanced powertrain technologies have improved engine performance with higher power output, lower exhaust emission, and better controllability. Chief among them is the development of spark-ignition direct-injection (SIDI) engines in which the in-Cylinder processes control the air Flow motion, fuel-air mixture formation, combustion, and soot formation. Specifically, intake air with strong swirl motion is usually introduced to form a directional in-Cylinder Flowfield. This approach improves the mixing process of air and fuel as well as the propagation of flame. In this study, the effect of intake air swirl on inCylinder Flow characteristics was experimentally investigated. High-speed particle image velocimetry (PIV) was conducted in an optical SIDI engine to record the Flowfield on a swirl plane. The intake air swirl motion was achieved by adjusting the opening of a swirl ratio (SR) control valve which was installed in one of the two intake ports in the optical engine. Ten opening angles of the SR control valve were adjusted to produce an intake SR from 0.55 to 5.68. The Flow structures at the same crank angle degree (CAD), but under different SR, were compared and analyzed using proper orthogonal decomposition (POD). The Flow dominant structures and variation structures were interpreted by different POD modes. The first POD mode captured the most dominant Flowfield structure characteristics; the corresponding mode coefficients showed good linearity with the measured SR at the compression stroke when the Flow was swirling and steady. During the intake stroke, strong intake air motion took place, and the structures and coefficients of the first modes varied along different SR. These modes captured the Flow properties affected by the intake swirl motion. Meanwhile, the second and higher modes captured the variation feature of the Flow at various CADs. In summary, this paper demonstrated a promising approach of using POD to interpret the effectiveness of swirl control valve on in-Cylinder swirl Flow characteristics, providing better understanding for engine intake system design and optimization
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Multi-plane time-resolved Particle Image Velocimetry (PIV) Flow field measurements in an optical Spark-Ignition Direct-Injection (SIDI) engine for Large-Eddy Simulation (LES) model validations
Oil & Gas Science and Technology - Revue d'IFP Energies nouvelles, 2019Co-Authors: Fengnian Zhao, Xiaofeng Yang, David L S Hung, Mengqi Liu, Cherian IdicheriaAbstract:In-Cylinder Flow characteristics play a significant role in the fuel–air mixing process of Spark-Ignition Direct-Injection (SIDI) engines. Typically, planar Particle Image Velocimetry (PIV) is used to measure a representative velocity field sectioning through the center plane of the engine Cylinder. However, a single Flow field offers very limited perspective regarding the Three-Dimensional nature of the Flow fields. Since the in-Cylinder Flow is stochastically complex, large datasets of Flow field measurements along multiple planes are needed to provide a complete panoramic understanding of the Flow dynamics. In this study, a high-speed PIV is applied to measure the crank-angle resolved Flow fields inside a single-Cylinder four-valve optical SIDI engine. Five Flow fields along different tumble planes are captured. These five planes include two orthogonal planes cutting through the spark plug tip, two parallel planes sectioning through middle point of the intake and exhaust valves, and one plane through the centers of two intake valves. In addition, numerical computations are carried out with Large-Eddy Simulation (LES) model in CONVERGE. With the guidance from multi-plane PIV measurements, a novel validation approach is proposed in this study. The quantitative analysis and comparison between LES simulations and PIV experiments are divided in terms of global and local comparison indices. The global comparison indices provide a quantitative single value to quickly check the overall similarity of velocity directions and magnitudes between PIV and LES results of a specific individual plane. The local comparison indices further evaluate the similarity between the Flow fields of LES and PIV point by point to identify any dissimilar regions and vortex features, which are likely to indicate the complex Flow structures at low-speed regions. In summary, not only can the combined data analysis approach provide a reliable way for LES model validations, it can also reveal the physical quantifications of the complex in-Cylinder Flow characteristics.
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characterization of the effect of intake air swirl motion on time resolved in Cylinder Flow field using quadruple proper orthogonal decomposition
Energy Conversion and Management, 2016Co-Authors: Hanyang Zhuang, David L S HungAbstract:The control of intake air swirl motion is often used in spark-ignition direct-injection (SIDI) engine to improve its in-Cylinder fuel–air mixing process especially under engine idle and low load conditions. In this experimental investigation, a novel technique combining the time-resolved particle image velocimetry (PIV) with quadruple proper orthogonal decomposition (POD) is implemented to analyze the time-resolved in-Cylinder velocity measurements in an optically-accessible SIDI engine. The intake air swirl motion is introduced into the engine Cylinder by a control valve installed in one of two air intake ports. Experimental results show that a strong linear correlation exists between the intake Flow swirl ratio and vorticity Flow field in the Cylinder. This correlation ensures high data reliability of swirl motion control and provides a novel basis to directly compare the Flow field measurements under different swirl ratio conditions. The quadruple proper orthogonal decomposition analysis is then applied to the velocity Flow fields to separate the highly dynamic in-Cylinder Flow characteristics into four distinct categories: (1) dominant Flow structure; (2) coherent structure; (3) turbulent structure; and (4) noise structure. The results show that the dominant Flow structure varies strongly with swirl ratio, and its kinetic energy is also directly related to the swirl ratio. The coherent structure captures the large scale Flow characteristics, but its kinetic energy is much lower and exhibits larger cycle-to-cycle variations. The turbulent structure contains similar level of kinetic energy at different swirl ratios but without much cycle-to-cycle variation. Finally, the noise structure contains very low kinetic energy which only alters the dynamic nature of the Flow field slightly. In summary, the effect of swirl ratio on in-Cylinder Flow field is mostly captured by the dominant Flow structure and partially captured by the coherent Flow structure. The turbulent Flow structure can characterize the high-order Flow variation. The noise structure can be neglected due to the low energy captured.
Fengnian Zhao - One of the best experts on this subject based on the ideXlab platform.
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time sequenced Flow field prediction in an optical spark ignition direct injection engine using bidirectional recurrent neural network bi rnn with long short term memory
Applied Thermal Engineering, 2020Co-Authors: Fengnian Zhao, Zhiming Ruan, Zongyu Yue, David L S Hung, Sibendu SomAbstract:Abstract To further improve the energy conversion efficiency of internal combustion engine, the transient and complex air Flow movement inside the Cylinder needs to be better understood and controlled. Although the in-Cylinder Flow fields are highly stochastic with strong cycle-to-cycle fluctuations, machine learning can still provide an efficient way to learn and regress the complex Flow movement process inside the Cylinder. In this work, a bidirectional recurrent neural network (bi-RNN) model with long short-term memory was applied to predict the in-Cylinder Flow fields at different time steps using training data from multi-cycle particle image velocimetry (PIV) measurements. To evaluate the agreement between the true and predicted Flow fields, structure and magnitude comparison indices are calculated both globally and locally. The comparison results show that the bi-RNN model can accurately predict the bulk Flow and vortex motions from early intake stroke to compression stroke. This work demonstrates that the machine learning model has the potential to predict the underlying dynamics of the interaction between in-Cylinder Flows and provides a reliable way to improve temporal resolution in PIV Flow data to better reveal transient in-Cylinder Flow features.
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Multi-plane time-resolved Particle Image Velocimetry (PIV) Flow field measurements in an optical Spark-Ignition Direct-Injection (SIDI) engine for Large-Eddy Simulation (LES) model validations
Oil & Gas Science and Technology - Revue d'IFP Energies nouvelles, 2019Co-Authors: Fengnian Zhao, Xiaofeng Yang, David L S Hung, Mengqi Liu, Cherian IdicheriaAbstract:In-Cylinder Flow characteristics play a significant role in the fuel–air mixing process of Spark-Ignition Direct-Injection (SIDI) engines. Typically, planar Particle Image Velocimetry (PIV) is used to measure a representative velocity field sectioning through the center plane of the engine Cylinder. However, a single Flow field offers very limited perspective regarding the Three-Dimensional nature of the Flow fields. Since the in-Cylinder Flow is stochastically complex, large datasets of Flow field measurements along multiple planes are needed to provide a complete panoramic understanding of the Flow dynamics. In this study, a high-speed PIV is applied to measure the crank-angle resolved Flow fields inside a single-Cylinder four-valve optical SIDI engine. Five Flow fields along different tumble planes are captured. These five planes include two orthogonal planes cutting through the spark plug tip, two parallel planes sectioning through middle point of the intake and exhaust valves, and one plane through the centers of two intake valves. In addition, numerical computations are carried out with Large-Eddy Simulation (LES) model in CONVERGE. With the guidance from multi-plane PIV measurements, a novel validation approach is proposed in this study. The quantitative analysis and comparison between LES simulations and PIV experiments are divided in terms of global and local comparison indices. The global comparison indices provide a quantitative single value to quickly check the overall similarity of velocity directions and magnitudes between PIV and LES results of a specific individual plane. The local comparison indices further evaluate the similarity between the Flow fields of LES and PIV point by point to identify any dissimilar regions and vortex features, which are likely to indicate the complex Flow structures at low-speed regions. In summary, not only can the combined data analysis approach provide a reliable way for LES model validations, it can also reveal the physical quantifications of the complex in-Cylinder Flow characteristics.
Xuesong Bai - One of the best experts on this subject based on the ideXlab platform.
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numerical estimation of asymmetry of in Cylinder Flow in a light duty direct injection engine with re entrant piston bowl
SAE 2017 International Powertrains Fuels and Lubricants Meeting FFL 2017, 2017Co-Authors: Christian Ibron, Mehdi Jangi, Tommaso Lucchini, Xuesong BaiAbstract:Partially premixed combustion (PPC) can be applied to decrease emissions and increase fuel efficiency in direct injection, compression ignition (DICI) combustion engines. PPC is strongly influenced by the mixing of fuel and oxidizer, which for a given fuel is controlled mainly by (a) the fuel injection, (b) the in-Cylinder Flow, and (c) the geometry and dynamics of the engine. As the injection timings can vary over a wide range in PPC combustion, detailed knowledge of the in-Cylinder Flow over the whole intake and compression strokes can improve our understanding of PPC combustion. In computational fluid dynamics (CFD) the in-Cylinder Flow is sometimes simplified and modeled as a solid-body rotation profile at some time prior to injection to produce a realistic Flow field at the moment of injection. In real engines, the in-Cylinder Flow motion is governed by the intake manifold, the valve motion, and the engine geometry. The deviation of the real in-Cylinder Flow from a solid body rotation Flow field varies with different piston positions. This paper reports on an CFD study of the formation and development of a real engine in-Cylinder Flow field in an optical light duty PPC engine from the opening of the intake valve at -360 CAD ATDC up to 20 CAD ATDC in a motored case (without fuel injection). The focus is put on the analysis of the temporal and spatial development of the swirl Flow motion. The resulting Flow field of the simulation is compared with the results from CFD simulation of an initial axially symmetric (sector-mesh) Flow in the Cylinder. The adequateness of sector type mesh including solid-body rotation assumption as an initial Flow is analyzed. (Less)
Christian Ibron - One of the best experts on this subject based on the ideXlab platform.
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numerical estimation of asymmetry of in Cylinder Flow in a light duty direct injection engine with re entrant piston bowl
SAE 2017 International Powertrains Fuels and Lubricants Meeting FFL 2017, 2017Co-Authors: Christian Ibron, Mehdi Jangi, Tommaso Lucchini, Xuesong BaiAbstract:Partially premixed combustion (PPC) can be applied to decrease emissions and increase fuel efficiency in direct injection, compression ignition (DICI) combustion engines. PPC is strongly influenced by the mixing of fuel and oxidizer, which for a given fuel is controlled mainly by (a) the fuel injection, (b) the in-Cylinder Flow, and (c) the geometry and dynamics of the engine. As the injection timings can vary over a wide range in PPC combustion, detailed knowledge of the in-Cylinder Flow over the whole intake and compression strokes can improve our understanding of PPC combustion. In computational fluid dynamics (CFD) the in-Cylinder Flow is sometimes simplified and modeled as a solid-body rotation profile at some time prior to injection to produce a realistic Flow field at the moment of injection. In real engines, the in-Cylinder Flow motion is governed by the intake manifold, the valve motion, and the engine geometry. The deviation of the real in-Cylinder Flow from a solid body rotation Flow field varies with different piston positions. This paper reports on an CFD study of the formation and development of a real engine in-Cylinder Flow field in an optical light duty PPC engine from the opening of the intake valve at -360 CAD ATDC up to 20 CAD ATDC in a motored case (without fuel injection). The focus is put on the analysis of the temporal and spatial development of the swirl Flow motion. The resulting Flow field of the simulation is compared with the results from CFD simulation of an initial axially symmetric (sector-mesh) Flow in the Cylinder. The adequateness of sector type mesh including solid-body rotation assumption as an initial Flow is analyzed. (Less)
Davinder Kumar - One of the best experts on this subject based on the ideXlab platform.
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effect of engine parameters on in Cylinder Flows in a two stroke gasoline direct injection engine
Applied Energy, 2016Co-Authors: Addepalli S Krishna, J M Mallikarjuna, Davinder KumarAbstract:Abstract This paper deals with the in-Cylinder Flow field analysis in a two-stroke engine under motoring conditions by particle image velocimetry (PIV) and computational fluid dynamics (CFD). The main objective is to analyze the effect of engine parameters viz., engine speed, compression ratio (CR) and port orientation on the in-Cylinder Flows in a loop-scavenged two-stroke gasoline direct injection (GDI) engine, with an aim to help researchers to design fuel efficient and less polluting two-stroke engines. In this study, a single-Cylinder 70 cm 3 two-stroke engine which is very commonly used for the two-wheeler application, is considered. The engine Cylinder is modified to provide optical access into the in-Cylinder region. The PIV experiments are conducted at various engine speeds viz., 500, 1000 and 1500 rev/min, and the plane averaged velocity vector fields obtained, are analyzed to understand the in-Cylinder Flow behavior. The CFD study is also carried out using the commercial CFD code, STARCD, to study and compare the in-Cylinder Flow parameters at various engine operating conditions. The CFD results are compared with the experimental results to the extent possible. The CFD predictions are found to be in good agreement with the experimental results. Therefore, the CFD analysis has been extended further to understand the effect of various engine parameters on the in-Cylinder Flows. We found that the turbulent kinetic energy and tumble ratio increased by about 25% and 20% respectively, when the engine speed was increased from 1000 to 1500 rev/min. Also, we found that the turbulent kinetic energy and tumble ratio decreased by about 13% and 26% when the compression ratio was increased from 7 to 8. In addition, we found that the port orientation, rather than port areas had a greater influence on the in-Cylinder Flow parameters.
