1,721,005 research outputs found
A thermally-limited bubble growth model for the relaxation time of superheated fuels
No full textWe propose a novel approach to evaluate the relaxation time of vapor bubble growth in the context of the flash boiling of a superheated liquid. In alternative to the empirical correlation derived from superheated water experiments almost fifty years ago, the new model describes the thermally-dominated growth of vapor bubbles in terms that are dependent on the local Jakob number (the ratio of sensible heat to latent heat during phase change) and the number density of vapor bubbles. The model is tested by plugging the resulting relaxation time into the Homogenous Relaxation Model (HRM). Flash-boiling simulations carried out with HRM are compared with n-pentane (C5H12) injection and boil-off experiments conducted with a real-size, axial-hole, transparent gasoline injector discharging into a constant-pressure vessel. The long-distance microscopy images from the experiments, processed to derive the projected liquid volume (PLV) of the spray, provide a unique set of time-resolved validation data for direct fuel injection simulations. At conditions ranging from flaring to mild and minimal flash boiling, we show that switching to the new relaxation time improves the agreement with the measured PLV profiles with respect to the standard empirical model. Particularly at flaring conditions, the predicted increase in gas cooling caused by rapid vapor production is shown to be more consistent with the observed boil-off. (C) 2020 Elsevier Ltd. All rights reserved.
Machine-learning based prediction of injection rate and solenoid voltage characteristics in GDI injectors
No full textCurrent state-of-the-art gasoline direct-injection (GDI) engines use multiple injections as one of the key technologies to improve exhaust emissions and fuel efficiency. For this technology to be successful, secured adequate control of fuel quantity for each injection is mandatory. However, nonlinearity and variations in the injection quantity can deteriorate the accuracy of fuel control, especially with small fuel injections. Therefore, it is necessary to understand the complex injection behavior and to develop a predictive model to be utilized in the development process. This study presents a methodology for rate of injection (ROI) and solenoid voltage modeling using artificial neural networks (ANNs) constructed from a set of Zeuch-style hydraulic experimental measurements conducted over a wide range of conditions. A quantitative comparison between the ANN model and the experimental data shows that the model is capable of predicting not only general features of the ROI trend, but also transient and non-linear behaviors at particular conditions. In addition, the end of injection (EOI) could be detected precisely with a virtually generated solenoid voltage signal and the signal processing method, which applies to an actual engine control unit. A correlation between the detected EOI timings calculated from the modeled signal and the measurement results showed a high coefficient of determination.
Assessment of the Ignition and Lift-off Characteristics of a Diesel Spray with a Transient Spreading Angle
No full textMulti-hole diesel fuel injectors have shown significant transients in spreading angle during injections, different than past fundamental research using single-hole injectors. We investigated the effect of a this transient spreading angle on combustion parameters such as ignition delay and lift-off length by comparing a three-hole nozzle (Spray B) and single-hole nozzle (Spray A) with holes of the same size and shape as targets for the Engine Combustion Network (ECN). With the temperature distribution for a target plume of Spray B characterized extensively in a constant-volume combustion chamber, the ignition delay and lift-off length were measured and compared. Results show that the lift-off length of Spray B increases and grows by approximately 1.5 mm after the initial stages of ignition, in an opposite trend compared to Spray A where the lift-off length decreases with time. The Spray B lift-off length increase is consistent with a transition to from wide to narrow spreading angle that would tend to increase lift-off length, but lift-off is stabilized for a substantial period of time by a wide annular region of combustion products formed when the plume was initially wide
The Influence of Charge Dilution and Injection Timing on Low-Temperature Diesel Combustion and Emissions
No full textThe effects of charge dilution on low-temperature diesel combustion and emissions were investigated in a small-bore single-cylinder diesel engine over a wide range of injection timing. The fresh air was diluted with additional N2 and CO2, simulating 0 to 65% exhaust gas recirculation in an engine. Diluting the intake charge lowers the flame temperature T due to the reactant being replaced by inert gases with increased heat capacity. In addition, charge dilution is anticipated to influence the local charge equivalence ratio Φ prior to ignition due to the lower O2 concentration and longer ignition delay periods. By influencing both Φ and T, charge dilution impacts the path representing the progress of the combustion process in the Φ-T plane, and offers the potential of avoiding both soot and NOx formation. In-cylinder pressure measurements, exhaust-gas emissions, and imaging of combustion luminosity were performed to clarify the path of the combustion process and the effects of charge dilution and injection timing on combustion and fuel conversion efficiency. Based on the findings, a postulated combustion process in the Φ-T plane is presented for different dilution levels and injection timings. Although the ignition delay increased with high dilution and early injection, the heat release analysis indicated that a large portion of the combustion and emissions formation processes was still dominated by the mixing-controlled phase rather than the premixed phase. Because of the incomplete premixing, and the need to mix a greater volume of charge with unbumed or partially-burned fuel to complete combustion, the diluted mixtures increased CO emissions. Injecting the fuel at earlier timings to extend the ignition delay helped alleviate this problem, but did not eliminate it. Fuel conversion efficiencies calculated for each dilution level and start of injection provide guidance as to the appropriate combustion phasing and practical levels of charge dilution for this low-temperature diesel combustion regime.Support for this research was provided by the U.S.
Department of Energy, Office of FreedomCAR and
Vehicle Technologies. The research was performed at
the Combustion Research Facility, Sandia National
Laboratories, Livermore, California. Sandia is a
multiprogram laboratory operated by Sandia Corporation,
a Lockheed Martin Company, for the United States
Department of Energy’s National Nuclear Security
Administration under contract DE-AC04-94AL85000. The
NRL and Future Vehicle Technology Development Corps.
of Korea supported Sanghoon Kook's visiting research.
The authors express their appreciation to Mark Musculus
and Cherian Idicheria for providing high speed camera
used in the experiments as well as Matlab source code
for image processing and adiabatic flame temperature
calculation. . Thanks are also due to Feng Tao of the
University of Wisconsin (Madison) for his assistance in
validating the estimated peak core gas temperatures
Development of limited-view tomography for measurement of Spray G plume direction and liquid volume fraction
No full textThe method for direct injection of fuel in the cylinder of an IC engines is important to high-efficiency and low-emission performance. Optical spray diagnostics plays an important role in understanding plume movement and interaction for multi-hole injectors, and providing baseline understanding used for computational optimization of fuel delivery. Traditional planar or line-of-sight diagnostics fail to capture the liquid distribution because of optical thickness concerns. This work proposes a high-speed (67 kHz) extinction imaging technique at various injector rotations coupled to computed tomography (CT) for time-resolved reconstruction of liquid volume fraction in three dimensions. The number of views selected and processing were based on synthetic (modeled) liquid volume fraction data where extinction and CT adequately reconstructed each plume. The exercise showed that for an 8-hole, symmetric-design injector (ECN Spray G), only three different views are enough to reproduce the direction of each plume, and particularly the mean plume direction. Therefore, the number of views was minimized for experiments to save expense. Measurements applying this limited-view technique confirm plume-plume variations also detected with mechanical patternation, while providing better spatial and temporal resolution than achieved previously. Uncertainties due to the limited view within pressurized spray chambers, the droplet size, and optically thick regions are discussed.
Y Spatio-temporal identification of plume dynamics by 3D computed tomography using engine combustion network spray G injector and various fuels
No full textUnderstanding of plume direction and mixture quality in a combustion chamber is crucial to improve engine performance. While a variety of diagnostics using laser and x-ray facilities have been applied to identify plume direction, most applications require sophisticated experimental setup as well as troubleshooting for light attenuation or scattering issues. In this study, we acquire temporally and spatially resolved liquid volume fraction by three-dimensional tomographic reconstruction of ensemble-averaged extinction images to produce unique information on plume movement and growth in the midst of a multi-plume spray. Measurements were carried out in a constant-flow spray vessel coupled with high-speed Mie-scattering, diffused back-illumination extinction, and schlieren imaging. Four different fuels, a single component iso-octane, a multi-component surrogate with di-isobutylene, a multi-component fuel with olefinic molecular structure, and a 70% standardized gasoline 30% ethanol (e30) blend were injected using Engine Combustion Network (ECN) Spray G injector under ECN G2 (50 kPa absolute), G3 (100 kPa absolute), and G3HT (G3 with 393 K ambient temperature) conditions. Planar slices, available from the tomographically reconstructed extinction data, confirmed greater plume-to-plume interaction for the flash-boiling G2 iso-octane condition with an approximately 6 degrees smaller plume direction angle relative to the injector axis, compared to the nozzle drill angle. The olefinic and e30 fuels, which have broader distillation curves, exhibited stronger plume growth and eventual complete spray plume collapse and longer time for evaporation. Using the 3D dataset, we show that factors that increase plume growth also create more interaction between plumes to ultimately reduce the plume direction angle.
Spray collapse characteristics of practical GDI spray for lateral-mounted GDI engines
No full textSpray collapsing and plume merging processes were investigated using a lateral-mounted gasoline direct injection (GDI) injector with a practical 'triangular' spray pattern. High-speed diffusive back illumination extinction imaging followed by computed tomography reconstruction was applied to understand the spa-tiotemporal plume dynamics under engine-like conditions. The spray chamber and injector conditions include (1) cold, subcooled standard temperature and pressure (STP) used by the injector manufacturer, (2) practical gasoline fuels with full-range distillation, (3) flash-boiling with fuel temperature and vac-uum gas pressure, and (4) high gas pressure and temperature typical of injection during compression. The novel experiments permit tracking of plume merging at different times and axial distances down-stream of the nozzle. A triangular 6-hole pattern, which is widely used in lateral-mounted GDI engines, was found to be prone to having the centrally located plumes move close to each other thus leading to spray collapse with these plumes at all practical test conditions (2)-(4). Variations of air entrainment and local pressure with different conditions were identified as dominant factors for the timing and position of spray collapse.(c) 2022 Elsevier Ltd. All rights reserved.
Machine Learning and transcritical sprays: A demonstration study of their potential in ECN Spray-A
No full textThe present work investigates the application of Machine Learning and Artificial Neural Networks for tackling the complex issue of transcritical sprays, which are relevant to modern compression-ignition engines. Such conditions imply the departure of the classical thermodynamic perspective of ideal gas or incompressible liquid, necessitating the use of costly and elaborate thermodynamic closures to describe property variation and simulation methods. Machine Learning can assist in several ways in speeding up such calculations, either as a compact, trained thermodynamic model that can be coupled to the flow solver, or as a surrogate predictive tool of spray characteristics. In this work, such applications are demonstrated and their performance is assessed against more traditional approaches. Such applications involve the prediction of macroscopic spray characteristics, for example, the spray penetration over time, or the spray distribution in space and time, and predictions of fluid properties for the thermodynamic states encountered in such applications. Macroscopic characteristics can be adequately predicted by relatively simple network structures, involving just a hidden layer of 3-4 neurons, whereas prediction of thermodynamic states requires several layers of 5-20 neurons each. The results of integrating Artificial Neural Networks in transcritical sprays are rather promising; prediction of thermodynamic properties at pressures greater than I bar has effectively zero error, yielding simulations indistinguishable from standard tabulated approaches with minimal overhead. When used as a regression method for time-histories either of spray characteristics or spray distributions, the results are within experimental uncertainty of similar experiments, not included in the training dataset. [GRAPHICS] .
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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