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End-of-injection transients have recently been shown to be important for combustion and emissions outcomes in diesel engines. The objective of this work is to develop an understanding of the coupling between end-of-injection transients and the propensity for second-stage ignition in mixtures upstream of the lifted diesel flame, or combustion recession. An injection system capable of varying the end-of-injection transient was developed to study single fuel sprays in a newly commissioned optically-accessible spray chamber under a range of ambient conditions. Simultaneous high-speed optical diagnostics, namely schlieren, OH* chemiluminescence, and broadband luminosity, were used to characterize the spatial and temporal development of combustion recession after the end of injection.

The fuel-ambient mixture in vaporized fuel jets produced by liquid sprays is fundamental to the performance and operation of engines. Unfortunately, experimental difficulties limit the direct measurement of local fuel-ambient mixture, inhibiting quantitative assessment of mixing. On the other hand, measurement of global quantities, such as the jet penetration rate, is relatively straightforward. Simplified models to predict local fuel-ambient mixture have also been developed, based on these global parameters. However, experimental data to validate these models over a range of conditions is needed. In the current work, we perform measurements of jet global quantities such as vapor-phase penetration, liquid-phase penetration, spreading angle, and nozzle flow coefficients over a range of conditions in a high-temperature, high-pressure vessel.

Spray processes, such as primary breakup, play an important role for subsequent combustion processes and emissions formation. Accurate modeling of these spray physics is therefore key to ensure faithful representation of both the global and local characteristics of the spray. However, the governing physical mechanisms underlying primary breakup in fuel sprays are still not known. Several theories have been proposed and incorporated into different engineering models for the primary breakup of fuel sprays, with the most widely employed models following an approach based on aerodynamically-induced breakup, or more recently, based on liquid turbulence-induced breakup. However, a complete validation of these breakup models and theories is lacking since no existing measurements have yielded the joint liquid mass and drop size distribution needed to fully define the spray, especially in the near-nozzle region.

The Georgia Tech FutureTruck Team has designed a strong parallel split-hybrid powertrain for the model year 2002 Ford Explorer SUV. The modified powertrain uses a Lincoln LS 3.0L, V-6, DOHC, aluminum engine driving the rear axle. An AC-150 from AC Propulsion is coupled to the front wheels through a 3.75:1 Auburn Gear speed reducer. This split-hybrid structure fits well into the Explorer and is to manufacture. The interior cabin has been maintained in a stock configuration by carefully integrating the added instrumentation and electric drive controls into the dash and console. The toque-blending hybrid electric control is designed to be charge sustaining such that the refueling procedures match those of the stock vehicle. When fully operational, this powertrain is expected to yield a net 25% increase in fuel efficiency while lowering emissions without any sacrifice in customer acceptability.

The present use of the carburetor to supply fuel to the Otto cycle engine has placed it in a difficult competitive position with the diesel engine, which has successfully operated with a fuel injection system. The purpose of this study was to consider the feasibility of utilizing a low pressure injection system for the Otto cycle engine. The proposed design is discussed in detail. As the author points out, this system will allow design changes in the engine that would be impossible if the carburetor were retained, and thus considerable improvement in performance and efficiency can be realized for the Otto cycle engine.

Fuel supercriticality has recently received significant attention due to the elevated pressures and temperatures that directly-injected (DI) fuel sprays encounter in modern internal combustion (IC) engines. This paper presents a theoretical examination of conventional and alternative DI fuels at conditions relevant to the operation of compression ignition (CI) engines. The focus is to identify the conditions under which the injected liquid fuel can bypass the atomization process and directly transition to a diffusional mixing regime with the chamber gas. Evaluating the microscopic length-scales of the phase boundary associated with the injection of liquid nitrogen into its own vapor, it is found that the conventional threshold based on the interfacial Knudsen number (i.e. Kn = 0.1) does not adequately quantify the direct transition between sub- and supercriticality. Instead, a threshold that is an order of magnitude smaller is more appropriate for this purpose.

Compressed natural gas (CNG) is an attractive, alternative fuel for spark-ignited (SI), internal combustion (IC) engines due to its high octane rating, and low energy-specific CO2 emissions compared with gasoline. Directly-injected (DI) CNG in SI engines has the potential to dramatically decrease vehicles’ carbon emissions; however, optimization of DI CNG fueling systems requires a thorough understanding of the behavior of CNG jets in an engine environment. This paper therefore presents an experimental and modeling study of DI gaseous jets, using methane as a surrogate for CNG. Experiments are conducted in a non-reacting, constant volume chamber (CVC) using prototype injector hardware at conditions relevant to modern DI engines. The schlieren imaging technique is employed to investigate how the extent of methane jets is impacted by changing thermodynamic conditions in the fuel rail and chamber.

Accurate modeling of the internal flow and spray characteristics in fuel injectors is a critical aspect of direct injection engine design. However, such high-fidelity computational fluid dynamics (CFD) models are often computationally expensive due to the requirement of resolving fine temporal and spatial scales. This paper addresses the computational bottleneck issue by proposing a machine learning-based emulator framework, which learns efficient surrogate models for spatiotemporal flow distributions relevant for static coupling injection maps, namely total void fraction, velocity, and mass, within a design space of interest. Different design points involving variations of needle lift, fuel viscosity, and level of non-condensable gas in the fuel were explored in this study. An interpretable Bayesian learning strategy was employed to understand the effect of the design parameters on the void fraction fields at the exit of the injector orifice.