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Modeling plume interaction and collapse for direct-injection gasoline sprays is important because of its impact on fuel-air mixing and engine performance. Nevertheless, the aerodynamic interaction between plumes and the complicated two-phase coupling of the evaporating spray has shown to be notoriously difficult to predict. With the availability of high-speed (100 kHz) Particle Image Velocimetry (PIV) experimental data, we compare velocity field predictions between plumes to observe the full temporal evolution leading up to plume merging and complete spray collapse. The target “Spray G” operating conditions of the Engine Combustion Network (ECN) is the focus of the work, including parametric variations in ambient gas temperature. We apply both LES and RANS spray models in different CFD platforms, outlining features of the spray that are most critical to model in order to predict the correct aerodynamics and fuel-air mixing.

A Machine Learning-Genetic Algorithm (ML-GA) approach was developed to virtually discover optimum designs using training data generated from multi-dimensional simulations. Machine learning (ML) presents a pathway to transform complex physical processes that occur in a combustion engine into compact informational processes. In the present work, a total of over 2000 sector-mesh computational fluid dynamics (CFD) simulations of a heavy-duty engine were performed. These were run concurrently on a supercomputer to reduce overall turnaround time. The engine being optimized was run on a low-octane (RON70) gasoline fuel under partially premixed compression ignition (PPCI) mode. A total of nine input parameters were varied, and the CFD simulation cases were generated by randomly sampling points from this nine-dimensional input space. These input parameters included fuel injection strategy, injector design, and various in-cylinder flow and thermodynamic conditions at intake valve closure (IVC).

An extensive numerical study of two-phase flow inside the nozzle holes and the issuing jets for a multi-hole direct injection gasoline injector is presented. The injector geometry is representative of the Spray G nozzle, an eight-hole counter-bored injector, from the Engine Combustion Network (ECN). Homogeneous Relaxation Model (HRM) coupled with the mixture multiphase approach in the Eulerian framework has been utilized to capture the phase change phenomena inside the nozzle holes. Our previous studies have demonstrated that this approach is capable of capturing the effect of injection transients and thermodynamic conditions in the combustion chamber, by predicting phenomenon such as flash boiling. However, these simulations were expensive, especially if there is significant interest in predicting the spray behavior as well.

A wide variety of spray models and their associated sub-models exist to assist with numerical spray development studies in the many applicable areas viz., turbines, internal combustion engines etc. The accuracy of a simulation when compared to the experiments varies, as these models chosen are varied. Also, the computational grid plays a crucial role in model correctness; a grid-converged CFD study is more valuable and assists in proper validation at later stages. Of primary relevance to this paper are the combustion models for a grid-converged Lagrangian spray modeling scenario. CONVERGE CFD code is used for simulation of split injection diesel (n-heptane) sprays and a structured methodology, using RNG k-ε turbulence model, is followed to obtain a grid-converged solution for the key Computational Fluid Dynamics (CFD) parameters viz., grid size, injected parcels and spray break-up time constant.

High-speed spray-to-spray liquid impingement could be an effective phenomenon for the spray propagation and droplet vaporization. To achieve higher vaporization efficiency, impingement from two-hole nozzles is analyzed in this paper. This paper focuses on investigating vaporization mechanism as a function of the impingement location and the collision breakup process provided by two-hole impinging jet nozzles. CFD (Computational Fluid Dynamics) is adopted to do simulation. Lagrangian model is used to predict jet-to-jet impingement and droplet breakup conditions while KH-RT breakup and O'Rourke collision models are implemented for the simulation. The paper includes three parts: First, a single spray injected into an initially quiescent constant volume chamber using the Lagrangian approach is simulated to identify the breakup region, which will be considered as a reference to study two-hole impinging jet nozzles. Lagrangian simulation results would be validated via experimental results.

Cavitation and cavitation-induced erosion have been observed in fuel injectors in regions of high acceleration and low pressure. Although these phenomena can have a large influence on the performance and lifetime of injector hardware, questions still remain on how these physics should be accurately and efficiently represented within a computational fluid dynamics model. While several studies have focused on the validation of cavitation predictions within canonical and realistic injector geometries, it is not well documented what influence the numerical and physical parameters selected to represent turbulence and phase change will have on the predictions for cavitation erosion propensity and severity. In this work, a range of numerical and physical parameters are evaluated within the mixture modeling approach in CONVERGE to understand their influence on predictions of cavitation, condensation and erosion.

A numerical study has been carried out to assess the effects of needle movement and internal nozzle flow on spray formation for a multi-hole Gasoline Direct Injection system. The coupling of nozzle flow and spray formation is dynamic in nature and simulations with pragmatic choice of spatial and temporal resolutions are needed to analyze the sprays in a GDI system. The dynamic coupling of nozzle flow and spray formation will be performed using an Eulerian-Lagrangian Spray Atomization (ELSA) approach. In this approach, the liquid fuel will remain in the Eulerian framework while exiting the nozzle, while, depending on local instantaneous liquid concentration in a given cell and amount of liquid in the neighboring cells, part of the liquid mass will be transferred to the Lagrangian framework in the form of Lagrangian parcels.

This work involves modeling internal and near-nozzle flows of a gasoline direct injection (GDI) nozzle. The Engine Combustion Network (ECN) Spray G condition has been considered for these simulations using the nominal geometry of the Spray G injector. First, best practices for numerical simulation of the two-phase flow evolution inside and the near-nozzle regions of the Spray G injector are presented for the peak needle lift. The mass flow rate prediction for peak needle lift was in reasonable agreement with experimental data available in the ECN database. Liquid plume targeting angle and liquid penetration estimates showed promising agreement with experimental observations. The capability to assess the influence of different thermodynamic conditions on the two-phase flow nature was established by predicting non-flashing and flashing phenomena.

Actual combustion strategies in internal combustion engines rely on fast and accurate injection systems to be successful. One of the injector designs that has shown good performance over the past years is the direct-acting piezoelectric. This system allows precise control of the injector needle position and hence the injected mass flow rate. Therefore, understanding how nozzle flow characteristics change as function of needle dynamics helps to choose the best lift law in terms of delivered fuel for a determined combustion strategy. Computational fluid dynamics is a useful tool for this task. In this work, nozzle flow of a prototype direct-acting piezoelectric has been simulated by using CONVERGE. Unsteady Reynolds-Averaged Navier-Stokes approach is used to take into account the turbulence. Results are compared with experiments in terms of mass flow rate. The nozzle geometry and needle lift profiles were obtained by means of X-rays in previous works.

The medium and heavy duty vehicle industry has fostered an increase in emissions research with the aim of reducing NOx while maintaining power output and thermal efficiency. This research describes a proof-of-concept numerical study conducted on a Caterpillar single-cylinder research engine. The target of the study is to reduce NOx by taking a unique approach to combustion air handling and utilizing enriched nitrogen and oxygen gas streams provided by Air Separation Membranes. A large set of test cases were initially carried out for closed-cycle situations to determine an appropriate set of operating conditions that are conducive for NOx reduction and gas diffusion properties. Several parameters - experimental and numerical, were considered. Experimental aspects, such as engine RPM, fuel injection pressure, start of injection, spray inclusion angle, and valve timings were considered for the parametric study.