(150 words)A theoretical scaling analysis is conducted to propose a diagram to predict weak and strong

No abstract

<div class="section abstract"><div class="htmlview paragraph">A computational fluid dynamics (CFD) guided combustion system optimization was conducted for a heavy-duty diesel engine running with a gasoline fuel that has a research octane number (RON) of 80. The goal was to optimize the gasoline compression ignition (GCI) combustion recipe (piston bowl geometry, injector spray pattern, in-cylinder swirl motion, and thermal boundary conditions) for improved fuel efficiency while maintaining engine-out NO_x within a 1-1.5 g/kW-hr window. The numerical model was developed using the multi-dimensional CFD software CONVERGE. A two-stage design of experiments (DoE) approach was employed with the first stage focusing on the piston bowl shape optimization and the second addressing refinement of the combustion recipe. For optimizing the piston bowl geometry, a software tool, CAESES, was utilized to automatically perturb key bowl design parameters. This led to the generation of 256 combustion chamber designs evaluated at several engine operating conditions. The second DoE campaign was conducted to optimize injector spray patterns, fuel injection strategies and in-cylinder swirl motion for the best performing piston bowl designs from the first DoE campaign. This comprehensive optimization study was performed on a supercomputer, Mira, to accelerate the development of an optimized fuel-efficiency focused design. Compared to the production combustion system in the baseline engine, the new combustion recipe from this study showed significantly improved closed-cycle fuel efficiency across key engine operating points while meeting the engine-out NO_x targets. Optimized piston bowl designs and injector spray patterns were predicted to provide enhanced in-cylinder air utilization and more rapid mixing-controlled combustion, thereby leading to a fuel efficiency improvement. In addition, shifting the engine thermal boundary conditions toward leaner operation was also key to the improved fuel efficiency.</div></div>

Auto-ignition characteristics of compositionally homogeneous reactant mixtures in the presence of thermal non-uniformities and turbulent velocity fluctuations were computationally investigated. The main objectives were to quantify the observed ignition characteristics and numerically validate the theory of the turbulent ignition regime diagram recently proposed by Im et al. [H.G. Im, P. Pal, M.S. Wooldridge, A.B. Mansfield, Combustion Science and Technology, 2015] that provides a framework to predict ignition behavior a priori based on the thermo-chemical properties of the reactant mixture and initial flow and scalar field conditions. Ignition regimes were classified into three categories: weak (where deflagration is the dominant mode of fuel consumption), reaction-dominant strong, and mixing-dominant strong (where volumetric ignition is the dominant mode of fuel consumption). Two-dimensional (2D) direct numerical simulations (DNS) of auto-ignition in a lean syngas/air mixture with uniform mixture composition at highpressure, low-temperature conditions were performed in a fixed volume. The initial conditions considered two-dimensional isotropic velocity spectrums, temperature fluctuations and localized thermal hot spots. A number of parametric test cases, by varying the characteristic turbulent Damköhler and Reynolds numbers, were investigated. The evolution of the auto-ignition phenomena, pressure rise, and heat release rate were analyzed. In addition, combustion mode analysis based on front propagation speed and computational singular perturbation (CSP) was applied to characterize the auto-ignition phenomena. All results supported that the observed ignition behaviors were consistent with the expected ignition regimes predicted by the theory of the regime diagram. This work provides new high-fidelity data on syngas ignition characteristics over a broad range of conditions and demonstrates that the regime diagram serves as a predictive guidance in the understanding of various physical and chemical mechanisms controlling auto-ignition in thermally inhomogeneous and compositionally homogeneous turbulent reacting flows.

No abstract