The present study deals with a comparative evaluation of a single-zone (SZ) thermodynamic model and a 3D computational fluid dynamics (CFD) model for heat release calculation in internal combustion engines. The first law, SZ, model is based on the first law of thermodynamics. This model is characterized by a very simplified modeling of the combustion phenomenon allowing for a great simplicity in the mathematical formulation and very low computational time. The CFD 3D models, instead, are able to solve the chemistry of the combustion process, the interaction between turbulence and flame propagation, the heat exchange with walls and the dissociation and re-association of chemical species. They provide a high spatial resolution of the combustion chamber as well. Nevertheless, the computation requirements of CFD models are enormously larger than the SZ techniques. However, the SZ model needs accurate experimental in-cylinder pressure data for initializing the heat release calculation. Therefore, the main objective of an SZ model is to evaluate the heat release, which is very difficult to measure in experiments, starting from the knowledge of the in-cylinder pressure data. Nevertheless, the great simplicity of the SZ numerical formulation has a margin of uncertainty which cannot be known a priori. The objective of this paper was, therefore, to evaluate the level of accuracy and reliability of the SZ model comparing the results with those obtained with a CFD 3D model. The CFD model was developed and validated using cooperative fuel research (CFR) engine experimental in-cylinder pressure data. The CFR engine was fueled with 2,2,4-trimethylpentane, at a rotational speed of 600 r/min, an equivalence ratio equal to 1 and a volumetric compression ratio of 5.8. The analysis demonstrates that, considering the simplicity and speed of the SZ model, the heat release calculation is sufficiently accurate and thus can be used for a first investigation of the combustion process.

The aim of this study is to find out the optimum operating conditions in a diesel engine fueled with compressed biogas (CBG) and pilot diesel dual-fuel. One-dimensional (1D) and three-dimensional (3D) computational fluid dynamics (CFD) code and multiobjective optimization code were employed to investigate the influence of CBG-diesel dual-fuel combustion performance and exhaust emissions on a diesel engine. In this paper, 1D engine code and multiobjective optimization code were coupled and evaluated about 15000 cases to define the proper boundary conditions. In addition, selected single diesel fuel (dodecane) and dual-fuel (CBG-diesel) combustion modes were modeled to compare the engine performances and exhaust emission characteristics by using CFD code under various operating conditions. In optimization study, start of pilot diesel fuel injection, CBG-diesel flow rate, and engine speed were optimized and selected cases were compared using CFD code. CBG and diesel fuels were defined as leading reactants using user defined code. The results showed that significantly lower NOx emissions were emitted under dual-fuel operation for all cases compared to single-fuel mode at all engine load conditions.

Hydrogen is a promising zero-carbon fuel for internal combustion engines; however, the geometric optimization of injectors for low-pressure direct-injection (LPDI) systems under lean-burn conditions remains underexplored. This study presents a high-fidelity optimization framework that couples a validated computational fluid dynamics (CFD) combustion model with a surrogate-assisted multi-objective genetic algorithm (MOGA). The CFD model was validated using particle image velocimetry (PIV) data from non-reacting flow experiments conducted in an optically accessible research engine developed by Sandia National Laboratories, ensuring accurate prediction of in-cylinder flow structures. The optimization focused on two critical geometric parameters: injector hole count and injection angle. Partial indicated mean effective pressure (pIMEP) and in-cylinder NO_x emissions were selected as conflicting objectives to balance performance and emissions. Adaptive mesh refinement (AMR) was employed to resolve transient in-cylinder flow and combustion dynamics with high spatial accuracy. Among 22 evaluated configurations including both capped and uncapped designs, the injector featuring three holes at a 15.24° injection angle outperformed the baseline, delivering improved mixture uniformity, reduced knock tendency, and lower NO_x emissions. These results demonstrate the potential of geometry-based optimization for advancing hydrogen-fueled LPDI engines toward cleaner and more efficient combustion strategies.