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With growing concern about global warming, alternatives to fossil fuels in internal combustion engines are searched. In this context, hydrogen is one of the most interesting fuels as it shows excellent combustion properties such as laminar flame speed and energy density. In this work a CFD methodology for 3D-CFD in-cylinder simulations of engine combustion is proposed and its predictive capabilities are validated against test-bench data from a direct injection spark-ignition (DISI) prototype. The original engine is a naturally aspirated, single cylinder compression ignition (Diesel fueled) unit. It is modified substituting the Diesel injector with a spark plug, adding two direct gas injectors, and lowering the compression ratio to run with hydrogen fuel. A 3D-CFD model is built, embedding in-house developed ignition and heat transfer models besides G-equation one for combustion.

The accurate representation of Internal Combustion Engine (ICE) flows via CFD is an extremely complex task: it strongly depends on a combination of highly impacting factors, such as grid resolution (both local and global), choice of the turbulence model, numeric schemes and mesh motion technique. A well-founded choice must be made in order to avoid excessive computational cost and numerical difficulties arising from the combination of fine computational grids, high-order numeric schemes and geometrical complexity typical of ICEs. The paper focuses on the comparison between different mesh motion technologies, namely layer addition and removal, morphing/remapping and overset grids. Different grid strategies for a chosen mesh motion technology are also discussed. The performance of each mesh technology and grid strategy is evaluated in terms of accuracy and computational efficiency (stability, scalability, robustness).

Engine knock is emerging as the main limiting factor for modern spark-ignition (SI) engines, facing increasing thermal loads and seeking demanding efficiency targets. To fulfill these requirements, the engine operating point must be moved as close as possible to the onset of abnormal combustion events. The turbulent regime characterizing in-cylinder flows and SI combustion leads to serious fluctuations between consecutive engine cycles. This forces the engine designer to further distance the target condition from its theoretical optimum, in order to prevent abnormal combustion to severely damage the engine components just because of few individual heavy-knocking cycles. A RANS-based model is presented in this study, which is able to predict not only the ensemble average knock occurrence but also a knock probability. This improves the knock tendency characterization, since the mean knock onset alone is a poorly meaningful indication in a stochastic event such as engine knock.

Knock is one of the main limitations on Spark-Ignited (SI) Internal Combustion Engine (ICE) performance and efficiency and so has been the object of study for over one hundred years. Great strides have been made in terms of understanding in that time, but certain rather elementary practical problems remain. One of these is how to interpret if a running engine is knocking and how likely this is to result in damage. Knocking in a development environment is typically quantified based on numerical descriptions of the high frequency content of a cylinder pressure signal. Certain key frequencies are observed, which Draper [1] explained with fundamental acoustic theory back in 1935. Since then, a number of approaches of varying complexity have been employed to correlate what is happening within the chamber with what is measured by a pressure transducer.

In the present paper, two different methodologies are adopted and critically integrated to analyze the knock behavior of a last generation small size spark ignition (SI) turbocharged VVA engine. Particularly, two full load operating points are selected, exhibiting relevant differences in terms of knock proximity. On one side, a knock investigation is carried out by means of an Auto-Regressive technique (AR model) to process experimental in-cylinder pressure signals. This mathematical procedure is used to estimate the statistical distribution of knocking cycles and provide a validation of the following 1D-3D knock investigations. On the other side, an integrated numerical approach is set up, based on the synergic use of 1D and 3D simulation tools. The 1D engine model is developed within the commercial software GT-Power™. It is used to provide time-varying boundary conditions (BCs) for the 3D code, Star-CD™.

In-cylinder large scale and small scale structures are widely recognized to strongly influence the mixing process in HSDI Diesel engines, and therefore combustion and pollutant emissions. In particular, swirl motion intensity and temporal evolution during the intake and compression strokes must be correctly estimated to properly target the spray jets. The experimental characterization of the attitude of a valve/port assembly to promote swirl is traditionally limited to the steady flow bench, in which the analysis is carried out for fixed valve positions / fixed pressure drops and with no piston. Since flow bench analyses cannot reproduce the highly complex instantaneous flow conditions typical of actual engine operations, the use of fully-transient in-cylinder numerical simulations can become extremely useful to correctly address the engine ability to promote adequate flow structures and patterns.

The paper reports the application of Proper Orthogonal Decomposition (POD) to LES calculations for the analysis of combustion and knock tendency in a highly downsized turbocharged GDI engine that is currently under production. In order to qualitatively match the cyclic variability of the combustion process, Large-Eddy Simulation (LES) of the closed-valve portion of the cycle is used with cycle-dependent initial conditions from a previous multi-cycle analysis [1, 2, 3]. Detailed chemical modelling of fuel's auto-ignition quality is considered through an ad-hoc implemented look-up table approach, as a trade-off between the need for a reasonable representation of the chemistry and that of limiting the computational cost of the LES simulations. Experimental tests were conducted operating the engine at knock-limited spark advance (KLSA) and the proposed knock model was previously validated for such engine setup [3].

The paper aims at defining a methodology for the prediction and understanding of knock tendency in internal combustion engine piston crevices by means of CFD simulations. The motivation for the analysis comes from a real design requirement which appeared during the development of a new high performance SI unit: it is in fact widely known that, in high performance engines (especially the turbocharged ones), the high values of pressure and temperature inside the combustion chamber during the engine cycle may cause knocking phenomena. “Standard” knock can be easily recognized by direct observation of the in-cylinder measured pressure trace; it is then possible to undertake proper actions and implement design and control improvements to prevent it with relatively standard 3D-CFD analyses.

The occurrence of knock is the most limiting hindrance for modern Spark-Ignition (SI) engines. In order to understand its origin and move the operating condition as close as possible to onset of this potentially harmful phenomenon, a joint experimental and numerical investigation is the most recommended approach. A preliminary experimental activity was carried out at IM-CNR on a 0.4 liter GDI unit, equipped with a flat transparent piston. The analysis of flame front morphology allowed to correlate high levels of flame front wrinkling and negative curvature to knock prone operating conditions, such as increased spark timings or high levels of exhaust back-pressure. In this study a detailed CFD analysis is carried out for the same engine and operating point as the experiments. The aim of this activity is to deeper investigate the reasons behind the main outcomes of the experimental campaign.

In spark-ignited direct-injected engines, the formation of fuel pools on the piston is one of the major promoters of unburnt hydrocarbons and soot: in order to comply with the increasingly stringent emission regulations (EU6 and forthcoming), it is therefore necessary to limit fuel deposit formation. The combined use of advanced experimental techniques and detailed 3D-CFD simulations can help to understand the mechanisms driving fuel pool formation. In the paper, a combined experimental and numerical characterization of pool formation in a GDI engine is carried out to investigate and understand the complex interplay of all the mentioned factors. In particular, a low-load low-rpm engine operation is investigated for different ignition phasing, and the impact of both fuel formulation and instantaneous piston temperature variations in the CFD analyses are evaluated.

The recent interest in alternative non-fossil fuels has led researchers to evaluate several alcohol-based formulations. However, one of the main requirements for innovative fuels is to be compatible with existing units’ hardware, so that full replacement or smart flexible-fuel strategies can be smoothly adopted. n-Butanol is considered as a promising candidate to replace commercial gasoline, given its ease of production from bio-mass and its main physical and chemical properties similar to those of Gasoline. The compared behavior of n-butanol and gasoline was analyzed in an optically-accessible DISI engine in a previous paper [1]. CFD simulations explained the main outcomes of the experimental campaign in terms of combustion behavior for two operating conditions. In particular, the first-order role of the slower evaporation rate of n-butanol compared to gasoline was highlighted when the two fuels were operated under the same injection phasing.

Polymer Electrolyte Membrane Fuel Cells (PEMFCs) are undergoing a rapid development, due to the ever-growing interest towards their use to decarbonize power generation applications. In the transportation sector, a key technological challenge is their thermal management, i.e. the ability to preserve the membrane at the optimal thermal state to maximize the generated power. This corresponds to a narrow temperature range of 75-80°C, possibly uniformly distributed over the entire active surface. The achievement of such a requirement is complicated by the generation of thermal power, the limited exchange area for radiators, and the poor heat transfer performance of conventional coolants (e.g., ethylene glycol). The interconnection of thermal/fluid/electrochemical processes in PEMFCs renders heat rejection as a potential performance limiter, suggesting its maximization for power density increase.

CFD simulations of reacting flows are fundamental investigation tools used to predict combustion behaviour and pollutants formation in modern internal combustion engines. Focusing on spark-ignited units, most of the flamelet-based combustion models adopted in current simulations use the fuel/air/residual laminar flame propagation speed as a background to predict the turbulent flame speed. This, in turn, is a fundamental requirement to model the effective burn rate. A consolidated approach in engine combustion simulations relies on the adoption of empirical correlations for laminar flame speed, which are derived from fitting of combustion experiments. However, these last are conducted at pressure and temperature ranges largely different from those encountered in engines: for this reason, correlation extrapolation at engine conditions is inevitably accepted. As a consequence, relevant differences between proposed correlations emerge even for the same fuel and conditions.

Enhanced calibration strategies and innovative engine combustion technologies are required to meet the new limits on exhaust gas emissions enforced in the field of marine propulsion and on-board energy production. The goal of the paper is to optimize the control parameters of a 4.2 dm3 unit displacement marine DI Diesel engine, in order to enhance the efficiency of the combustion system and reduce engine out emissions. The investigation is carried out by means of experimental tests and CFD simulations. For a better control of the testing conditions, the experimental activity is performed on a single cylinder prototype, while the engine test bench is specifically designed to simulate different levels of boosting. The numerical investigations are carried out using a set of different CFD tools: GT-Power for the engine cycle analysis, STAR-CD for the study of the in-cylinder flow, and a customized version of the KIVA-3V code for combustion.

CFD and FE tools are intensively adopted by engine manufacturers in order to prevent thermo-mechanical failures reducing time- and cost-to market. The capability to predict correctly the physical factors leading to damages is hence essential for their application in the industrial practice. This is even more important for last generation SI engines, where the more and more stringent need to lower fuel consumption and pollutant emissions is pushing designers to reduce engine displacement in favor of higher specific power, usually obtained by means of turbocharging. This brings to a new generation of SI engines characterized by higher and higher adiabatic efficiency and thermo-mechanical loads. A recent research highlighted the different behavior of the thermal boundary layer of such engines operated at high revving speeds and high loads if compared to the same engines operated at low loads and revving speeds or even engines with a lower specific power.

The detailed study of part-load conditions is essential to characterize engine-out emissions in key operating conditions. The relevance of part-load operations is further emphasized by the recent regulations such as the new WLTP standard. Combustion development at part-load operations depends on a complex interplay between moderate turbulence levels (low engine speed and tumble ratio), low in-cylinder pressure and temperature, and stoichiometric-to-lean mixture quality (to maximize fuel efficiency). From a modelling standpoint, the reduced turbulence intensity compared to full-load operations complicates the interaction between different sub-models (e.g., reconsideration of the flamelet hypothesis adopted by common combustion models). In this article, the authors focus on chemistry-based simulations for laminar flame speed of gasoline surrogates at conditions typical of part-load operations. The analysis is an extension of a previous study focused on full-load operations.

Engine knock is one of the most limiting factors for modern Spark-Ignition (SI) engines to achieve high efficiency targets. The stochastic nature of knock in SI units hinders the predictive capability of RANS knock models, which are based on ensemble averaged quantities. To this aim, a knock model grounded in statistics was recently developed in the RANS formalism. The model is able to infer a presumed log-normal distribution of knocking cycles from a single RANS simulation by means of transport equations for variances and turbulence-derived probability density functions (PDFs) for physical quantities. As a main advantage, the model is able to estimate the earliest knock severity experienced when moving the operating condition into the knocking regime.

With the aim of identifying technical solutions to lower the particulate matter emissions, the engine research community made a consistent effort to investigate the root causes leading to soot formation. Nowadays, the computational power increase allows the use of advanced soot emissions models in 3D-CFD turbulent reacting flows simulations. However, the adaptation of soot models originally developed for Diesel applications to gasoline direct injection engines is still an ongoing process. A limited number of studies in literature attempted to model soot produced by gasoline direct injection engines, obtaining a qualitative agreement with the experiments. To the authors’ best knowledge, none of the previous studies provided a methodology to quantitatively match particulate matter, particulate number and particle size distribution function measured at the exhaust without a case-by-case soot model tuning.

Hybrid URANS/LES turbulence modeling is rapidly emerging as a valuable complement to standard LES for full-engine multi-cycle simulation. Among the available approaches, zonal hybrids are potentially attractive due to the possibility of clearly identify URANS and LES zones, eventually introducing further zone types with dynamically switching behavior. The present work aims at evaluating the impact of different zonal configurations on the simulated flow statistics using the well-assessed TCC-III experimental engine setup. More specifically, different methods (URANS, LES or seamless DES) are applied inside the cylinder volume, as well as into the intake/exhaust ports and plenums. For each of the five tested configurations, in-cylinder flow features are compared against the reference TCC-III experimental measurements, in terms of velocity field statistics and quality indices.

The development of the additive manufacturing technology has enabled the design of components with complex structures that were previously unfeasible with conventional techniques. Among them, the Triply Periodic Minimal Surface (TPMS) structures are gaining scientific interest in several applications. Thanks to their high surface-to-volume ratio, lightweight construction, and exceptional mechanical properties, TPMS structures are being investigated for the production of high-performance heat exchangers to be adopted in different industrial fields, such as automotive and aerospace. Another significant advantage of the TPMS structures is their high degree of design flexibility. Each structure is created by replicating a characteristic unit cell in the three spatial dimensions. The three key parameters, namely cell type, cell dimension and wall thickness can be adjusted to provide considerable versatility in the design process.