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Schlieren/shadowgraphy has been adopted in the combustion research as a standard technique for tip penetration analysis of sprays under diesel-like engine conditions. When dealing with schlieren images of reacting sprays, the combustion process and the subsequent light emission from the soot within the flame have revealed both limitations as well as considerations that deserve further investigation. Seeking for answers to such concerns, the current work reports an experimental study with this imaging technique where, besides spatial filtering at the Fourier plane, both short exposure time and chromatic filtering were performed to improve the resulting schlieren image, as well as the reliability of the subsequent tip penetration measurement. The proposed methodology has reduced uncertainties caused by artificial pixel saturation (blooming).

In the past few years’ various studies have shown how the application of a highly premixed dual fuel combustion for CI engines leads a strong reduction for both pollutant emissions and fuel consumption. In particular a drastic soot and NOx reduction were achieved. In spite of the most common strategy for dual fueling has been represented by using two different injection systems, various authors are considering the advantages of using a single injection system to directly inject blends in the chamber. In this scenario, a characterization of the behavior of such dual-fuel blend spray became necessary, both in terms of inert and reactive ambient conditions. In this work, a light extinction imaging (LEI) has been performed in order to obtain two-dimensional soot distribution information within a spray flame of different diesel/gasoline commercial fuel blends. All the measurements were conducted in an optically accessible two-stroke engine equipped with a single-hole injector.

The spatial and temporal locations of autoignition depend on fuel chemistry and the temperature, pressure, and mixing trajectories in the fuel jets. Dual-fuel systems can provide insight into fuel-chemistry aspects through variation of the proportions of fuels with different reactivities, and engine operating condition variations can provide information on physical effects. In this context, the spatial and temporal progression of two-stage autoignition of a diesel-fuel surrogate, n-heptane, in a lean-premixed charge of synthetic natural gas (NG) and air is imaged in an optically accessible heavy-duty diesel engine. The lean-premixed charge of NG is prepared by fumigation upstream of the engine intake manifold.

With ever-demanding emission legislations in Compression Ignition (CI) engines, new premixed combustion strategies have been developed in recent years seeking both, emissions and performance improvements. Since it has been shown that in-cylinder air flow affects the combustion process, and hence the overall engine performance, the study of swirling structures and its interaction with fuel injection are of great interest. In this regard, possible Turbulent Kinetic Energy (TKE) distribution changes after fuel injection may be a key parameter for achieving performance improvements by reducing in-cylinder heat transfer. Consequently, this paper aims to gain an insight into spray-swirl interaction through the analysis of in-cylinder velocity fields measured by Particle Image Velocimetry (PIV) when PCCI conditions are proposed. Experiments are carried out in a single cylinder optical Diesel engine with bowl-in-piston geometry.

Dual-mode dual-fuel combustion is a promising combustion concept to achieve the required emissions and CO2 reductions imposed by the next standards. Nonetheless, the fuel formulation requirements are stricter than for the single-fuel combustion concepts as the combustion concept relies on the reactivity of two different fuels. This work investigates the effect of the low reactivity fuel sensitivity (S=RON-MON) and the octane number at different operating conditions representative of the different combustion regimes found during the dual-mode dual-fuel operation. For this purpose, experimental tests were performed using a PRF 95 with three different sensitivities (S0, S5 and S10) at operating conditions of 25% load/950 rpm, 50%/1800 rpm and 100%/2200 rpm. Moreover, air sweeps varying ±10% around a reference air mass were performed at 25%/1800 rpm and 50%/1800 rpm. Conventional diesel fuel was used as high reactivity fuel in all the cases.

Predicting and preventing combustion anomalies leads to safe and efficient operation of the hydrogen internal combustion engine. This research presents the application of three machine learning (ML) models – K-Nearest Neighbors (KNN), Random Forest (RF) and Logistic Regression (LR) – for the prediction of combustion anomalies in a hydrogen internal combustion engine. A small experimental dataset was used to train the models and posterior experiments were used to evaluate their performance and predicting capabilities (both in operating points -speed and load- within the training dataset and operating points in other areas of the engine map). KNN and RF exhibit superior accuracy in classifying combustion anomalies in the training and testing data, particularly in minimizing false negatives, which could have detrimental effects on the engine.

Using renewable fuels is a reliable approach for decarbonization of combustion engines. iso-Butanol and n-butanol are known as longer chain alcohols and have the potential of being used as gasoline substitute or a renewable fraction of gasoline. The combustion behavior of renewable fuels in modern combustion engines and advanced combustion concepts is not well understood yet. Low-temperature combustion (LTC) is a concept that is a basis for some of the low emissions-high efficiency combustion technologies. Fuel ɸ-sensitivity is known as a key factor to be considered for tailoring fuels for these engines. The Lund ɸ-sensitivity method is an empirical test method for evaluation of the ɸ-sensitivity of liquid fuels and evaluate fuel behavior in thermal. iso-Butanol and n-butanol are two alcohols which like other alcohol exhibit nonlinear behavior when blended with (surrogate) gasoline in terms of RON and MON.