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Internal combustion engines (ICEs) exhaust emissions, particularly nitrogen oxides (NOx), have become a growing environmental and health concern. The biggest challenge for contemporary ICE industry is the development of clean ICEs, and the use of advanced design tools like Computational Fluid Dynamics (CFD) simulation is paramount to achieve this goal. In particular, the development of aftertreatment systems like Selective Catalyst Reduction (SCR) is a key step to reduce NOx emissions, and accurate and efficient CFD models are essential for its design and optimization. In this work, we propose a novel 3D-CFD methodology, which uses a Machine Learning (ML) approach as a surrogate model for the SCR catalyst chemistry, which aims to enhance accuracy of the simulations with a moderate computational cost. The ML approach is trained on a dataset generated from a set of 1D-CFD simulations of a single channel of an SCR catalyst.

Close-coupled aftertreatment systems (ATS) for automotive Diesel engines composed of DOC and SCR offer a significant potential in terms of pollutant emission control capability even with the introduction of more aggressive driving cycles and rigorous limits for type-approval tests. This is particularly important for incoming certification standards where the forecast is showing a trade-off towards ultra-low NOx emissions values. As the SCR system NOx conversion capability largely relies on both the UWS mixing device and on NOx sensors used to detect the actual NH3 slip and residual NOx concentration, developing numerical simulation tools for the analysis of the actual flow pattern and species concentration over peculiar sections of the exhaust system is crucial to support the ATS development process.

A comprehensive experimental and numerical analysis of two state-of-the-art diesel AfterTreatment Systems (ATS) for automotive applications is presented in this work. Both systems, designed to fulfill Euro 6 emissions regulations standards, consist of a closed-coupled Diesel Oxidation Catalyst (DOC) followed by a Selective Catalytic Reduction (SCR) catalyst coated on a Diesel Particulate Filter (DPF), also known as SCR on Filter (SCRoF or SCRF). While the two systems feature the same Urea Water Solution (UWS) injector, major differences could be observed in the UWS mixing device, which is placed upstream of the SCRoF, whose design represents a crucial challenge due to the severe flow uniformity and compact packaging requirements.

In order to optimize gasoline direct injection combustion systems, a very accurate control of the fuel flow rate from the injector must be attained, along with appropriate spray characteristics in terms of drop sizing and jets global penetration/diffusion in the combustion chamber. Injection rate measurement is therefore one of the crucial tasks to be accomplished in order both to develop direct injection systems and to properly match them with a given combustion system. Noticeably, the hydraulic characteristics of GDI injectors should be determined according to a non-intrusive measuring approach. Unfortunately, the operation of all conventional injection analyzers requires the injection in a volume filled with liquid and the application of a significant counter-pressure downstream of the injector. This feature prevents any operation with low pressure injection systems such as PFIs.

In the present paper an innovative approach for the shot-to-shot hydraulic characterization of low pressure injection systems is experimentally assessed. The proposed methodology is an inverse application of the Zeuch’s method, which in this case is applied to a closed volume upstream the injector instead of downstream of it as in conventional injection analyzers. By this approach, the well-known constraint of having a finite volume pressurized with the injected liquid downstream the injector is circumvented. As a consequence, with the proposed instrument low pressure injectors - such as PFI, fed with gasoline or water, SCR injectors - can operate with the prescribed upstream-downstream pressure differential. Further, the injector can spray directly in atmosphere or in any ambient at arbitrary pressure and temperature conditions, allowing the simultaneous application of other diagnostics such as imaging, momentum flux measurement or sizing instruments.

The effects of using blended renewable diesel fuel (30% vol.), obtained from Rapeseed Methyl Ester (RME) and Hydrotreated Vegetable Oil (HVO), in a Euro 5 small displacement passenger car diesel engine have been evaluated in this paper. The hydraulic behavior of the common rail injection system was verified in terms of injected volume and injection rate with both RME and HVO blends fuelling in comparison with commercial diesel. Further, the spray obtained with RME B30 was analyzed and compared with diesel in terms of global shape and penetration, to investigate the potential differences in the air-fuel mixing process. Then, the impact of a biofuel blend usage on engine performance at full load was first analyzed, adopting the same reference calibration for all the tested fuels.