Periodic Reporting for period 2 - AHEAD (Advanced techniques for quantification and modelling of phase-change processes of renewable fuels and their blends)
Período documentado: 2021-01-21 hasta 2022-01-20
Decarbonising the transport sector, responsible for approximately 25% of Green House Gas (GHG) emissions, is increasingly urgent in the race to address climate change. The European Union (EU) has already taken bold steps in this direction with the launch of the European Green Deal, in which achieving net zero GHG emissions by 2050 is the primary strategic objective. Notwithstanding this fact, electrification of internal combustion engine (ICE) vehicles seems to be a long-term process. Recent forecasts are suggesting that electric passenger cars will achieve a market penetration of almost 58% by 2040. Nevertheless, at least for the next three decades, heavy-duty vehicles will be primarily powered by diesel engines, as current state-of-the-art limitations, for instance battery capacity and thermal management, do not allow a similar technology shift when high power output for an extended period of time is required. A disappointing ~25% growth in liquid fossil fuel demand globally is foreseen, due to increased commercial activity, people mobility and product transportation
Active research on clean combustion is necessitated by the stringent emissions legislation to be imposed in Europe and the US within the next decade. On a broader perspective, societal and environmental concerns on the use of fossil fuels and after-effects on climate change dictate the development of ICE with enhanced fuel efficiency and reduced emissions primarily operating with renewable fuels. The project demonstrated tangible outcomes in terms of novel diagnostics for multiphase flows, modelling approaches for complex thermodynamics and vaporising sprays, as well as fuel technology for greener internal-combustion engines. The research activities implemented in the course of the Fellowship have demonstrated that a systematic, quantitative characterisation of the fuel injection process, encompassing both the internal flow path of the injector orifice and the downstream spray region, is crucial for the understanding of combustion quality and eventually pollutants emissions. Novel imaging techniques based on x-ray and neutron irradiation have shown great potential for the two-phase flow quantification within real fuel-injector devices, a capability which, of course, is not possible with conventional optical imaging. Furthermore, the novel predictive method implemented, suitable for deriving the thermodynamic properties of fluids of complex composition, offers increased accuracy to the numerical simulations of vaporising fuel sprays. It must be emphasised that the method is not limited to multi-component fuels but can be extended to a wide range of fluids with relevance to industrial and biomedical applications. The numerical framework developed during the fellowship has been extended to non-deterministic modelling methodologies, namely Machine Learning algorithms, which have been proven more robust in the prediction of propagation of flashing sprays in comparison to physics-based models. More importantly the project has demonstrated the potential of synthetic and alternative fuels with respect to enhanced spray atomisation and mixing, eventually leading to reduced pollutants emissions.
Active research on clean combustion is necessitated by the stringent emissions legislation to be imposed in Europe and the US within the next decade. On a broader perspective, societal and environmental concerns on the use of fossil fuels and after-effects on climate change dictate the development of ICE with enhanced fuel efficiency and reduced emissions primarily operating with renewable fuels. The project demonstrated tangible outcomes in terms of novel diagnostics for multiphase flows, modelling approaches for complex thermodynamics and vaporising sprays, as well as fuel technology for greener internal-combustion engines. The research activities implemented in the course of the Fellowship have demonstrated that a systematic, quantitative characterisation of the fuel injection process, encompassing both the internal flow path of the injector orifice and the downstream spray region, is crucial for the understanding of combustion quality and eventually pollutants emissions. Novel imaging techniques based on x-ray and neutron irradiation have shown great potential for the two-phase flow quantification within real fuel-injector devices, a capability which, of course, is not possible with conventional optical imaging. Furthermore, the novel predictive method implemented, suitable for deriving the thermodynamic properties of fluids of complex composition, offers increased accuracy to the numerical simulations of vaporising fuel sprays. It must be emphasised that the method is not limited to multi-component fuels but can be extended to a wide range of fluids with relevance to industrial and biomedical applications. The numerical framework developed during the fellowship has been extended to non-deterministic modelling methodologies, namely Machine Learning algorithms, which have been proven more robust in the prediction of propagation of flashing sprays in comparison to physics-based models. More importantly the project has demonstrated the potential of synthetic and alternative fuels with respect to enhanced spray atomisation and mixing, eventually leading to reduced pollutants emissions.
Qualitative and quantitative measurements, comprising extinction, microscopy, diffuse-backlight-illumination and schlieren imaging, combined with computed tomography have been conducted in the internal flow path and the spray region of different gasoline and diesel-injector outlets for a wide range of conventional, renewable and additised gasoline and diesel blends. Evaluation has been conducted in realistic, pressure/temperature ambient conditions resembling those in the cylinders of IC engines under non-reacting and reacting conditions. In addition, quantitative (absorption) X-ray and neutron imaging has illustrated the extent and dynamics of cavitation forming in enlarged diesel-injector replicas. The wide dataset generated, comprises liquid/vapour fraction data in the internal flow path and spray region of different injector geometries, in-nozzle vorticity magnitude, liquid and vapour penetration data with reference to fuel sprays, droplet size distribution in the near-nozzle region and finally quantitative data for soot formation under reacting conditions. Furthermore, a numerical framework for the prediction of spray flow propagation has been implemented and validated against the obtained experimental measurements. The produced data has facilitated solid conclusions to be drawn regarding the influence of fuel thermodynamic and rheological properties, in-nozzle phase change and secondary-flow motion on the composition and expansion characteristics of the injected spray, which have been disseminated through journal publications, as well as participation to conferences, workshops and industrial events.
Novel experimental techniques have been implemented and evaluated in the frame of the project which will be of benefit to research with relevance to fuel injection equipment and to the scientific community of multi-phase flows in general. Special mention should be made to the novel high-speed imaging technique implemented combining diffused backlight illumination with tomographic reconstruction to quantify the three-dimensional composition of flashing and vaporising sprays. The research tasks of the fellowship also included the first-ever successful attempt to comparatively assess the suitability of different methodologies that can be classified as nuclear imaging, i.e. utilising x-ray irradiation and neutron radiation, to quantity cavitating flow in opaque orifices. Finally, in terms of numerical modelling, the novel PC-SAFT based framework implemented, has been found to enhance the accuracy of CFD simulations, disengaging them from the use of empirical models which rely on ad hoc tuning factors. Referring to the understanding of physical phenomena relevant to fuel injection, distinct characteristics, such as thermodynamic properties and rheological behaviour, of renewable and alternative (e.g. containing viscoelasticity-inducing agents) fuels have been highlighted that lead to enhanced atomisation behaviour and therefore combustion quality.
From a fuel technology standpoint, the efficiency of several alternative gasoline and diesel blends, including no-fossil samples, with low resource depletion potential have been comparatively assessed. Incorporation of such fuels in modern IC engines of hybrid vehicles will lead to enhanced fuel efficiency and reduced pollutants emissions, thus facilitating the compliance with strict EU environmental regulations, especially referring to heavy-duty and long-haul transportation. An extensive experimental dataset has been created with reference to fuel injection and combustion of a wide range of conventional, renewable and alternative (e.g. additised, synthetic) gasoline and diesel blends. Data have been made available to the relevant community through the Engine Combustion Network. The fuel-characterisation dataset developed will enable the relevant fuel industry to develop novel products, e.g. by creating conventional/renewable fuel blends at specified compositions or including atomisation-enhancing additives, of a more environmentally sustainable nature. Besides, the know-how produced on imaging techniques is directly applicable to the research and development departments of OEMs developing ICE and auxiliary systems.
From a fuel technology standpoint, the efficiency of several alternative gasoline and diesel blends, including no-fossil samples, with low resource depletion potential have been comparatively assessed. Incorporation of such fuels in modern IC engines of hybrid vehicles will lead to enhanced fuel efficiency and reduced pollutants emissions, thus facilitating the compliance with strict EU environmental regulations, especially referring to heavy-duty and long-haul transportation. An extensive experimental dataset has been created with reference to fuel injection and combustion of a wide range of conventional, renewable and alternative (e.g. additised, synthetic) gasoline and diesel blends. Data have been made available to the relevant community through the Engine Combustion Network. The fuel-characterisation dataset developed will enable the relevant fuel industry to develop novel products, e.g. by creating conventional/renewable fuel blends at specified compositions or including atomisation-enhancing additives, of a more environmentally sustainable nature. Besides, the know-how produced on imaging techniques is directly applicable to the research and development departments of OEMs developing ICE and auxiliary systems.