Fossil fuel consumption is expected to increase by over 20% over the next 3 decades in order to meet the increasing demand for infrastructure, trade and transportation. Development of engines complying with the forthcoming 2020 emission legislations, relies on the effective design of advanced high-pressure fuel injection systems and represents a key industrial priority. Such advanced injection systems can improve internal combustion engine performance in the following ways:
- Formation of high velocity fuel jets that lead to finer atomization and better air/fuel mixing.
- Increase of engine efficiency.
- Decrease of cavitation side effects, reduction of erosion damage and improvement of injector reliability.
- Reduction of soot and CO2 emissions.
The objectives of the present project involve the study of high pressure fuel systems injecting fuel at high temperature and pressure conditions, relevant to Diesel engines. The project involved experiments (outgoing phase at Sandia National Laboratories) and simulations (return phase) to study the phenomena occurring during fuel injection and how they can be exploited to improve engine design.
In particular, the following objectives have been achieved, each corresponding to the respective work package of the project:
(1) advanced thermodynamic models have been developed for describing fuel properties at extreme conditions. These models are demonstrated to accurately describe the thermodynamic and transport properties of Diesel surrogates/fuels and are superior to the current state of the art.
(2) novel experiments have been performed at Sandia National Laboratories (SNL), involving quantification of spray characteristics. Additionally, new techniques have been developed for in-nozzle diagnostics.
(3) numerical tools have been developed to predict the coupled in-nozzle flow and spray, using the developed models of objective (1) above. These tools are capable of describing all the relevant physical mechanisms during diesel fuel injection, with less ad-hoc assumptions of existing models.
(4) the aforementioned numerical tools have been validated and adapted to industrial cases, involving real-world complexities. Additionally, having in mind the application of said tools to an industrial setting, where fast, but accurate calculations are required, novel Machine Learning methods have been developed for predicting spray characteristics.
(5) the Researcher's skills have been greatly expanded, as the project enabled him to undergo a wide variety of activities, ranging from hands-on experiments at high-end facilities around the world (at Sandia National Laboratories, Argonne National Laboratory, Paul Scherrer Institut), broadening his knowledge on thermodynamics and numerical methods and finally disseminating important findings through the participation in conferences and workshops and publications in journals.
