An experimental campaign was performed to study the behavior of a common-rail Diesel engine in automotive configuration when it is fuelled with blends of Diesel fuel (DF) and waste cooking oil (WCO). In particular the tested fuels are: B20 blend, composed of 20% WCO and 80% DF; B50, composed of 50% WCO and 50% DF; WCO 100% and 100% DF. \ud
In order to fuel the engine with fuel having a similar viscosity, this quantity, together with density, has been meas-ured at temperature ranging from rom to about 80 °C. According to these measurements, before fuelling the engine B20 was heated up to 35 °C and B50 to 75 °C.\ud
An in-house software was developed to acquire the data elaborated by the electronic control unit.\ud
Results show the trend in torque and global efficiency at different gas pedal position (gpp) and different engine speed. The experiments show that larger discrepancies are measured at smaller gpp values, while at larger ones dif-ferences become smaller. A similar trend is noticed for engine global efficiency
Induced draft fans extract coal flred boiler combustion products, including particles of un-burnt coal and ash. As a consequence of the particles, the axial fan blades' leading edges are subject to erosion. Erosion results in the loss of the blade leading edge aerodynamic proflle and a reduction of blade chord and effective camber that together degrade aerodynamic performance. An experimental study demonstrated that while the degradation of aerodynamic performance begins gradually, it collapses as blade erosion reaches a critical limit. This paper presents a numerical study on the evolution of blade leading edge erosion patterns in an axial induced draft fan. The authors calculated particle trajectories using an in-house computational fluid dynamic (CED) solver coupled with a trajectory predicting solver based on an original finite element interpolation scheme. The numerical study clarifles the influence of flow structure, initial blade geometry, particle size, and concentration on erosion pattern.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.