Fuel atomization and combustion at engine-like conditions are complicated and sensitive processes which make it hard to perform quantitative experiments with high precision and reproducibility. A better understanding of the processes can be obtained by controlling the boundary conditions. Variable parameters with an important influence on the sprays include fuel temperature, chamber temperature, injection pressure, gas velocity. Controlling all these parameters in an experimental setup is not evident since a lot of them fluctuate with time or interact with each other. Constant volume combustion chambers, using the pre-combustion method, have already shown to be a useful experimental tool for this kind of research purposes. The obtained quantitative results can in a next step be used to evaluate either multi-dimensional or simplified lower dimensional models.
In this work the importance of temperature dependency of the fuel properties and spray characteristics is shown, especially when comparing different and viscous fuels. As a consequence, temperature of both the fuel and ambient need to be controlled. The quantitative results are unique for each experimental setup, however, the methods, guidelines and conclusions are useful for any research activity. A method with good accuracy for determining the fuel temperature in the injector is proposed. The temperature distribution inside the constant volume combustion chamber during and after pre-combustion is experimentally evaluated with fast responding thermocouples. The flow and mixing inside the vessel is mainly determined by the fan to obtain a fast and complete combustion as well as a homogeneous resulting temperature and velocity field at time of injection. Finally, the influence of the pre-combustion upon the in-nozzle temperature is evaluated. The resulting effect on the fuel temperature is estimated and found to be negligible. The same conclusion holds for the fuel temperature increase during injection. As a result, the initial conditions at start of injection can be estimated as well as the uncertainties and reproducibility.