On Flow Predictions in Fuel Filler Pipe Design - Physical Testing vs Computational Fluid Dynamics

University essay from Linköpings universitet/Mekanisk värmeteori och strömningslära; Linköpings universitet/Tekniska högskolan

Abstract: The development of a fuel filler pipe is based solely on experience and physical experiment. The challenge lies in designing the pipe to fulfill the customer needs. In other words designing the pipe such as the fuel flow does not splash back on the fuel dispenser causing a premature shut off. To improve this “trial-and-error” based development a computational fluid dynamics (CFD) model of the refueling process is investigated. In this thesis a CFD model has been developed that can predict the fuel flow in the filler pipe. Worst case scenario of the refueling process is during the first second when the tank is partially filled. The most critical fluid is diesel due to the commercially high volume flow of 55 l/min. Due to limitations of computational resources the simulations are focused on the first second of the refueling process. The challenge in this project is creating a CFD model that is time efficient, thus require the least amount of computational resources necessary to provide useful information. A multiphase model is required to simulate the refueling process. In this project the implicit volume of fluid (VOF) has been used which has previously proven to be a suitable choice for refueling simulations. The project is divided into two parts. Part one starts with experiments and simulations of a simplified fuel system with water as acting liquid with a Reynolds number of 90 000. A short comparison between three different turbulence models has been investigated (LES, DES and URANS) where the most promising turbulence model is URANS, specifically the SST k-ω model. A sensitivity analysis was performed on the chosen turbulence model. Between the chosen mesh and the densest mesh the difference of streamwise velocity in the boundary layer was 2.6 %. The chosen mesh with 1.9 M cells and a time step of 1e-4 s was found to be the best correlating model with respect to the experiments. In part two a real fuel filling system was investigated both with experiments and simulations with the same computational model as the chosen one from part one. The change of fluid and geometry resulted in a lower Reynolds number of 12 000. Two different versions of the fuel system was investigated; with a bypass pipe and without a bypass pipe. Because of a larger volumetric region the resulting mesh had 3.7 M cells. The finished model takes about 230 h on a local workstation with 11 cores. On a cluster with 200 cores the same simulation takes 30 h. The resulting model suffered from interpolation errors at the inlet which resulted in a volume flow of 50 l/min as opposed to 55 l/min in the experiments. Despite the difference the model could capture the key flow characteristics. With the developed model a new filler pipe can be easily implemented and provide results in shorter time than a prototype filler pipe can be ordered. This will increase the chances of ordering one single prototype that fulfills all requirements. While the simulation model cannot completely replace verification by experiments it provides information that transforms the development of the filler pipe to knowledge based development.

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