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When a vehicle with a partially filled fuel tank undergoes sudden acceleration, braking, turning or pitching motion, fuel sloshing is experienced. It is important to establish a CAE methodology to accurately predict slosh phenomenon. Fuel slosh can lead to many failure modes such as noise, erroneous fuel indication, irregular fuel supply at low fuel level and durability issues caused by high impact forces on tank surface and internal parts. This paper summarizes activities carried out by the fuel system team at Ford Motor Company to develop and validate such CAE methodology. In particular two methods are discussed here. The first method is Volume Of Fluid (VOF) based incompressible multiphase Eulerian transient CAE method. The CFD solvers used here are Star CD and Star CCM+. The second method incorporates Fluid-Structure interaction (FSI) using Arbitrary Lagrangian-Eulerian (ALE) formulation.

With years of experience in applying CAE (Computer-Aided Engineering) tools in different automotive plastics component design analyses, authors try to define the accuracy of CAE simulations through three carefully selected case studies: natural frequency prediction, vibration stress calculation, and fatigue analysis. The first case study demonstrates that CAE is able to achieve great accuracy in predicting structural global properties such as natural frequency. The second case shows that CAE results do not correlate so well for the predictions of local properties such as vibration induced stress or strain response, while the third one indicates that CAE predictions on A to B comparison is always accurate even in the case of fatigue life prediction, that is known as a difficult task. Therefore, the CAE global property predictions should weigh heavier in plastic component design evaluation than on the local ones.

In this paper, a CAE (Computer-Aided Engineering) methodology to simulate the vibration test and predict fatigue life of head lamp bulb shield is presented. A modal analysis is performed first to determine the critical elements from the strain energy density distribution patterns. A random vibration frequency response analysis is then performed to monitor the stress response power spectral densities (PSDs) for critical elements due to the g-load input PSDs, measured at the mounting point in all three directions. Fatigue life can be estimated based on the stress response PSDs and material S-N curve by using Dirlik's method. The fundamentals for frequency domain fatigue analysis are reviewed and a case study with test correlation is then presented.