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In the aviation community, there is a high priority to develop all-electric aircraft. Electro-mechanical actuation systems would replace traditional, large, heavy and difficult-to-maintain hydraulic actuation systems. This movement from hydraulic actuation to electrical actuation enhances the flexibility to integrate redundancy and emergency system in future military aircraft. Elimination of the hydraulic fluid removes the possibility of leakage of corrosive hydraulic fluid and the associated fire hazard, as well as environmental concerns. The switch from hydraulic to electrical actuation provides additional benefits in reduced aircraft weight, improved survivability and improved maintainability. The heat load in an electro-mechanical actuation (EMA) is highly transient and localized in nature; therefore a phase change material could be embedded in the heat generating components to store peak heat load.

The development of electromechanical actuators (EMAs) is the key technology to build an all-electric aircraft. One of the greatest hurdles to replacing all hydraulic actuators on an aircraft with EMAs is the acquisition, transport and rejection of waste heat generated within the EMAs. The absence of hydraulic fluids removes an attractive and effective means of acquiring and transporting the heat. To address thermal management under limited cooling options, accurate spatial and temporal information on heat generation must be obtained and carefully monitored. In military aircraft, the heat loads of EMAs are highly transient and localized. Consequently, a FEA-based thermal model should have high spatial and temporal resolution. This requires tremendous calculation resources if a whole flight mission simulation is needed. A lumped node thermal network is therefore needed which can correctly identify the hot spot locations and can perform the calculations in a much shorter time.

This paper describes the integrated modeling of a permanent magnet (PM) motor used in an electromechanical actuator (EMA). A nonlinear, lumped-element motor electric model is detailed. The parameters, including nonlinear inductance, rotor flux linkage, and thermal resistances, and capacitances, are tuned using FEM models of a real, commercial motor. The field-oriented control (FOC) scheme and the lumped-element thermal model are also described.

In this paper the nature and analytical methodologies for sheet metal panel oil canning are introduced. Lab tests, numerical predictions using finite element analysis and their correlations on oil canning of a door outer panel are described. Different modeling approaches in finite element analysis are discussed, and a simplified approach of loading by using a coupling element is recommended.

Springback study on a Dodge Ram fender outer panel is detailed in this paper. A simple measurement fixture is designed for the panel, wherein non-contact laser scan technology is applied The measurement data are compared with the original CAD design surface and deviation contour maps are obtained. Consistency of measurement is studied at different sections among three samples. Details of FEA simulations are outlined. The comparison between measurement and simulation prediction is summarized. A method to describe the consistency of measurement and the accuracy of simulation prediction is proposed. The targets for measurement consistency and simulation accuracy are verified. A sensitivity analysis is also performed to investigate various simulation input parameters.

The use of commercial finite element analysis (FEA) software to perform stamping feasibility studies of automotive components has grown extensively over the last decade. Although product and process engineers have now come to rely heavily on results from FEA simulation for manufacturability of components, the prediction of springback has still not been perfected. Springback prediction for simple geometries is found to be quite accurate while springback prediction in complex components fails to compare with experimental results. Since most forming simulation FEA software uses a dynamic explicit solution method, the choice of various input parameters greatly affects the prediction of post formed stresses in the final component. Accurate stress prediction is critical for determination of springback, therefore this study focuses on the effects of some of the simulation parameters such as, element size, tool/loading speed and loading profile.

The springback behavior might be different due to different gap clearances between die and punch. A study using FEA simulation is done to investigate the die gap effect. A 3D brick element and an explicit-implicit method are employed to investigate a few simple problems. A draw form, a crash form with an upper pad and a flange form are investigated separately. Numisheet’93 2D draw bending springback problem is also investigated using an explicit dynamic code. Comparisons between springback simulation results on several different die gaps are illustrated. The Kirchhoff assumption of C° shell element and the Mindlin/Love assumption of thin shell element are also examined on different cases. A case study then is performed on a rail type panel. Conclusions and recommendations for future studies are summarized.

A springback study on three rail type panels is summarized. Numisheet'96 S-rail, A/S P rail II and a Daimlerchrysler rail are presented with experiment data and FEA simulation predictions. The details of the measurement on experiment samples and simulation models are illustrated. The comparison between the experiment data and the simulation results from four different softwares is made on separate cases. The correlation between experiment data and simulation results is analyzed.

A study on the FEA simulation of the springback prediction is summarized. The discussion is focused on the accuracy of the simulation and the factors that might contribute to the inaccurate results of the simulation. First, springback simulation results based on both 3 parameter Barlat plasticity model and transversely anisotropic plasticity model are studied. The numisheet'93 2D draw bending problem and a rail type automobile panel are selected for the material model study using LS-DYNA and LS-NIKE. The simulations based on different friction coefficients along the rolling direction and the transverse direction are studied using the DaimlerChrysler in-house FEA code Cform. A study is also performed to investigate the different springback behavior due to friction coefficient changes between the flat tooling area and the curved tooling area. Some other issues such as the dynamic effect and the penalty factor effect are also briefly discussed.