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After establishing the performance requirements and initial design assumptions, CAE concept models are used to set targets for major structural components to achieve desirable crash performance. When the designs of these major components become available they are analyzed in detail using nonlinear crash finite element models to evaluate their performance. All these components are assembled together later in a full car model to predict the overall vehicle crash performance. If the analysis shows that the targets are met, the design drawings are released for prototype fabrication. When CAE tools are effectively used, it will reduce product development cycle time and the number of prototypes. Crash analysis methodology has been validated and applied for steel automotive product development. Recently, aluminum is replacing steel for lighter and more fuel efficient automobiles. In general aluminum has quite different performance from steel, in particular with lower ductility.

A multipurpose test-bed for integrating user interface and sensor technologies has been developed, based on a client- server architecture. Various interaction modalities (Speech recognition, 3-D Audio, Pointing, wireless Handheld- PC-based control and interaction, sensor interaction, etc.) are implemented as servers, encapsulating and exposing commercial and research software packages. The system allows for integrated user interaction with large and small displays using speech commands combined with pointing, spatialized audio, and other modalities. Simultaneous and independent speech recognition for two users is supported; users may be equipped with conventional acoustic or new body-coupled microphones.

Human Computer Interface (HCI) in applications for the maintenance of complex machinery such as an aircraft can be enhanced by exploiting new developments in HCI. We have developed a multimodal HCI demonstration system for maintenance applications, incorporating Augmented Reality (AR), Speech Recognition, and 3- dimensional audio technologies. The Augmented Reality interface is based on an original dynamic tracking approach to provide rapid update of the scene with graphical overlays. We enhance the use of this interface with speech recognition to control the system and to add annotations using dictation-based text information. A combination of 3-D audio, graphic animations, and text displays is used to communicate information to the user.