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When performing vibration analysis of complex vehicle structures, it is often important to be able to evaluate the effects of design changes in one or more substructures (e.g., for design optimization). It may also be convenient to allow different components to be modeled independently by different groups or organizations. For both cases, it is inevitable that some substructures will have non-matching finite element meshes at the interface where they are physically connected. Thus, a key challenge is to be able to handle the dynamic assembly of components with non-matching meshes and the subsequent global vibration analysis in a systematic and efficient manner. To tackle this problem, the enhancement of component mode synthesis methods for handling finite element models partitioned into non-matching substructures is considered in this paper. Some existing methods are reviewed, and new methods are developed.

Vehicle ride motion produces a dynamic response of the seated operator, which disturbs the intended fingertip trajectory during reach activities. This perturbation induces deviations that must be corrected to successfully complete the reach. Visual and/or proprioceptive information are necessary to detect these deviations and provide feedback to the controller of the neuromuscular system. In an attempt to predict movement alterations and adjustments under whole body vibration exposure, a trajectory planning and feedback controller was developed using split sample data from a series of reaching experiments on a six degree of freedom motion platform.

ADRPM (Acoustic Detection Range Prediction Model) is a software program that models the propagation of acoustic energy through the atmosphere and evaluates detectable distance. ADRPM predicts the distance of detection for a noise source based on the acoustic signature of the source. The acoustic signature of a vehicle is computed by combining BEA and EBEA computations with nearfield measurements. The computed signature is utilized as the input to ADRPM. Once the initial detection range is predicted the main contributors to the acoustic detection are identified by ADRPM and their location on the vehicle is modified in order to assess the corresponding effect to the detectable distance of the vehicle.

When structures may have dynamic instability complex eigenvalue analysis is a useful tool to predict it. Although the accurate prediction itself is significant, it is also crucial to obtain sensitivity of unstable eigensolutions in order to eliminate instability efficiently. Since the mathematical relationship between stiffness matrix and design variables may seldom be found in reality, finite difference method has been typically used to approximate the sensitivity. The novel way to accurately calculate the sensitivity is developed without implementing finite difference method. This paper shows the advantages of analytical sensitivity analysis compared to other methods for choosing the most important components' eigenvalues. It also provides necessary amount of frequency shift for each chosen components' eigenvalue to eliminate unstable eigenvalues.

A formulation that accounts for manufacturing variability in the analysis of structural/acoustic systems is presented. The methodology incorporates the concept of fast probability integration with finite element (FEA) and boundary element analysis (BEA) for producing the probabilistic acoustic response of a structural/acoustic system. The advanced mean value method is used for integrating the system probability density function. FEA and BEA are combined for producing the acoustic response that constitutes the performance function. The probabilistic acoustic response is calculated in terms of a cumulative distribution function. The new methodology is used to illustrate the difference between the results from a probabilistic analysis that accounts for manufacturing uncertainty, and an equivalent deterministic simulation through applications. The probabilistic computations are validated by comparison to Monte Carlo simulations.

In this paper an algorithm is developed for combining finite element analysis and boundary element techniques in order to compute the noise radiated from a panel subjected to boundary layer loading. The excitation is presented in terms of the auto and cross power spectral densities of the fluctuating wall pressure. The structural finite element model for the panel is divided into a number of sub-panels. A uniform fluctuating pressure is applied as excitation on each sub-panel separately. The corresponding vibration is computed, and is utilized as excitation for an acoustic boundary element analysis. The acoustic response is computed at any data recovery point of interest. The relationships between the acoustic response and the pressure excitation applied at each particular sub-panel constitute a set of transfer functions.

Sound attenuation and flow loss reduction are often two competing demands in vehicle breathing systems. The present study considers a full vehicle exhaust system and investigates both the sound attenuation and the flow performance of production configurations including the catalyst, the resonator, and the muffler. Dynamometer experiments have been conducted with a firing Ford 3.0L, V-6 engine at wide-open throttle with speeds ranging from 1000 to 5000 rpm. Measurements including the flow rates, the temperatures and the absolute dynamic pressures of the hot exhaust gases at key locations (upstream and downstream of every component) with fast-response, water-cooled piezo-resistive pressure transducers facilitate the calculation of acoustic performance of each component, as well as the determination of flow losses caused by these elements and their influence on the engine performance.

Expansion chambers are widely used in the breathing systems of engines due to their desirable broadband noise attenuation characteristics. Following an earlier analytical and computational work of Sahasrabudhe et al. (1992), the present study investigates the effect of the length on the acoustic attenuation performance of concentric expansion chambers. Three approaches are employed to determine the transmission loss: (1) a two-dimensional, axisymmetric analytical solution; (2) a three-dimensional computational solution based on the boundary element method; and (3) experiments on an extended impedance tube setup with nine expansion chambers fabricated with fixed inlet and outlet ducts, fixed chamber diameters, and varying chamber length to diameter ratios from to 3.53. The results from all three approaches are shown to agree well. The effect of multi-dimensional propagation is discussed in comparison with the classical treatment for the breakdown of planar waves.