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This paper presents a method and corresponding software implementation for powertrain (PWT) mounting system layout design for decoupling rigid-body modes in the torque roll axis system. The novelty in the proposed method is that it requires a minimal set of inputs for determining mount topology, orientation and stiffness properties for decoupling powertrain modes, and as such it can be used at early design stages, unlike the conventional approaches based on analysis and optimization techniques. Consequently, PWT mounts can be positioned and oriented close to their optimal configuration, allowing to develop more realistic full vehicle models for conceptual (or early stage) designs and to run a more accurate dynamic analysis concerning secondary ride and vibrations. The proposed methodology is illustrated on a powertrain mounting system design example case.

Acoustic performance of vehicle engines is a real challenge for powertrain design engineers. Quiet engines are required to reduce noise pollution and satisfy pass-by noise regulations, but also to improve the driving comfort. Simulation techniques such as the Boundary Element Method (BEM) have already been available for some time and allow predicting the vibro-acoustic response of engines. Although the accuracy of these simulation techniques has been proven, a challenge still remains in the required computation time. Given the large amount of speeds for a full engine run-up and the need to cover a large frequency range, computation times are significant, which limits the possibility to perform many design iterations to optimize the system. In 2001, Acoustic Transfer Vectors (ATV) [1] have been presented to adequately deal with multiple rpm. The ATV provide the acoustic response for unit surface velocities and are therefore independent from the engine's actual surface vibrations.

The development of new design tools to predict the vibro-acoustic behavior within the vehicle development process is of essential importance to achieve better products in an ever shorter timeframe. In this paper, an energy flow post-processing tool for structural dynamic analysis is presented. The method is based on the conversion of conventional finite element (FE) results into energy quantities corresponding with each of the vehicle subcomponents. Based on the global dynamic system behavior and local subcomponent descriptions, one can efficiently evaluate the energy distribution and analyze the vibro-acoustic behavior in complex structures. By using energy as a response variable, instead of conventional design variables as pressure or velocity, one can obtain important information regarding the understanding of the vibro-acoustic behavior of the system.

Inverse numerical acoustics is a method which reconstructs the source surface normal velocity from the sound measured in the near-field around the source. This is of particular interest when the source is rotating or moving, too light or too hot to be instrumented by accelerometers. The use of laser vibrometers is often of no remedy due to the complex shape of the source. The Inverse Numerical Acoustics technique is based on the inversion of transfer relations (Acoustic Transfer Vectors) using truncated Singular Value Decomposition (SVD). Most of the time the system is underdetermined which results in a non unique solution. The solution obtained by the truncated SVD is the minimal solution in the RMS sense. This paper is investigating the impact of non homogeneities in the mesh density (local mesh refinement) on the retrieved solution for underdetermined systems. It will be shown that if transfer quantities are inverted as such, big elements get a higher weight in the inversion.

While CAE methods allow improving nominal product design using virtual prototypes, uncertainty and variability in properties and manufacturing processes lead to scatter in actual performances. Uncertainty must hence be incorporated in the CAE process to guarantee the robustness and reliability of the design. This paper presents an overview of uncertainty-based design in automotive and aerospace engineering. Fuzzy methods take uncertainty into account, whereas reliability analysis and a reliability-based design optimization framework can deal with variability. Key enabling technologies to alleviate the computational burden, such as workflow automation, substructuring and design of experiments, are discussed, and industrial applications are presented.

This paper discusses the requirement for CAE methods to properly take into account the variabilities and uncertainties that characterizes design input properties without leading to oversized structures. Optimizing the structural behaviour while taking into account expected variability and uncertainty in the structure and its model, requires the adoption of a reliability-based design optimization approach. This paper starts with an overview of the problem of simulation uncertainty. The key focus is then on the description of the most commonly used methods and enabling tools for reliability analysis and reliability based design optimization. The theory is illustrated by real automotive design problems.