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Vibro-acoustic simulation methods such as FEM and BEM have made an enormous progress for modelling and describing the acoustic and vibro-acoustic behaviour of mechanical systems. In order to make these techniques truly become part of the “virtual” industrial design process however, the specific challenges related to industrial-sized problems must be overcome. The paper reviews the critical issues to building and solving large-scale problems and discusses practical aspects such as the correct load definition and simulation performance requirements and improvements. Some breakthrough solutions like Acoustic Transfer Vectors and parallel computing are discussed. Specific attention is devoted to the potential of hybrid methods combining virtual models with experimental data. The discussed are illustrated by means of powertrain noise and vibration case studies.

The effectiveness of vehicle design' modifications based on an experimental SEA model will strongly depend on the confidence one can have in the identified model. This paper deals with the estimation of the variances of the experimentally derived internal and coupling loss factors, allowing to assess the confidence levels of the SEA predictions. The theory concerning the statistical aspects of the Power Injection Method (PIM) is outlined and the derived analytical expressions are validated based on a Monte-Carlo variability analysis. The statistical formulas are then applied to a railway carriage of a high-speed train, illustrating that the calculation of confidence levels is a very useful tool to assess the accuracy of the experimental SEA model.