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Statistical Energy Analysis (Noise & Vibration Predictions)

Fuselage_SEA.JPG
Fig. 1 Statistical Energy Analysis model of experimental aircraft fuselage structure.

SEA prediction of fuselage response versus measurements
Fig. 2 SEA prediction of fuselage response versus measurements.

Wave transmission coefficients for L-plate junction as function of angle of incidence
Fig. 3 Wave transmission coefficients for L-plate junction as function of angle of incidence.

Three-dimensional plot of sound radiation efficiency of plate in wavenumber space
Fig. 4 Three-dimensional plot of sound radiation efficiency of plate in wavenumber space (k-space).

Sound radiation efficiency corrected for influency of baffle compared with measurements
Fig. 5 Sound radiation efficiency corrected for influency of baffle compared with measurements.

Statistical Energy Analysis model of a truck for prediction of noise levels
Fig. 6 Statistical Energy Analysis model of a truck for prediction of noise levels.

Statistical Energy Analysis predicted interior noise levels compared with measured data
Fig. 7 Statistical Energy Analysis predicted interior noise levels compared with measured data.


Statistical Energy Analysis (SEA) is a powerful method for prediction of the response of complex coupled acoustic spaces and structures. The method was originally developed in the sixties for prediction of the response of the Saturn launch vehicle. The method has undergone continuously development and it has been applied successfully to most areas of engineering e.g. aerospace & spacecraft structures, road & rail vehicles, civil engineering structures (buildings) and naval structures.

Statistical Energy Analysis is primarily intended for high frequency prediction. The term 'high frequency' depends on the size of the structure. By high frequency is normally meant that the wavelength is relatively short compared to the dimensions of the structure. For a car, high frequency might be above say 500Hz. In the high frequency range the dynamic response is normally rather sensitive to exact dimensions, material properties, assembly etc. and this makes it difficult to predict the response accurately. A deterministic approach such as e.g. the finite element method will normally not be suited for high frequency predictions due to the uncertainties as well as the number of elements required.

The 'Statistical' in Statistical Energy Analysis refers to that SEA employs certain averaging procedures and that it aims at predicting the response of an average structure so-called assembly average. Assuming that the conditions for SEA are fulfilled, a good prediction will normally predict the response levels within ±3dB.

The 'Energy' in Statistical Energy Analysis refers to that the primary parameter for a SEA model is the energy level of the various sub-systems: acoustic and structural. As there is a relation between energy of acoustic spaces and structural systems it is possible from the energy levels to estimate the sound pressure levels for acoustic spaces and vibrations levels for structural systems.

An important part of a Statistical Energy Analysis model is to predict accurately the energy exchange between various parts of the SEA model. These SEA energy exchanges are found from coupling loss factors,ηij, that normally are calculated from transmission coefficients, τ, and sound radiation efficiencies, σ. These coefficients and efficiencies are either determined from analytical calculations, measurements or finite element models. An example of transmission coefficients, τ, for plate to plate coupling is shown in Fig. 3. The transmission coefficients shown in Fig. 3 are for an incident bending wave on a 900 degree plate junction. The coefficients are a function of angle of incidence cos(φ). Three wave types are required to fulfil the boundary conditions at the coupling: bending waves, shear waves and longitudinal waves. The sound radiation efficiencies, σ, (Figs. 4 & 5) are used for calculation of the coupling loss factors between structures and acoustic fluids. For sound transmission through partitions, transmission coefficients similar to those shown on the page  are employed.

The agreement shown in Fig. 2 between the Statistical Energy Analysis predicted results and the measurements are typically. At high frequencies where several modes are present within each frequency band, the agreement is normally good i.e. within ±3dB. However at lower frequencies with fewer or no modes at all, the agreement is generally poor, as the conditions for the SEA model are no longer fulfilled.

Fig. 6 shows an Statistical Energy Analysis model of a truck used for prediction of interior and exterior noise levels. A comparison of the measured and the predicted interior noise level is shown in Fig. 6. In general the agreement is excellent.