A graph cut strategy for transmission path problems in statistical energy analysis

Guasch, Oriol; Aragonès, Àngels; Janer, Marcel

doi:10.1016/j.ymssp.2011.10.006

Cited by 12 publications

(10 citation statements)

References 18 publications

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“…A final SmEdA simulation would verify the performance of the solution in terms of noise reduction. A similar automatized procedure in the easier case of SEA was developed in the framework of graph theory in [28]. The development of an analogous process for SmEdA as described is, however, outside the scope of this paper.…”

Section: Pathmentioning

confidence: 99%

“…In [24], an adaptation of the MSP algorithm (see [25,26]) for the efficient computation and ranking of energy transmission paths from sources to receivers in SEA systems was presented, the inclusion of variance recently being taken into account in [27]. Graph cut algorithms were also used in [28] in an optimizing process to diminish energy transmission between subsystems in SEA. The prospect of defining SEA graphs for the more general ED models has recently been deemed viable in.…”

Section: Introductionmentioning

confidence: 99%

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A graph theory approach to identify resonant and non-resonant transmission paths in statistical modal energy distribution analysis

Aragonès

Maxit

Guasch

2015

Journal of Sound and Vibration

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International audienceStatistical modal energy distribution analysis (SmEdA) extends classical statistical energy analysis (SEA) to the mid frequency range by establishing power balance equations between modes in different subsystems. This circumvents the SEA requirement of modal energy equipartition and enables applying SmEdA to the cases of low modal overlap, locally excited subsystems and to deal with complex heterogeneous subsystems as well. Yet, widening the range of application of SEA is done at a price with large models because the number of modes per subsystem can become considerable when the frequency increases. Therefore, it would be worthwhile to have at one's disposal tools for a quick identification and ranking of the resonant and non-resonant paths involved in modal energy transmission between subsystems. It will be shown that previously developed graph theory algorithms for transmission path analysis (TPA) in SEA can be adapted to SmEdA and prove useful for that purpose. The case of airborne transmission between two cavities separated apart by homogeneous and ribbed plates will be first addressed to illustrate the potential of the graph approach. A more complex case representing transmission between non-contiguous cavities in a shipbuilding structure will be also presented

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Section: Pathmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A graph theory approach to identify resonant and non-resonant transmission paths in statistical modal energy distribution analysis

Aragonès

Maxit

Guasch

2015

Journal of Sound and Vibration

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“…Connecting SEA with graph theory allows to infer very useful results with regards to the vibro-acoustic behavior of a SEA system. These will basically depend on the type of weights selected for E SEA and on the operations to carry on with them [5,6,15,8].…”

Section: Deterministic and Stochastic Sea Graphsmentioning

confidence: 99%

“…Yet, the possibility to rank contributions of individual paths in an efficient way has been made possible recently by establishing a connection between SEA and graph theory [5]. In [6], the deterministic MPS algorithm [7] based on deviation path computations was adapted for this purpose (see also [8] for related applications of graph theory to SEA).…”

Section: Introductionmentioning

confidence: 99%

Ranking paths in statistical energy analysis models with non-deterministic loss factors

Aragonès

Guasch

2015

Mechanical Systems and Signal Processing

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“…This contributes to the low computational cost of the problem, which is particularly important because the identification of subsystems is a preprocessing step in SEA calculation, and one of the main features of SEA is its low computational cost. Finally, it is worth mentioning that subsystem identification is not only a topic of interest for SEA applications like [18] but also in the analysis of mechanical systems/problems in general, see for example [19].…”

Section: Introductionmentioning

confidence: 99%

Automatic subsystem identification in statistical energy analysis

Díaz-Cereceda

Poblet-Puig

Ferran

2015

Mechanical Systems and Signal Processing

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An automatic methodology for identifying SEA (statistical energy analysis) subsystems within a vibroacoustic system is presented. It consists in dividing the system into cells and grouping them into subsystems via a hierarchical cluster analysis based on the problem eigenmodes. The subsystem distribution corresponds to the optimal grouping of the cells, which is defined in terms of the correlation distance between them. The main advantages of this methodology are its automatic performance and its applicability both to vibratory and vibroacoustic systems. Moreover, the method allows the definition of more than one subsystem in the same geometrical region when required. This is the case of eigenmodes with a very different mechanical response (e.g. out-of-plane or in-plane vibration in shells).

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A graph cut strategy for transmission path problems in statistical energy analysis

Cited by 12 publications

References 18 publications

A graph theory approach to identify resonant and non-resonant transmission paths in statistical modal energy distribution analysis

A graph theory approach to identify resonant and non-resonant transmission paths in statistical modal energy distribution analysis

Ranking paths in statistical energy analysis models with non-deterministic loss factors

Automatic subsystem identification in statistical energy analysis

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