Literature on turbulence is very wide, providing several models for the power spectral density function of the single-point turbulence components, for the two-point coherence function of the same turbulence component and for the single-point coherence function of different turbulence components. On the other hand, no suitable and simple model seems to be available for representing the two-point coherence function of different turbulence components, in particular of the longitudinal and vertical turbulence components, which would be useful for modelling buffeting actions on bridges. The Proper Orthogonal Decomposition provides efficient tools to formulate a new model of the turbulence field based on principal components. Furthermore, it suggests physical principles and defines mathematical rules to establish an appropriate model of the two-point coherence function of the longitudinal and vertical components, completing the statistical model of turbulence. Embedded in a Monte Carlo framework, this new representation can be used to simulate multi-dimensional and multi-variate random turbulence fields.

A turbulence model based on principal components

SOLARI, GIOVANNI;TUBINO, FEDERICA
2002

Abstract

Literature on turbulence is very wide, providing several models for the power spectral density function of the single-point turbulence components, for the two-point coherence function of the same turbulence component and for the single-point coherence function of different turbulence components. On the other hand, no suitable and simple model seems to be available for representing the two-point coherence function of different turbulence components, in particular of the longitudinal and vertical turbulence components, which would be useful for modelling buffeting actions on bridges. The Proper Orthogonal Decomposition provides efficient tools to formulate a new model of the turbulence field based on principal components. Furthermore, it suggests physical principles and defines mathematical rules to establish an appropriate model of the two-point coherence function of the longitudinal and vertical components, completing the statistical model of turbulence. Embedded in a Monte Carlo framework, this new representation can be used to simulate multi-dimensional and multi-variate random turbulence fields.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11567/214785
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