This work deals with the application of the proper orthogonal decomposition (POD) to structural dynamics. On one hand, a physical interpretation of the proper orthogonal modes (POM) is given using the singular value decomposition (SVD). It is shown that the POM converge to the normal modes under some circumstances. On the other hand, the POM are exploited for model reduction purposes. The efficiency of the reduced model for the prediction of the response is tested on a nonlinear beam. The comparison with another reduced model obtained via the normal modes of the linearised system points out that the POM are optimal for the reconstruction of the dynamics of a system
Abstract. Modal analysis is used extensively for understanding the dynamic behavior of structures. H...
The present study focuses on the model reduction of non-linear systems. The proper orthogonal decomp...
AbstractThe aim of this paper is to propose a new way to measure the efficiency of the proper orthog...
This work deals with the application of the proper orthogonal decomposition (POD) to structural dyna...
Proper Orthogonal Decomposition (POD), also known as Karhunen-Loeve decomposition, or principal comp...
Proper Orthogonal Decomposition (POD), also known as Karhunen-Loeve decomposition, or principal comp...
Modal analysis is extensively used for the analysis and design of structures. However, a major conce...
Modal analysis is extensively used for the analysis and design of structures. However, a major conce...
Proper orthogonal decomposition (POD), also known as Karhunen}Loeve (K}L) decomposition, is emergin...
The present study focuses on the model reduction of non-linear systems. The proper orthogonal decomp...
peer reviewedProper orthogonal decomposition (POD), also known as Karhunen}Loeve (K}L) decompositio...
peer reviewedModal analysis is used extensively for understanding the dynamic behavior of structures...
An approach to develop Proper Orthogonal Decomposition (POD) based reduced order models for systems ...
The modern engineering deals with applications of high complexity. From a mathematical point of view...
A new approach to model order reduction of nonlinear control systems is aimed at developing persiste...
Abstract. Modal analysis is used extensively for understanding the dynamic behavior of structures. H...
The present study focuses on the model reduction of non-linear systems. The proper orthogonal decomp...
AbstractThe aim of this paper is to propose a new way to measure the efficiency of the proper orthog...
This work deals with the application of the proper orthogonal decomposition (POD) to structural dyna...
Proper Orthogonal Decomposition (POD), also known as Karhunen-Loeve decomposition, or principal comp...
Proper Orthogonal Decomposition (POD), also known as Karhunen-Loeve decomposition, or principal comp...
Modal analysis is extensively used for the analysis and design of structures. However, a major conce...
Modal analysis is extensively used for the analysis and design of structures. However, a major conce...
Proper orthogonal decomposition (POD), also known as Karhunen}Loeve (K}L) decomposition, is emergin...
The present study focuses on the model reduction of non-linear systems. The proper orthogonal decomp...
peer reviewedProper orthogonal decomposition (POD), also known as Karhunen}Loeve (K}L) decompositio...
peer reviewedModal analysis is used extensively for understanding the dynamic behavior of structures...
An approach to develop Proper Orthogonal Decomposition (POD) based reduced order models for systems ...
The modern engineering deals with applications of high complexity. From a mathematical point of view...
A new approach to model order reduction of nonlinear control systems is aimed at developing persiste...
Abstract. Modal analysis is used extensively for understanding the dynamic behavior of structures. H...
The present study focuses on the model reduction of non-linear systems. The proper orthogonal decomp...
AbstractThe aim of this paper is to propose a new way to measure the efficiency of the proper orthog...