free vibration analysis of repetitive structures using decomposition, and divide-conquer methods

Free Vibration Analysis of Repetitive Structures using Decomposition, and Divide-Conquer Methods

This paper consists of three sections. In the first section an efficient method is used for decomposition of the canonical matrices associated with repetitive structures. to this end, cylindrical coordinate system, as well as a special numbering scheme were employed. In the second section, divide and conquer method have been used for eigensolution of these structures, where the matrices are in ...

Free vibration analysis of steel framed structures

This study based on free vibration analysis and study the behavior of framed structure under different frequency of vibration using ANSYS software and shaking table. A small scale uni-axial shaking table was prepared in laboratory, which can produce lower to moderate vibration, regarding frequency and velocity. Moment resisting framed structures constructed with connecting beam and column eleme...

Free Vibration of Large Regular Repetitive Structures

In this paper, free vibrations of large repetitive regular planar and space trusses are considered. For this kind of structures the corresponding stiffness and mass matrices have tri-diagonal block and in the canonical form, ) , , ( T F B A B K  and ) , , ( 0 D 0 M G  , which simplifies their Eigen frequencies. Practical large space and planar trusses contains with repetitive units, known as ...

Divide to conquer: decomposition methods for energy optimization

Free Vibration Analysis of a Nonlinear Beam Using Homotopy and Modified Lindstedt-Poincare Methods

In this paper, homotopy perturbation and modified Lindstedt-Poincare methods are employed for nonlinear free vibrational analysis of simply supported and double-clamped beams subjected to axial loads. Mid-plane stretching effect has also been accounted in the model. Galerkin's decomposition technique is implemented to convert the dimensionless equation of the motion to nonlinear ordinary differ...

Divide-and-Conquer Methods for Solving MDPs

The Markov Decision Process (MDP) is the principal theoretical formalism in the area of Reinforcement Learning (RL). An import from optimal control in operations research, this construct is generic enough to represent problems comprising almost all of AI research, but consequently, it suffers from the curse of dimensionality where learning involves an exponential number of parameters. Researche...