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Reinforced Thermoplastic Pipe (RTP) is a composite material flexible pipe. Due to RTP superior behavior, it encouraged the industry for using to offshore and inshore applications. Marine risers and cross-country pipelines resting on elastic medium are slender flexible structures conveying fluid and exhibit complex dynamic behaviors. Therefore, it requires accurate dynamic modeling for prediction the vibration characteristics. Transfer Matrix Method for Multibody Systems (MSTMM) is one of the sophisticated methods that can be used efficiently to model large systems and calculate its vibration characteristics and dynamic responses. The size of matrices in MSTMM remains small regardless of the number of elements in the model. Having smaller matrix sizes helps to have less computational expense leading to a faster answer. Based on the MSTMM advantages and Euler-Bernoulli linear theory, transfer matrix of the pipe in both offshore and inshore industry applications is built-up for vibration analysis. Recursive eigenvalue search algorithm is used to determine the system frequencies. Numerical examples are performed to validate with those published in the open literature.

In this paper we propose to apply parafac-based source separation techniques for jammer suppression in direct spread spectrum communication systems. The jammer excision is formulated as an optimization problem and a new algorithm is presented which is based on the parafac tri-iterative least square algorithm. By jointly diagonalizing the time delay correlation matrix of the observed signals and using the new proposed method, a better solution is achieved. The proposed algorithm can successfully separate communication signals and jamming signals. Simulation results reveal that our proposed algorithm has the better blind signal separation performance than joint diagonalization method. Our proposed algorithm doesn’t require whitening processing. Moreover our proposed algorithm works well in the underdetermined condition, where the number of sources exceeds than the number of antennas.