Stress Wave Propagation Analysis on Vortex-Induced Vibration of Marine Risers

To analyze the stress wave propagation associated with the vortex-induced vibration（VIV） of a marine riser, this paper employed a multi-signal complex exponential method. This method is an extension of the classical Prony＇s method which decomposes a complicated signal into a number of complex exponential components. Because the proposed method processes multiple signals simultaneously, it can estimate the “global” dominating frequencies（poles） shared by those signals.The complex amplitude（residues） corresponding to the estimated frequencies for those signals is also obtained in the process. As the signals were collected at different locations along the axial direction of a marine riser, the phenomena of the stress wave propagation could be analyzed through the obtained residues of those signals. The Norwegian Deepwater Program（NDP） high mode test data were utilized in the numerical studies, including data sets in both the in-line（IL） and cross-flow（CF） directions. It was found that the most dominant component in the IL direction has its stress wave propagation along the riser being dominated by a standing wave, while that in the CF direction dominated by a traveling wave.

A Novel Approach for Evaluating Nonstationary Response of Dynamic Systems to Stochastic Excitation

The transient state of a dynamic system,such as offshore structures,to random excitation is always nonstationary.Many studies have contributed to evaluating response covariances at the transient state of a linear multi-degree-of-freedom(MDOF)system to random excitations,but a closed-form solution was not available unless the excitation was assumed to be a physically unrealizable white noise process.This study derives explicit,closed-form solutions for the response covariances at the transient state by using a pole-residue(PR)approach operated in the Laplace domain when the excitations are assumed to be stationary random processes described by physically realizable spectral density functions.By using the PR method,we can analytically solve the triple integral in evaluating the nonstationary response covariance.As this approach uses the poles and residues of system transfer functions,rather than the conventional mode superposition technique,the method is applicable to MDOF systems with non-classical damping models.Particular application of the proposed method is demonstrated for multi-story shear buildings to stochastic ground acceleration characterized by the Kanai–Tajimi spectral density function model,and a numerical example is provided to illustrate the detailed steps.No numerical integrations are required for computing the response covariances as the exact closed-form solution has been derived.The correctness of the proposed method is numerically verified by Monte Carlo simulations.

Employing incomplete complex modes for model updating and damage detection of damped structures

In the study of finite element model updating or damage detection,most papers are devoted to undamped systems.Thus,their objective has been exclusively restricted to the correction of the mass and stiffness matrices.In contrast,this paper performs the model updating and damage detection for damped structures.A theoretical contribution of this paper is to extend the cross-model cross-mode(CMCM) method to simultaneously update the mass,damping and stiffness matrices of a finite element model when only few spatially incomplete,complex-valued modes are available.Numerical studies are conducted for a 30-DOF(degree-of-freedom) cantilever beam with multiple damaged elements,as the measured modes are synthesized from finite element models.The numerical results reveal that applying the CMCM method,together with an iterative Guyan reduction scheme,can yield good damage detection in general.When the measured modes utilized in the CMCM method are corrupted with irregular errors,assessing damage at the location that possesses larger modal strain energy is less sensitive to the corrupted modes.

Model updating based on incomplete modal data

The objective of model updating is to improve the accuracy of a dynamic model based on the correlation between the measured data and the analytical (finite element) model. In this paper, we intend to update the mass and stiffness matrices of an analytical model when only modal frequencies or spatially incomplete modal data are available. While the proposed method is systematic in nature, it also preserves the initial configuration of the analytical model, and physical equality and/or inequality constraints can be easily incorporated into the solution procedure. Numerical examples associated with a simple 5-DoF (degree of freedom) mass-spring system are chosen to illustrate the detailed procedure and the effectiveness of the proposed method. Numerical scenarios ranging from the updating for stiffness terms only to that for all mass and stiffness terms based on various kinds of incomplete modal data are studied. The obtained model updating results are excellent when the measured modal data are noise-free. Uncertainty studies are also conducted based on simulations of corrupted modal data, but a thorough theoretical analysis of the noise effect on the proposed method is still needed.

Improved polyreference time domain method for modal identification using local or global noise removal techniques

Modal identification involves estimating the modal parameters, such as modal frequencies, damping ratios, and mode shapes, of a structural system from measured data. Under the condition that noisy impulse response signals associated with multiple input and output locations have been measured, the primary objective of this study is to apply the local or global noise removal technique for improving the modal identification based on the polyreference time domain (PTD) method. While the traditional PTD method improves modal parameter estimation by over-specifying the computational model order to absorb noise, this paper proposes an approach using the actual system order as the computational model order and rejecting much noise prior to performing modal parameter estimation algorithms. Two noise removal approaches are investigated: a "local" approach which removes noise from one signal at a time, and a "global" approach which removes the noise of multiple measured signals simultaneously. The numerical investigation in this article is based on experimental measurements from two test setups: a cantilever beam with 3 inputs and 10 outputs, and a hanged plate with 4 inputs and 32 outputs. This paper demonstrates that the proposed noise-rejection method outperforms the traditional noise-absorption PTD method in several crucial aspects.

Fundamental modeling issues on benchmark structure for structural health monitoring

The IASC-ASCE Structural Health Monitoring Task Group developed a series of benchmark problems, and participants of the benchmark study were charged with using a 12-degree-of-freedom (DOF) shear building as their identification model. The present article addresses improperness, including the parameter and modeling errors, of using this particular model for the intended purpose of damage detec- tion, while the measurements of damaged structures are synthesized from a full-order finite-element model. In addressing parameter errors, a model calibration procedure is utilized to tune the mass and stiffness matrices of the baseline identification model, and a 12-DOF shear building model that preserves the first three modes of the full-order model is obtained. Sequentially, this calibrated model is employed as the baseline model while performing the damage detection under various damage scenarios. Numerical results indicate that the 12-DOF shear building model is an over-simplified identification model, through which only idealized damage situations for the benchmark structure can be detected. It is suggested that a more sophisticated 3-dimensional frame structure model should be adopted as the identification model, if one intends to detect local member damages correctly.