Modeling and Identification of a Nonlinear SDOF Moored Structure, Part 2—Comparisons and Sensitivity Study

2004 ◽  
Vol 126 (2) ◽  
pp. 183-190 ◽  
Author(s):  
S.C.S. Yim ◽  
S. Narayanan
Keyword(s):  
System Identification ◽  
Small Body ◽  
Ocean Waves ◽  
System Response ◽  
Mooring System ◽  
Nonlinear Structure ◽  
Single Output ◽  
Submerged Sphere ◽  
Multiple Input ◽  
Identification Technique

A system-identification technique based on the Reverse Multiple-Input/Single-Output (R-MI/SO) procedure is applied to identify the parameters of an experimental mooring system exhibiting nonlinear behavior. In Part 1, two nonlinear small-body hydrodynamic Morison type formulations: (A) with a relative-velocity (RV) model, and (B) with an independent-flow-field (IFF) model, are formulated. Their associated nonlinear system-identification algorithms based on the R-MI/SO system-identification technique: (A.1) nonlinear-structure linearly damped, and (A.2) nonlinear-structure coupled hydrodynamically damped for the RV model, and (B.1) nonlinear-structure nonlinearly damped for the IFF model, are developed for an experimental submerged-sphere nonlinear mooring system under ocean waves. The analytic models and the associated algorithms for parametric identification are described. In this companion paper (Part 2), we use the experimentally measured input wave and output system response data and apply the algorithms derived based on the multiple-input/single-output linear analysis of the reverse dynamic systems to identify the system parameters. The two nonlinear models are examined in detail and the most suitable physical representative model is selected for the mooring system considered. A sensitive analysis is conducted to investigate the coupled hydrodynamic forces modeled by the Morison equation, the nonlinear stiffness from mooring lines and the nonlinear response. The appropriateness of each model is discussed in detail.

Modeling and Identification of a Nonlinear SDOF Moored Structure, Part 1—Hydrodynamic Models and Algorithms

2004 ◽  
Vol 126 (2) ◽  
pp. 175-182 ◽  
Author(s):  
S. Narayanan ◽  
S. C. S. Yim
Keyword(s):  
System Identification ◽  
Nonlinear System ◽  
Small Body ◽  
Nonlinear System Identification ◽  
Ocean Waves ◽  
System Response ◽  
Restoring Force ◽  
Nonlinear Structure ◽  
Submerged Sphere ◽  
Highly Nonlinear

The highly nonlinear responses of compliant ocean structures characterized by a large-geometry restoring force and coupled fluid-structure interaction excitation are of great interest to ocean and coastal engineers. Practical modeling, parameter identification, and incorporation of the inherent nonlinear dynamics in the design of these systems are essential and challenging. The general approach of a nonlinear system technique using very simple models has been presented in the literature by Bendat. In Part 1 of this two-part study, two specific nonlinear small-body hydrodynamic Morison type formulations: (A) with a relative-velocity (RV) model, and (B) with an independent flow-field (IFF) model, are formulated. Their associated nonlinear system-identification algorithms based on the reverse multiple-input/single-output (R-MI/SO) system-identification technique: (A.1) nonlinear-structure linearly damped, and (A.2) nonlinear-structure coupled hydrodynamically damped for the RV model, and (B.1) nonlinear-structure nonlinearly damped for the IFF model, are developed for a specific experimental submerged-sphere mooring system under ocean waves exhibiting such highly nonlinear response behaviors. In Part 2, using the measured input wave and output system response data, the algorithms derived based on the MI/SO linear analysis of the reverse dynamic systems are applied to identify the properties of the highly nonlinear system. Practical issues on the application of the R-MI/SO technique based on limited available experimental data are addressed.

Output error MISO system identification using fractional models

2021 ◽  
Vol 24 (5) ◽  
pp. 1601-1618
Author(s):  
Abir Mayoufi ◽  
Stéphane Victor ◽  
Manel Chetoui ◽  
Rachid Malti ◽  
Mohamed Aoun
Keyword(s):  
System Identification ◽  
Optimization Algorithm ◽  
Simulation Analysis ◽  
Good Efficiency ◽  
Output Error ◽  
Single Output ◽  
Multiple Input ◽  
Fractional Models ◽  
Definition Of ◽  
Initialization Procedure

Abstract This paper deals with system identification for continuous-time multiple-input single-output (MISO) fractional differentiation models. An output error optimization algorithm is proposed for estimating all parameters, namely the coefficients and the differentiation orders. Given the high number of parameters to be estimated, the output error method can converge to a local minimum. Therefore, an initialization procedure is proposed to help the convergence to the optimum by using three variants of the algorithm. Moreover, a new definition of structured-commensurability (or S-commensurability) has been introduced to cope with the differentiation order estimation. First, a global S-commensurate order is estimated for all subsystems. Then, local S-commensurate orders are estimated (one for each subsystem). Finally the S-commensurability constraint being released, all differentiation orders are further adjusted. Estimating a global S-commensurate order greatly reduces the number of parameters and helps initializing the second variant, where local S-commensurate orders are estimated which, in turn, are used as a good initial hit for the last variant. It is known that such an initialization procedure progressively increases the number of parameters and provides good efficiency of the optimization algorithm. Monte Carlo simulation analysis are provided to evaluate the performances of this algorithm.

Nonlinear Model for Sub- and Superharmonic Motions of a MDOF Moored Structure, Part 1—System Identification

2005 ◽  
Vol 127 (4) ◽  
pp. 283-290 ◽  
Author(s):  
S. Raman ◽  
S. C. S. Yim ◽  
P. A. Palo
Keyword(s):  
System Identification ◽  
Nonlinear System Identification ◽  
Experimental System ◽  
Degree Of Freedom ◽  
System Model ◽  
Single Degree Of Freedom ◽  
Sdof System ◽  
Single Output ◽  
Motion Responses ◽  
Identification Technique

In this first part of a two-part study, the general nonlinear system identification methodology developed earlier by the authors for a single-degree-of-freedom (SDOF) system using the reverse-multi-input/single-output (R-MI/SO) technique is extended to a multi-degree-of-freedom (MDOF), sub-merged, moored structure with surge and heave motions. The physical nonlinear MDOF system model and the formulation of the R-MI/SO system-identification technique are presented. The corresponding numerical algorithm is then developed and applied to the experimental data of the MDOF system using only the subharmonic motion responses to identify the system parameters. The resulting model is then employed in Part 2 for a detailed analysis of both the sub and superharmonic dynamic behavior of the MDOF experimental system and a comparison of the MDOF response results and observations with those of the corresponding SDOF system examined earlier by the authors.

ARMAV Techniques for Traffic Excited Bridges

1998 ◽  
Vol 120 (3) ◽  
pp. 713-718 ◽  
Author(s):  
L. Garibaldi ◽  
E. Giorcelli ◽  
B. A. D. Piombo
Keyword(s):  
System Identification ◽  
Time Window ◽  
Moving Average ◽  
System Response ◽  
Model Parameters ◽  
Sampled Data ◽  
Discrete Time System ◽  
Traffic Conditions ◽  
Multiple Input ◽  
Auto Regressive

In this paper ARMAV (Auto Regressive Moving Average Vector) models are used for system identification and modal analysis purposes. This time domain technique allows to estimate a discrete time system response function without performing any domain change (i.e. it doesn’t use FFT and IFFT to evaluate the model parameters) and without applying any time window (also when sampled data are non periodic): this leads to well-estimated system parameters, also for short data records. These models are useful to perform system identification for multiple input-output cases also when the excitation is just statistically known. The present analysis is dedicated to a scaled bridge, designed according to the theory of models, whose static and dynamic characteristics are compatible to those of real bridges. The aim of the tests is to collect a series of supervised measurements in a controlled environment, with statistically defined traffic conditions; the comparison of the model results with those acquired on the real bridge is the compulsory step towards a correct modelling of bridges for their identification and monitoring. The paper reports encouraging results obtained with experimental simulations on the model.

Stochastic Analysis of Nonlinear Response of a Moored Structural System Under Narrowband Excitations

2006 ◽  
Author(s):  
Solomon C. Yim ◽  
Dongjun Yuk ◽  
Arvid Naess ◽  
I.-Ming Shih
Keyword(s):  
Analytical Method ◽  
Stochastic Analysis ◽  
Extreme Values ◽  
Probability Distributions ◽  
Structural Response ◽  
Nonlinear Behavior ◽  
Random Waves ◽  
Nonlinear Structure ◽  
Single Output ◽  
Multiple Input

A semi-analytical method is developed for the stochastic analysis of a nonlinear moored ocean structure subjected to narrowband random waves. The method is then used to investigate the probability distribution of extreme values of the responses. To verify the accuracy and capability of the method in handling complex nonlinear behavior of the nonlinear moored ocean structure, experimental results are employed to calibrate numerical simulations and the resulting probability distributions obtained from the semi-analytical method. A nonlinear-structure nonlinearly damped model is employed to model the moored structure considered and the system coefficients are identified through the reverse multiple-input/single-output technique. An examination of the comparisons indicates that the structural response extreme value probability distributions obtained from the semi-analytical predictions are quite accurate.

Bifurcations of a Nonlinear Small-Body Ocean-Mooring System Excited by Finite-Amplitude Waves

1997 ◽  
Vol 119 (4) ◽  
pp. 234-238 ◽  
Author(s):  
O. Gottlieb
Keyword(s):  
Small Body ◽  
Finite Amplitude ◽  
System Response ◽  
Mooring System ◽  
Geometrically Nonlinear ◽  
Restoring Force ◽  
Nonlinear Restoring Force ◽  
Dissipation Mechanism ◽  
Finite Amplitude Waves ◽  
Control Stability

We investigate the response of a nonlinear small-body ocean-mooring system excited by finite-amplitude waves. The system is characterized by a coupled geometrically nonlinear restoring force defined by a single elastic tether. The nonlinear hydrodynamic exciting force includes both dissipative and convective terms that are not negligible in a finite wave amplitude environment. Stability of periodic motion is determined numerically and the bifurcation structure includes ultrasubharmonic and quasi-periodic response. The dissipation mechanism is found to control stability thresholds, whereas the convective nonlinearity governs the evolution to chaotic system response.

A System Identification Method for Excitation-Frequency Dependent Rotordynamic Coefficients

2012 ◽  
Author(s):  
Timothy W. Dimond ◽  
Amir A. Younan ◽  
Paul Allaire
Keyword(s):  
System Identification ◽  
Measurement Uncertainty ◽  
Excitation Frequency ◽  
Frequency Dependent ◽  
Rotordynamic Coefficients ◽  
Adjoint Systems ◽  
Dynamic Coefficients ◽  
Backward Whirl ◽  
Identification Technique ◽  
Damped Systems

Experimental identification of rotordynamic systems presents unique challenges. Gyroscopics, generally damped systems, and non-self-adjoint systems due to fluid structure interaction forces mean that symmetry cannot be used to reduce the number of parameters to be identified. Rotordynamic system experimental measurements are often noisy, which complicates comparisons with theory. When linearized, the resulting dynamic coefficients are also often a function of excitation frequency, as distinct from operating speed. In this paper, a frequency domain system identification technique is presented that addresses these issues for rigid-rotor test rigs. The method employs power spectral density functions and forward and backward whirl orbits to obtain the excitation frequency dependent effective stiffness and damping. The method is highly suited for use with experiments that employ active magnetic exciters that can perturb the rotor in the forward and backward whirl directions. Simulation examples are provided for excitation-frequency reduced tilting pad bearing dynamic coefficients. In the simulations, 20 and 50 percent Gaussian output noise was considered. Based on ensemble averages of the coefficient estimates, the 95 percent confidence intervals due to noise effects were within 1.2% of the identified value. The method is suitable for identification of linear dynamic coefficients for rotordynamic system components referenced to shaft motion. The method can be used to reduce the effect of noise on measurement uncertainty. The statistical framework can also be used to make decisions about experimental run times and acceptable levels of measurement uncertainty. The data obtained from such an experimental design can be used to verify component models and give rotordynamicists greater confidence in the design of turbomachinery.

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