• Structural Engineering and Mechanics
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• v.14 no.1
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• pp.57-70
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• 2002

This work presents an iterative mesh partitioning approach to improve the efficiency of parallel substructure finite element computations. The proposed approach employs an iterative strategy with a set of empirical rules derived from the results of numerical experiments on a number of different finite element meshes. The proposed approach also utilizes state-of-the-art partitioning techniques in its iterative partitioning kernel, a cost function to estimate the computational cost of each submesh, and a mechanism that adjusts element weights to redistribute elements among submeshes during iterative partitioning to partition a mesh into submeshes (or substructures) with balanced computational workloads. In addition, actual parallel finite element structural analyses on several test examples are presented to demonstrate the effectiveness of the approach proposed herein. The results show that the proposed approach can effectively improve the efficiency of parallel substructure finite element computations.

• Structural Engineering and Mechanics
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• v.52 no.3
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• pp.633-646
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• 2014

A semi-analytical numerical approach for the effective structural dynamic response analysis of spar floating substructure for offshore wind turbine subject to wave-induced excitation is introduced in this paper. The wave-induced rigid body motions at the center of mass are analytically solved using the dynamic equations of rigid ship motion. After that, the flexible structural dynamic responses of spar floating substructure for offshore wind turbine are numerically analyzed by letting the analytically derived rigid body motions be the external dynamic loading. Restricted to one-dimensional sinusoidal wave excitation at sea state 3, pitch and heave motions are considered. Through the numerical experiments, the time responses of heave and pitch motions are solved and the wave-induced dynamic displacement and effective stress of flexible floating substructure are investigated. The hydrodynamic interaction between wave and structure is modeled by means of added mass and wave damping, and its modeling accuracy is verified from the comparison of natural frequencies obtained by experiment with a 1/100 scale model.

• Smart Structures and Systems
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• v.30 no.3
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• pp.273-286
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• 2022

In recent years, vision-based monitoring has received great attention. However, structural identification using vision-based displacement measurements is far less established. Especially, simultaneous identification of structural systems and unknown excitation using vision-based displacement measurements is still a challenging task since the unknown excitations do not appear directly in the observation equations. Moreover, measurement accuracy deteriorates over a wider field of view by vision-based monitoring, so, only a portion of the structure is measured instead of targeting a whole structure when using monocular vision. In this paper, the identification of structural system and excitations using vision-based displacement measurements is investigated. It is based on substructure identification approach to treat of problem of limited field of view of vision-based monitoring. For the identification of a target substructure, substructure interaction forces are treated as unknown inputs. A smoothing extended Kalman filter with unknown inputs without direct feedthrough is proposed for the simultaneous identification of substructure and unknown inputs using vision-based displacement measurements. The smoothing makes the identification robust to measurement noises. The proposed algorithm is first validated by the identification of a three-span continuous beam bridge under an impact load. Then, it is investigated by the more difficult identification of a frame and unknown wind excitation. Both examples validate the good performances of the proposed method.

• Smart Structures and Systems
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• v.12 no.6
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• pp.619-640
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• 2013

It is highly desirable to explore efficient algorithms for detecting structural damage of large size structural systems with limited input and output measurements. In this paper, a new structural damage detection algorithm based on substructure approach is proposed for large size structural systems with limited input and output measurements. Inter-connection effect between adjacent substructures is treated as 'additional unknown inputs' to substructures. Extended state vector of each substructure and its unknown excitations are estimated by sequential extended Kalman estimator and least-squares estimation, respectively. It is shown that the 'additional unknown inputs' can be estimated by the algorithm without the measurements on the substructure interface DOFs, which is superior to previous substructural identification approaches. Also, structural parameters and unknown excitation are estimated in a sequential manner, which simplifies the identification problem compared with other existing work. Structural damage can be detected from the degradation of the identified substructural element stiffness values. The performances of the proposed algorithm are demonstrated by several numerical examples and a lab experiment. Measurement noise effect is considered. Both the simulation results and experimental data validate that the proposed algorithm is viable for structural damage detection of large size structural systems with limited input and output measurements.

• Smart Structures and Systems
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• v.4 no.6
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• pp.795-807
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• 2008

A challenging problem in structural damage detection based on vibration data is the requirement of a large number of sensors and the numerical difficulty in obtaining reasonably accurate results when the system is large. To address this issue, the substructure identification approach may be used. Due to practical limitations, the response data are not available at all degrees of freedom of the structure and the external excitations may not be measured (or available). In this paper, an adaptive damage tracking technique, referred to as the sequential nonlinear least-square estimation with unknown inputs and unknown outputs (SNLSE-UI-UO) and the sub-structure approach are used to identify damages at critical locations (hot spots) of the complex structure. In our approach, only a limited number of response data are needed and the external excitations may not be measured, thus significantly reducing the number of sensors required and the corresponding computational efforts. The accuracy of the proposed approach is illustrated using a long-span truss with finite-element formulation and an 8-story nonlinear base-isolated building. Simulation results demonstrate that the proposed approach is capable of tracking the local structural damages without the global information of the entire structure, and it is suitable for local structural health monitoring.

• Structural Engineering and Mechanics
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• v.21 no.6
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• pp.621-634
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• 2005

A direct transfer substructure method is presented in this paper for analyzing the dynamic characteristics and the seismic random responses of a series reactor. This method combines the concept of FRF (frequency response function) and the transfer matrix algorithm with the substructure approach. The inner degrees of freedom of each substructure are eliminated in the process of reconstruction and the computation cost is reduced greatly. With the convenient solution procedure, the dynamic characteristics analysis of the structure is valid and efficient. Associated with the pseudo excitation algorithm, the direct transfer substructure method is applied to investigating the seismic random responses of the series reactor. The numerical results demonstrate that the presented method is efficient and practicable in engineering. Finally, a precise time integration method is employed in performing a time-history analysis on the series reactor under El Centro and Taft earthquake waves.

• Smart Structures and Systems
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• v.15 no.2
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• pp.425-445
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• 2015

Parametric identification of structures is one of the important aspects of structural health monitoring. Most of the techniques available in the literature have been proved to be effective for structures with small degree of freedoms. However, the problem becomes challenging when the structure system is large, such as bridge structures. Therefore, it is highly desirable to develop parametric identification methods that are applicable to complex structures. In this paper, the LSE based techniques will be combined with the substructure approach for identifying the parameters of a cable-stayed bridge with large degree of freedoms. Numerical analysis has been carried out for substructures extracted from the 2-dimentional (2D) finite element model of a cable-stayed bridge. Only vertical white noise excitations are applied to the structure, and two different cases are considered where the structural damping is not included or included. Simulation results demonstrate that the proposed approach is capable of identifying the structural parameters with high accuracy without measurement noises.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.7 s.100
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• pp.813-820
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• 2005

A deployable missile control fin has some structural nonlinearities because of the worn or loose hinges and the manufacturing tolerance. The structural nonlinearity cannot be eliminated completely, and exerts significant effects on the static and dynamic characteristics of the control fin. Thus, It is important to establish the accurate deployable missile control fin model. In the present study, the nonlinear dynamic model of 4he deployable missile control fin is developed using a substructure synthesis method. The deployable missile control fin can be subdivided Into two substructures represented by linear dynamic models and a nonlinear hinge with structural nonlinearities. The nonlinear hinge model is established by using a system identification method, and the substructure modes are improved using the Frequency Response Method. A substructure synthesis method Is expanded to couple the substructure models and the nonlinear hinge model, and the nonlinear dynamic model of the fin is developed. Finally, the established nonlinear dynamic model of the deployable missile control fin is verified by dynamic tests. The established model is In good agreement with test results, showing that the present approach is useful in aeroelastic stability analyses such as time-domain nonlinear flutter analysis.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2011.10a
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• pp.607-613
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• 2011

In this study, structural vibration analyses for a 5MW offshore wind wind-turbine model have been performed for different substructure models. The efficient equivalent modeling method based on computational multi-body dynamics are applied to the finite element models of the present offshore wind turbines. Monopile and tri-pod substructure types of the typical offshore wind-turbine are considered herein. Detailed finite element modeling concepts and boundary conditions are described and the comparison results for previous analyses are presented in order to show the verification of the present numerical approach. Campbell diagrams are also present to investigate the rotational resonance characteristics of the offshore wind-turbines with different substructures.

• Computational Structural Engineering : An International Journal
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• v.3 no.1
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• pp.1-7
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• 2003

For system identification of large structures, it is not practical to identify the entire structure due to the prohibitive computational time and difficulty in numerical convergence. This paper explores the possibility of performing system identification at substructure level, taking advantage of reduction in both the number of unknowns and the number of degrees of freedom involved. Another advantage is that different portions (substructures) of a structural system can be identified independently and even concurrently with parallel computing. Two substructural identification methods are formulated on the basis whether substructural approach is used to obtain first-order or second-order model. For substructural first-order model, identification at the substructure level will be performed by means of the Observer/Kalman filter Identification (OKID) and the Eigensystem Realization Algorithm (ERA) whereas identification at the global level will be performed to obtain second-order model in order to evaluate the system's stiffness and mass parameters. In the case of substructural second-order model, identification will be performed at the substructure level throughout the identification process. The efficiency of the proposed technique is shown by numerical examples for multi-storey shear buildings subjected to random forces, taking into consideration the effects of noisy measurement data. The results indicate that both the proposed methods are effective and efficient for damage identification of large structures.