• Interaction and multiscale mechanics
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• v.4 no.1
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• pp.49-64
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• 2011

A methodology for jointed rock mass characterization starts with a research based on geological data and tests in order to define the geotechnical models used to support the decision about location, orientation and shape of cavities. Afterwards a more detailed characterization of the rock mass is performed allowing the update of the geomechanical parameters defined in the previous stage. The observed results can be also used to re-evaluate the geotechnical model using inverse methodologies. Cases of large underground structures modeling are presented. The first case concerns the modeling of cavities in volcanic formations. Then, an application to a large station from the Metro do Porto project developed in heterogeneous granite formations is also presented. Finally, the last case concerns the modeling of large cavities for a hydroelectric powerhouse complex. The finite element method and finite difference method software used is acquired from Rocscience and ITASCA, respectively.

• Steel and Composite Structures
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• v.51 no.2
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• pp.203-223
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• 2024

This study shows functionally graded material structural topology optimization under buckling constraints. The SIMP (Solid Isotropic Material with Penalization) material model is used and a method of moving asymptotes is also employed to update topology design variables. In this study, the quadrilateral element is applied to compute buckling load factors. Instead of artificial density properties, functionally graded materials are newly assigned to distribute optimal topology materials depending on the buckling load factors in a given design domain. Buckling load factor formulations are derived and confirmed by the resistance of functionally graded material properties. However, buckling constraints for functionally graded material topology optimization have not been dealt with in single material. Therefore, this study aims to find the minimum compliance topology optimization and the buckling load factor in designing the structures under buckling constraints and generate the functionally graded material distribution with asymmetric stiffness properties that minimize the compliance. Numerical examples verify the superiority and reliability of the present method.

• Structural Engineering and Mechanics
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• v.81 no.3
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• pp.293-303
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• 2022

As infrastructure ages and traffic load increases, serious public concerns have arisen for the well-being of bridges. The current health monitoring practice focuses on large-scale bridges rather than short span bridges. However, it is critical that more attention should be given to these behind-the-scene bridges. The relevant information about the construction methods and as-built properties are most likely missing. Additionally, since the condition of a bridge has unavoidably changed during service, due to weathering and deterioration, the material properties and boundary conditions would also have changed since its construction. Therefore, it is not appropriate to continue using the design values of the bridge parameters when undertaking any analysis to evaluate bridge performance. It is imperative to update the model, using finite element (FE) analysis to reflect the current structural condition. In this study, a FE model is established to simulate a concrete culvert bridge in New South Wales, Australia. That model, however, contains a number of parameter uncertainties that would compromise the accuracy of analytical results. The model is therefore updated with a neural network (NN) optimisation algorithm incorporating Monte Carlo (MC) simulation to minimise the uncertainties in parameters. The modal frequency and strain responses produced by the updated FE model are compared with the frequency and strain values on-site measured by sensors. The outcome indicates that the NN model updating incorporating MC simulation is a feasible and robust optimisation method for updating numerical models so as to minimise the difference between numerical models and their real-world counterparts.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2008.04a
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• pp.139-144
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• 2008

In this study, damage detection method using harmony search method and frequency response is proposed. In order to verify this method, the following approaches are implemented. Firstly, damage detection method using harmony search is developed. To detect damage, objective function that minimize difference with natural frequency and modal strain energy from undamaged and damaged model is used. Secondly, finite element model for beam structure is created. And damage scenario is determined. Lastly, damage detection is performed by proposed method and utility of proposed method is verified.

• Journal of the Earthquake Engineering Society of Korea
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• v.10 no.6 s.52
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• pp.19-28
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• 2006

Most conventional model updating methods must use mathematical objective function with experimental modal matrices and analytical system matrices or must use information about the gradient or higher derivatives of modal properties with respect to each updating parameter. Therefore, most conventional methods are not appropriate for complex structural system such as bridge structures due to stability problem in inverse analysis with ill-conditions. Sometimes, moreover, the updated model may have no physical meaning. In this paper, a new FE model updating method based on a hybrid optimization technique using genetic algorithm (GA) and Holder-Mead simplex method (NMS) is proposed. The performance of hybrid optimization technique on the nonlinear problem is demonstrated by the Goldstein-Price function with three local minima and one global minimum. The influence of the objective function is evaluated by the case study of a simulated 10-dof spring-mass model. Through simulated case studies, finally, the objective function is proposed to update mass as well as stiffness at the same time. And so, the proposed hybrid optimization technique is proved to be an efficient method for FE model updating.

• Smart Structures and Systems
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• v.10 no.4_5
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• pp.375-391
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• 2012

This paper reports the structural health monitoring benchmark study results for the Canton Tower using Bayesian methods. In this study, output-only modal identification and finite element model updating are considered using a given set of structural acceleration measurements and the corresponding ambient conditions of 24 hours. In the first stage, the Bayesian spectral density approach is used for output-only modal identification with the acceleration time histories as the excitation to the tower is unknown. The modal parameters and the associated uncertainty can be estimated through Bayesian inference. Uncertainty quantification is important for determination of statistically significant change of the modal parameters and for weighting assignment in the subsequent stage of model updating. In the second stage, a Bayesian model updating approach is utilized to update the finite element model of the tower. The uncertain stiffness parameters can be obtained by minimizing an objective function that is a weighted sum of the square of the differences (residuals) between the identified modal parameters and the corresponding values of the model. The weightings distinguish the contribution of different residuals with different uncertain levels. They are obtained using the Bayesian spectral density approach in the first stage. Again, uncertainty of the stiffness parameters can be quantified with Bayesian inference. Finally, this Bayesian framework is applied to the 24-hour field measurements to investigate the variation of the modal and stiffness parameters under changing ambient conditions. Results show that the Bayesian framework successfully achieves the goal of the first task of this benchmark study.

• Journal of Ocean Engineering and Technology
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• v.26 no.4
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• pp.86-91
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• 2012

A new identification method for a nonproportional damping matrix using the finite element (FE) model updating technique is proposed. Mass and stiffness matrices of the undamped system are identified by FE model updating method. Sensitivity analysis is used to update the FE model, and zero frequencies are considered as design parameters to supplement the information of vibration characteristics. The nonproportional damping matrix is identified through the proposed method. A numerical example is considered to verify the performance of the proposed method. As a result, the damping matrix of the nonproportional system is estimated accurately.

• Journal of Information Processing Systems
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• v.8 no.1
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• pp.55-66
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• 2012

This paper presents a dual modeling method that simulates the graphic and haptic behavior of a volumetric deformable object and conveys the behavior to a human operator. Although conventional modeling methods (a mass-spring model and a finite element method) are suitable for the real-time computation of an object's deformation, it is not easy to compute the haptic behavior of a volumetric deformable object with the conventional modeling method in real-time (within a 1kHz) due to a computational burden. Previously, we proposed a fast volume haptic rendering method based on the S-chain model that can compute the deformation of a volumetric non-rigid object and its haptic feedback in real-time. When the S-chain model represents the object, the haptic feeling is realistic, whereas the graphical results of the deformed shape look linear. In order to improve the graphic and haptic behavior at the same time, we propose a dual modeling framework in which a volumetric haptic model and a surface graphical model coexist. In order to inspect the graphic and haptic behavior of objects represented by the proposed dual model, experiments are conducted with volumetric objects consisting of about 20,000 nodes at a haptic update rate of 1000Hz and a graphic update rate of 30Hz. We also conduct human factor studies to show that the haptic and graphic behavior from our model is realistic. Our experiments verify that our model provides a realistic haptic and graphic feeling to users in real-time.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.11a
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• pp.350-355
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• 2003

This paper presents results of vibration analysis of a end-winding of large generator for fossil power plant. A finite element analysis using a commercial S/W is performed to calculate alternating electromagnetic forces, mainly of 120㎐ in 60㎐ machines, acting on the end-winding, and then to calculate forced response of the end-winding under electromagnetic forces. Also, this paper presents analytical and experimental modal analysis results of generator end-winding to validate FE model. We calculated forced response of end-winding on 120㎐, double rotating frequency. These results will be used to evaluate structural reliability of end-winding and applied to update model.

• Smart Structures and Systems
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• v.15 no.3
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• pp.751-767
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• 2015

A new procedure is proposed for assessing probabilistic condition of structures considering effect of measured data uncertainty. In this procedure, multiple Finite Element (FE) models are identified by using weighting vectors that represent the uncertainty conditions of measured data. The distribution of structural parameters is analysed using a Principal Component Analysis (PCA) in relation to uncertainty conditions, and the identified models are classified into groups according to their similarity by using a K-means method. The condition of a structure is then assessed probabilistically using FE models in the classified groups, each of which represents specific uncertainty condition of measured data. Yeondae bridge, a steel-box girder expressway bridge in Korea, is used as an illustrative example. Probabilistic condition of the bridge is evaluated by the distribution of load rating factors obtained using multiple FE models. The numerical example shows that the proposed method can quantify uncertainty of measured data and subsequently evaluate efficiently the probabilistic condition of bridges.