• Structural Engineering and Mechanics
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• v.75 no.3
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• pp.283-294
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• 2020

In general, the study of a high-rise building's behaviour when subjected to a horizontal load (wind or earthquake) is carried out through numerical modelling with finite elements method. This paper proposes a new, original approach based on the use of a multi-beams model. By redistributing bending and axial stiffness of horizontal elements (beams and slabs) along vertical elements, it becomes possible to produce a system of differential equations able to represent the structural behaviour of the whole building. In this paper this approach is applied to the study of bending behaviour in a 37-storey building (Torre Pontina, Latina, Italy) with a regular reinforced concrete structure. The load considered is the wind, estimated in accordance with Italian national technical rules and regulations. To simplify the explanation of the approach, the wind load was considered uniform on the height of building with a value equal to the average value of the wind load distribution. The system of differential equations' is assessed numerically, using Matlab, and compared with the obtainable solution from a finite elements model along with the obtainable solutions via classical Euler-Bernoulli beam theory. The comparison carried out demonstrates, in the case study examined, an excellent approximation of structural behaviour.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1997.10a
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• pp.145-154
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• 1997

The results of optimum design by the deterministic approach adopted in the current design codes depend upon the safety levels of the applied code. But, it is now generally recognized that structural problems are nondeterministic and, consequently, that engineering optimum design must cope with uncertainties. Therefore, it is not an overstatement to affirm that the combination of reliability-based design procedures and optimization techniques is the only means of providing a powerful tool to obtain a practical optimum design solution. In the paper, reliability based optimum design procedure as a rational approach to optimum structural design is presented. The design constraints are formulated based on the ASD, LRFD and reliability theories. The reliability analysis is based on an advanced first-order second moment approach. Uncertainties in the structural strength and loading due to inherent variability as well as modeling and prediction errors are included in failure due to combined bending and shear. For the realistic reliability-based optimization of continuous steel box girder bridges, interactive non-linear limit state model is formulated based on the von Mises's combined stress yield criterion. Comparative results are presented when the ASD criteria are used for the optimum design of a structure under reliability constraints. In addition, this study comparatively shows the results of the optimum design for various criteria of design codes.

• 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.29 no.2
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• pp.321-336
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• 2022

Model uncertainty is a key factor that could influence the accuracy and reliability of numerical model-based analysis. It is necessary to acquire an appropriate updating approach which could search and determine the realistic model parameter values from measurements. In this paper, the Bayesian model updating theory combined with the transitional Markov chain Monte Carlo (TMCMC) method and K-means cluster analysis is utilized in the updating of the structural model parameters. Kriging and polynomial chaos expansion (PCE) are employed to generate surrogate models to reduce the computational burden in TMCMC. The selected updating approaches are applied to three structural examples with different complexity, including a two-storey frame, a ten-storey frame, and the national stadium model. These models stand for the low-dimensional linear model, the high-dimensional linear model, and the nonlinear model, respectively. The performances of updating in these three models are assessed in terms of the prediction uncertainty, numerical efforts, and prior information. This study also investigates the updating scenarios using the analytical approach and surrogate models. The uncertainty quantification in the Bayesian approach is further discussed to verify the validity and accuracy of the surrogate models. Finally, the advantages and limitations of the surrogate model-based updating approaches are discussed for different structural complexity. The possibility of utilizing the boosting algorithm as an ensemble learning method for improving the surrogate models is also presented.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.36 no.4
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• pp.64-70
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• 2013

Estimation approaches for casual relation model with high-order factors have strict restrictions or limits. In the case of ML (Maximum Likelihood), a strong assumption which data must show a normal distribution is required and factors of exponentiation is impossible due to the uncertainty of factors. To overcome this limitation many PLS (Partial Least Squares) approaches are introduced to estimate the structural equation model including high-order factors. However, it is possible to yield biased estimates if there are some differences in the number of measurement variables connected to each latent variable. In addition, any approach does not exist to deal with general cases not having any measurement variable of high-order factors. This study compare several approaches including the repeated measures approach which are used to estimate the casual relation model including high-order factors by using PLS (Partial Least Squares), and suggest the best estimation approach. In other words, the study proposes the best approach through the research on the existing studies related to the casual relation model including high-order factors by using PLS and approach comparison using a virtual model.

• Proceedings of the Korea Concrete Institute Conference
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• 2003.05a
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• pp.181-186
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• 2003

There are many uncertainties in structural failures or structures, so probabilistic failure cause assessment should be performed in order to consider the uncertainties. However, in many cases of forensic engineering, the failure cause assessments are performed by deterministic approach though number of uncertainties are existed in the failures or structures. Thus, deterministic approach may have possibility for leading to unreasonable and unrealistic failure cause assessment due to ignorance of the uncertainties. Therefore, probabilistic approach is needed to complement the shortcoming of deterministic approach and to perform the more reasonable and realistic failure cause assessment. In this study, reliability-based failure cause assessment (reliability based forensic engineering) is performed, which can incorporate uncertainties in failures and structures. For more practical application, the modified ETA technique is proposed, which automatically generates the defected structural model, performs structural analysis and reliability analysis, and calculates the failure probabilities of the failure events and the occurrence probabilities of the failure scenarios. Also, for more precise reliability analysis, uncertainties are estimated more reasonably by using bayesian approach based on the experimental laboratory testing data in forensic report.

• Steel and Composite Structures
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• v.22 no.3
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• pp.589-611
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• 2016

The primary objectives of this research are to investigate the energy factor response of steel moment resisting frame (MRF) systems equipped with fuses subject to ground motions and to develop an energy-based evaluation approach for evaluating the damage-control behavior of the system. First, the energy factor of steel MRF systems with fuses below the resilience threshold is derived utilizing the energy balance equation considering bilinear oscillators with significant post-yielding stiffness ratio, and the effect of structural nonlinearity on the energy factor is investigated by conducting a parametric study covering a wide range of parameters. A practical transformation approach is also proposed to associate the energy factor of steel MRF systems with fuses with classic design spectra based on elasto-plastic systems. Then, the energy balance is extended to structural systems, and an energy-based procedure for damage-control evaluation is proposed and a damage-control index is also derived. The approach is then applied to two types of steel MRF systems with fuses to explore the applicability for quantifying the damage-control behavior. The rationality of the proposed approach and the accuracy for identifying the damage-control behavior are demonstrated by nonlinear static analyses and incremental dynamic analyses utilizing prototype structures.

• Journal of Information Processing Systems
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• v.13 no.4
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• pp.834-851
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• 2017

The amount of sources of information available on the web using ontologies as support continues to increase and is often heterogeneous and distributed. Ontology alignment is the solution to ensure semantic interoperability. In this paper, we describe a new ontology alignment approach, which consists of combining structure-based and reasoning-based approaches in order to discover new semantic correspondences between entities of different ontologies. We used the biblio test of the benchmark series and anatomy series of the Ontology Alignment Evaluation Initiative (OAEI) 2012 evaluation campaign to evaluate the performance of our approach. We compared our approach successively with LogMap and YAM++ systems. We also analyzed the contribution of our method compared to structural and semantic methods. The results obtained show that our performance provides good performance. Indeed, these results are better than those of the LogMap system in terms of precision, recall, and F-measure. Our approach has also been proven to be more relevant than YAM++ for certain types of ontologies and significantly improves the structure-based and reasoningbased methods.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1995.04a
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• pp.160-169
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• 1995

This study presents an application of object-oriented methodology for structural dcsign process. A prototype system of integrated a structural design system is developed by introducing a structural analysis object model(SAOM) and structural design object model(SDOM). The SAOM module. which is modeled as a part of structural member, performs structural analysis using FEM approach and the SDOM module checks structural members based on Korea steel design standard. Above mentionedmodelsareabstraclencapsulatibleandreusable.

• Structural Engineering and Mechanics
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• v.74 no.1
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• pp.55-67
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• 2020

The common practice to predict the characteristic structural load effects (LEs) in long reference periods is to employ the extreme value theory (EVT) for building limit distributions. However, most applications ignore that LEs are driven by multiple loading events and thus do not have the identical distribution, a prerequisite for EVT. In this study, we propose the composite extreme value modeling approach using clustering to (a) cluster initial blended samples into finite identical distributed subsamples using the finite mixture model, expectation-maximization algorithm, and the Akaike information criterion; (b) combine limit distributions of subsamples into a composite prediction equation using the generalized Pareto distribution based on a joint threshold. The proposed approach was validated both through numerical examples with known solutions and engineering applications of bridge traffic LEs on a long-span bridge. The results indicate that a joint threshold largely benefits the composite extreme value modeling, many appropriate tail approaching models can be used, and the equation form is simply the sum of the weighted models. In numerical examples, the proposed approach using clustering generated accurate extrema prediction of any reference period compared with the known solutions, whereas the common practice of employing EVT without clustering on the mixture data showed large deviations. Real-world bridge traffic LEs are driven by multi-events and present multipeak distributions, and the proposed approach is more capable of capturing the tendency of tailed LEs than the conventional approach. The proposed approach is expected to have wide applications to general problems such as samples that are driven by multiple events and that do not have the identical distribution.