• Smart Structures and Systems
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• v.16 no.1
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• pp.47-65
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• 2015

A novel finite element (FE) model updating method based on multi-resolution analysis (MRA) is proposed. The true stiffness of the FE model is considered as the superposition of two pieces of stiffness information of different resolutions: the pre-defined stiffness information and updating stiffness information. While the resolution of former is solely decided by the meshing density of the FE model, the resolution of latter is decided by the limited information obtained from the experiment. The latter resolution is considerably lower than the former. Second generation wavelet is adopted to describe the updating stiffness information in the framework of MRA. This updating stiffness in MRA is realized at low level of resolution, therefore, needs less number of updating parameters. The efficiency of the optimization process is thus enhanced. The proposed method is suitable for the identification of multiple irregular cracks and performs well in capturing the global features of the structural damage. After the global features are identified, a refinement process proposed in the paper can be carried out to improve the performance of the MRA of the updating information. The effectiveness of the method is verified by numerical simulations of a box girder and the experiment of a three-span continues pre-stressed concrete bridge. It is shown that the proposed method corresponds well to the global features of the structural damage and is stable against the perturbation of modal parameters and small variations of the damage.

• Earthquakes and Structures
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• v.16 no.5
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• pp.523-532
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• 2019

Different types of gas reservoir such as Liquid Natural Gas (LNG) are among the strategic infrastructures, and have great importance for any government or their private owners. To keep the tank and its contents safe during earthquakes especially if the contents are of hazardous or flammable materials; using seismic protection systems such as base isolator can be considered as an effective solution. However, the major deficiency of this system can be the large deformation in the isolation level which may lead to the failure of bearing system. In this paper, as a solution, the efficacy of an optimally designed combined vibration control system, the combined laminated rubber isolator and rotational friction damper, is investigated to evaluate the enhancement of an existing metal tank response under both far- and near-field earthquakes. Responses like impulsive and convective accelerations, base shear, and sloshing height are studied herein. The probabilistic framework is used to consider the uncertainties in the structural modeling, as well as record-to-record variability. Due to the high calculation cost of probabilistic methods, a simplified structural model is used. By using the Mont-Carlo simulation approach, it is revealed that this combined isolation system is a highly reliable system which provides considerable enhancement in the performance of reservoir, not only leads to the reduction of probability of catastrophic failure of the tank but also decrease the reservoir damage during the earthquake. Moreover, the relative displacement of the isolation level is controlled very well by this combined system.

• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.1
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• pp.10-18
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• 2022

This report describes the development and stability evaluation of a seismic retrofit method to evaluate the seismic performance of existing school buildings by analyzing the earthquake waveforms that occurred in Korea. Currently, Facilities for seismic retrofit designed for excessive reinforcement are being applied. To compensate for this, optimised the retrofit mothod suitable for domestic situation considering the characteristics of the seismic region, generated a Korean-style artificial seismic wave that meets the seismic design criteria, which is less frequent than other countries.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.2
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• pp.45-51
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• 2006

In this paper, we propose a new architecture of Information Granulation based genetically optimized Self-Organizing Fuzzy Polynomial Neural Networks (IG_gSOFPNN) that is based on a genetically optimized multilayer perceptron with fuzzy polynomial neurons (FPNs) and discuss its comprehensive design methodology involving mechanisms of genetic optimization, especially information granulation and genetic algorithms. The proposed IG_gSOFPNN gives rise to a structurally optimized structure and comes with a substantial level of flexibility in comparison to the one we encounter in conventional SOFPNNs. The design procedure applied in the construction of each layer of a SOFPNN deals with its structural optimization involving the selection of preferred nodes (or FPNs) with specific local characteristics (such as the number of input variables, the order of the polynomial of the consequent part of fuzzy rules, and a collection of the specific subset of input variables) and addresses specific aspects of parametric optimization. In addition, the fuzzy rules used in the networks exploit the notion of information granules defined over system's variables and formed through the process of information granulation. That is, we determine the initial location (apexes) of membership functions and initial values of polynomial function being used in the premised and consequence part of the fuzzy rules respectively. This granulation is realized with the aid of the hard c-menas clustering method (HCM). To evaluate the performance of the IG_gSOFPNN, the model is experimented with using two time series data(gas furnace process and NOx process data).

• Structural Monitoring and Maintenance
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• v.6 no.4
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• pp.317-346
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• 2019

Performance assessment of pavements proves useful, in terms of handling the ride quality, controlling the travel time of vehicles and adequate maintenance of pavements. Roughness profiles provide a good measure of the deteriorating condition of the pavement. For the accurate estimates of pavement roughness from dynamic vehicle responses, vehicle parameters should be known accurately. Information on vehicle parameters is uncertain, due to the wear and tear over time. Hence, condition monitoring of pavement requires the identification of pavement roughness along with vehicle parameters. The present study proposes a scheme which estimates the roughness profile of the pavement with the use of accurate estimates of vehicle parameters computed in parallel. Pavement model used in this study is a two-layer Euler-Bernoulli beam resting on a nonlinear Pasternak foundation. The asphalt topping of the pavement in the top layer is modeled as viscoelastic, and the base course bottom layer is modeled as elastic. The viscoelastic response of the top layer is modeled with the help of the Burgers model. The vehicle model considered in this study is a half car model, fitted with accelerometers at specified points. The identification of the coupled system of vehicle-pavement interaction employs a coupled scheme of an unbiased minimum variance estimator and an optimization scheme. The partitioning of observed noisy quantities to be used in the two schemes is investigated in detail before the analysis. The unbiased minimum variance estimator (MVE) make use of a linear state-space formulation including roughness, to overcome the linearization difficulties as in conventional nonlinear filters. MVE gives estimates for the unknown input and fed into the optimization scheme to yield estimates of vehicle parameters. The issue of ill-posedness of the problem is dealt with by introducing a regularization equivalent term in the objective function, specifically where a large number of parameters are to be estimated. Effect of different objective functions is also studied. The outcome of this research is an overall measure of pavement condition.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.8
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• pp.561-570
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• 2004

In this paper, new architectures and comprehensive design methodologies of Genetic Algorithms(GAs) based Genetically optimized Neurofuzzy Networks(GoNFN) are introduced, and a series of numeric experiments are carried out. The proposed GoNFN is based on the rule-based Neurofuzzy Networks(NFN) with the extended structure of the premise and the consequence parts of fuzzy rules being formed within the networks. The premise part of the fuzzy rules are designed by using space partitioning in terms of fuzzy sets defined in individual variables. In the consequence part of the fuzzy rules, three different forms of the regression polynomials such as constant, linear and quadratic are taken into consideration. The structure and parameters of the proposed GoNFN are optimized by GAs. GAs being a global optimization technique determines optimal parameters in a vast search space. But it cannot effectively avoid a large amount of time-consuming iteration because GAs finds optimal parameters by using a given space. To alleviate the problems, the dynamic search-based GAs is introduced to lead to rapidly optimal convergence over a limited region or a boundary condition. In a nutshell, the objective of this study is to develop a general design methodology o GAs-based GoNFN modeling, come up a logic-based structure of such model and propose a comprehensive evolutionary development environment in which the optimization of the model can be efficiently carried out both at the structural as well as parametric level for overall optimization by utilizing the separate or consecutive tuning technology. To evaluate the performance of the proposed GoNFN, the models are experimented with the use of several representative numerical examples.

• Journal of the Korea Society for Simulation
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• v.29 no.3
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• pp.49-55
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• 2020

A goal of improving projectile is to increasing achievable range. The shape of a projectile is generally selected on the basis of combined aerodynamics and structural considerations. The choice of body, nose and boattail shape has a large effect on aerodynamic design. One of the main design factors that affect projectile configuration is aerodynamic drag. The aerodynamic drag refers to the aerodynamic force that acts opposite to the relative motion of a projectile. An investigation was made to predict the effects of nose, boattail and body shapes on the aerodynamic characteristics of projectiles using a semi-empirical technique. A parametric study is conducted which includes different projectile geometry. Performance predictions of achievable range are conducted using a trajectory simulation model. The potential of extending the range of a projectile using optimization of projectile configuration is evaluated. The maximum range increase is achieved due to the combination of optimal body shapes.

• Computers and Concrete
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• v.29 no.6
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• pp.375-391
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• 2022

This paper examined the impact of the cross-sectional structure on the structural results under different loading conditions of reinforced concrete (RC) members' management limited in Carbon Fiber Reinforced Polymers (CFRP). The mechanical properties of CFRC was investigated, then, totally 32 samples were examined. Test parameters included the cross-sectional shape as square, rectangular and circular with two various aspect rates and loading statues. The loading involved concentrated loading, eccentric loading with a ratio of 0.46 to 0.6 and pure bending. The results of the test revealed that the CFRP increased ductility and load during concentrated processing. A cross sectional shape from 23 to 44 percent was increased in load capacity and from 250 to 350 percent increase in axial deformation in rectangular and circular sections respectively, affecting greatly the accomplishment of load capacity and ductility of the concentrated members. Two Artificial Intelligence Models as Extreme Learning Machine (ELM) and Particle Swarm Optimization (PSO) were used to estimating the tensile and flexural strength of specimen. On the basis of the performance from RMSE and RSQR, C-Shape CFRC was greater tensile and flexural strength than any other FRP composite design. Because of the mechanical anchorage into the matrix, C-shaped CFRCC was noted to have greater fiber-matrix interfacial adhesive strength. However, with the increase of the aspect ratio and fiber volume fraction, the compressive strength of CFRCC was reduced. This possibly was due to the fact that during the blending of each fiber, the volume of air input was increased. In addition, by adding silica fumed to composites, the tensile and flexural strength of CFRCC is greatly improved.

• Journal of Aerospace System Engineering
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• v.12 no.3
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• pp.70-78
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• 2018

This research was carried out to develop an integrated folding wing made from carbon composite materials. Design requirements were reviewed and composite wing sizing was conducted using design optimization with commercial software. Three composite manufacturing processes including hot-press, pultrusion, and autoclave were evaluated and the most suitable processes for the integrated wing fabrication were selected, with consideration given to performance and cost. The determined manufacturing process was verified by two design development tests for selecting the design concept. Stiffness and strength of the composite wing were estimated through structural analyses. The test loads were calculated and static tests about design limit load and design ultimate load were performed using both wings. As a result, the evaluation criterions of the tests were satisfied and structural safety was verified through the series of structural analyses and testing.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.27 no.4
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• pp.231-238
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• 2014

In the buildings, the systems of structures are influenced by the gravity load changes due to room alteration or construction stage. This paper proposes a system identification method establishing mass as well as stiffness to parameters in model updating process considering mass change in the buildings. In this proposed method, modified genetic algorithm, which is optimization technique, is applied to search those parameters while minimizing the difference of dynamic characteristics between measurement and FE model. To search more global solution, the proposed modified genetic algorithm searches in the wider search space. It is verified that the proposed method identifies the system of structure appropriately through the analytical study on a steel beam structure in the building. The comparison for performance of modified genetic algorithm and existing simple genetic algorithm is carried out. Furthermore, the existing model updating method neglecting mass change is performed to compare with the proposed method.