• Structural Monitoring and Maintenance
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• v.10 no.1
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• pp.63-86
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• 2023

Structural health monitoring and damage detection are essential for assessing, maintaining, and rehabilitating structures. Most of the existing damage detection approaches compare the current state structural response with the undamaged vibrational structural response, which is unsuitable for old and existing structures where undamaged vibrational responses are absent. One of the approaches for existing structures, numerical model updating/inverse modelling, available in the literature, is limited to numerical studies with high-end software. In this study, an attempt is made to study the effectiveness of the model updating technique, simplify modelling complexity, and economize its usability. The optimization-based detection problem is addressed by using programmable open-sourced code, OpenSees^® and a derivative-free optimization code, NOMAD^®. Modal analysis is used for damage identification of beam-like structures with several damage scenarios. The performance of the proposed methodology is validated both numerically and experimentally. The proposed method performs satisfactorily in identifying both locations and intensity of damage in structures.

• Journal of the Korea institute for structural maintenance and inspection
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• v.8 no.3
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• pp.131-140
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• 2004

The main objective of the research is to develop an algorithm for the optimum design of two dimensional steel frames using refined plastic hinge analysis which considers material and geometrical nonlinearities. Using developed algorithm, an optimum design was perform without calculating an effective length factor of the column (K-factor). A multi-level discrete optimization technique with two parameters has been developed and employed in the optimum design algorithm. The optimization algorithm is applied to structural design with the objective of minimizing the weight of a structure and with constraints on load limit, frame drift, ductility. Various application example is provided to demonstrate the feasibility, validity and efficiency of the developed program.

• Korean Journal of Materials Research
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• v.29 no.11
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• pp.670-676
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• 2019

We study substrate support structures and materials to improve uptime and shorten preventive maintenance cycles for chemical vapor deposition equipment. In order to improve the rolling of the substrate support, the bushing device adopts a ball transfer method in which a large ball and a small ball are mixed. When the main transfer ball of the bushing part of the substrate support contacts the substrate support, the small ball also rotates simultaneously with the rotation of the main ball, minimizing the resistance that can be generated during the vertical movement of the substrate support. As a result of the improvement, the glass substrate breakage rate is reduced by more than 90 ~ 95 %, and the equipment preventive maintenance and board support replacement cycles are extended four times or more, from once a month to more than four months, and the equipment uptime is at least 15 % improved. This study proposes an optimization method for substrate support structure and material improvement of chemical vapor deposition equipment.

• Journal of the Korea institute for structural maintenance and inspection
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• v.11 no.2
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• pp.93-102
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• 2007

A large number of FRP decks are already in service worldwide because the lighter FRP-based bridge decks are ideal for rapid construction to reduce the dead load of superstructures. And the proper design process is demanded for the effective FRP deck application. In this paper, to get the basic prototype of FRP bridge decks, the ratio of individual parameters, which compose the specification of FRP bridge decks, are determined by a finite element analysis. In addition, optimum FRP deck shapes are determined considering complex constraints and material properties of bi-directional characteristics. Upon these results, the prototype of FRP bridge decks is validated.

• Journal of the Korean Geosynthetics Society
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• v.22 no.4
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• pp.17-26
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• 2023

To consider the risk of damage and fracture of P.C strands, the existing post-maintenance system alone has the limitations, hence it is necessary to quantitatively evaluate and predict the deterioration, durability and safety of facilities and establish a reasonable maintenance system considering the asset value of facilities. Therefore, it is worth considering a preventive maintenance plan that allows proactive measures to be taken before a major defect occurs in the temporary anchor. This study devised a preventive over tension method, reviewed its effectiveness through design and field tests, by calculating the resistance factors by performing a reliability-based optimization design. At this time, the over tension anchor method was evaluated using the ratio of the residual tension force after the fracture of P.C strands to the effective tension force before the fracture of P.C strand, followed by the resistance factor calculated by the optimal solution for each random variables using Excel solver and applying it to the limit state equations. As a result of the study, if the over tension ratio is 125% to 130%, the remaining strands showed a high resistance effect even after the fracture of P.C strand. As a result of the optimization design, it was found that it is appropriate to apply the load factor (γ) of 1.25, and the resistance factors of Φ₁, Φ₂, Φ₃ as 0.7, 0.5, 0.6.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.823-825
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• 1996

This paper proposes a preventive maintenance scheduling system which is a user-friendly decision-making support system. The objective of the development of the package is to supply KEPCO's working experts with a useful tool for gaining a practical maintenance schedule. This program based on the MS Windows is made up of two main modules. The first is an interactive decision-making support module(IDSM). The main objective of this module is to provide various useful text and graphic information to users, and enable practicing engineers with sensitivity analysis of a targeting maintenance schedule. The second is a mathematical optimization module(MOM). In this module, the objective function of levelizing net reserve ratio with daily time-increment is optimized using the relaxation method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.10
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• pp.82-88
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• 2018

The decoy defensive weapon system is a one-shot system. Reliability is maintained through periodic inspection and high reliability is required to confirm whether or not the functioning is normal after launch. The maintenance cycle of a decoy was set up without target reliability and reliability prediction during the development period. However, the number of operations in the military has been increasing, necessitating the optimization of the maintenance cycle. Reliability is analyzed using the maintenance data of a decoy operated for several decades and the optimal maintenance cycle is suggested. In chapter 2, data collection and classification methods are presented and analysis methodology is briefly introduced. In chapter 3, the data distribution analysis and fitness verification confirmed that applying the Weibull distribution is the most suitable for the maintenance data of the decoy. In chapter 4, we present the analysis result of percentile, survival probability and MTBF and the optimal maintenance cycle was derived from the reliability analysis. Finally, we suggest the application methods for this paper in the future.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.2
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• pp.254-260
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• 2017

The service life of civil infrastructure needs to be maintained or extended through appropriate inspections and maintenance planning, which results from the optimization process. A multi-objective optimization process can lead to more rational and flexible trade-off solutions rather than a single-objective optimization for the service life management of civil infrastructure. Recent investigations on the service life management of civil infrastructure were generally based on minimizing the life-cycle cost analysis and maximizing the structural performance. Various objectives for service life management have been developed using novel probabilistic concepts and methods over the last few decades. On the other hand, an increase in the number of objectives in a multi-objective optimization problem can lead to difficulties in computational efficiency, visualization, and decision making. These difficulties can be overcome using the objective reduction approach to identify the redundant and essential objectives. As a result, the efficiency in computational efforts, visualization, and decision making can be improved. In this paper, the multi-objective optimization using the objective reduction approach was applied to the service life management of concrete bridges. The results showed that four initial objectives can be reduced by two objectives for the optimal service life management.

• 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.

• Journal of the Korea institute for structural maintenance and inspection
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• v.7 no.4
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• pp.121-128
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• 2003

In recent years, various artificial neural network algorithms are used in the damage assessment of civil infrastructures. So far, many researchers have used the artificial neural network as a pattern classifier for the structural damage assessment but, in this paper, the neural network is used as a structural reanalysis tool not as a pattern classifier. For the model updating using the optimization algorithm, the summation of the absolute differences in the structural vibration modes between undamaged structures and damaged ones is considered as an objective function. The stiffness of structural components are treated as unknown parameters to be determined. The structural damage detection is achieved using model updating based on the optimization techniques which determine the estimated stiffness of components minimizing the objective function. For the verification of the proposed damage identification algorithm, it is numerically applied to a simply supported bridge model.