• Journal of the Earthquake Engineering Society of Korea
• /
• v.14 no.2
• /
• pp.1-13
• /
• 2010

This paper proposes an optimal design method for the nonlinear seismic isolated bridge. The probabilities of failure at the pier and the seismic isolator are considered as objective functions for optimal design, and a multi-objective optimization technique is employed to efficiently explore a set of multiple solutions optimizing mutually-conflicting objective functions at the same time. In addition, a stochastic linearization method is incorporated into the multi-objective optimization framework in order to effectively estimate the stochastic responses of the bridge without performing numerous nonlinear time history analyses during the optimization process. As a numerical example to demonstrate the efficiency of the proposed method, the Nam-Han river bridge is taken into account, and the proposed method and the existing life-cycle-cost based design method are both applied for the purpose of comparing their seismic performances. The comparative results demonstrate that the proposed method not only shows better seismic performance but also is more economical than the existing cost-based design method. The proposed method is also proven to guarantee improved performance under variations in seismic intensity, in bandwidth and in the predominant frequency of the seismic event.

• Structural Engineering and Mechanics
• /
• v.65 no.2
• /
• pp.173-181
• /
• 2018

In this paper, finite element (FE) model updating based on multi-objective optimization with the surrogate model for a steel plate girder bridge is investigated. Conventionally, FE model updating for bridge structures uses single-objective optimization with finite element analysis (FEA). In the case of the conventional method, computational burden occurs considerably because a lot of iteration are performed during the updating process. This issue can be addressed by replacing FEA with the surrogate model. The other problem is that the updating result from single-objective optimization depends on the condition of the weighting factors. Previous studies have used the trial-and-error strategy, genetic algorithm, or user's preference to obtain the most preferred model; but it needs considerable computation cost. In this study, the FE model updating method consisting of the surrogate model and multi-objective optimization, which can construct the Pareto-optimal front through a single run without considering the weighting factors, is proposed to overcome the limitations of the single-objective optimization. To verify the proposed method, the results of the proposed method are compared with those of the single-objective optimization. The comparison shows that the updated model from the multi-objective optimization is superior to the result of single-objective optimization in calculation time as well as the relative errors between the updated model and measurement.

• Journal of Electrical Engineering and Technology
• /
• v.9 no.6
• /
• pp.1882-1890
• /
• 2014

This paper proposes an augmented Lagrange Hopfield network (ALHN) based method for solving multi-objective short term fixed head hydrothermal scheduling problem. The main objective of the problem is to minimize both total power generation cost and emissions of $NO_x$, $SO_2$, and $CO_2$ over a scheduling period of one day while satisfying power balance, hydraulic, and generator operating limits constraints. The ALHN method is a combination of augmented Lagrange relaxation and continuous Hopfield neural network where the augmented Lagrange function is directly used as the energy function of the network. For implementation of the ALHN based method for solving the problem, ALHN is implemented for obtaining non-dominated solutions and fuzzy set theory is applied for obtaining the best compromise solution. The proposed method has been tested on different systems with different analyses and the obtained results have been compared to those from other methods available in the literature. The result comparisons have indicated that the proposed method is very efficient for solving the problem with good optimal solution and fast computational time. Therefore, the proposed ALHN can be a very favorable method for solving the multi-objective short term fixed head hydrothermal scheduling problems.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.8 no.4
• /
• pp.153-163
• /
• 2004

The main objective of this study is to develop a multi-objective fuzzy optimum design program of steel structures and to verify that the multi-objective fuzzy optimum design is more reasonable than the single objective optimum design in real structural design. In the optimization formulation, the objective functions are both total weight and deflection. The design constraints are derived from the ultimate strength of service ability requirement of AISC-LRFD specification. The structural analysis was performed by the finite element method and also considered geometric non-linearity. The different importance of optimum criteria were reflected with two weighting methods ; membership weighting method and objective weighting method. Thus, designers could choose rational optimum solution of structures with application of two weighting methods.

• Bulletin of the Society of Naval Architects of Korea
• /
• v.25 no.1
• /
• pp.11-20
• /
• 1988

From the engineering point of view, a synthesis as well as an analysis technique is explored to search for the improved design of grillage which is common in ship structure. As an approximate analysis method for the grillage, an interaction reaction method is developed and compared with the finite element method. It is found that the discrepancy between these two methods is so negligible that the percent method could be used effectively for the grillage analysis. As an optimization technique, a feasible direction method could be used is combined with the intersection reaction method in order to design a minimum weight optimal grillage. The feasible direction method shows a good numerical performance although it requires more calculation times compared with the direct search method. Finally, the application of multiple objective optimization method to grillage is investigated in order to resolve conflicts existed between the multiple objectives which is a common characteristic of structure design problem. Goal programming method is extended to handle a nonlinear property of constraints and objective functions. It seems that the nonlinear goal programming could help not only to establish a relative importance of each objective, but also enable the designer to choose the best combination of design variables.

• Structural Engineering and Mechanics
• /
• v.63 no.6
• /
• pp.825-835
• /
• 2017

Significant improvements to methodologies on structural damage detection (SDD) have emerged in recent years. However, many methods are related to inversion computation which is prone to be ill-posed or ill-conditioning, leading to low-computing efficiency or inaccurate results. To explore a more accurate solution with satisfactory efficiency, a PSO-INM algorithm, combining particle swarm optimization (PSO) algorithm and an improved Nelder-Mead method (INM), is proposed to solve multi-sample objective function defined based on Bayesian inference in this study. The PSO-based algorithm, as a heuristic algorithm, is reliable to explore solution to SDD problem converted into a constrained optimization problem in mathematics. And the multi-sample objective function provides a stable pattern under different level of noise. Advantages of multi-sample objective function and its superior over traditional objective function are studied. Numerical simulation results of a two-storey frame structure show that the proposed method is sensitive to multi-damage cases. For further confirming accuracy of the proposed method, the ASCE 4-storey benchmark frame structure subjected to single and multiple damage cases is employed. Different kinds of modal identification methods are utilized to extract structural modal data from noise-contaminating acceleration responses. The illustrated results show that the proposed method is efficient to exact locations and extents of induced damages in structures.

• Journal of Electrical Engineering and Technology
• /
• v.13 no.6
• /
• pp.2187-2195
• /
• 2018

In order to realize the multi-objective control of single-input multi-output nonlinear differential algebraic system (NDAS) and to improve the dynamic characteristics and static accuracy, a design method of nonlinear control with multi-objective feedback (NCMOF) is proposed, the principium of this method to arrange system poles, as well as its nature to coordinate dynamic characteristics and static accuracy of the system are analyzed in detail. Through NCMOF design method, the multi-objective control of the system is transformed into linear space, and then it is effectively controlled under the nonlinear feedback control law, the problem to balance all control objectives caused by less input and more output of the system thus is solved. Applying NCMOF design method to generator excitation system, the nonlinear excitation control law with terminal voltage, active power and rotor speed as objective outputs is designed. Simulation results show that NCMOF can not only improve the dynamic characteristics of generator, but also damp the mechanical oscillation of a generator in transient process. Moreover, NCMOF can control the terminal voltage of the generator to the setting value with no static error under typical disturbances.

• Steel and Composite Structures
• /
• v.33 no.6
• /
• pp.767-776
• /
• 2019

In this article, a simple and robust multi-objective assessment method to control design angles and node positions connected among steel outrigger truss members is proposed to approve both structural safety and economical cost. For given outrigger member layouts, the present method utilizes general-purpose prototypes of outrigger members, having resistance to withstand lateral load effects directly applied to tall buildings, which conform to variable connecting node and design space deposition. Outrigger layouts are set into several initial design conditions of height to width of an arbitrary given design space, i.e., variable design space. And then they are assessed in terms of a proposed multi-objective function optimizing both minimal total displacement and material quantity subjected to design impact factor indicating the importance of objectives. To evaluate the proposed multi-objective function, an analysis model uses a modified Maxwell-Mohr method, and an optimization model is defined by a ground structure assuming arbitrary discrete straight members. It provides a new robust assessment model from a local design point of view, as it may produce specific optimal prototypes of outrigger layouts corresponding to arbitrary height and width ratio of design space. Numerical examples verify the validity and robustness of the present assessment method for controlling prototypes of outrigger truss members considering a multi-objective optimization achieving structural safety and material cost.

• Communications for Statistical Applications and Methods
• /
• v.14 no.3
• /
• pp.601-608
• /
• 2007

Lee, et al. (1999) proposed a unique but universal robust objective function replacing the square objective function for the radial basis function network, and demonstrated some advantages. In this article, the robust objective function in Lee, et al. (1999) is adapted for a multilayer perceptron (MLP). The shape of the robust objective function is formed by the scale parameter. Another method of determining a proper value of that parameter is proposed.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2002.10a
• /
• pp.263-270
• /
• 2002

This study proposes a multi-objective optimum design method for a rational optimization of high-speed railway bridges. This multi-objective optimization is found to be effective in optimizing multi-objective problems that incorporate cost and dynamic responses such as vertical acceleration and displacement. These design factors are so important in the high-speed railway bridges. And the trade off method which is one of the most typical multi-objective optimization methods is used in this study, since the dynamic factors are formulated as objective function and also considered as constraints. And the Pareto curve can be obtained by performing the multi-objective optimization for real high-speed railway bridges. Thus, it is found that more reasonable design can be obtained when compared with those using conventional design procedure.