• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.863-865
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• 1988

This paper presents a optimal Var allocation algorithm for minimizing transmission line losses and improving voltage profile in a given system. In this paper, nodal input data is considered as Gaussian distribution with their mean value and their variance. A Stocastic Linear programming technique based on chance constrained method is applied, to solve the var allocation problem with probabilistic constraint. The test result in 6-Bus Model system showes that the voltage distribution of load buses is improved and the power loss is more reduced than before var allocation.

• Journal of Korea Water Resources Association
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• v.36 no.1
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• pp.45-59
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• 2003

The method in this study, which is more efficiency than the existing method, propose the optimal rehabilitation model based on the deterioration prediction of the laying pipe by using the deterioration survey method of the water distribution system. The deterioration prediction model divides the deterioration degree of each pipe into 5 degree by using the probabilistic neural network. Also, the optimal residual durability is estimated by the calculated deterioration degree in each pipe and pipe diameter. The optimal rehabilitation model by integer programming base on the shortest path can calculate a time and cost of maintenance, rehabilitation, and replacement. Also, the model is divided into budget constraint and no budget constraint. Consequently, the model proposed by the study can be utilized as the quantitative method for the management of the water distribution system.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.6 s.177
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• pp.1529-1539
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• 2000

A newly developed optimization method which uses the genetic algorithm combined with the sensitivity analysis is presented in this paper. The genetic algorithm is a probabilistic method, searching the optimum at several points simultaneously, requiring only the values of the object and constraint functions. It has therefore more chances to find global solution and can be applied various problems. Nevertheless, it has such shortcomings that even it approaches the optimum rapidly in the early stage, it slows down afterward and it can't consider the constraints explicitly. It is only because it can't search the local area near the current points. The traditional method, on the other hand, using sensitivity analysis is of great advantage in searching the near optimum. Thus the combination of the two techniques makes use of the individual advantages, that is, the superiority both in global searching by the genetic algorithm and in local searching by the sensitivity analysis. Application of the method to the several test functions verifies that the method suggested is very efficient and powerful to find the global solutions, and that the constraints can be considered properly.

• Earthquakes and Structures
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• v.22 no.1
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• pp.95-107
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• 2022

This paper introduces a novel, rigorous, and efficient probabilistic methodology for the performance-based optimal design (PBOD) of semi-active tuned mass damper (SATMD) for seismically excited nonlinear structures. The proposed methodology is consistent with the modern performance-based earthquake engineering framework and aims to design reliable control systems. To this end, an optimization problem has been defined which considers the parameters of control systems as design variables and minimization of the probability of exceeding a targeted structural performance level during the lifetime as an objective function with a constraint on the failure probability of stroke length damage state associated with mass damper mechanism. The effectiveness of the proposed methodology is illustrated through a numerical example of performance analysis of an eight-story nonlinear shear building frame with hysteretic bilinear behavior. The SATMD with variable stiffness and damping have been designed separately with different mass ratios. Their performance has been compared with that of uncontrolled structure and the structure controlled with passive TMD in terms of probabilistic demand curves, response hazard curves, fragility curves, and exceedance probability of performance levels during the lifetime. Numerical results show the effectiveness, simplicity, and reliability of the proposed PBOD method in designing SATMD with variable stiffness and damping for the nonlinear frames where they have reduced the exceedance probability of the structure up to 49% and 44%, respectively.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.8
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• pp.975-981
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• 2013

A robust optimization is only one of the ways to minimize the effects of variances in design variables on the objective functions at the preliminary design stage. To predict the variances and to formulate the probabilistic constraints are the most important procedures for the robust optimization formulation. Though several methods such as the process capability index and the six sigma technique were proposed for the prediction and formulation of the variances and probabilistic constraints, respectively, there are few attempts using a percent defective which has been widely applied in the quality control of the manufacturing process for probabilistic constraints. In this study, the robust optimization for a lower control arm of automobile vehicle was carried out, in which the design space showing the mean and variance sensitivity of weight and stress was explored before robust optimization for a lower control arm. The 2nd order Taylor expansion for calculating the standard deviation was used to improve the numerical accuracy for predicting the variances. Simplex algorithm which does not use the gradient information in optimization was used to convert constrained optimization into unconstrained one in robust optimization.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.10
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• pp.1458-1466
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• 2004

Deterministic optimum designs that are obtained without consideration of uncertainties could lead to unrealiable designs. Such deterministic engineering optimization tends to promote the structural system with less reliability redundancy than obtained with conventional design procedures using the factor of safety. Consequently, deterministic optimized structures will usually have higher failure probabilities than unoptimized structures. This paper proposes the reliability based design optimization technique fur apressure tank considering temperature effect. This paper presents an efficient and stable reliability based design optimization method by using the advanced first order second moment method, which evaluates a probabilistic constraint for more accuracy. In addition, the response surface method is utilized to approximate the performance functions describing the system characteristics in the reliability based design optimization procedure.

• 한국전산유체공학회:학술대회논문집
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• 2004.03a
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• pp.9-16
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• 2004

This study presents results of aerodynamic wing optimization under uncertainties. To consider uncertainties, an alternative strategy for reliability-based design optimization(RBDO) is developed. The strategy utilizes a single loop algorithm and a sequential approximation optimization(SAO) technique. The SAO strategy relies on the trust region-SQP framework which validates approximated functions at every iteration. Further improvement in computational efficiency is achieved by applying the same sensitivity of limit state functions in the reliability analysis and in the equivalent deterministic constraint calculation. The framework is examined by solving an analytical test problem to show that the proposed framework has the computational efficiency over existing methods. The proposed strategy enables exploiting the RBDO technique in aerodynamic design. For the aerodynamic wing design problem, the solution converges to the reliable point satisfying the probabilistic constraints.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.32 no.4
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• pp.432-446
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• 1996

A stochastic Hamilton variational principle(SHVP) is formulated for dynamic problems of linear continuum. The SHVP allows incorporation of probabilistic distributions into the finite element analysis. The formulation is simplified by transformation of correlated random variables to a set of uncorrelated random variables through a standard eigenproblem. A procedure based on the Fourier analysis and synthesis is presented for eliminating secularities from the perturbation approach. In addition to, a method to analyse stochastic design sensitivity for structural dynamics is present. A combination of the adjoint variable approach and the second order perturbation method is used in the finite element codes. An alternative form of the constraint functional that holds for all times is introduced to consider the time response of dynamic sensitivity. The algorithms developed can readily be adapted to existing deterministic finite element codes. The numerical results for stochastic analysis by proceeding approach of cantilever, 2D-frame and 3D-frame illustrates in this paper.

• Journal of Computing Science and Engineering
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• v.4 no.4
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• pp.276-290
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• 2010

The join operator is fundamental in relational database systems. Evaluating join queries on large tables is challenging because records need to be efficiently matched based on a given key. In this work, we analyze join queries in SQL with large tables in which a foreign key may be null, invalid or valid, given a referential integrity constraint. We conduct an extensive join performance evaluation on three DBMSs. Specifically, we study join queries varying table sizes, row size and key probabilistic distribution, inserting null, invalid or valid foreign key values. We also benchmark three well-known query optimizations: view materialization, secondary index and join reordering. Our experiments show certain optimizations perform well across DBMSs, whereas other optimizations depend on the DBMS architecture.

• Structural Engineering and Mechanics
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• v.17 no.3_4
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• pp.593-609
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• 2004

Peak response is a more suitable index than mean response in the light of structural safety. In this study, a controller optimization method is proposed to restrict peak responses of building structures subject to earthquake excitations, which are modeled as partially stationary stochastic process. The constraints are given with specified failure probabilities of peak responses. LQR is chosen to assure stability in numerical process of optimization. Optimization problem is formulated with weightings on controlled outputs as design variables and gradients of objective and constraint functions are derived. Full state feedback controllers designed by the proposed method satisfy various design objectives and output feedback controllers using LQG also yield similar results without significant performance deterioration.