• Journal of Ocean Engineering and Technology
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• v.24 no.1
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• pp.20-33
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• 2010

The paper deals with strength design of a riser support installed on floating production storage and offloading (FPSO) vessel under various loading conditions - operation, extreme, damaged, one line failure case (OLFC) and installation. The design problem is formulated such that thickness sizing variables are determined by minimizing the weight of a riser support structure subject to stresses constraints. The initial design model is generated based on an actual FPSO riser support specification. The finite element analysis (FEA) is conducted using MSC/NASTRAN, and optimal solutions are obtained via moving least squares method (MLSM) in the context of response surface based approximate optimization. For the meta-modeling of inequality constraint functions of stresses, a constraint-feasible moving least squares method (CF-MLSM) is used in the present study. The method of CF-MLSM, compared to a conventional MLSM, has been shown to ensure the constraint feasibility in a case where the approximate optimization process is employed. The optimization results present improved design performances under various riser operating conditions.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.12
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• pp.3053-3060
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• 2000

Alternative formulation is presented for robust optimization problems and an efficient computational scheme for reliability estimation is proposed. Both design variables and design parameters considered as random variables about their nominal values. To ensure the robustness of objective performance a new cost function bounding the performance and a new constraint limiting the performance variation are introduced. The constraint variations are regulated by considering the probability of feasibility. Each probability constraint is transformed into a sub-optimization problem and then is resolved with the modified advanced first order second moment(AFOSM) method for computational efficiency. The proposed robust optimization method has advantages that the mean value and the variation of the performance function are controlled simultaneously and the second order sensitivity information is not required even in case of gradient based optimization. The suggested method is examined by solving three examples and the results are compared with those for deterministic case and those available in literature.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.1
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• pp.112-123
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• 1997

The optimization techniques have been applied to versatile engineering problems for reducing manufacturing cost and for automatic design. The deterministic approaches or op5imization neglect the effects on uncertainties of design variables. The uncertainties include variation or perturbation such as tolerance band. The optimum may be useless when the constraints considering worst cases of design variables can not be satisfied, which results from constraint variation. The variation of design variables can also give rise to drastic change of performances. The two issues are related to constraint feasibility and insensitive performance. Robust design suggested in the present study is developed to gain an optimum insensitive to variation on design variables within feasible region. The multiobjective function is composed to the mean and the standard deviation of original objective function, while the constraints are supplemented by adding penalty term to original constraints. This method has a advantage that the second derivatives of the constraints are not required. A mathematical problem and several standard problems for structural optimization are solved to check out the usefulness of the suggested method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.1
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• pp.49-56
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• 2013

In this paper, for constrained optimization problem, one multi-objective optimization algorithm that ensures both performance robustness and constraint feasibility is proposed when uncertainties are involved in design variables. In the proposed algorithm, the gradient index of objective function assisted by design sensitivity with the help of finite element method is applied to evaluate robustness; the reliability calculated by the sensitivity-assisted Monte Carlo simulation method is used to assess the feasibility of constraint function. As a demonstration, the performance and numerical efficiency of the proposed method is investigated through application to the optimal design of TEAM problem 22--a superconducting magnetic energy storage system.

• Journal of Intelligence and Information Systems
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• v.8 no.1
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• pp.119-139
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• 2002

In electronic catalogs, each item is represented as an independent unit while the parts of the item can be composed of a higher level of functionality. Thus, the search for this kind of product database is limited to the retrieval of most similar standard commodities. However, many industrial products need to configure optional parts to fulfill the required specifications. Since there are many paths in finding the required specifications, we need to develop a search system via the configuration process. In this system, we adopt a two-phased approach. The first phase finds the most similar template, and the second phase adjusts the template specifications toward the required set of specifications by the Constraint and Rule Satisfaction Problem approach. There is no guarantee that the most similar template can find the most desirable configuration. The search system needs backtracking capability, so the search can stop at a satisfied local optimal satisfaction. This framework is applied to the configuration of computers and peripherals. Template-based reasoning is basically the same as case-based reasoning. The required set of specifications is represented by a list of criteria, and matched with the product specifications to find the closest ones. To measure the distance, we develop a thesaurus of values, which can identify the meaning of numbers, symbols, and words. With this configuration, the performance of the search by configuration algorithm is evaluated in terms of feasibility and admissibility.

• Journal of the Korean Operations Research and Management Science Society
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• v.37 no.4
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• pp.67-72
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• 2012

In this paper a new method of handling linear constraints for the genetic algorithm is suggested. The method is designed to maintain the feasibility of offsprings during the evolution process of the genetic algorithm. In the genetic algorithm, the chromosomes are coded as the vectors in the real vector space constrained by the linear constraints. A method of handling the linear constraints already exists in which all the constraints of equalities are eliminated so that only the constraints of inequalities are considered in the process of the genetic algorithm. In this paper a new method is presented in which all the constraints of inequalities are eliminated so that only the constraints of equalities are considered. Several genetic operators such as arithmetic crossover, simplex crossover, simple crossover and random vector mutation are designed so that the resulting offspring vectors maintain the feasibility subject to the linear constraints in the framework of the new handling method.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.24 no.5
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• pp.543-551
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• 2011

The paper deals with the comparative study of design optimization based on various approximation techniques in strength design of riser support structure installed on floating production storage and offloading unit(FPSO) using offshore operation loading conditions. The design optimization problem is formulated such that structural member sizing variables are determined by minimizing the weight of riser support structure subject to the constraints of structural strength in terms of loading conditions. The approximation techniques used in the comparative study are response surface method based sequential approximate optimization(RBSAO), Kriging based sequential approximate optimization(KBSAO), and the enhanced moving least squares method(MLSM) based approximate optimization such as CF(constraint feasible)-MLSM and Post-MLSM. Commercial process integration and design optimization(PIDO) tools are employed for the applications of RBSAO and KBSAO. The enhanced MLSM based approximate optimization techniques are newly developed to ensure the constraint feasibility. In the context of numerical performances such as design solution and computational cost, the solution results from approximate techniques based design optimization are compared to actual non-approximate design optimization.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.11
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• pp.1603-1611
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• 2010

The comparative study of regression-model-based approximate optimization techniques used in the strength design of an automotive knuckle component that will be under bump and brake loading conditions is carried out. The design problem is formulated such that the cross-sectional sizing variables are determined by minimizing the weight of the knuckle component that is subjected to stresses, deformations, and vibration frequency constraints. The techniques used in the comparative study are sequential approximate optimization (SAO), sequential two-point diagonal quadratic approximate optimization (STDQAO), and approximate optimization based on enhanced moving least squares method (MLSM), such as CF (constraint feasible)-MLSM and Post-MLSM. Commercial process integration and design optimization (PIDO) tools are utilized for the application of SAO and STDQAO. The enhanced MLSM-based approximate optimization techniques are newly developed to ensure constraint feasibility. The results of the approximate optimization techniques are compared with those of actual non-approximate optimization to evaluate their numerical performances.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.7
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• pp.1270-1276
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• 2016

This paper proposes the controller design for regulation control of two-link robot arm using sum of squares (SOS) control method that takes into account the input constraint. The existing studies of two link robotic arm system used a linear model of all the non-linearity of the system is linearized. For a linear controller, since the model of the system is simplified, it is possible to design a controller in consideration of constraints on the disturbance. However, there is a limit to the performance using a linearized model for a system with a complex nonlinear properties. To compensate for this in the case of using a fuzzy LMI method, it is necessary to have a large number of linear models and thus there is a disadvantage that the system becomes complicated. To solve these problems, we represents a two-link robot arm system with a polynomial model using a Taylor series expansion and design the controller considering the case where the magnitude of the control input is limited using SOS method. We demonstrate by simulations the feasibility of the proposed algorithm.

• The Journal of Korea Robotics Society
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• v.6 no.4
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• pp.308-316
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• 2011

This work deals with development of effective redundancy resolution algorithms for the motion control of manipulator. Differently from the typical kinematically redundant robots that are attached to the fixed ground, the ZMP condition should be taken into account in the manipulator motion in order to guarantee the system stability. In this paper, a new motion planning algorithm for redundant manipulator not fixed to the ground is introduced. A sequential redundancy resolution algorithm is proposed, which ensures the ZMP (Zero Moment Point) stability, the planned operational motion, and additional sub-criteria such as joint limit index. A geometric constraint equation derived by reshaping the existing ZMP equation enables one to employ the sequential redundancy algorithm. The feasibility of the proposed algorithm is verified by simulating a redundant manipulator model.