• 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.

• 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.

• Journal of Ocean Engineering and Technology
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• v.26 no.6
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• pp.80-85
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• 2012

The methods of robust design optimization (RDO) and reliability-based robust design optimization (RBRDO) were implemented in the present study. RBRDO is an integrated method that accounts for the design robustness of an objective function and for the reliability of constraints. The objective function in RBRDO is expressed in terms of the mean and standard deviation of an original objective function. Thus, a multi-objective formulation is employed. The regressive approximate models are generated via the moving least squares method (MLSM) and constraint-feasible moving least squares method (CF-MLSM), which make it possible to realize the feasibility regardless of the multimodality/nonlinearity of the constraint function during the approximate optimization processes. The regression model based RBRDO is newly devised and its numerical characteristics are explored using the design of an actively controlled ten bar truss structure.