• Proceedings of the KSME Conference
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• 2003.04a
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• pp.1234-1239
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• 2003

In the product design process computer-aided engineering and optimization tools are widely utilized in order to reduce the total development time and cost. Since several simulation tools are involved in the process, information losses, omissions, or errors are common and the importance of seamless information exchange among the tools has been increased. In this study ISO STEP standards are adopted to represent the neutral format for CAE/CAO information exchange. The schema of AP209 is used to define the information of finite element analysis and the new schema is proposed to describe the information of structural optimization based on the STEP methodology. The schema is implemented by EXPRESS, information modeling language, and ST-Developer is employed to generate C++ classes and STEP Rose Library by using the schema denoted. To substantiate the proposed approach, the information access interfaces of the finite element modeling software (FEMAP), structural optimization software (GENESIS) and in-house topology optimization program are developed. Examples of the size optimization of a three-bar truss and topology optimization of a MBB beam are shown to validate the information exchange of finite element analysis and structural optimization using STEP standards.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.3
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• pp.369-380
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• 2001

Although extensive efforts have been devoted to the optimal design of composite laminated plates in recent years, some practical issues still need further research. Two of them are: the handling of the ply angle as either continuous or discrete; and that of the uncertainties in material properties, which were treated as continuous and ignored respectively in most researches in the past. In this paper, an algorithm for stacking sequence optimization which deals with discrete ply angles and that for thickness optimization which considers uncertainties in material properties are used for a two step optimization of composite laminated plates. In the stacking sequence optimization, the branch and bound method is modified to handle discrete variables; and in the thickness optimization, the convex modeling is used in calculating the failure criterion, given as constraint, to consider the uncertain material properties. Numerical results show that the optimal stacking sequence is found with fewer evaluations of objective function than expected with the size of feasible region taken into consideration; and the optimal thickness increases when the uncertainties of elastic moduli considered, which shows such uncertainties should not be ignored for safe and reliable designs.

• Nuclear Engineering and Technology
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• v.52 no.5
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• pp.956-963
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• 2020

Dose optimization for Radioactive Occupational Personal (ROP) is an important subject in nuclear and radiation safety field. The geometric environment of a nuclear facility is complex and the work area is radioactive, so traditional navigation model and radioactive data field cannot form an effective environment model for dose assessment and dose optimization. The environment model directly affects dose assessment and indirectly affects dose optimization, this is an urgent problem needed to be solved. Therefore, this paper focuses on an environment model used for Dose Assessment and Dose Optimization (DA&DO). We designed a multi-layer radiation field coupling modeling method, and then explored the influence of the environment model to DA&DO by virtual simulation. Then, a simulation test is done, the multi-layer radiation field coupling model for nuclear facilities is demonstrated to be effective for dose assessment and dose optimization through the experiments and analysis.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.31 no.8
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• pp.27-35
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• 2003

Geometric modeling tool and analysis tool of shell surface have been developed in the different environments and purposes. Thus they cannot be naturally fitted to each other for the integrated design and analysis. In the present study, an integrated framework of geometric modeling, analysis， and design optimization is proposed. It is based on the common representation of B-spline surface patch. In the analysis module, a geometrically-exact shell finite element is implemented. In shape optimization module, control points of the surface are selected as design variables. For the computation of shape sensitivities, semi-analytical method is used. Sequential linear programming(SLP) is adopted for the shape optimization of surfaces. The developed integrated framework should serve as a powerful tool for the geometric modeling, analysis, and shape design of surfaces.

• Korean Journal of Computational Design and Engineering
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• v.11 no.2
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• pp.128-137
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• 2006

In this paper, a CAD/CAE integrated optimal design system is developed, in which design and analysis process is automated using CAD/CAE softwares for a complex model in which the modeling by parametric feature is not easy to apply. Unigraphics is used for CAD modeling, in which the process is automated by using UG/Knowledge Fusion for modeling itself and UG/Open API function for the other functions respectively. Structural analyses are also carried out automatically by ANSYS using the imported parasolid model. The developed system is applied for the PLS(Plasma Lighting System) consisting of more than 20 components, which is a next generation illumination system that is used to illuminate stadium or outdoor advertizing panel. The analyses include responses by static, wind and impact loads. As a result of analyses, tilt assembly, which is a link between upper and lower body, is found to be the most critical component bearing higher stresses. Experiment is conducted using MTS to validate the analysis result. Optimization is carried out using the software Visual DOC for the tilt assembly to minimize material volume while maintaining allowable stress level. As a result of optimization, the maximum stress is reduced by 57% from the existing design, though the material volume has increased by 21%.

• Ocean Systems Engineering
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• v.9 no.2
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• pp.111-133
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• 2019

Flow through a scaled horizontal axis marine current turbine was numerically simulated after validation and the turbine design was optimized. The computational fluid dynamics (CFD) code Ansys-CFX 16.1 for numerical modeling, an in-house blade element momentum (BEM) code for analytical modeling and an in-house surrogate-based optimization (SBO) code were used to find an optimal turbine design. The blade-pitch angle (${\theta}$) and the number of rotor blades (NR) were taken as design variables. A single objective optimization approach was utilized in the present work. The defined objective function was the turbine's power coefficient ($C_P$). A $3{\times}3$ full-factorial sampling technique was used to define the sample space. This sampling technique gave different turbine designs, which were further evaluated for the objective function by solving the Reynolds-Averaged Navier-Stokes equations (RANS). Finally, the SBO technique with search algorithm produced an optimal design. It is found that the optimal design has improved the objective function by 26.5%. This article presents the solution approach, analysis of the turbine flow field and the predictability of various surrogate based techniques.

• Structural Engineering and Mechanics
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• v.61 no.2
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• pp.283-293
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• 2017

The main contribution of the present paper is to propose an intelligent fuzzy inference system approach for modeling the debonding strength of masonry elements retrofitted with Fiber Reinforced Polymer (FRP). To achieve this, the hybrid of meta-heuristic optimization methods and adaptive-network-based fuzzy inference system (ANFIS) is implemented. In this study, particle swarm optimization with passive congregation (PSOPC) and real coded genetic algorithm (RCGA) are used to determine the best parameters of ANFIS from which better bond strength models in terms of modeling accuracy can be generated. To evaluate the accuracy of the proposed PSOPC-ANFIS and RCGA-ANFIS approaches, the numerical results are compared based on a database from laboratory testing results of 109 sub-assemblages. The statistical evaluation results demonstrate that PSOPC-ANFIS in comparison with ANFIS-RCGA considerably enhances the accuracy of the ANFIS approach. Furthermore, the comparison between the proposed approaches and other soft computing methods indicate that the approaches can effectively predict the debonding strength and that their modeling results outperform those based on the other methods.

• Food Science of Animal Resources
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• v.37 no.1
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• pp.139-146
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• 2017

Response surface methodology (RSM) is a useful set of statistical techniques for modeling and optimizing responses in research studies of food science. In the analysis of response surface data, a second-order polynomial regression model is usually used. However, sometimes we encounter situations where the fit of the second-order model is poor. If the model fitted to the data has a poor fit including a lack of fit, the modeling and optimization results might not be accurate. In such a case, using a fullest balanced model, which has no lack of fit, can fix such problem, enhancing the accuracy of the response surface modeling and optimization. This article presents how to develop and use such a model for the better modeling and optimizing of the response through an illustrative re-analysis of a dataset in Park et al. (2014) published in the Korean Journal for Food Science of Animal Resources.

• Korean Journal of Computational Design and Engineering
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• v.12 no.3
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• pp.163-170
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• 2007

A torque converter, connected to a transmission/transaxle input shaft, connects, multiplies and interrupts the flow of engine torque into the transmission. Damper springs are usually equipped in a torque converter to convert stably the torque power supplied from engine. Damper Springs generally have the most flexible design variables among vehicle transmission parts, so that they could be effective design factors to improve the entire vehicle's performance. Damper spring, however, has geometric complexity after it equipped in a torque converter. For that reason, modeling a damper spring requires expert's knowledge to determine many design parameters and satisfy the functional requirements at the same time. In this paper, we introduce an optimum design method applied in detailed-design stage to reduce design process and financial loss caused by adequate design. Many design variables have to be classified and structuralized for Optimization. This also could make designer concentrate on functional requirements of damper spring, not on design possibility. In addition, modeling an assembled spring has technical restriction with primitives of the current major CAD solutions because of complexity of assembled spring shape. Thus, one of modeling solution presented in this paper since detailed and exact modeling is important for CAE or DMU.

• International Journal of Control, Automation, and Systems
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• v.1 no.3
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• pp.289-300
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• 2003

In this paper, we introduce an identification method in Fuzzy Relation-based Fuzzy Neural Networks (FRFNN) through a hybrid identification algorithm. The proposed FRFNN modeling implement system structure and parameter identification in the efficient form of "If...., then... " statements, and exploit the theory of system optimization and fuzzy rules. The FRFNN modeling and identification environment realizes parameter identification through a synergistic usage of genetic optimization and complex search method. The hybrid identification algorithm is carried out by combining both genetic optimization and the improved complex method in order to guarantee both global optimization and local convergence. An aggregate objective function with a weighting factor is introduced to achieve a sound balance between approximation and generalization of the model. The proposed model is experimented with using two nonlinear data. The obtained experimental results reveal that the proposed networks exhibit high accuracy and generalization capabilities in comparison to other models.er models.