• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.74-78
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• 2001

In this study, a multi-step optimization technique combined with a simple genetic algorithm is introduce to the structural design optimization of a high speed machining center. In this case, the design problem is to find out the best design variables which minimize the static compliance, the dynamic compliance, and the weight of the machine structure and meet some design constraints simultaneously. Dimensional thicknesses of the thirteen structural members along the static force loop of the machine structure are adopted as design variables. The first optimization step is a static design optimization, in which the static compliance and the weight are minimized under some dimensional and safety constraints. The second step is a dynamic design optimization, where the dynamic compliance and the weight are minimized under the same constraints. After optimization, the weight of the moving body was reduced to 9.1% of the initial design respectively. Both static and dynamic compliances of the optimum design are also in the feasible range even thought they were slightly increased than before.

• International Journal of CAD/CAM
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• v.9 no.1
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• pp.1-16
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• 2010

When Deterministic Design Optimization (DDO) methods are used, deterministic optimum designs are frequently pushed to the design constraint boundary, leaving little or no room for tolerances (or uncertainties) in design, manufacture, and operating processes. In the Reliability-Based Design Optimization (RBDO) model for robust system design, the mean values of uncertain system variables are usually used as design variables, and the cost is optimized subject to prescribed probabilistic constraints as defined by a nonlinear mathematical programming problem. Therefore, a RBDO solution that reduces the structural weight in uncritical regions does not only provide an improved design but also a higher level of confidence in the design. In this work, we seek to improve the quality of RBDO processes using efficient optimization techniques with object of improving the resulting objective function and satisfying the required constraints. Our recent RBDO developments show its efficiency and applicability in this context. So we present some recent structural engineering applications demonstrate the efficiency of these developed RBDO methods.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.1
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• pp.138-144
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• 2013

The automation technology for overlay welding is needed due to the occurrence of severe corrosion and abrasion on the surface of internal contact in different shape of fittings. In Korea, different shapes of fittings have been manufactured by using the imported equipment of overlay welding automation at some companies. Thus the research on the development of overlay welding automation system (in short, OWAS) for a large L-type tube is urgently needed. In this paper, the investigation is focused on the optimal design of a supporting base for the (currently developing) OWAS of large L-type tube. Specifically we assume that the base which supports the equipment during the process of overlay welding is loaded as self-weight in the direction of gravity through static analysis especially when it is rotated 180 degree on the OWAS. For optimal design of a supporting base for OWAS of large L-type tube, Solidworks(R) (for 3-dimensional modelling) and ANASYS Workbench(R) (for structural analysis) are incorporated so as to proceed an optimization routines based on Response Surface Method (RSM) and Design of Experiment (DOE). In more specific, DOE finds out major factors (or dimensions) of the supporting base by using MINITAB(R). Then the regression equations between design variables (the major factors of supporting base) and response variables (deformation, stress and safety factor for the supporting base), which will be resulted in by RSM, verify the major factors of DOE. In the next step, Central Composite Design (CCD) plans 20 simulations of ANASYS Workbench(R) and then figures out the optimal values of design variables which will be reflected on the manufacturing of supporting base. Finally welding experiment is conducted to figure out the influence of overlay welding quality in applying the optimized design values of supporting base to the actual OWAS.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.32 no.8
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• pp.693-700
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• 2008

The primary mirror system in a satellite camera is an opto-mechanically coupled system for a reason that optical and mechanical behaviors are intricately interactive. In order to enhance the opto-mechanical performance of the primary mirror system, opto-mechanical behaviors should be thoroughly investigated by using various analysis procedures such as elastic, thermo-elastic, optical and eigenvalue analysis. In this paper, optimal design of the bipod flexure mounts for high opto-mechanical performance is performed. Optomechanical performances considered in this paper are RMS wavefront error under the gravity and thermal loading conditions and 1st natural frequency of the mirror system. The procedures of the flexure mounts design based on design of experiments and statistics is as follows. The experiments for opto-mechanical analysis are constructed based on the tables of orthogonal arrays and analysis of each experiment is carried out. In order to deal with the multiple opto-mechanical properties, MADM (Multiple-attribute decision making) is employed. From the analysis results, the critical design variables of the flexure mounts which have dominant influences on opto-mechanical performance are determined through analysis of variance and F-test. The regression model in terms of the critical design variables is constructed based on the response surfaceanalysis. Then the critical design variables are optimized from the regression model by using SQP algorithm. Opto-mechanical performance of the optimal bipod flexure mounts is verified through analysis.

• Journal of Korean Society of Steel Construction
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• v.12 no.1 s.44
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• pp.45-54
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• 2000

Design-oriented approximate structural reanalysis models are compared and assessed, particularly with focus on the case of large changes of design variables. The effectiveness and reliability are demonstrated by means of numerical examples. The results of the study suggest the following conclusions relative to the potential of the procedures. (A) local approximation is only appropriate for the case of small changes in design : (B) global approximation is exact for the case of large changes in a small number of design variables, but inefficient : (C) local-global approximation is most effective and reliable for the case of large changes with a large number of design variables. These methods can improve the total efficiency when they are appropriately used to the design information for the redesign process of large scale structures.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.13 no.4
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• pp.417-425
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• 2000

This paper describes the application of discretized continuum-type optimality criteria(DCOC) and the development of optimum design program for the reinforced concrete continuous beams with rectangular cross-section. The cost of construction as objective function which includes the costs of concrete, reinforcing steel and formwork is minimized. The design constraints include limits on the maximum deflection, flexural and shear strengths, in addition to ductility requirements, and upper and lower bounds on design variables as stipulated by the design Code. Based on Kuhn-Tucker necessary conditions, the optimality criteria are explicitly derived in terms of the design variables-effective depth, and steel ratio. The self-weight of the beam is included in the equilibrium equation of the real system. An iterative procedure and computer program for updating the design variables are developed. Two numerical examples of reinforced concrete continuous beams are presented to show the applicability and efficiency of the DCOC-based technique.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.20 no.4
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• pp.407-416
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• 2007

Fuel spray nozzle has a critical effect on combustion characteristics. Mass flow rate and SMD(sauter mean diameter) were selected as design variables by using the experiment data of various types of duplex fuel nozzles for the swirl atomizers. The sensitivity of each design variable on the mass flow rate and SMD was analyzed and the uniformity of mass flow rate was investigated through the shape optimization of duel-orifice-type swirl atomizers. The design variables that have a little effect on the optimum design were excluded using the DOE(design of experiments) method, which enabled the optimization of sensitive design variables on mass flow rate and limit tolerance. The SMD of the research spray nozzle that was used in this study was found to be most similar to that of the calculation results using the Jasuja's SMD relationship. This study showed the specific characteristics of duel orifice type swirl atomizers and the optimization of these kinds of nozzle. This study provided the optimization design of mass flow rate and its allowable tolerance.

• Computational Structural Engineering
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• v.10 no.4
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• pp.315-325
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• 1997

This paper describes the application of discretized continuum-type optimality criteria (DCOC) and the development of optimum design program for the multispan partially prestressed concrete beams. The cost of construction as objective function which includes the costs of concrete, prestressing steel, non-prestressing steel and formwork is minimized. The design constraints include limits on the maximum deflection, flexural and shear strengths, in addition to ductility requirements, and upper and lower bounds on design variables as stipulated by the design Code. Based on Kuhn-Tucker necessary conditions, the optimality criteria are explicitly derived in terms of the design variables-effective depth, eccentricity of prestressing steel and non-prestressing steel ratio. The prestressing profile is prescribed by parabolic functions. The self-weight of the structure is included in the equilibrium equation of the real system, as is the secondary effect resulting from the prestressing force. An iterative procedure and computer program for updating the design variables are developed. Two numerical examples of multispan PPC beams with rectangular cross-section are solved to show the applicability and efficiency of the DCOC-based technique.

• Computers and Concrete
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• v.16 no.3
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• pp.357-380
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• 2015

In this study, a simple indeterminate strut-tie model which reflects complicated characteristics of the ultimate structural behavior of continuous reinforced concrete deep beams was proposed. In addition, the load distribution ratio, defined as the fraction of applied load transferred by a vertical tie of truss load transfer mechanism, was proposed to help structural designers perform the analysis and design of continuous reinforced concrete deep beams by using the strut-tie model approaches of current design codes. In the determination of the load distribution ratio, a concept of balanced shear reinforcement ratio requiring a simultaneous failure of inclined concrete strut and vertical steel tie was introduced to ensure the ductile shear failure of reinforced concrete deep beams, and the primary design variables including the shear span-to-effective depth ratio, flexural reinforcement ratio, and compressive strength of concrete were reflected upon. To verify the appropriateness of the present study, the ultimate strength of 58 continuous reinforced concrete deep beams tested to shear failure was evaluated by the ACI 318M-11's strut-tie model approach associated with the presented indeterminate strut-tie model and load distribution ratio. The ultimate strength of the continuous deep beams was also estimated by the experimental shear equations, conventional design codes that were based on experimental and theoretical shear strength models, and current strut-tie model design codes. The validity of the proposed strut-tie model and load distribution ratio was examined through the comparison of the strength analysis results classified according to the primary design variables. The present study associated with the indeterminate strut-tie model and load distribution ratio evaluated the ultimate strength of the continuous deep beams fairly well compared with those by other approaches. In addition, the present approach reflected the effects of the primary design variables on the ultimate strength of the continuous deep beams consistently and reasonably. The present study may provide an opportunity to help structural designers conduct the rational and practical strut-tie model design of continuous deep beams.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.6
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• pp.33-43
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• 2021

A60 class bulkhead penetration piece is a fire resistance system installed on a bulkhead compartment to protect lives and to prevent flame diffusion in a fire accident on a ship and offshore plant. This study focuses on the approximate optimization of the fire resistance design of the A60 class bulkhead penetration piece using a multi-island genetic algorithm. Transient heat transfer analysis was performed to evaluate the fire resistance design of the A60 class bulkhead penetration piece. For approximate optimization, the bulkhead penetration piece length, diameter, material type, and insulation density were considered discrete design variables; moreover, temperature, cost, and productivity were considered constraint functions. The approximate optimum design problem based on the meta-model was formulated by determining the discrete design variables by minimizing the weight of the A60 class bulkhead penetration piece subject to the constraint functions. The meta-models used for the approximate optimization were the Kriging model, response surface method, and radial basis function-based neural network. The results from the approximate optimization were compared to the actual results of the analysis to determine approximate accuracy. We conclude that the radial basis function-based neural network among the meta-models used in the approximate optimization generates the most accurate optimum design results for the fire resistance design of the A60 class bulkhead penetration piece.