• Computers and Concrete
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• v.3 no.5
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• pp.313-334
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• 2006

A novel formulation aiming to achieve optimal design of reinforced concrete (RC) structures is presented here. Optimal sizing and reinforcing for beam and column members in multi-bay and multistory RC structures incorporates optimal stiffness correlation among all structural members and results in cost savings over typical-practice design solutions. A Nonlinear Programming algorithm searches for a minimum cost solution that satisfies ACI 2005 code requirements for axial and flexural loads. Material and labor costs for forming and placing concrete and steel are incorporated as a function of member size using RS Means 2005 cost data. Successful implementation demonstrates the abilities and performance of MATLAB's (The Mathworks, Inc.) Sequential Quadratic Programming algorithm for the design optimization of RC structures. A number of examples are presented that demonstrate the ability of this formulation to achieve optimal designs.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.7
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• pp.1234-1242
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• 2003

In this paper we present a simple and efficient robust optimal design formulation for MEMS structures and its application to a resonant-type micro probe. The basic idea is to use the gradient index (GI) to improve robustness of the objective and constraint functions. In the robust optimal design procedure, a deterministic optimization for performance of MEMS structures is followed by design sensitivity analysis with respect to uncertainties such as fabrication errors and change of operating conditions. During the process of deterministic optimization and sensitivity analysis, dominant performance and uncertain variables are identified to define GI. The GI is incorporated as a term of objective and constraint functions in the robust optimal design formulation to make both performance and robustness improved. While most previous approaches for robust optimal design require statistical information on design variations, the proposed GI based method needs no such information and therefore is cost-effective and easily applicable to early design stages. For the micro probe example, robust optimums are obtained to satisfy the targets for the measurement sensitivity and they are compared in terms of robustness and production yield with the deterministic optimums through the Monte Carlo simulation. This method, although shown for MEMS structures, may as well be easily applied to conventional mechanical structures where information on uncertainties is lacking but robustness is highly important.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.1254-1261
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• 2003

In this paper we present a simple and efficient robust optimal design formulation and its application to a resonant-type micro probe. The basic idea is to use the Gradient Index (GI) to improve robustness of the objective and constraint functions. In the robust optimal design procedure, a deterministic optimization for performance of MEMS structures is followed by design sensitivity analysis with respect to uncertainties such as fabrication errors and change of operating conditions. During the process of deterministic optimization and sensitivity analysis, dominant performance and uncertain variables are identified to define GI. The GI is incorporated as a term of objective and constraint functions in the robust optimal design formulation to make both performance and robustness improved. While most previous approaches for robust optimal design require statistical information on design variations, the proposed GI based method needs no such information and therefore is cost-efficient and easily applicable to early design stages. For the micro probe example, robust optimums are obtained to satisfy the targets for the measurement sensitivity and they are compared in terms of robustness and production yield with the deterministic optimums through the Monte Carlo simulation.

• Journal of Computational Design and Engineering
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• v.2 no.3
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• pp.157-164
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• 2015

This paper discusses an optimization-based approach for the design of a product platform for industrial three-axis linear-type robots, which are widely used for handling objects in manufacturing lines. Since the operational specifications of these robots, such as operation speed, working distance and orientation, weight and shape of loads, etc., will vary for different applications, robotic system vendors must provide various types of robots efficiently and effectively to meet a range of market needs. A promising step toward this goal is the concept of a product platform, in which several key elements are commonly used across a series of products, which can then be customized for individual requirements. However the design of a product platform is more complicated than that of each product, due to the need to optimize the design across many products. This paper proposes an optimization-based fundamental framework toward the design of a product platform for industrial three-axis linear-type robots; this framework allows the solution of a complicated design problem and builds an optimal design method of fundamental features of robot frames that are commonly used for a wide range of robots. In this formulation, some key performance metrics of the robot are estimated by a reducedorder model which is configured with beam theory. A multi-objective optimization problem is formulated to represent the trade-offs among key design parameters using a weighted-sum form for a single product. This formulation is integrated into a mini-max type optimization problem across a series of robots as an optimal design formulation for the product platform. Some case studies of optimal platform design for industrial three-axis linear-type robots are presented to demonstrate the applications of a genetic algorithm to such mathematical models.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1997.03a
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• pp.113-118
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• 1997

A new approach to process optimal design in non-isothermal, non-steady state metal forming is presented. In this approach, the optimal design problem is formulated on the basis of the integrated thermo-mechanical finite element process model so as to cover a wide range of the objective functions and design variables, and the derivative based approach is adopted for conducting optimization by design iteration. The process model, the formulation for process optimal design, and the procedures for the evaluation of the design sensitivity and for design iteration for optimization are described.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.315-318
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• 1995

The optimum design problem of a coat-hanger die is solved by the inverse formulation. The flow in the die is analyzed using three-dimensional model. The new model for the manifold geometry is developed for the inverse formulation. The inverse problem for the optimum die geometry is formed as the optimization problem whose objective function is the linear combination of the square sum of pressure gradient deviation at die exit and the penalty function relating to the measure of non-smoothness of solution. From the several iterative solutions of the optimization problem, the optimum solution can be obtained automatically while producing the uniform flow rate distribution at die exit.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1998.03a
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• pp.113-116
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• 1998

A derivative based approach to process optimal design in powder forging is presented. The process model, the formulation for process optimal design, and the schemes for the evaluation of the design sensitivity, and an iterative procedure for the optimization are described in detail. The validity of the schemes for the evaluation of the design sensitivity is examined by performing numerical tests. The capability of the proposed approach to deal with diverse process parameters and objective functions is demonstrated through applications to some selected process design problems.

• Structural Engineering and Mechanics
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• v.14 no.4
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• pp.473-489
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• 2002

A static linear programming formulation for minimum weight design of frames that is based on a matrix displacement method is presented in this paper. According to elementary theory of plasticity, minimum weight design of frames can be carried out by using only the equilibrium equations, because the system is statically determinate when at an incipient collapse state. In the present formulation, a statically determinate released frame is defined by introducing hinges into the real frame and the bending moments in yield constraints are expressed in terms of unit hinge rotations and the external loads respectively, by utilizing the matrix displacement method. Conventional Simplex algorithm with some modifications is utilized for the solution of linear programming problem. As the formulation is based on matrix displacement method, it may be easily adopted to the weight optimization of frames with displacement and deformation limitations. Four illustrative examples are also given for comparing the results to those obtained in previous studies.

• Transactions of the Korean Society of Automotive Engineers
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• v.18 no.4
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• pp.1-7
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• 2010

Large quantity of bending deformation as well as irregular rotating torque fluctuation are the main struggles of the balance shaft module during a high speed rotation. Since two issues are much sensitive to the location of both supporting bearing and unbalance mass at a balance shaft, it is recommended to construct a design strategy on balance shaft at the early stage so as to save developing time and effort before approaches to the detailed design process. In this paper, an optimal design formulation is proposed to minimize the elastic strain energy due to bending as well as the kinematic energy of polar moment of inertia in rotation. Case studies of optimal design are conducted for different mass ratio as well as linear combination of objective function and its consequence reveals that global optimum of balance shaft model is existed over possible design conditions. Simulation shows that best locations of both supporting bearing and unbalance are globally 20% and 80%, respectively, over total length of a balance shaft.

• Proceedings of the KIEE Conference
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• 2001.07a
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• pp.161-163
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• 2001

In this paper, a method for optimal design of PID controller using the immune algorithm(IA) has been proposed to improve the stability of A.C.-D.C. power system. To design optimal PID controller, formulation of AC-DC system equation, selection of stability analysis model, formulation immune algorithm and application model of optimal PID controller are proposed in order of the paper. In case of various disturbance, computer simulations have been performed and the proposed IA-PID controller has been compared with base controller which is conventional control technique for dynamics. From simulation results, it is demonstrated that proposed IA-PID controller has good dynamic responses about the disturbance of power system and reliability as compared with the base control.