• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.4
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• pp.36-44
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• 2007

This paper is focused on the optimum design for decreasing volume and increasing reliability of multi-stage gear drive. For the optimization on volume and reliability, multi-objective optimization is used. The genetic algorithm is introduced to multi-objective optimization method and it is used to develop the optimum design program using exterior penalty function method to solve the complicated subject conditions. A 5 staged gear drive(geared motor) is chosen to compare the result of developed optimum design method with the existing design. Each of the volume objective, reliability objective, and volume-reliability multi-objectives are performed and compared with existing design. As a result, optimum solutions are produced, which decrease volume and increase reliability. It is shown that the developed design method is good for multi-stage gear drive design.

• Journal of Korean Association for Spatial Structures
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• v.13 no.3
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• pp.91-98
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• 2013

A multi-input single-output (MISO) semi-active control systems were studied by many researchers. For more improved vibration control performance, a structure requires more than one control device. In this paper, multi-input multi-output (MIMO) semi-active fuzzy controller has been proposed for vibration control of seismically excited small-scale buildings. The MIMO fuzzy controller was optimized by multi-objective genetic algorithm. For numerical simulation, five-story example building structure is used and two MR dampers are employed. For comparison purpose, a clipped-optimal control strategy based on acceleration feedback is employed for controlling MR dampers to reduce structural responses due to seismic loads. Numerical simulation results show that the MIMO fuzzy control algorithm can provide superior control performance to the clipped-optimal control algorithm.

• Structural Engineering and Mechanics
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• v.81 no.6
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• pp.677-689
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• 2022

Generally, the goal of seismic retrofit design of an existing structure using energy dissipation devices is to determine the optimum design parameters of a retrofit device to satisfy a specified limit state with minimum cost. However, the presence of multiple parameters to be optimized and the computational complexity of performing non-linear analysis make it difficult to find the optimal design parameters in the realistic 3D structure. In this study, genetic algorithm-based optimal seismic retrofit methods for determining the required number, yield strength, and location of steel slit dampers are proposed to retrofit an asymmetric soft first-story structure. These methods use a multi-objective and single-objective evolutionary algorithms, each of which varies in computational complexity and incorporates nonlinear time-history analysis to determine seismic performance. Pareto-optimal solutions of the multi-objective optimization are found using a non-dominated sorting genetic algorithm (NSGA-II). It is demonstrated that the developed multi-objective optimization methods can determine the optimum number, yield strength, and location of dampers that satisfy the given limit state of a three-dimensional asymmetric soft first-story structure. It is also shown that the single-objective distribution method based on minimizing plan-wise stiffness eccentricity turns out to produce similar number of dampers in optimum locations without time consuming nonlinear dynamic analysis.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.2
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• pp.145-152
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• 2004

This paper proposes a representation for the embodiment design of mechanical structures and a genetic algorithm suited for the representation. In order to represent early stages and latter stages of the embodiment design, the designs are modeled as simultaneous multi-objective optimization problems of parametric designs for parts and of layout generation for structures. The study, thus, involves genotypes that are adequate to represent phenotypes of the models for the genetic algorithm to solve the given problems. We demonstrate the implementation of the genetic algorithm with the result applied to the gear equipment design.

• Journal of Korean Society of Water and Wastewater
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• v.32 no.2
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• pp.115-122
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• 2018

Direct spring loaded pressure relief valve(DSLPRV) is a safety valve to relax surge pressure of the pipeline system. DSLPRV is one of widely used safety valves for its simplicity and efficiency. However, instability of the DSLPRV can caused by various reasons such as insufficient valve volume, natural vibration of the spring, etc. In order to improve reliability of DSLPRV, proper selection of design factors of DSLPRV is important. In this study, methodology for selecting design factors for DSLPRV was proposed. Dynamics of the DSLPRV disk was integrated into conventional 1D surge pressure analysis. Multi-objective genetic algorithm was also used to search optimum design factors for DSLPRV.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.4
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• pp.499-506
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• 2003

The design cycle associated with large engineering systems requires an initial decomposition of the complex system into design processes which are coupled through the transference of output data. Some of these design processes may be grouped into iterative subcycles. In analyzing or optimizing such a coupled system, it is essential to determine the best order of the processes within these subcycles to reduce design cycle time and cost. This is accomplished by decomposing large multidisciplinary problems into several sub design structure matrices (DSMs) and processing them in parallel This paper proposes a new method for parallel decomposition of multidisciplinary problems to improve design efficiency by using the multi-objective genetic algorithm and two sample test cases are presented to show the effect of the suggested decomposition method.

• International Journal of Fluid Machinery and Systems
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• v.2 no.2
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• pp.102-109
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• 2009

A design optimization system for Francis turbine was developed. The system consists of design program and CFD solver. Flow passage shapes are optimized automatically by using the system with Multi-Objective Genetic Algorithm (MOGA). In this study, the system was applied to a high specific speed Francis turbine (nSP = 250m-kW). The runner profile and the draft tube shape were optimized to decrease hydraulic losses. As the results, it was shown that the turbine efficiency was improved in wide operating range, furthermore, the height of draft tube was reduced with the hydraulic performance kept.

• International journal of steel structures
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• v.18 no.5
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• pp.1598-1606
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• 2018

An integrated optimal structural design method for a diagrid structure and control device was developed. A multi-objective genetic algorithm was used and a 60-story diagrid building structure was developed as an example structure. Artificial wind and earthquake loads were generated to assess the wind-induced and seismic responses. A smart tuned mass damper (TMD) was used as a structural control system and an MR (magnetorheological) damper was employed to develop a smart TMD (STMD). The multi-objective genetic algorithm used five objectives including a reduction of the dynamic responses, additional stiffness and damping, mass of STMD, capacity of the MR damper for the integrated optimization of a diagrid structure and a STMD. From the proposed method, integrated optimal designs for the diagrid structure and STMD were obtained. The numerical simulation also showed that the STMD provided good control performance for reducing the wind-induced and seismic responses of a tall diagrid building structure.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.41 no.7
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• pp.509-515
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• 2013

In this study, the real-coded adaptive range multi-objective genetic algorithm code, which represents the global multi-objective optimization algorithm, was developed for an airfoil shape design. In order to achieve the better aerodynamic characteristics than reference airfoil at landing and cruise conditions, maximum lift coefficient and lift-to-drag ratio were chosen as object functions. Futhermore, the PARSEC method reflecting geometrical properties of airfoil was adopted to generate airfoil shapes. Finally, two airfoils, which show better aerodynamic characteristics than a reference airfoil, were chosen. As a result, maximum lift coefficient and lift-to-drag ratio were increased of 4.89% and 5.38% for first candidate airfoil and 7.13% and 4.33% for second candidate airfoil.

• Industrial Engineering and Management Systems
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• v.3 no.1
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• pp.78-84
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• 2004

To optimize movement of a multi-joint robot arm is known to be a difficult problem, because it is a kind of redundant system. Although the end-effector is set its position by each angle of the joints, the angle of each joint cannot be uniquely determined by the position of the end-effector. There exist the infinite number of different sets of joint angles which represent the same position of the end-effector. This paper describes how to manage the angle of each joint to move its end-effector preferably on an X-Y plane with obstacles in the end-effector’s reachable area, and how to optimize the movement of a multi-joint robot arm, evading obstacles. The definition of “preferable” movement depends upon a purpose of robot operation. First, we divide viewpoints of preference into two, 1) the standpoint of the end-effector, and 2) the standpoint of joints. Then, we define multiple objective functions, and formulate it into a multi-objective programming problem. Finally, we solve it using multi-purpose genetic algorithm, and obtain reasonable results. The method described here is possible to add appropriate objective function if necessary for the purpose.