• Smart Structures and Systems
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• v.16 no.3
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• pp.401-414
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• 2015

A developed hybrid method for crack identification of beams is presented. Based on the Euler-Bernouli beam theory and concepts of fracture mechanics, governing equation of the cracked beams is reformulated. Finite element (FE) method as a powerful numerical tool is used to discritize the equation in space domain. After transferring the equations from time domain to frequency domain, frequencies and mode shapes of the beam are obtained. Efficiency of the governed equation for free vibration analysis of the beams is shown by comparing the results with those available in literature and via ANSYS software. The used equation yields to move the influence of cracks from the stiffness matrix to the mass matrix. For crack identification measured data are produced by applying random error to the calculated frequencies and mode shapes. An objective function is prepared as root mean square error between measured and calculated data. To minimize the function, hybrid genetic algorithms (GAs) and particle swarm optimization (PSO) technique is introduced. Efficiency, Robustness, applicability and usefulness of the mixed optimization numerical tool in conjunction with the finite element method for identification of cracks locations and depths are shown via solving different examples.

• Proceedings of the KSME Conference
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• 2008.11b
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• pp.3140-3141
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• 2008

The output power efficiency of the fuel cell system depends on the demanded current, stack temperature, air excess ratio, hydrogen excess ratio and inlet air humidity. Thus, it is necessary to determine the optimal operation condition for maximum power efficiency. In this paper, we developed a dynamic model of fuel cell system which contains mass flow model, diffusivity gas layer model, membrane hydration and electrochemistry model. In order to determine the maximum output power and minimum use of hydrogen in a certain power condition, response surface methodology (RSM) optimization based on the proposed PEMFC stack model is presented. The results provide an effective method to optimize the operation condition under varied situations.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.23 no.1
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• pp.56-61
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• 2015

Because of kinematic complexities, nonlinear behavior, etc, the performance of oleo-pneumatic landing gear is predicted by qualified commercial softwares. While commercial softwares predict more exactly, it takes a long time to construct or modify a model. At initial design stage, design parameters can be determined quickly and exactly enough with simple 2 degree of freedom model of mass, spring and damping. 2 degree of freedom model can be easily applied to optimization and reliability analysis which takes repetitive computation. In this paper, oleo-pneumatic landing gear is modeled as a nonlinear 2 degree of freedom model. The analysis are compared with landing gear drop test. To determine design parameter, optimization problem is solved with genetic algorithm and 2 degree of freedom model.

• Structural Engineering and Mechanics
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• v.78 no.2
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• pp.145-161
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• 2021

Dynamic compaction of Aluminum powder using gas detonation forming technique was investigated. The experiments were carried out on four different conditions of total pre-detonation pressure. The effects of the initial powder mass and grain particle size on the green density and strength of compacted specimens were investigated. The relationships between the mentioned powder design parameters and the final features of specimens were characterized using Response Surface Methodology (RSM). Artificial Neural Network (ANN) models using the Group Method of Data Handling (GMDH) algorithm were also developed to predict the green density and green strength of compacted specimens. Furthermore, the desirability function was employed for multi-objective optimization purposes. The obtained optimal solutions were verified with three new experiments and ANN models. The obtained experimental results corresponding to the best optimal setting with the desirability of 1 are 2714 kg·m-3 and 21.5 MPa for the green density and green strength, respectively, which are very close to the predicted values.

• Structural Engineering and Mechanics
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• v.63 no.4
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• pp.537-549
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• 2017

One of the main concerns of civil engineering researchers is developing or modifying an energy dissipation system that can effectively control structural vibrations, and keep the structural response within tolerable limits during unpredictable events like earthquakes, wind and any kind of thrust load. This article proposes a new type of mass damper system for controlling wideband earthquake vibrations, called Multiple Wall Dampers (MWD). The basic principle of the Tuned Mass Damper (TMD) was used to design the proposed wall damper system. This passive energy dissipation system does not require additional mass for the damping system because the boundary wall mass of the building was used as a damper mass. The multi-mode approach was applied to determine the location and design parameters of the dampers. The dampers were installed based on the maximum amplitude of modes. To optimize the damper parameters, the multi-objective optimization Response Surface Methodology was used, with frequency response and maximum displacement as the objective functions. The obtained structural responses under different earthquake forces demonstrated that the MWD is one of the most capable tools for reducing the responses of multi-storied buildings, and this system can be practically used for new and existing building structures.

• Design & Manufacturing
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• v.14 no.3
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• pp.1-7
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• 2020

This paper predicts the mass and the length of injection-molded products through the Artificial Neural Network (ANN) method. The ANN was implemented with 5 input parameters and 2 output parameters(mass, length). The input parameters, such as injection time, melt temperature, mold temperature, packing pressure and packing time were selected. 44 experiments that are based on the mixed sampling method were performed to generate training data for the ANN model. The generated training data were normalized to eliminate scale differences between factors to improve the prediction performance of the ANN model. A random search method was used to find the optimized hyper-parameter of the ANN model. After the ANN completed the training, the ANN model predicted the mass and the length of the injection-molded product. According to the result, average error of the ANN for mass was 0.3 %. In the case of length, the average deviation of ANN was 0.043 mm.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.22 no.3
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• pp.259-265
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• 2009

This paper studies the Element Connectivity Parameterization Method(ECP method) for topology optimization considering dynamic compliance. The previous element density based topology optimization method interpolates Young's modulus with respect to design variables defined in each element for topology optimization. Despite its various applications, these element density based methods suffer from numerical instabilities for nonlinear structure and multiphysics systems. To resolve these instabilities, recently a new numerical method called the Element Connectivity Parameterization(ECP) Method was proposed. Unlike the existing design methods, the ECP method optimizes the connectivities among plane or solid elements and it shows some advantages in topology optimization for both nonlinear structure and multiphysics systems. In this study, the method was expanded for topology optimization for the dynamic compliance by developing a way to model the mass matrix in the framework of the ECP method.

• International Journal of Aeronautical and Space Sciences
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• v.13 no.1
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• pp.43-57
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• 2012

In a modern aircraft, there are many variations in its mass, stiffness, and aerodynamic characteristics. Recently, an analytical approach was proposed, and this approach uses the idea of uncertainty to find out the most critical flight flutter boundary due to the variations in such aerodynamic characteristics. An analytical method that has been suggested to predict robust stability is the mu method. We previously analyzed the robust flutter boundary by using the mu method, and in that study, aerodynamic variations in the Mach number, atmospheric density, and flight speed were taken into consideration. The authors' previous attempt and the results are currently quoted as varying Mach number mu analysis. In the author's previous method, when the initial flight conditions were located far from the nominal flutter boundary, conservative predictions were obtained. However, relationships among those aerodynamic parameters were not applied. Thus, the varying Mach number mu analysis results required validation. Using an optimization approach, the varying Mach number mu analysis was found out to be capable of capturing a reasonable robust flutter boundary, i.e., with a low percentage difference from boundaries that were obtained by optimization. Regarding the optimization approach, a discrete nominal flutter boundary is to be obtained in advance, and based on that boundary, an interpolated function was established. Thus, the optimization approach required more computational effort for a larger number of uncertainty variables. And, this produced results similar to those from the mu method which had lower computational complexity. Thus, during the estimation of robust aeroelastic stability, the mu method was regarded as more efficient than the optimization method was. The mu method predicts reasonable results when an initial condition is located near the nominal flutter boundary, but it does not consider the relationships that are among the aerodynamic parameters, and its predictions are not very accurate when the initial condition is located far from the nominal flutter boundary. In order to provide predictions that are more accurate, the relationships among the uncertainties should also be included in the mu method.

• Smart Structures and Systems
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• v.21 no.6
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• pp.727-740
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• 2018

Tuned mass dampers (TMDs) are passive damping devices widely employed to mitigate the pedestrian-induced vibrations on footbridges. The TMD design must ensure an adequate performance during the overall life-cycle of the structure. Although the TMD is initially adjusted to match the natural frequency of the vibration mode which needs to be controlled, its design must further take into account the change of the modal parameters of the footbridge due to the modification of the operational and environmental conditions. For this purpose, a motion-based design optimization method is proposed and implemented herein, aimed at ensuring the adequate behavior of footbridges under uncertainty conditions. The uncertainty associated with the variation of such modal parameters is simulated by a probabilistic approach based on the results of previous research reported in literature. The pedestrian action is modelled according to the recommendations of the Synpex guidelines. A comparison among the TMD parameters obtained considering different design criteria, design requirements and uncertainty levels is performed. To illustrate the proposed approach, a benchmark footbridge is considered. Results show both which is the most adequate design criterion to control the pedestrian-induced vibrations on the footbridge and the influence of the design requirements and the uncertainty level in the final TMD design.

• Textile Coloration and Finishing
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• v.19 no.1 s.92
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• pp.53-60
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• 2007

In order to optimize the process for development of super deep black fiber, the silica-containing polyester fabric, SN2000, was investigated in terms of mass reduction process by sodium hydroxide, selection of high color strength dyes, and resin treatment. As the results, the mass reduction condition which used 15g/L of sodium hydroxide at $120^{\circ}C$ was determined and Dianix Deep Black Plus was selected for the best deep coloration at around 5% owf. Contrary to the prevailed understanding that the additional use of chromatic dyes would enhance the deep coloration, four kinds of chromatic dyes such as yellow, red, blue, and green dyes did not make great effect on the deep coloration. To increase the effect, the commercial resin that has low refractive index was used additionally and the resin made it possible to lower the lightness of the fabrics down to 8.7 which was generally accepted for super highly deep black fabric.