• Fibers and Polymers
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• v.7 no.4
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• pp.404-413
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• 2006

This study examines multiple quality optimization of the injection molding for Polyether Ether Ketone (PEEK). It also looks into the dimensional deviation and strength of screws that are reduced and improved for the molding quality, respectively. This study applies the Taguchi method to cut down on the number of experiments and combines grey relational analysis to determine the optimal processing parameters for multiple quality characteristics. The quality characteristics of this experiment are the screws' outer diameter, tensile strength and twisting strength. First, one should determine the processing parameters that may affect the injection molding with the $L_{18}(2^1{\times}3^7)$ orthogonal, including mold temperature, pre-plasticity amount, injection pressure, injection speed, screw speed, packing pressure, packing time and cooling time. Then, the grey relational analysis, whose response table and response graph indicate the optimum processing parameters for multiple quality characteristics, is applied to resolve this drawback. The Taguchi method only takes a single quality characteristic into consideration. Finally, a processing parameter prediction system is established by using the back-propagation neural network. The percentage errors all fall within 2%, between the predicted values and the target values. This reveals that the prediction system established in this study produces excellent results.

• Journal of the Korean Society for Precision Engineering
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• v.29 no.12
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• pp.1304-1312
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• 2012

According to the successful development of hybrid vehicle, hybridization of construction equipments like excavator, wheel loader, and backhoe etc., is gaining increasing attention. However, hybridization of excavator and commercial vehicle is very different. Therefore a specialized energy management control algorithm for excavator should be developed. In this paper, hybridization of excavators is investigated and a new energy management control algorithm is proposed. Four control parameters, i.e., lower baseline, upper baseline, idling generation speed, and idling generation torque, are newly introduced and a new operating principle using those four control parameters is proposed. The use of Genetic Algorithm for the optimization of the four control parameters from the view point of minimization of fuel consumption for standard excavating operation is suggested. In order to verify the proposed algorithm, dedicated simulation program of hybrid excavator was developed. The proposed algorithm is applied to a specific hydraulic excavator and 20.7% improvement of fuel consumption is achieved.

• 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.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.769-777
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• 2017

The research of air gap flux density has a significant effect on predicting and optimizing the structure parameters of electrical machines. In the paper, the air gap coefficient, leakage flux factor and saturation coefficient are first analytically expressed in terms of motor properties and structure parameters. Subsequently, the analytical model of average air gap flux density for surface-mounted permanent magnet synchronous machines is proposed with considering slotting effect and saturation. In order to verify the accuracy of the proposed analytical model, the experiment and finite element analysis (FEA) are used. It shows that the analytical results keep consistency well with the experimental result and FEA results, and the errors between FEA results and analytical results are less than 5% for SPM with high power. Finally, the analytical model is applied to optimizing the motor structure parameters. The optimal results indicate that the analytical calculation model provides a great potential to the machine design and optimization.

• International Journal of Concrete Structures and Materials
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• v.9 no.2
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• pp.185-206
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• 2015

This paper presents statistical models developed to study the influence of key mix design parameters on the properties of lightweight self-consolidating concrete (LWSCC) with expanded shale (ESH) aggregates. Twenty LWSCC mixtures are designed and tested, where responses (properties) are evaluated to analyze influence of mix design parameters and develop the models. Such responses included slump flow diameter, V-funnel flow time, J-ring flow diameter, J-ring height difference, L-box ratio, filling capacity, sieve segregation, unit weight and compressive strength. The developed models are valid for mixes with 0.30-0.40 water-to-binder ratio, high range water reducing admixture of 0.3-1.2 % (by total content of binder) and total binder content of $410-550kg/m^3$. The models are able to identify the influential mix design parameters and their interactions which can be useful to reduce the test protocol needed for proportioning of LWSCCs. Three industrial class ESH-LWSCC mixtures are developed using statistical models and their performance is validated through test results with good agreement. The developed ESH-LWSCC mixtures are able to satisfy the European EFNARC criteria for self-consolidating concrete.

• Tribology and Lubricants
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• v.23 no.3
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• pp.103-108
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• 2007

In this paper, the optimized design and strength analysis have been presented based on the finite element and Taguchi's experimental methods. The stress, strain and displacement characteristics of OPC drum tubes are affected by rolling contact pressures between an OPC drum tube and a paper, design parameters of an aluminum tube and material properties. The OPC drum tubes with nine different geometrical models are analyzed for design parameters that are related to the outer diameter, the thickness, and the length of an aluminum tube for a toner cartridge. The optimized design parameters for an aluminum tube may be selected as the outer diameter of 28 mm, the thickness of 0.8 mm, and the length of 220 mm. But the currently used aluminum tube for a laser printer is fairly optimized based on the Taguchi's design analysis. The calculated FEM results showed that the affection ratio of the design parameter t, which may control the strength of an aluminum tube, is the most influential parameter among the length and an outer diameter of a tube.

• Journal of The Korean Society of Agricultural Engineers
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• v.46 no.5
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• pp.41-52
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• 2004

In this study, parameters of long and short term runoff model were optimized using genetic algorithm as a basic research for integrated water management in a watershed. In case of Korea where drought and flood occurr frequently, the integrated water management is necessary to minimize possible damage of drought and flood. Modified TANK model was optimized as a long term runoff model and storage-function model was optimized as a short term runoff model. Besides distinguished parameters were applied to modified TANK model for supplementing defect that the model estimates less runoff in the storm period. As a result of application, simulated long and short term runoff results showed 7% and 5% improvement compared with before optimized on the average. In case of modified TANK model using distinguished parameters, the simulated runoff after optimized showed more interrelationship than before optimized. Therefore, modified TANK model can be applied for the long term water balance as an integrated water management in a watershed. In case of storage-function model, simulated runoff in the storm period showed high interrelationship with observed one. These optimized models can be applied for the runoff analysis of watershed.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.9
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• pp.903-912
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• 2009

This study is focused on simulation-based dimensional tolerance optimization process (DTOP) to minimize vehicle pulls by reduction of dimensional variation in front suspension system. In previous studies, the effect of tires and wheel alignment sensitivity have mainly been investigated to eliminate vehicle pulls in nominal design condition without allocating optimal tolerance level for selected components, among various factors regarding vehicle pulls such as vehicle design parameters, vehicle weight balance, tires, and environmental factors. Unfortunately, there are wide variations in the real vehicle, and these have impacted actual vehicle pulls, especially wheel alignment effects from suspension geometry variation has not been considered in the previous studies. In the tolerance design of suspension, tolerance variables with the uncertainty such as parts dimensional variation, assembly process, datum position and direction, and assembly tool tolerance has a great influence on the variation of the suspension dimensional performances. This study introduces total vehicle pull prediction model in considering major key factors for vehicle pull sensitivity. The Monte Carlo-based tolerance analysis model using Taguchi robust method is developed to optimize dimensional tolerance parameters, satisfying on the target variation level.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.16 no.12 s.117
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• pp.1192-1200
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• 2006

Viscoelastic damping materials are widely used to reduce noise and vibration because of its low cost and easy implementation, for examples, on the body structure of passenger cars, air planes, electric appliances and ships. To design the damped structures, the material property such as elastic modulus and loss factor is essential information. The four-parameter fractional derivative model well describes the dynamic characteristics of the viscoelastic damping materials with respect to both frequency and temperature. However, the identification procedure of the four-parameter is very time-consuming one. In this study a new identification procedure of the four-parameters is proposed by using an FE model and a gradient-based numerical search algorithm. The identification procedure goes two sequential steps to make measured frequency response functions(FRF) coincident with simulated FRFs: the first one is a peak alignment step and the second one is an amplitude adjustment step. A numerical example shows that the proposed method is useful in identifying the viscoelastic material parameters of fractional derivative model.

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.6
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• pp.72-80
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• 2013

For the proper cooling of in-wheel motor, the cooling channel should have the characteristics which are low pressure drop and adequate cooling oil supply to motor part. In this study, the flow performance of cooling channel for in-wheel motor was evaluated and the shape of the channel was optimized. First, the pressure drop and flow distribution characteristics of the initial channel model were evaluated using numerical analysis. Also, by the result of analysis and design modification, 4 design parameters of the channel were selected. Second, using the Taguchi optimal method, the cooling channel was optimized. In the method, nine models with different levels of the design parameters were generated and the flow characteristics of each models was estimated. Base on the result, the main effect of the design parameters was founded and optimized model was obtained. For the optimized model, the pressure drop and oil flow rate were about 0.196 bar and 0.207 L/min, respectively. The pressure drop decreased by about 0.3 bar and the oil flow rate to the motor part increased by about 0.2 L/min compared to the initial model.