• Journal of Power System Engineering
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• v.18 no.2
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• pp.50-56
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• 2014

Friction welding is a very useful joining process to weld metals which have axially symmetric cross section. In this paper, for the friction welding with tube-to-tube shape, the feasibility of industry application was determined using analyzing mechanical properties of weld and optimized welding variables was suggested. In order to accomplish this object, rotating speed, friction heating pressure, and friction heating time were selected as the major process variables and the experiment was performed in three levels of each parameter. Weld characteristic was investigated in terms of weld shape and metal loss, and 7mm of metal loss was regarded as the optimal metal loss. By tensile test, tensile strength and yielding strength was measured and fracture was occurred at base metal. In order to optimize the welding condition, fitness function was defined with respect to metal loss and yielding strength and the fitness values for each welding condition could be calculated in experimental range. Consequently, we set the optimal welding condition as the point which had maximum value of fitness function. As the result of this paper the optimal welding variables could be suggested as rotating speed was 1300 rpm, friction heating pressure was 15 MPa, and friction heating time was 10 sec.

• Steel and Composite Structures
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• v.39 no.1
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• pp.81-93
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• 2021

Splitting tensile strength (STS) is an important mechanical parameter of concrete. This study offers novel methodologies for the early prediction of this parameter. Artificial neural network (ANN), which is a leading predictive method, is synthesized with two metaheuristic algorithms, namely atom search optimization (ASO) and equilibrium optimizer (EO) to achieve an optimal tuning of the weights and biases. The models are applied to data collected from the published literature. The sensitivity of the ASO and EO to the population size is first investigated, and then, proper configurations of the ASO-NN and EO-NN are compared to the conventional ANN. Evaluating the prediction results revealed the excellent efficiency of EO in optimizing the ANN. Accuracy improvements attained by this algorithm were 13.26 and 11.41% in terms of root mean square error and mean absolute error, respectively. Moreover, it raised the correlation from 0.89958 to 0.92722. This is while the results of the conventional ANN were slightly better than ASO-NN. The EO was also a faster optimizer than ASO. Based on these findings, the combination of the ANN and EO can be an efficient non-destructive tool for predicting the STS.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.5
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• pp.128-134
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• 2021

A press-fitted shaft is an essential part used in industrial machines, and it is generally used to transmit large quantities of power. Very high contact pressure occurs at the end parts of the contact between the shaft and boss, which are press-fitted shaft components. Such contact pressure not only damages the contact surface of a press-fitted shaft but also reduces its fatigue strength. To improve a press-fitted shaft's fatigue strength, the contact pressure on the contact surface, which directly affects the fatigue strength, should be minimized. Thus, in this study, the design configuration optimization of the end part of the boss was based on the approximate optimization method and was aimed at minimizing the contact pressure at the end of a press-fitted shaft. Comparison of the contact pressure and the contact stress of a conventional press-fitted shaft with those of the optimized press-fitted shaft showed that the boss design of the optimized press-fitted shaft effectively improved the fatigue life.

• Computers and Concrete
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• v.28 no.6
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• pp.635-642
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• 2021

In this paper, soft learning techniques are used to predict the ultimate torsional capacity of Reinforced Concrete beams strengthened with Fiber Reinforced Polymer. Soft computing techniques, namely Artificial Neural Network, trained by various back propagation algorithms, and Particle Swarm Optimization (PSO) algorithm, have been used to model and predict the torsional strength of Reinforced Concrete beams strengthened with Fiber Reinforced Polymer. The performance of each model has been evaluated by using statistical parameters such as coefficient of determination (R²), Root Mean Square Error (RMSE), and Mean Absolute Percentage Error (MAPE). The hybrid PSO NN model resulted in an R² of 0.9292 with an RMSE of 5.35 for training and an R² of 0.9328 with an RMSE of 4.57 for testing. Another model, ANN BP, produced an R² of 0.9125 with an RMSE of 6.17 for training and an R² of 0.8951 with an RMSE of 5.79 for testing. The results of the PSO NN model were in close agreement with the experimental values. Thus, the PSO NN model can be used to predict the ultimate torsional capacity of RC beams strengthened with FRP with greater acceptable accuracy.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.7 no.3
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• pp.17-24
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• 2008

Rail clamps are mechanical components installed to fix the container crane to its lower members against wind blast or slip. According to rail clamps should be designed to survive harsh wind loading conditions. In this study, a jaw structure, which is a part of a wedge-typed rail clamp, is optimized with respect to its strength under a severe wind loading condition. According to the classification of structural optimization, the structural optimization of a jaw is included in the category of shape optimization. Conventional structural optimization methods have difficulties in defining complex shape design variables and preventing mesh distortions. To overcome the difficulties, the metamodel using Kriging interpolation method is introduced to replace the true response by an approximate one. This research presents the shape optimization of a jaw using iterative Kriging interpolation models and a simulated annealing algorithm. The new Kriging models are iteratively constructed by refining the former Kriging models. This process is continued until the convergence criteria are satisfied. The optimum results obtained by the suggested method are compared with those obtained by the DOE (design of experiments) and VT (variation technology) methods built in ANSYS WORKBENCH.

• Journal of the Korea Concrete Institute
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• v.11 no.6
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• pp.57-67
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• 1999

Optimization scheme is presented for the design of precast prestressed double-tee beams used as slabs in the parking or market structures. The objective considered is defined by a function that minimizes the hight of the double-tee beam, including the prefabricated element and the concrete topping poured in a second phase. The Sequential Quadratic Programming method is adopted to solve the problem. As an example 12 double-tee beams are designed with the design loads of the current design code of our country. The results from optimization process show that at least 29cm less in overall height than that designed by PCI design handbook. The section determined from the optimization process was refined for practical considerations. A MathCad 7.0 Pro Spreadsheet was prepared to verify all ACI requirements for flexure, shear and deflections. Flexural tests are performed on four full-scale 12.5m prototype models and show that all the specimens are fully comply the flexural strength requirements as specified by ACI 318-95. The present optimization scheme can be used for wider application of the design of precast prestressed double-tee beams with different materials and configurations particularly for in a large scale or for important designs.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.15 no.3
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• pp.8-14
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• 2016

Medical bed head consoles (BHC) are generally used to increase the efficiency of medical equipment and speed the medical treatment response time. The BHC design has been consistently improved including a movable shelf unit that is embedded to mount stably medical instruments on the lower part of the main console. The cost of a BHC can be reduced through design optimization to limit the overall weight. However, as the size of a head console might decrease due to design optimization, the BHC deflection could be increased. In this study, multi-objective optimal design was adopted to consider this BHC design problem. In order to reduce the cost of optimization planning, an approximate model was applied for the design optimization. In the context of approximate optimization, we used the response surface method and non-dominant sorting genetic algorithm developed from various fields. Multi-objective optimal solutions were also compared with a single objective optimal design.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.32 no.10
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• pp.882-889
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• 2008

A humanoid is a robot with its overall appearance based on that of the human body. When the humanoid moves or walks, dynamic forces act on the body structure. Although the humanoid keeps the balance by using a precise control, the dynamic forces generate unexpected deformation or vibration and cause difficulties on the control. Generally, the structure of the humanoid is designed by the designer's experience and intuition. Then the structure can be excessively heavy or fragile. A humanoid design scenario for a systematic design is proposed to reduce the weight of the structure while sufficient strength is kept. Lower parts of the humanoid are selected to apply the proposed design scenario. Multi-body dynamics is employed to calculate the external dynamic forces on the parts and structural optimization is carried out to design the lower parts. Because structural optimization using dynamic forces directly is fairly difficult, linear dynamic response structural optimization using equivalent static loads is utilized. Topology and shape optimizations are adopted for two steps of initial and detailed designs, respectively. Various commercial software systems are used for analysis and optimization. Improved designs are obtained and the design results are discussed.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.2
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• pp.329-334
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• 2006

Rail clamps are mechanical components installed to fix the container crane to its bottoms from wind blast or slip. Rail clamps should be designed to survive the harsh wind loading condition. In this study, the jaw structure that is one part of wedge-typed rail clamp is optimized, considering strength under the severe wind loading condition. According to the classification of structural optimization, the structural optimization of a jaw belongs to shape optimization. In the conventional structural optimization methods, they have difficulties in defining complex shape design variables and preventing mesh distortions. To overcome the difficulties, the metamodel using kriging interpolation method is introduced, replacing true response by approximate one. This research presents the shape optimization of a jaw using iterative kriging interpolation models and simulated annealing algorithm. The new kriging models are iteratively constructed by refining the former kriging models. This process is continued until the convergence criteria are satisfied. The optimum results obtained by the suggested method are compared with those obtained by the DOE (design of experiments) and VT (variation technology) methods built in ANSYS WORKBENCH.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.4
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• pp.68-78
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• 2003

Recently, low speed vehicle (LSV) is beginning to appear for various usages. The body of the LSV is usually made of the aluminum space frame (ASF) type rather than the monocoque or unitary construction type. A pa.1 of the reason is that it is easier to reduce mass efficiently while the required stiffness and strength are maintained. A design flow for LSV is proposed. Design specifications for structural performances of LSV do not exist yet. Therefore, they are defined through a comparative study with general passenger automobiles. An optimization problem is formulated by the defined specifications. At first, one pillar which has an important role in structural performances is selected and the reinforcements of the pillar are determined from topology optimization to maximize the stiffness. At second, the thicknesses of cross sections are determined to minimize the mass of the body while design specifications are satisfied. The optimum solution is compared with an existing design. The optimization process has been performed using a commercial optimization software system, GENESIS 7.0.