• Transactions of Materials Processing
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• v.11 no.6
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• pp.487-494
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• 2002

A new method of optimal blank shape design using the initial nodal velocity (INOV) has been proposed for the drawings of arbitrary shaped cups. With the given information of tool shape and the final product shape, corresponding initial blank shape has been found from the motion of boundary nodes. Although the sensitivity method, the past work of the present authors, has been proved to be excellent method to find optimal blank shapes, the method has a problem that a couple of deformation analysis is required at each design step and it also exhibits an abnormal behaviors in the rigid body rotation prevailing region. In the present method INOV, only a single deformation analysis per each design stage is required. Drawings of practical products as well as oil-pan, have been chosen as the examples. At every case the optimal blank shapes have been obtained only after a few times of modification without predetermined deformation path. The deformed shape with predicted optimal blank almost coincides with the target shape at every case. Through the investigation the INOV is found to be very effective in the arbitrary shaped drawing process design.

• Transactions of Materials Processing
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• v.33 no.5
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• pp.341-347
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• 2024

Many studies have focused on the optimal design of multi-stage forging molds. For optimal design progress, geometry parameters must be automatically modified, and the updated analysis file delivered. However, existing automation processes set and change parameters at the analysis input file stage, limiting them to simpler tasks like 2D shapes and basic process conditions (e.g., friction, elasticity), making it challenging to handle 3D asymmetric shapes. To address these limitations, an automated program was developed that modifies geometry directly in the CAD model, enabling the automation of complex 3D and asymmetrical shapes. In this process, a 3D mold is generated immediately after the drawing is input, automating the design of both the product and the mold without manual intervention. The program's effectiveness was demonstrated in the design and forging analysis of a multi-stage mold for M10 hex head bolts. This fully automated program reduced preprocessing time by approximately 6.7 times and successfully performed sensitivity analysis without manual input.

• Journal of Power System Engineering
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• v.5 no.1
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• pp.50-56
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• 2001

Jet pumps are used in a great number of engineering applications. In the present study, jet shapes, mixing chamber shapes, and numerical methods for predicting the performance of an annular-type jet pump are investigated to determine the optimal turbulence model. The flow fields are simulated by solving the momentum and the continuity equations with the standard ${\kappa}-{\epsilon}$ and the RNG ${\kappa}-{\epsilon}$ turbulence models at different Reynolds numbers. After that, they are compared with the corresponding experimental data to determine the optimal model. Next, various calculations are conducted to find an optimal shape using the selected turbulence model. The study shows us that the RNG ${\kappa}-{\epsilon}$ model predicts the performance more exactly, and also shows that the most effective performance can be achieved with $12^{\circ}$ reducing angle and 130mm throat length.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1997.10a
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• pp.445-450
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• 1997

Optimal design of a piezoelectric smart structure is studied for cabin noise control. A cubic shaped acoustic cavity with a flat plate which covers one side is taken as the problem. The sensor signal is returned to the actuator through a negative gain. The acoustic cavity is modeled using the modal approach which represents the pressure fields in the cavity as a sum of mode shapes of the cavity with unknown coefficients. By using orthogonality of the mode shapes of the cavity, finite element equation for the structure with the influence of the acoustic cavity is derived. The objective function is the average pressure at a certain region, so-called silent zone, in the cavity and the design variables are the locations and sizes of the piezoelectric actuator and sensor. The optimal design is performed at several frequencies and the results show a remarkable noise reduction.

• Journal of the Earthquake Engineering Society of Korea
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• v.7 no.4
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• pp.81-87
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• 2003

In this paper, the feasibility of using Shannon's sampling theorem to reconstruct exact mode shapes of a structural system from a limited number of sensor points and localizing damage in that structure with reconstructed mode shapes is investigated. Shannon's sampling theorem for the time domain is reviewed. The theorem is then extended to the spatial domain. To verify the usefulness of extended theorem, mode shapes of a simple beam are reconstructed from a limited amount of data and the reconstructed mode shapes are compared to the exact mode shapes. On the basis of the results, a simple rule is proposed for the optimal placement of accelerometers in modal parameter extraction experiments. Practicality of the proposed rule and the extended Shannon's theorem is demonstrated by detecting damage in laboratory beam structure with two-span via applying to mode shapes of pre and post damage states.

• Smart Structures and Systems
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• v.13 no.3
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• pp.389-406
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• 2014

Optimal sensor placement techniques play a significant role in enhancing the quality of modal data during the vibration based health monitoring of civil structures, where many degrees of freedom are available despite a limited number of sensors. The literature has shown a shift in the trends for solving such problems, from expansion or elimination approach to the employment of heuristic algorithms. Although these heuristic algorithms are capable of providing a global optimal solution, their greatest drawback is the requirement of high computational effort. Because a highly efficient optimisation method is crucial for better accuracy and wider use, this paper presents an improved simulated annealing (SA) algorithm to solve the sensor placement problem. The algorithm is developed based on the sensor locations' coordinate system to allow for the searching in additional dimensions and to increase SA's random search performance while minimising the computation efforts. The proposed method is tested on a numerical slab model that consists of two hundred sensor location candidates using three types of objective functions; the determinant of the Fisher information matrix (FIM), modal assurance criterion (MAC), and mean square error (MSE) of mode shapes. Detailed study on the effects of the sensor numbers and cooling factors on the performance of the algorithm are also investigated. The results indicate that the proposed method outperforms conventional SA and Genetic Algorithm (GA) in the search for optimal sensor placement.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.26 no.7
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• pp.945-950
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• 2002

Shape optimization of a flow system is done to obtain the required effects, in the engineering fields. Most of these designs are accomplished by empirical or numerical analysis. In empirical analysis, it is difficult to obtain an optimal shape in the feasible design region. And, in numerical method, it usually needs much calculation expenses for shape optimization, because of design sensitivity analysis. In this study, we used the growth-strain method having only one distributed parameter such as a design variable. It optimizes a shape by making a distributed parameter such as dissipation energy uniform in a flow system, and then applied to two-flow systems. In order to overcome the stability occurred in numerical analysis performed by Azegami, the equation of volumic strain has been modified. Also, the shapes were compared with the known optimal shapes for the flow systems. Consequently, we confirm that the modified growth-strain method is very efficient and practical in shape optimization of the flow systems.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.25 no.1
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• pp.73-80
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• 2012

It is important to design the optimal shape in the initial process because the influences on the design and construction are large according to the shape and pattern of spatial structures. However, the existing optimal shape designs for spatial structure are performed by the designer's intuition and experiences. Therefore, this study proposes the integrated process using the topology optimization and cellular automata model. First, the initial optimal shapes are obtained by using the topology optimization, and then the spatial truss structural patterns are created through the application of cellular automata rules. Finally, the optimal shapes to satisfy the various design conditions are generated by the structural analysis and size optimization.

• International Journal of Advanced Culture Technology
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• v.12 no.3
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• pp.434-440
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• 2024

SIZE KOREA updates body measurement data every five years, providing essential information for the fashion industry. This anthropometric data is widely used to diagnose consumer body shapes and develop optimal clothing sizes. Artificial intelligence, particularly machine learning, excels in predicting such body shape classifications. This study seeks to enhance the suitability of clothing design by applying the new analytical methodology of machine learning techniques to better capture and classify the unique body shapes of Korean women. In this study, machine learning techniques such as K-means clustering, Silhouette analysis, and Decision Tree analysis were used to classify the lower body shapes of Korean women in their twenties and identify standard body shapes useful for slacks design. The results showed that the lower body of the age group could be classified into three categories: 'small stature' (the majority), 'tall with an average lower body volume,' and 'medium height with a fuller lower body' (the smallest share). The three-cluster approach is validated through Silhouette analysis, which minimizes misclassification. Decision Tree analysis then further defines the criteria for these clusters, highlighting waist height and hip depth as the most significant factors, achieving a classification accuracy of 90.6%. While this study is not directly related to Robotic Process Automation, its detailed analysis of body shapes for slacks patterns can aid RPA in clothing production. Future research should continue integrating machine learning in human body and fashion design studies.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1999.03a
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• pp.45-48
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• 1999

The optimal blank design method by sensitivity analysis has been applied to the formings of oil-pan, tailored blank and front panel have been chosen as the examples. Die shape is prepared by a commercial CAD system. Excellent results has been obtained between the numerical results and the target contour shapes. Through the investigation, the proposed systematic method of optimal blank design is found to be effective in the practical forming processes.