• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.26 no.9
• /
• pp.1866-1873
• /
• 2002

The pipe-cutting machine developed in this study is a portable device used to cut a steel pipe. The machine, which is attached to the steel pipe by magnetic force, is moving around the pip e using four wheels. It also works for straight cutting of a steel plate. For the higher precision and labor time reduction, the automation of a pipe-cutting process is needed. However, it is not easily achieved because of vibrations and the loss of track. It is also found that the problems of the automation arise from the coupling of the functional requirements for the pipe-cutting machine. So, it is very difficult io solve the problems by a conventional design method. To overcome the difficulties the new design process for the pipe-cutting machine is established by axiomatic approach in this paper. Based on the Independence Axiom design process, a new product is designed and manufactured. Finally, it is verified by experiments that the performance of the automatic pipe-cutting machine is improved

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.27 no.6
• /
• pp.1020-1027
• /
• 2003

A traditional mold design has been conducted by an experience-based trial and error, whereby the mold designer would decide the gate locations and processing conditions based on the caring characteristics and its functional requirements. The paper suggests an optimal gate location and processing conditions in the injection molding using a global search method referred to as micro genetic algorithm( ${\mu}$ GA). ${\mu}$ GA yields the optimal solution with a small size of population without respect to design variables for saving time that is needed to calculate the fitness of many individuals. Due to the reason, the paper uses a commercial analysis package of injection molding(CAPA) to analysis a state of flux. In addition to that, axiomatic approach .is applied in the beginning of design. It is a useful method to draw a well-organized and reasonable idea to handle a problem.

• Journal of Mechanical Science and Technology
• /
• v.17 no.12
• /
• pp.1969-1976
• /
• 2003

In the early phases of the product life cycle, Life Cycle Assessment (LCA) is recently used to support the decision-making for the product concepts, and the best alternative can be selected based on its estimated LCA and benefits. Both the lack of detailed information and time for a full LCA for a various range of design concepts need a new approach for the environmental analysis. This paper explores a new approximate LCA methodology for the product concepts by grouping products according to their environmental characteristics and by mapping product attributes into environmental impact driver (EID) index. The relationship is statistically verified by exploring the correlation between total impact indicator and energy impact category. Then, a neural network approach is developed to predict an approximate LCA of grouping products in conceptual design. Trained learning algorithms for the known characteristics of existing products will quickly give the result of LCA for newly designed products. The training is generalized by using product attributes for an EID in a group as well as another product attributes for the other EIDs in other groups. The neural network model with back propagation algorithm is used, and the results are compared with those of multiple regression analysis. The proposed approach does not replace the full LCA but it would give some useful guidelines for the design of environmentally conscious products in conceptual design phase.

• Korean Journal of Computational Design and Engineering
• /
• v.6 no.2
• /
• pp.78-88
• /
• 2001

In order to adopt feature-based parametric modeling, CAD/CAM applications must have a geometric constraint solver that can handle a large set of geometric configurations efficiently and robustly. In this paper, we describe a graph constructive approach to solving geometric constraint problems. Usually, a graph constructive approach is efficient, however it has its limitation in scope; it cannot handle ruler-and-compass non-constructible configurations and under-constrained problems. To overcome these limitations. we propose an algorithm that isolates ruler-and-compass non-constructible configurations from ruler-and-compass constructible configurations and applies numerical calculation methods to solve them separately. This separation can maximize the efficiency and robustness of a geometric constraint solver. Moreover, the solver can handle under-constrained problems by classifying under-constrained subgraphs to simplified cases by applying classification rules. Then, it decides the calculating sequence of geometric entities in each classified case and calculates geometric entities by adding appropriate assumptions or constraints. By extending the clustering types and defining several rules, the proposed approach can overcome limitations of previous graph constructive approaches which makes it possible to develop an efficient and robust geometric constraint solver.

• Korean Journal of Computational Design and Engineering
• /
• v.21 no.2
• /
• pp.159-169
• /
• 2016

In order to realize the virtual prototyping (VP) of digital products, it is important to provide the people involved in product development with the appropriate visualization and interaction of the products, and the vivid simulation of user interface (UI) behaviors in an interactive 3D virtual environment. In this paper, we propose an approach to web-based 3D virtual experience using Unity and Leap Motion. We adopt Unity as an implementation platform which easily and rapidly implements the visualization of the products and the design and simulation of their UI behaviors, and allows remote users to get an easy access to the virtual environment. Additionally, we combine Leap Motion with Unity to embody natural and immersive interaction using the user's hand gesture. Based on the proposed approach, we have developed a testbed system for web-based 3D virtual experience and applied it for the design evaluation of various digital products. Button selection test was done to investigate the quality of the interaction using Leap Motion, and a preliminary user study was also performed to show the usefulness of the proposed approach.

• Journal of Forest and Environmental Science
• /
• v.6 no.1
• /
• pp.18-28
• /
• 1989

The purpose of this study is to emphasize the indispensability and generalization of ecological approach in landscape planning and design, by describing the main ecological principles and the process and method applying them to landscape planning and presenting the case study of ecological planning. Landscape architecture is the science dealing with nature and therefore ecological approach in it cannot be emphasized too much. The main ecological principles that must be considered in landscape planning and design are energy flow, food chains, biogeochemical cycles, limiting factors, carrying capacity and homeostasis, vegetational succession, ecotone and edge effect, ecological niche, etc.. The seven component factors of natural ecosystem are climate, geology, physiography, hydrology, soil, vegetation, wildlife. These seven factors are interrelated by the above mentioned ecological principles. In landscape planning and design process, it is necessary that landscape architect should interpret and assess not only the component factors of natural ecosystem but also the interrelationships and ecological principles immanent in them and apply the data to final plan.

• Journal of Mechanical Science and Technology
• /
• v.19 no.5
• /
• pp.1080-1086
• /
• 2005

The preliminary design optimization of multi-stage spur gear reduction units has been a subject of considerable interest, since many high-performance power transmission applications (e.g., automotive and aerospace) require high-performance gear reduction units. There are multiple objectives in the optimal design of multi-stage spur gear reduction unit, such as minimizing the volume and maximizing the surface fatigue life. It is reasonable to formulate the design of spur gear reduction unit as a multi-objective optimization problem, and find an appropriate approach to solve it. In this paper an interactive physical programming approach is developed to place physical programming into an interactive framework in a natural way. Class functions, which are used to represent the designer's preferences on design objectives, are fixed during the interactive physical programming procedure. After a Pareto solution is generated, a preference offset is added into the class function of each objective based on whether the designer would like to improve this objective or sacrifice the objective so as to improve other objectives. The preference offsets are adjusted during the interactive physical programming procedure, and an optimal solution that satisfies the designer's preferences is supposed to be obtained by the end of the procedure. An optimization problem of three-stage spur gear reduction unit is given to illustrate the effectiveness of the proposed approach.

• Wind and Structures
• /
• v.9 no.1
• /
• pp.37-58
• /
• 2006

The paper describes a study about effects of upstream hills on design wind loads using two mathematical approaches: Computational Fluid Dynamics (CFD) and Artificial Neural Network (NN for short). For this purpose CFD and NN tools have been developed using an object-oriented approach and C++ programming language. The CFD tool consists of solving the Reynolds time-averaged Navier-Stokes equations and $k-{\varepsilon}$ turbulence model using body-fitted nearly-orthogonal coordinate system. Subsequently, design wind load parameters such as speed-up ratio values have been generated for a wide spectrum of two-dimensional hill geometries that includes isolated and multiple steep and shallow hills. Ground roughness effect has also been considered. Such CFD solutions, however, normally require among other things ample computational time, background knowledge and high-capacity hardware. To assist the enduser, an easier, faster and more inexpensive NN model trained with the CFD-generated data is proposed in this paper. Prior to using the CFD data for training purposes, extensive validation work has been carried out by comparing with boundary layer wind tunnel (BLWT) data. The CFD trained NN (CFD-NN) has produced speed-up ratio values for cases such as multiple hills that are not covered by wind design standards such as the Commentaries of the National Building Code of Canada (1995). The CFD-NN results compare well with BLWT data available in literature and the proposed approach requires fewer resources compared to running BLWT experiments.

• Advances in Computational Design
• /
• v.1 no.3
• /
• pp.235-251
• /
• 2016

We have performed a design optimization of a stiffened panel with curvilinear stiffeners using an artificial neural network (ANN) residual kriging based surrogate modeling approach. The ANN residual kriging based surrogate modeling involves two steps. In the first step, we approximate the objective function using ANN. In the next step we use kriging to model the residue. We optimize the panel in an iterative way. Each iteration involves two steps-shape optimization and size optimization. For both shape and size optimization, we use ANN residual kriging based surrogate model. At each optimization step, we do an initial sampling and fit an ANN residual kriging model for the objective function. Then we keep updating this surrogate model using an adaptive sampling algorithm until the minimum value of the objective function converges. The comparison of the design obtained using our optimization scheme with that obtained using a traditional genetic algorithm (GA) based optimization scheme shows satisfactory agreement. However, with this surrogate model based approach we reach optimum design with less computation effort as compared to the GA based approach which does not use any surrogate model.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.28 no.5
• /
• pp.106-114
• /
• 2014

The interior permanent-magnet synchronous motor (IPMSM) is often used for the traction motor of hybrid electric vehicles (HEVs) and electric vehicles (EVs) due to its high power density and wide speed range. This paper introduces the 120kW class IPMSM for traction motors in military trucks. This system, as a SHEV (series hybrid electric vehicle), requires a traction motor that can generate high torque. This study introduces a way to reduce costs by proposing a design approach that creates reluctance torque that can be maximized by varying the dq-axis inductance. If a model designed by a design approach meets the desired torque, the magnetic torque can be reduced by an amount equal to the increase in reluctance torque and consequently the amount of permanent magnets can be reduced. A reduction gear and high speed operation of motors are necessary for the miniaturization of the motor. Thus, a fairly large centrifugal force is generated due to the high speed rotation. This force causes mechanical interference between the rotor and the stator, and a design approach for adding an iron bridge is explained to solve the interference. In this study, the initial model and the improved model that reduces cost and improves mechanical durability are compared by FEA, and the models are produced. Finally, the FEM results were verified experimentally.