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

• Water for future
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• v.27 no.1
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• pp.141-150
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• 1994

The purpose of this study is develope the algorithm of channel routing model which can be used for flood forecasting. In routing model, the hydrulic technique of the implicit scheme in the dynamic equation is chosen to route the unsteady varied flow. The channel routing model is connected with conceptual watershed model which is able to compute the flood hydrograph from each subbasin. The comparative study shows that the conceptual model can simulate the watershed runoff accurately. As a result of investigating the channel routing model, the optimal weighting factor $\theta$ which fixes two points between time line is selected. And also, the optimal error tolerance which satisfies computing time and converge of solution is chosen.

• Journal of the Society of Naval Architects of Korea
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• v.35 no.3
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• pp.79-87
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• 1998

The purpose of this paper is to develope a neurofuzzy system for a ship design which can determine efficiently design values e.g. principal dimensions and hull factors in a conceptual design. The neurofuzzy system for a ship design(NeFHull) applies a information about given input-output data to fuzzy theories and deals these fuzzificated values with neural networks, e.g. first, redefines normalized input-output data ad membership functions and then executes these fuzzficated information with backpropagation neural networks. We use a hybrid learning algorithm in the training of neural networks and examine the usefulness of suggested method through mathematical and mechanical examples.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.6
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• pp.754-760
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• 2012

To improve the efficiency and economics of national defence, the needs for defence M&S systems are greatly increased, but the lack of interoperability and reusability lowers the level of reliability in the existing simulations models. Recently, many research activities have been performed and some conceptual models, such as CMMS, DCMF, and KAMA, were introduced. However, these models don't support the whole process of defence M&S system development nor provide integrated domain knowledge and up-to-date data. In this paper, we analyzed the analysts' guidances and doctrines, which are the basic ingredients for the simulation system development, and proposed a systematic structure for all the defence M&S stakeholders to share the standardized domain knowledge, modeling algorithm and data. This will be a logical bridge between Mission Space and Simulation Space, and provide substantial data sets to build simulation systems.

• Journal of Astronomy and Space Sciences
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• v.38 no.2
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• pp.105-117
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• 2021

In this study, a preliminary trajectory design is conducted for a conceptual spacecraft mission to a near-Earth asteroid (NEA) (99942) Apophis, which is expected to pass by Earth merely 32,000 km from the Earth's surface in 2029. This close approach event will provide us with a unique opportunity to study changes induced in asteroids during close approaches to massive bodies, as well as the general properties of NEAs. The conceptual mission is set to arrive at and rendezvous with Apophis in 2028 for an advanced study of the asteroid, and some near-optimal (in terms of fuel consumption) trajectories under this mission architecture are to be investigated using a global optimization algorithm called monotonic basin hopping. It is shown that trajectories with a single swing-by from Venus or Earth, or even simpler ones without gravity assist, are the most feasible. In addition, launch opportunities in 2029 yield another possible strategy of leaving Earth around the 2029 close approach event and simply following the asteroid thereafter, which may be an alternative fuel-efficient option that can be adopted if advanced studies of Apophis are not required.

• Journal of The Korean Society of Agricultural Engineers
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• v.47 no.3
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• pp.3-13
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• 2005

The conceptual rainfall-runoff models are used to predict complex hydrological effects of a basin. However, to obtain reliable results, there are some difficulties and problems in choosing optimum model, calibrating, and verifying the chosen model suitable for hydrological characteristics of the basin. In this study, Genetic Algorithm and SCE-UA method as global optimization methods were applied to compare the each optimization technique and to analyze the application for the rainfall-runoff models. Modified TANK model that is used to calculate outflow for watershed management and reservoir operation etc. was optimized as a long term rainfall-runoff model. And storage-function model that is used to predict real-time flood using historical data was optimized as a short term rainfall-runoff model. The optimized models were applied to simulate runoff on Pyeongchang-river watershed and Bocheong-stream watershed in 2001 and 2002. In the historical data study, the Genetic Algorithm and the SCE-UA method showed consistently good results considering statistical values compared with observed data.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.451-455
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• 2003

Major concern in modern industry is how to reduce the time and cost for product efficient production. Among many mechanical parts of a satellite, bracket plays an important role to support the load when the satellite is launched to space. so enough strength and stiffness. A designer could add unnecessary material and strength it so as not to fail when it used. But if mechanical part of satellite is over-designed, cost will rise and it also goes against to the aim of lightness. To achieve lightness and enough strength and stiffness, optimization algorithm should be introduced in design process. In this study, conceptual design of bracket is carried out to increase the performance of satellite. Some parameter which could change the weight of this part are selected as design variables. Total weight of bracket is to be minimized while displacement and stress should not exceed limit. Size optimization is done with 3D solid element and PLBA, the RQP algorithm. The weight of 0.262kg of initial model is reduced to 0.241kg after optimization process, so 9.8% of weight reduction is obtained.

• Journal of Korean Institute of Industrial Engineers
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• v.35 no.2
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• pp.150-159
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• 2009

The heterogeneous fleet vehicle routing problem(HVRP) is a variant of the classical vehicle routing problem in which customers are served by a heterogeneous fleet of vehicles with various capacities, fixed costs and variable costs. We propose a new conceptual HVRPCR(HVRP with customer restriction) model including additional customer restrictions in HVRP. In this paper, we develop hybrid particle swarm optimization(HPSO) algorithm with 2-opt and node exchange technique for HVRP. The solution representation is a n-dimensional particle for HVRP with N customers. The decoding method for this representation starts with the transformation of particle into a priority list of customer to enter route and limit of vehicle to serve each customer. The vehicle routes are then constructed based on the customer priority list and limit of vehicle to serve. The proposed algorithm is tested using 8 benchmark problems and it consistently produces high-quality solutions, including new best solutions. The numerical results show that the proposed algorithm is robust and efficient.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.2
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• pp.313-320
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• 2011

SPH(Smoothed Particle Hydrodynamics) is a gridless Lagrangian technique that is useful as an alternative numerical analysis method used to analyze high deformation problems as well as astrophysical and cosmological problems. In SPH, all points within the support of the kernel are taken as neighbours. The accuracy of the SHP is highly influenced by the method for choosing neighbours from all particle points considered. Typically a linked-list method or tree search method has been used as an effective tool because of its conceptual simplicity, but these methods have some liability in anisotropy situations. In this study, convex hull algorithm is presented as an improved method to eliminate this artifact. A convex hull is the smallest convex set that contains a certain set of points or a polygon. The selected candidate neighbours set are mapped into the new space by an inverse square mapping, and extract a convex hull. The neighbours are selected from the shell of the convex hull. These algorithms are proved by Fortran programs. The programs are expected to use as a searching algorithm in the future SPH program.

• The Transactions of the Korea Information Processing Society
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• v.6 no.6
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• pp.1571-1580
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• 1999

When a hierarchical structure is derived from data set for data mining and machine learning, using a conceptual clustering algorithm, one of the unsupervised learning paradigms, it is not unusual to have a different set of outcomes with respect to the order of processing data objects. To overcome this problem, the first classification process is proceeded to construct an initial partition. The partition is expected to imply the possible range in the number of final classes. We apply center sorting to the data objects in the classes of the partition for new data ordering and build a new partition using ITERATE clustering procedure. We developed an algorithm, REIT that leads to the final partition with stable and best partition score. A number of experiments were performed to show the minimization of order bias effects using the algorithm.