• Structural Engineering and Mechanics
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• 제48권6호
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• pp.791-807
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• 2013

Ultra High Performance Cementitious Composites with compressive strength 200MPa (UHPCC-200) is proposed for the structural design of super high hybrid wind turbine tower to gain durability, ductility and high strength design objectives. The minimal wall thickness is analyzed using basic bending and compression theory and is modified by a toque influence coefficient. Two cases of wall thickness combination of middle and bottom segment including varied ratio and constant ratio are considered within typical wall thickness dimension. Using nonlinear finite element analysis, the effects of wall thickness combinations with varied and constant ratio and prestress on the structural stress and lateral displacement are calculated and analyzed. The design limitation of the segmental wall thickness combinations is recommended.

• International Journal of Naval Architecture and Ocean Engineering
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• 제10권3호
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• pp.270-281
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• 2018

Application of the LeMoS hybrid (LH) URANS/LES method for the wake parameters prediction is considered. The wake fraction coefficient is calculated for inland ship model M1926 under shallow water conditions and compared to results of PIV measurements. It was shown that due to lack of the resolved turbulence at the interface between LES and RANS zones the artificial grid induced separations can occur. In order to overcome this drawback, a shielding function is introduced into LH model. The new version of the model is compared to the original one, RANS $k-{\omega}$ SST and SST-IDDES models. It is demonstrated that the proposed modification is robust and capable of wake prediction with satisfactory accuracy.

• Journal of Mechanical Science and Technology
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• 제15권5호
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• pp.544-554
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• 2001

A shop floor can be considered as an important level to develop Computer Integrated Manufacturing system (CIMs). However, a shop floor is a dynamic environment where unexpected events continuously occur, and impose changes to the planned activities. To deal with this problem, a shop floor should adopt an appropriate control system that is responsible for the coordination and control of the manufacturing physical flow and information flow. In this paper, a hybrid control system is described with a shop floor activity methodology called Multi-Layered Task Initiation Diagram (MTD). The architecture of the control model contains three levels: i.e., he shop floor controller (SFC), the intelligent agent controller (IAC) and the equipment controller (EC). The methodology behind the development of the control system is an intelligent multi-agent paradigm that enables the shop floor control system to be an independent, an autonomous, and distributed system, and to achieve an adaptability to change of the manufacturing environment.

• 한국신재생에너지학회:학술대회논문집
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• 한국신재생에너지학회 2006년도 추계학술대회
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• pp.109-112
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• 2006

In the recent studies, various types of multi mode electric variable transmission for hybrid electric vehicle have been proposed. Multi mode electric variable transmission consists of two or more different type planetary gear hybrid powertrain system(PGHP), which can change its power flow type by means of clutches for improving transmission efficiencies. Generally the power flows can be classified into three different types such as Input split, output split nd compound split. In This paper, we present velocity and torque equations of the input-split powertrain and analyze its optimal Performances. There are six combinations of the input-split powertrain, each combination has various lever length. We find optimal planetary gear ratios for fuel economy and acceleration performance, and compare performances of each combination.

• 제어로봇시스템학회논문지
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• 제4권5호
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• pp.651-657
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• 1998

In this study, an intelligent scheduling with hybrid architecture, which integrates expert system and neural network, is proposed. Neural network is trained with the data acquired from simulation model of FMC to obtain the knowledge about the relationship between the state of the FMC and its best dispatching rule. Expert system controls the scheduling of FMC by integrating the output of neural network, the states of FMS, and user input. By applying the hybrid system to a scheduling problem, the human knowledge on scheduling and the generation of non-logical knowledge by machine teaming, can be processed in one scheduler. The computer simulation shows that comparing with MST(Minimum Slack Time), there is a little increment in tardness, 5% growth in flow time. And at breakdown, tardness is not increased by expert system comparing with EDD(Earliest Due Date).

• 대한설비공학회:학술대회논문집
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• 대한설비공학회 2009년도 하계학술발표대회 논문집
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• pp.236-241
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• 2009

After analyzing the characteristics of the cooling dryer, the mixed cooling dryer was developed by adding the desiccant dryer which supplement the cooling dryer's demerits. Also, the hybrid desiccant cooling dryer was developed to use effectively the exhaust heat energy of the cooling dryer. It could make a more that 20 percent reduction in energy compared with the mixed desiccant cooling dryer. It has become essential to supply this equipment and search the suitable drying product.

• International Journal of Precision Engineering and Manufacturing
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• 제1권2호
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• pp.124-131
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• 2000

A shop floor can be considered as and importand level to develop a Computer Integrated Manufacturing system (CIMs). The shop foor is a dynamic environment where unexpected events contrinuously occur, and impose changes to planned activities. The shop floor should adopt an appropriate control system that is responsible for scheduling coordination and moving the manufacturing material and information flow. In this paper, the architecture of the hybrid control model identifies three levels; i.e., the shop floor controller (SFC), the cell controller(CC) and the equipment controller (EC). The methodology for developing these controller is employ an object-oriented approach for static models and IDEF0 for function models for dispatching a job. SFC and CC are coordinated by employing a multi-factors bidding and an adapted Analytic Hierarchy Process(AHP) prove applicability of the suggested method. Test experiment has been conducted by with the shopfloor, consisting of six manufacturing cells.

• 한국산업융합학회 논문집
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• 제2권2호
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• pp.3-10
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• 1999

Recently, It is proceeding the project of offshore structures in the many contury. A hybrid boundary-integral method is developed for computing wave forces on floating bodies. In this method, using the cylindric boundary for deviding elements, it is convenient to analysis but is difficult to apply to the rectangular or slender bodies. Thus, in this paper, I propose the new method by using the fictitious vertical cylinder of arbitary cross-section and shows results of the numerical analysis for testing.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제20권4호
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• pp.277-293
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• 2016

We develop an efficient numerical method for pricing the Derivative Linked Securities (DLS). The payoff structure of the hybrid DLS consists with a standard 2-Star step-down type ELS and the range accrual product which depends on the number of days in the coupon period that the index stay within the pre-determined range. We assume that the 2-dimensional Geometric Brownian Motion (GBM) as the model of two equities and a no-arbitrage interest model (One-factor Hull and White interest rate model) as a model for the interest rate. In this study, we employ the Monte Carlo simulation method with the Compute Unified Device Architecture (CUDA) parallel computing as the General Purpose computing on Graphic Processing Unit (GPGPU) technology for fast and efficient numerical valuation of DLS. Comparing the Monte Carlo method with single CPU computation or MPI implementation, the result of Monte Carlo simulation with CUDA parallel computing produces higher performance.

• 전자공학회논문지B
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• 제31B권12호
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• pp.116-123
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• 1994

A modified Hybrid learning rule(MHLR) is proposed, which is derived from combining the Back Propagation algorithm that is known as an excellent classifier with modified Hebbian by changing the orginal Hebbian which is a good feature extractor. The network architecture of MHLR is multi-layered neural network. The weights of MHLR are calculated from sum of the weight of BP and the weight of modified Hebbian between input layer and higgen layer and from the weight of BP between gidden layer and output layer. To evaluate the performance, BP, MHLR and the proposed Hybrid learning rule (HLR) are simulated by Monte Carlo method. As the result, MHLR is the best in recognition rate and HLR is the second. In learning speed, HLR and MHLR are much the same, while BP is relatively slow.