• 제목/요약/키워드: network design parameters

검색결과 686건 처리시간 0.027초

Thermal Hydraulic Design Parameters Study for Severe Accidents Using Neural Networks

  • Roh, Chang-Hyun;Chang, Soon-Heung
    • 한국원자력학회:학술대회논문집
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    • 한국원자력학회 1997년도 추계학술발표회논문집(1)
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    • pp.469-474
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    • 1997
  • To provide tile information ell severe accident progression is very important for advanced or new type of nuclear power plant (NPP) design. A parametric study, therefore was performed to investigate the effect of thermal hydraulic design parameters ell severe accident progression of pressurized water reactors (PWRs), Nine parameters, which are considered important in NPP design or severe accident progression, were selected among the various thermal hydraulic design parameters. The backpropagation neural network (BPN) was used to determine parameters, which might more strongly affect the severe accident progression, among mile parameters. For training. different input patterns were generated by the latin hypercube sampling (LHS) technique and then different target patterns that contain core uncovery time and vessel failure time were obtained for Young Gwang Nuclear (YGN) Units 3&4 using modular accident analysis program (MAAP) 3.0B code. Three different severe accident scenarios, such as two loss of coolant accidents (LOCAs) and station blackout(SBO), were considered in this analysis. Results indicated that design parameters related to refueling water storage tank (RWST), accumulator and steam generator (S/G) have more dominant effects on the progression of severe accidents investigated, compared to tile other six parameters.

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인공 신경회로망을 이용한 전자비례 감압밸브의 솔레노이드 형상 최적화 (Optimization of Design Parameters of a EPPR Valve Solenoid using Artificial Neural Network)

  • 윤주호;웬민냣;이현수;윤장원;김당주;이동원;안경관
    • 드라이브 ㆍ 컨트롤
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    • 제13권2호
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    • pp.34-41
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    • 2016
  • Unlike the commonly used On/Off solenoid, constant attraction force which is independent of plunger displacement is a considerably important characteristic to proportional solenoid of the EPPR Valve. Attraction force uniformity is mainly affected by the internal shape design parameters. Due to a number of shape design parameters, the optimal parameter values are very complex and time consuming to find by trial and error method. Much research has been conducted or are still in progress to find the optimal parameter values by applying various optimization techniques like Genetic Algorithm, Evolution Strategy, Simulated Annealing, or the Taguchi method. In this paper, the design parameters which have primary effects on the attraction force uniformity and the average attraction force are decided by main effects analysis of Design of Experiments. Optimal parameter values are derived using finite-element analysis and a neural network model.

로봇 GMA용접에 최적의 비드폭 예측 시스템 개발에 관한 연구 (A Study on Development of System for Prediction of the Optimal Bead Width on Robotic GMA Welding)

  • 김일수
    • 한국생산제조학회지
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    • 제7권6호
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    • pp.57-63
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    • 1998
  • An adaptive control in the robotic GMA welding is employed to monitor information about weld characteristics and process parameters as well as to modify those parameters to hold weld quality within acceptable limits. Typical characteristics are the bead geometry, composition, microstructure, appearance, and process parameters which govern the quality of the final weld. The main objectives of this thesis are to realize the mapping characteristics of bead width through learning. After learning, the neural estimation can estimate the bead width desired form the learning mapping characteristic. The design parameters of the neural network estimator(the number of hidden layers and the number of nodes in a layer) are chosen from an estimation error analysis. A series of bead of bead-on-plate GMA welding experiments was carried out in order to verify the performance of the neural network estimator. The experimental results show that the proposed neural network estimator can predict the bead width with reasonable accuracy and guarantee the uniform weld quality.

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A Neural Network Model for Building Construction Projects Cost Estimating

  • El-Sawalhi, Nabil Ibrahim;Shehatto, Omar
    • Journal of Construction Engineering and Project Management
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    • 제4권4호
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    • pp.9-16
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    • 2014
  • The purpose of this paper is to develop a model for forecasting early design construction cost of building projects using Artificial Neural Network (ANN). Eighty questionnaires distributed among construction organizations were utilized to identify significant parameters for the building project costs. 169 case studies of building projects were collected from the construction industry in Gaza Strip. The case studies were used to develop ANN model. Eleven significant parameters were considered as independent input variables affected on "project cost". The neural network model reasonably succeeded in estimating building projects cost without the need for more detailed drawings. The average percentage error of tested dataset for the adapted model was largely acceptable (less than 6%). Sensitivity analysis showed that the area of typical floor and number of floors are the most influential parameters in building cost.

컴퓨터 통합 생산을 위한 통신망의 성능 관리 (Performance Management of Communication Networks for Computer Intergrated Manufacturing)

  • Lee, S.
    • 한국정밀공학회지
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    • 제11권4호
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    • pp.126-137
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    • 1994
  • Performance management of computer networks is intended to improve a given network performance in order for more efficient information exchange between subsystems of an integrated large-scale system. Importance of perfomance management is growing as many functions of the large- scale system depend on the quality of communication services provided by the network. The role of performance management is to manipulate the adjustable protocol parameters on line so that the network can adapt itself to a dynamic environment. This can be divided into two subtasks : performance evaluation to find how changes in protocol parameters affect the network performance and decision making to determine the magnitude and direction of parameter adjustment. This paper is the first part of the two papers focusing on conceptual design, development, and evaluation of performance management for token bus networks. This paper specifically deals with the task of performance evaluation which utilizes the principle of perturbation analysis of discrete event dynamic systems. The developed algorithm can estimate the network performance under a perturbed protocol parameter setting from observations of the network operations under a nominal parameter setting.

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비자성체 용기 가열을 위한 Induction Cooker 공진 네트워크 설계 및 검증 (Resonant Network Design and Verification of Induction Cooker for Heating Nonmagnetic Vessel)

  • 장은수;박상민;주동명;이병국
    • 전력전자학회논문지
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    • 제22권6호
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    • pp.504-509
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    • 2017
  • This paper proposes a procedure for designing a resonant network for induction cookers that enables the induction heating of magnetic and non-magnetic vessels. In order to design such network, the range of operating frequency must be determined according to the material of the vessels by measuring several parameters, such as equivalent resistance and inductance, which are reflected in the working coil of the vessels. Through this process, the capacitance of the resonant capacitor is determined. The PSIM simulation and experiment results verify the feasibility of the proposed design and the heating performance of the designed resonant network.

자동차용 차동 베벨기어의 최적 예비성형체 설계 (The Optimal Preform Design for Automotive Differential Bevel Gear)

  • 김병민;김동환;정구섭
    • 한국자동차공학회논문집
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    • 제12권1호
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    • pp.184-189
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    • 2004
  • In this paper, the warm forging process sequence has been determined to manufacture the warm forged product for the precision bevel gear used as the differential gear unit of a commercial automobile. The preform shape of bevel gear influences the dimensional accuracy and stiffness of final product. The aspect ratio and chamfer length are considered as design parameters to achieve adequate metal distribution in the finish forging operation. Then the optimal conditions of design parameters have been selected by artificial neural network (ANN). Finally, to verify the optimal preform shape, the experiments of the warm forging of the bevel gear have been executed. The proposed method can give more systematic and economically feasible means for designing the preform shape in metal forming process.

신경회로망 동정기법에 기초한 HIA 적응 PID 제어기를 이용한 AGV의 주행제어에 관한 연구 (A Study on Driving Control of an Autonomous Guided Vehicle using Humoral Immune Algorithm Adaptive PID Controller based on Neural Network Identifier Technique)

  • 이영진;서진호;이권순
    • 한국정밀공학회지
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    • 제21권10호
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    • pp.65-77
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    • 2004
  • In this paper, we propose an adaptive mechanism based on immune algorithm and neural network identifier technique. It is also applied fur an autonomous guided vehicle (AGV) system. When the immune algorithm is applied to the PID controller, there exists the case that the plant is damaged due to the abrupt change of PID parameters since the parameters are almost adjusted randomly. To solve this problem, we use the neural network identifier (NNI) technique fur modeling the plant and humoral immune algorithm (HIA) which performs the parameter tuning of the considered model, respectively. After the PID parameters are determined in this off-line manner, these gains are then applied to the plant for the on-line control using an immune adaptive algorithm. Moreover, even though the neural network model may not be accurate enough initially, the weighting parameters are adjusted to be accurate through the on-line fine tuning. Finally, the simulation and experimental result fur the control of steering and speed of AGV system illustrate the validity of the proposed control scheme. These results for the proposed method also show that it has better performance than other conventional controller design methods.

동기식 전송망에 적용되는 DP-PLL 특성에 관한 연구 (A study on the characteristics of DP-PLL in a SDH-based network)

  • 이창기;홍재근
    • 한국통신학회논문지
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    • 제22권6호
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    • pp.1289-1301
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    • 1997
  • In a SDH network, one of the most important issues is the realization of network synchronization. In this paper, we presented the relationship between parameters and control algorithm of DP-PLL for design in a SDH based time, SSM processing time, PJE counter and reference switching time, and analyzed phase transients for one node and mutiple nodes through our simulation results with a standard specification. We suggested suitable design method of SDH-DP-PLL.

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Design and Fabrication of Low Power Sensor Network Platform for Ubiquitous Health Care

  • Lee, Young-Dong;Jeong, Do-Un;Chung, Wan-Young
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2005년도 ICCAS
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    • pp.1826-1829
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    • 2005
  • Recent advancement in wireless communications and electronics has enabled the development of low power sensor network. Wireless sensor network are often used in remote monitoring control applications, health care, security and environmental monitoring. Wireless sensor networks are an emerging technology consisting of small, low-power, and low-cost devices that integrate limited computation, sensing, and radio communication capabilities. Sensor network platform for health care has been designed, fabricated and tested. This system consists of an embedded micro-controller, Radio Frequency (RF) transceiver, power management, I/O expansion, and serial communication (RS-232). The hardware platform uses Atmel ATmega128L 8-bit ultra low power RISC processor with 128KB flash memory as the program memory and 4KB SRAM as the data memory. The radio transceiver (Chipcon CC1000) operates in the ISM band at 433MHz or 916MHz with a maximum data rate of 76.8kbps. Also, the indoor radio range is approximately 20-30m. When many sensors have to communicate with the controller, standard communication interfaces such as Serial Peripheral Interface (SPI) or Integrated Circuit ($I^{2}C$) allow sharing a single communication bus. With its low power, the smallest and low cost design, the wireless sensor network system and wireless sensing electronics to collect health-related information of human vitality and main physiological parameters (ECG, Temperature, Perspiration, Blood Pressure and some more vitality parameters, etc.)

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