• 제목/요약/키워드: target problem

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HYPER 빔창의 열수력 해석에 의한 운전특성에 관한 연구 (A Study on the Operating Characteristics by Heat Flow Analysis of HYPER Beam Window)

  • 송민근;최진호;주은선;송태영
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2001년도 춘계학술대회논문집D
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    • pp.915-920
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    • 2001
  • A spent fuel problem has prevented the nuclear power from claiming to be a completely clean energy source. The nuclear transmutation technology to incinerate the long lived radioactive nuclides and produce energy during the incineration process is believed to be one or the best solutions. HYPER(Hybrid Power Extraction Reactor) is the accelerator driven transmutation system which is being developed by KAERI(Korea Atomic Energy Research Institute). Some major feature of HYPER have been developed and employed. On-power fueling concepts are employed to keep system power constant with minimum variation of accelerator power. A hollow cylinder-type metal fuel is designed for the on-line refueling concept. Lead-bismuth(Pb-Bi) is adopted as a coolant and Spallation target material. HYPER is a subcritical reactor which needs an external neutron source. 1GeV proton beam is irradiated to Lead-bismuth(Pb-Bi) target inside HYPER, and spallation neutrons are produced. When proton beams are irradiated, much heat is also deposited in the Pb-Bi target and beam window which separates Pb-Bi and accelerator vacuum. Therfore, an effective cooling is needed for HYPER target. In this paper, we performed the thermal-hydraulic analysis of HYPER target using FLUENT code, and also calculated thermal and mechanical stress of the beam window using ANSYS code.

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다중 UAV 협업을 위한 선형 분산 피동 표적추적 필터 설계 (Linear Distributed Passive Target Tracking Filter for Cooperative Multiple UAVs)

  • 이윤하;김찬영;나원상;황익호
    • 전기학회논문지
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    • 제67권2호
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    • pp.314-324
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    • 2018
  • This paper proposes a linear distributed target tracking filter for multiple unmanned aerial vehicles(UAVs) sharing their passive sensor measurements through communication channels. Different from the conventional nonlinear filtering schemes, the distributed passive target tracking problem is newly formulated within the framework of a linear robust state estimation theory incorporated with a linear uncertain measurement equation including the coordinate transform uncertainty. To effectively cope with the performance degradation due to the coordinate transform uncertainty, a linear consistent robust Kalman filter(CRKF) theory is devised and applied for designing a distributed passive target tracking filter. Through the simulations for typical UAV surveillance mission, the superior performance of the proposed method over the existing schemes of distributed passive target tracking are demonstrated.

무선 센서 네트워크의 목표 수명을 만족시키기 위한 에너지 효율적 라우팅 (Energy Efficient Routing for Satisfying Target Lifetime in Wireless Sensor Networks)

  • 이건택;박선주;김학진;한승재
    • 한국정보과학회논문지:정보통신
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    • 제36권6호
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    • pp.505-513
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    • 2009
  • 대부분의 무선 센서 네트워크를 활용한 어플리케이션에서는 네트워크를 설치한 후 언제까지 작동해야 하는 지를 나타내는 목표 수명(target lifetime)을 가진다. 하지만 무선 센서 네트워크는 많은 경우에 각 센서 노드들이 배터리를 이용하여 작동하기 때문에 목표 수명을 만족시키는 것은 쉬운 문제가 아니며 이를 달성하기 위해서는 에너지 효율적인 라우팅 알고리즘이 필요하다. 본 논문에서는 무선 센서 네트워크의 목표 수명을 만족시키기 위한 라우팅 알고리즘을 제안한다. 제안하는 알고리즘은 선형 프로그래밍(Linear Programming)을 이용하여 에너지 효율적인 경로를 찾는 동시에 감지 비율(sensing rate)을 조절함으로써 무선 센서 네트워크의 목표 수명을 만족시킨다. 시뮬레이션을 통해 제안한 기법의 성능을 다른 기법들의 성능과 비교한다.

최적 생산/판매 계획을 통한 기업 목표 관리 사례 (Management for Company Objectives with Considerations of Optimal Production/Sales Planning)

  • 정재헌
    • 한국경영과학회지
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    • 제34권2호
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    • pp.77-90
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    • 2009
  • Total profit level Increases if a company increase the cost for achieving R&D related goals of equipment productivity enhancement, production cost saving, or for achieving equipment scale target, sales volume goal. But how much money should be invested to achieve a certain level of profit? We formulated the model to set the optimal goal levels to minimize the investment cost under the constraint that certain level of total profit should be guaranteed. This model derived from a case of P steel company. We found that this should be considered in relation with the production sales planning (known as optimal product mix problem) to guarantee the profit. We suggested a nonlinear programming model, 3 valiant form of the p+roduct mix problem. We can find the optimal Investment level for the R&D related goals or sales volume goal, equipment scale target for the P steel company using the model.

특징점을 이용한 매니퓰래이터 자세 시각 제어 (Visual Servoing of manipulator using feature points)

  • 박성태;이민철
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 2004년도 추계학술대회 논문집
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    • pp.1087-1090
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    • 2004
  • stereo vision system is applied to a mobile manipulator for effective tasks. The robot can recognize a target and compute the position of the target using a stereo vision system. In this paper we persent a visual approach to the problem of object grasping. First we propose object recognization method which can find the object position and pose using feature points. A robot recognizes the feature point to Object. So a number of feature point is the more, the better, but if it is overly many, the robot have to process many data, it makes real-time image processing ability weakly. In other to avoid this problem, the robot selects only two point and recognize the object by line made by two points. Second we propose trajectory planing of the robot manipulator. Using grometry of between object and gripper, robot can find a goal point to translate the robot manipulator, and then it can grip the object successfully.

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A Knowledge-Based Fuzzy Post-Adjustment Mechanism:An Application to Stock Market Timing Analysis

  • Lee, Kun-Chang
    • 한국경영과학회지
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    • 제20권1호
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    • pp.159-177
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    • 1995
  • The objective of this paper is to propose a knowledge-based fuzzy post adjustment so that unstructured problems can be solved more realistically by expert systems. Major part of this mechanism forcuses on fuzzily assessing the influence of various external factors and accordingly improving the solutions of unstructured problem being concerned. For this purpose, three kinds of knowledge are used : user knowledge, expert knowledge, and machine knowledge. User knowledge is required for evaluating the external factors as well as operating the expert systems. Machine knowledge is automatically derived from historical instances of a target problem domain by using machine learning techniques, and used as a major knowledge source for inference. Expert knowledge is incorporate dinto fuzzy membership functions for external factors which seem to significantly affect the target problems. We applied this mechanism to a prototyoe expert system whose major objective is to provide expert guidance for stock market timing such as sell, buty, or wait. Experiments showed that our proposed mechanism can improve the solution quality of expert systems operating in turbulent decision-making environments.

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벤치마크 태그를 이용한 도착시간 차 기반의 RFID 측위 알고리즘 (TDOA-Based Localization Algorithms for RFID Systems Using Benchmark Tags)

  • 주운기
    • 경영과학
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    • 제29권3호
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    • pp.1-11
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    • 2012
  • This paper considers a localization problem in time difference of arrival (TDOA)-based radio frequency identification (RFID) systems. To estimate the position of a target tag, this paper suggests three localization algorithms that use benchmark tags. The benchmark tags are the same type as the target tag, but either the locations or distance of the benchmark tags are known. Two algorithms use the benchmarks for auxiliary information to improve the estimation accuracy of the other localization algorithms such as least squared estimator (LSE). The other one utilizes the benchmarks as essential tags to estimate the location. Numerical tests show that the localization accuracy can be improved by using benchmark tags especially when an algorithm using the LSE is applied to the localization problem. Furthermore, this paper shows that our benchmark algorithm is valuable when the measurement noise is large.

전동 부스터의 슬라이딩 모드 제어 (Sliding Mode Control of Electric Booster System)

  • 양이진;최규웅;허건수
    • 제어로봇시스템학회논문지
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    • 제18권6호
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    • pp.519-525
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    • 2012
  • Electric brake booster systems replace conventional pneumatic brake boosters with electric motors and rotary-todisplacement mechanisms including ECU (Electronic Control Unit). Electric booster brake systems require precise target pressure tracking and control robustness because vehicle brake systems operate properly given the large range of loading and temperature, actuator saturation, load-dependent friction. Also for the implement of imbedded control system, the controller should be selected considering the limited memory size and the cycle time problem of real brake ECU. In this study, based on these requirements, a sliding mode controller has been chosen and applied considering both model uncertainty and external disturbance. A mathematical model for the electric booster is derived and simulated. The developed sliding mode controller considering chattering problem has been compared with a conventional cascade PID controller. The effectiveness of the controller is demonstrated in some braking cases.

개선된 부가비례항법을 이용한 3차원 유도법칙의 구현 (The Realization of the Three Dimensional Guidance Law Using Modified Augmented Proportional Navigation)

  • 김용민;서진헌
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1995년도 추계학술대회 논문집 학회본부
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    • pp.222-224
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    • 1995
  • This paper deals with 3-dimensional missile guidance law. This presents the general optimal solution of the state equation which includes the target maneuvering as the Gauss-Markov processing. The main results ore about the transformation between the Cartesian coordinates on which both the guidance law and the filter are bused and the polar coordinates system in real missile guidance and measurement information. And the extended Kalman filter and adjustment of the estimated target acceleration by triangular functions is proposed solution to this transformation problem. It is shown that this proposed transformation is valid in real 3-dimensional guidance problem by the computer simulation.

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Domain Adaptation for Opinion Classification: A Self-Training Approach

  • Yu, Ning
    • Journal of Information Science Theory and Practice
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    • 제1권1호
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    • pp.10-26
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    • 2013
  • Domain transfer is a widely recognized problem for machine learning algorithms because models built upon one data domain generally do not perform well in another data domain. This is especially a challenge for tasks such as opinion classification, which often has to deal with insufficient quantities of labeled data. This study investigates the feasibility of self-training in dealing with the domain transfer problem in opinion classification via leveraging labeled data in non-target data domain(s) and unlabeled data in the target-domain. Specifically, self-training is evaluated for effectiveness in sparse data situations and feasibility for domain adaptation in opinion classification. Three types of Web content are tested: edited news articles, semi-structured movie reviews, and the informal and unstructured content of the blogosphere. Findings of this study suggest that, when there are limited labeled data, self-training is a promising approach for opinion classification, although the contributions vary across data domains. Significant improvement was demonstrated for the most challenging data domain-the blogosphere-when a domain transfer-based self-training strategy was implemented.