• 한국작물학회지
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• 제11권
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• pp.105-117
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• 1972

본연구는 맥류의 도복에 관여하는 주요형질의 상호관계를 구명함과 아울러 주요 대소맥 품종의 내도복성정도를 분류하고, 내도복성 품종 선발의 기준을 인정하여 보고자 한 것이며, 그 결과를 요약하면 다음과 같다. 1. 포장도복과 도복지수는 고도의 정의 상관(대맥 r=0.44-0.67 소맥 r=0.46-0.68)이 있으며 지상부 Bending moment에 간자체의 정도를 가미한 지수로서 도복저항성 검정에 가장 유효하다. 2. 간의 Bending stiffness를 표시하는 좌절시 Bending moment와 단면 2차 moment와는 정의 높은 상관(대백 r=0.59, 소맥 r=0.46-0.53)을 보였다. 3. 간의 Bending stiffness(좌절시 Bending moment 단면 2차 moment)와 간에의 건물집적량을 표시하는 단위간건물중과는 높은 정의 상관 (대맥 r=0.35-1.40, 소맥 r=0.33-0.76)을 보였다. 4. 도복지수와 단위간건물중 (대맥 r=-0.51～-0.70, 소맥 r=-0.65～-0.83) 좌절시 Bending moment (대맥 r=-0.29～-0.69, 소맥 r=-0.54～-0.89)과는 특히 높은 부의 상관을 보였으며, 소맥의 경우는 좌절하중, 단면 2차 moment, 단면계수와는 높은 부의 상관을 보였다. 5. 간외경은 간내경보다 간의 물리적 특성과 상관이 높으며 좌절하중 (대맥 r=0.42-0.56, 소맥 r=0.39-0.44), 좌절시 Bending moment (대맥 r=0.40-0.41, 소맥 r=0.38-0.49), 단면 2차 moment (대맥 r=0.56-0.97, 소맥 r=0.0.28-0.28), 단면계수(소맥 r=0.22-0.96)와는 정의 높은 상관이 있었고, 간벽후와 물리적특성과도 정의 상관을 보였다. 6. 간장은 포장도복과는 품종군에 따라서는 정의 상관은 보이나, 간의 강도를 고려한다면 내도복저항성품종 선발의 지표로서 이용하기는 어려울 것으로 보인다. 7. 대소맥의 많은 품종의 내도복성 정도를 분류한 결과, 한국품종중 대맥은 내도복저항성품종이 많고, 대맥은 내도복성인 품종의 분포가 대맥보다 적었으나, 일본품종들을 대소맥 모두 내도복저항성인 품종이 많았다. 8. 내도복저항성인 품종의 선발을 위하여는 도복지수가 대맥 1.67 소맥 1.76 정도 이하인 것은 고도의 저항성이 있었다.

• Structural Engineering and Mechanics
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• 제47권4호
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• pp.513-530
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• 2013

In this paper, an improved version of particle swarm optimization based optimum design algorithm (IPSO) is presented for the steel grillage systems. The optimum design problem is formulated considering the provisions of American Institute of Steel Construction concerning Load and Resistance Factor Design. The optimum design algorithm selects the appropriate W-sections for the beams of the grillage system such that the design constraints are satisfied and the grillage weight is the minimum. When an improved version of the technique is extended to be implemented, the related results and convergence performance prove to be better than the simple particle swarm optimization algorithm and some other metaheuristic optimization techniques. The efficiency of different inertia weight parameters of the proposed algorithm is also numerically investigated considering a number of numerical grillage system examples.

• 에너지공학
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• 제5권2호
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• pp.131-137
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• 1996

Typical size distribution of emission particulates is bi-modal in shape with particles in the fine mode (< 2.0 $\mu\textrm{m}$) and the coarse mode. An experimental study of pressure drop across the industrial gas cleaning filters has been conducted using particle mixture of fine alumina and coarse Arizona dusts with a rotating aerosol disperser to generate the bi-modal test aerosol. Pressure drop increased linearly with increasing mass loading. The pressure drop was found to be strongly dependent upon the mass ratio of fine to coarse particles. The smaller the mass ratio of fine to coarse particles and the higher face velocity are, the faster pressure drop rises. The fine particles and the greater inertia of the particle moving fast would cause a denser cake formation on the filter surface, resulting in a greater specific resistance to the gas flow.

• 로봇학회논문지
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• 제15권4호
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• pp.398-403
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• 2020

Robot's throwing control is difficult to accurately calculate because of air resistance and rotational inertia, etc. This complexity can be solved by using machine learning. Reinforcement learning using reward function puts limit on adapting to new environment for robots. Therefore, this paper applied deep reinforcement learning using neural network without reward function. Throwing is evaluated as a success or failure. AI network learns by taking the target position and control policy as input and yielding the evaluation as output. Then, the task is carried out by predicting the success probability according to the target location and control policy and searching the policy with the highest probability. Repeating this task can result in performance improvements as data accumulates. And this model can even predict tasks that were not previously attempted which means it is an universally applicable learning model for any new environment. According to the data results from 520 experiments, this learning model guarantees 75% success rate.

• Structural Engineering and Mechanics
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• 제51권6호
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• pp.1017-1036
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• 2014

Steel tubes have an efficient shape with large second moment of inertia relative to their light weight. One of the main problems of these members is their low buckling resistance caused from having thin walls. In this study, steel foams with high strength over weight ratio is used to fill the steel tube to beneficially modify the response of steel tubes. The linear eigenvalue and plastic collapse FE analysis is done on steel foam filled tube under pure compression and three point bending simulation. It is shown that steel foam improves the maximum strength and the ability of energy absorption of the steel tubes significantly. Different configurations with different volume of steel foam and composite behavior is investigated. It is demonstrated that there are some optimum configurations with more efficient behavior. If composite action between steel foam and steel increases, the strength of the element will improve, in a way that, the failure mode change from local buckling to yielding.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년 학술대회 논문집 정보 및 제어부문
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• pp.260-262
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• 2006

This paper presents Hybrid-PI controller of induction motor drive using fuzzy control. In general, PI controller in computer numerically controlled machine process fixed gain. They may perform well under some operating conditions, but not all. To increase the robustness, fixed gain PI controller, Hybrid-PI controller proposes a new method based self tuning PI controller. Hybrid-PI controller is developed to minimize overshoot and settling time following sudden parameter changes such as speed, load torque, inertia, rotor resistance and self inductance. The results on a speed controller of induction motor are presented to show the effectiveness of the proposed gain tuner. And this controller is better than the fixed gains one in terms of robustness, even under great variations of operating conditions and load disturbance.

• 제어로봇시스템학회논문지
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• 제13권3호
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• pp.192-197
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• 2007

This paper presents Hybrid PI controller of IPMSM drive using fuzzy adaptive mechanism(FAM) control. In general, PI controller in computer numerically controlled machine process fixed gain. They may perform well under some operating conditions, but not all. To increase the robustness, fixed gain PI controller, Hybrid PI controller proposes a new method based self tuning PI controller. Hybrid PI controller is developed to minimize overshoot and settling time following sudden parameter changes such as speed, load torque, inertia, rotor resistance and self inductance. The results on a speed controller of IPMSM are presented to show the effectiveness of the proposed gain tuner. And this controller is better than the fixed gains one in terms of robustness, even under great variations of operating conditions and load disturbance.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 심포지엄 논문집 정보 및 제어부문
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• pp.210-212
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• 2006

This paper presents Hybrid PI(HBPI) controller of IPMSM drive using fuzzy adaptive mechanism control. In general, PI controller in computer numerically controlled machine process fixed gain. They may perform well under some operating conditions, but not all. To increase the robustness, fixed gain PI controller, HBPI controller proposes a new method based self tuning PI controller. HBPI controller is developed to minimize overshoot and settling time following sudden parameter changes such as speed, load torque, inertia, rotor resistance and self inductance. The results on a speed controller of IPMSM are presented to show the effectiveness of the proposed gain tuner. And this controller is better than the fixed gains one in terms of robustness, even under great variations of operating conditions and load disturbance.

• 전력전자학회:학술대회논문집
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• 전력전자학회 1998년도 전력전자학술대회 논문집
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• pp.234-238
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• 1998

Parameter estimation of induction motor for vector control presented in this paper can be easily implemented and applied to inverters in the industrial field, because it needs no additional hardware such as voltage sensor and measuring equipment. At first, the stator resistance including switching loss of inverter is measured by simple voltage-current equation. Next, in pre-magnetization of machine by imposing the d-axis constant field-current, q-axis torque current is forced to the machine until its speed feedback reachs to pre-defined level of speed limit. At this time, we can measure the rotor time-constant by decreasing the distorted output-voltage of inverter. At last, stator inductance, transient inductance, and moment of inertia can be measured by the relationship of output voltage, output torque and speed feedback. The validity and usufulness of this method is verified by experimental results.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제54권8호
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• pp.395-401
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• 2005

This paper presents Hybrid PI(HBPI) controller of induction motor drive using fuzzy control. In general, PI controllers used in computer numerically controlled machines process fixed gain. They may perform well under some operating conditions, but not all. To increase the robustness of fixed gain PI controller, HBPI controller proposes a new method based self tuning PI controller. HBPI controller is developed to minimize overshoot and settling time following sudden parameter changes such as speed, load torque, inertia, rotor resistance and self inductance. The results on a speed controller of induction motor are presented to show the effectiveness of the proposed gam tuner. And this controller is better than the fixed gains one in terms of robustness, even under great variations of operating conditions and load disturbance.