• Title/Summary/Keyword: Equipment Reinforcement

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A Study on Deep Reinforcement Learning Framework for DME Pulse Design

  • Lee, Jungyeon;Kim, Euiho
    • Journal of Positioning, Navigation, and Timing
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    • v.10 no.2
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    • pp.113-120
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    • 2021
  • The Distance Measuring Equipment (DME) is a ground-based aircraft navigation system and is considered as an infrastructure that ensures resilient aircraft navigation capability during the event of a Global Navigation Satellite System (GNSS) outage. The main problem of DME as a GNSS back up is a poor positioning accuracy that often reaches over 100 m. In this paper, a novel approach of applying deep reinforcement learning to a DME pulse design is introduced to improve the DME distance measuring accuracy. This method is designed to develop multipath-resistant DME pulses that comply with current DME specifications. In the research, a Markov Decision Process (MDP) for DME pulse design is set using pulse shape requirements and a timing error. Based on the designed MDP, we created an Environment called PulseEnv, which allows the agent representing a DME pulse shape to explore continuous space using the Soft Actor Critical (SAC) reinforcement learning algorithm.

Lifetime Prediction of Geogrids for Reinforcement of Embankments and Slopes through Time-Temperature Superposition

  • Koo, Hyun-Jin;Kim, You-Kyum;Kim, Dong-Whan
    • Corrosion Science and Technology
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    • v.4 no.4
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    • pp.147-154
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    • 2005
  • The creep resistance of geogrids is one of the most significant long-term safety characteristics used as the reinforcement in slopes and embankments. The failure of geogrids is defined as creep strain greater than 10%. In this study, the accelerated creep tests were applied to polyester geogrids at various loading levels of 30, 50% of the yield strengths and temperatures using newly designed test equipment. Also, the new test equipment permitted the creep testing at or above glass transition temperature($T_g$) of 75, 80, $85^{\circ}C$. The time-dependent creep behaviors were observed at various temperatures and loading levels. And then the creep curves were shifted and superposed in the time axis by applying time-temperature supposition principles. The shifting factors(AFs) were obtained using WLF equation. In predicting the lifetimes of geogrids, the underlying distribution for failure times were determined based on identification of the failure mechanism. The results confirmed that the failure distribution of geogrids followed Weibull distribution with increasing failure rate and the lifetimes of geogrids were close to 100 years which was required service life in the field with 1.75 of reduction factor of safety. Using the newly designed equipment, the creep test of geogrids was found to be highly accelerated. Furthermore, the time-temperature superposition with the newly designed test equipment was shown to be effective in predicting the lifetimes of geogrids with shorter test times and can be applied to the other geosynthetics.

Study on Selection of Nuclear Seismic Fragile Equipment and Its Enhancement of Seismic Performance (주요기기 내진성능 상향을 위한 설비보강 및 취약부 도출연구)

  • Son, Jung-Dae;Koo, Gyeong-Hoi
    • Transactions of the Korean Society of Pressure Vessels and Piping
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    • v.14 no.2
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    • pp.16-23
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    • 2018
  • In order to investigate the ways to enhance the seismic performance of APR1400 seismic fragile equipment by direct design changes, four equipment such as Reactor Vessel Support, Integrated Head Assembly, Remote Shutdown Console, and Pressurizer are reviewed using information of the main dimensions, seismic stress evaluation results, design FRS, etc. in this paper. In addition to the direct reinforcement of equipments, the feasibility of seismic isolation for the safety related cabinet is also investigated and the actual adaption plan of a commercial spring-damper system is briefly reviewed.

Evaluation of Reinforcement Efficiency and Applicability Using a Reinforcement Method for Liquefiable Ground (액상화 발생 지반에 대한 보강공법 별 보강 효과 및 적용성 분석)

  • Yoo, Mintaek ;Han, Jin-Tae;Park, Youngjun ;Kim, Seok-Jung
    • Journal of the Korean Geotechnical Society
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    • v.39 no.5
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    • pp.41-50
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    • 2023
  • This study reviewed the liquefaction reinforcement and ground reinforcement methods widely used domestically and abroad through construction method characteristics and analyzed the economic feasibility and reinforcement efficiency of each reinforcement method. The analysis results were used to evaluate the applicability of the appropriate reinforcement method for the liquefaction reinforcement of new and existing structures. As a result of evaluating the applicability of the reinforcement method based on the economic feasibility and reinforcement effect of each reinforcement method, the compaction method, which secures the construct ability by applying large equipment, is advantageous when reinforcing a new structure, and the low-fluidity mortar injection method (C.G.S method) and the high-pressure injection method (J.S.P method) are considered appropriate in the existing structure.

A Study on the Ground Reinforcement and Impermeable Effect by McG (McG(맥) 주입공법에 의한 지반보강 및 차수효과에 관한 연구)

  • Jung, Jong-Ju;Do, Kyung-Yang;Shin, Tai-Wook;Park, Won-Chun
    • Proceedings of the Korean Geotechical Society Conference
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    • 2005.10a
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    • pp.581-590
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    • 2005
  • The grouting method is widely used as the impermeable effect and ground reinforcement in construction. But, it has a problem that cement and grout material are not mixed well in the injection tip equipment and an opposite flow and interception state of the chemical grouting is happened. so, continuous work is difficult. McG method installed a special grouting and device, made possible go well mixing of grouting material and prevent flowing backward and block of nozzle also diversify powder rate of cement that is grouting material to select sutible material in layer conditions. YSS that lowered $Na_2O$ influencing durability and circumstance is developed by gel-forming reaction material. so eco-circumstance and durability is increased by minimizing dissolution of underground water. In this study, it is assumed that seepage state of the injection material using a special injection tip equipment and a unconfined compressive strenth by mixing a various injection material of various. And it is confirmed that strenth increase effect and permeable decrease of the improved body through the test execution and field execution.

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The Suggestion of Reliability Improvement Method based on Failure Trend Analysis of Chiller (냉동기 고장경향분석을 통한 설비신뢰도향상 방안 제시)

  • Lee, Sang Dae;Yeom, Dong Un;Hyun, Jin Woo
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.64 no.4
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    • pp.251-255
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    • 2015
  • Chiller system plays an important role of maintaining room temperature constantly by supplying chilled water to Heating, Ventilating and Air Conditioning(HVAC)or area room cooler equipment during plant normal operation or accident condition. Chiller failures are one of the most frequently occurring equipment failures. If the types of chiller failures are analyzed and grouped thoroughly, it would be helpful to make chiller maintenance strategy at the plants. That would enhance equipment reliability of chiller in the end. In this paper, chiller failure data during three years were analyzed and categorized by specific failure code. In addition, the various proposals to improve equipment reliability of chiller were suggested such as Preventive Maintenance Optimization(PMO) strategy and performance monitoring reinforcement and so on.

Reinforcement Learning based Autonomous Emergency Steering Control in Virtual Environments (가상 환경에서의 강화학습 기반 긴급 회피 조향 제어)

  • Lee, Hunki;Kim, Taeyun;Kim, Hyobin;Hwang, Sung-Ho
    • Journal of Drive and Control
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    • v.19 no.4
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    • pp.110-116
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    • 2022
  • Recently, various studies have been conducted to apply deep learning and AI to various fields of autonomous driving, such as recognition, sensor processing, decision-making, and control. This paper proposes a controller applicable to path following, static obstacle avoidance, and pedestrian avoidance situations by utilizing reinforcement learning in autonomous vehicles. For repetitive driving simulation, a reinforcement learning environment was constructed using virtual environments. After learning path following scenarios, we compared control performance with Pure-Pursuit controllers and Stanley controllers, which are widely used due to their good performance and simplicity. Based on the test case of the KNCAP test and assessment protocol, autonomous emergency steering scenarios and autonomous emergency braking scenarios were created and used for learning. Experimental results from zero collisions demonstrated that the reinforcement learning controller was successful in the stationary obstacle avoidance scenario and pedestrian collision scenario under a given condition.

A Structural Analysis of Tsunami-proof Damper in Nuclear Power Plant (원자력 발전소에서 쓰나미 방지용 댐퍼에 대한 구조해석)

  • Chin, Do-Hun
    • Journal of the Korean Society of Industry Convergence
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    • v.23 no.4_2
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    • pp.603-609
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    • 2020
  • The purpose of this study is to research dampers, which are applied mainly to buildings adjacent to the coast, such as nuclear facilities, and used for ventilation and can safely protect lives and equipment in emergency situations. Comparing the equivalent stress for three models with hinge reinforcement and support reinforcement based on the early design model for Damper, in the Base model, the highest stress occurred in the part of hinge, especially in the centrally mounted hinge, and after reinforced the hinge, it was occurred in the rear support. For models reinforced hinges and supports, it is considered that reinforcement for stiffness will be required in the future as it entered within the range of allowable stress. For the safety factor distribution, the minimum safety ratio was sufficiently secured at least 1 and was high at the edge of the Damper frame and the Blade. As the hinge was reinforced, the safety factor distribution of Blade was increased, and it was verified that the safety factor was secured through the support reinforcement.

Evaluation of vibration characteristics according to changes in the fixing conditions of the electrical cabinet in power plants under an earthquake

  • Lee, Sang-Moon;Jeon, Bub-Gyu;Jung, Woo-Young
    • Earthquakes and Structures
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    • v.23 no.3
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    • pp.245-257
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    • 2022
  • This study is a basic study on the seismic reinforcement method of anchors of fixed parts in order to reduce the effect of seismic motion that affects the facilities in the event of an earthquake. By applying the test method of ICC ES AC 156, a seismic simulation experiment was performed on the vibration table with three axes simultaneously using the number of connecting bolts between cabinets and channels as a parameter. In addition, the reliability of the experiment was verified using numerical analysis, and the part about the dynamic characteristics that could not be performed according to the experimental limit was investigated through numerical analysis. As a result of the experiment, it was confirmed that the natural frequency of the main body was increased due to the increase in the number of connecting bolts between the cabinet-channel. Accordingly, it was judged that the rigidity of the lower part of the cabinet was increased due to seismic reinforcement. It was analyzed that the impact delivered to the body was effectively reduced. In the future, if the reinforcement of the connection parts mentioned in this study is added to the existing seismic reinforcement of the electrical cabinets, it is expected that the damage to the electrical cabinets of the power plant equipment caused by an earthquake will be effectively reduced.

Machine Scheduling Models Based on Reinforcement Learning for Minimizing Due Date Violation and Setup Change (납기 위반 및 셋업 최소화를 위한 강화학습 기반의 설비 일정계획 모델)

  • Yoo, Woosik;Seo, Juhyeok;Kim, Dahee;Kim, Kwanho
    • The Journal of Society for e-Business Studies
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    • v.24 no.3
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    • pp.19-33
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    • 2019
  • Recently, manufacturers have been struggling to efficiently use production equipment as their production methods become more sophisticated and complex. Typical factors hindering the efficiency of the manufacturing process include setup cost due to job change. Especially, in the process of using expensive production equipment such as semiconductor / LCD process, efficient use of equipment is very important. Balancing the tradeoff between meeting the deadline and minimizing setup cost incurred by changes of work type is crucial planning task. In this study, we developed a scheduling model to achieve the goal of minimizing the duedate and setup costs by using reinforcement learning in parallel machines with duedate and work preparation costs. The proposed model is a Deep Q-Network (DQN) scheduling model and is a reinforcement learning-based model. To validate the effectiveness of our proposed model, we compared it against the heuristic model and DNN(deep neural network) based model. It was confirmed that our proposed DQN method causes less due date violation and setup costs than the benchmark methods.