• Title/Summary/Keyword: Real-scale Hydraulic model experiment

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Construction of a Hydraulic Scale Model for Representing the Field Tracer Experiment in River (하천 현장 실험 재현을 위한 수리모형 장치 제작)

  • Chun, Il Young;Kim, Ki Chul;Lee, Jung Lyul;Suh, Kyung Suk
    • Journal of Radiation Industry
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    • v.2 no.3
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    • pp.155-161
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    • 2008
  • A hydraulic scale model was constructed to investigate the characteristics of flows and pollutant transport in laboratory. The distorted hydraulic scale model by assuming Froude similarity was adopted to represent hydrodynamics and dispersion in a river system. The scale model was composed of water reservoir, slope control part, booster pump, distributing plate and main channel. A constructed scale model will be used to present the overall concentration profiles of tracer and a research will be performed to convert the measured values using a hydraulic scale model to real field scale.

A Study on Safety at Stairs Flow using the Real-scale Hydraulic Model Experiment (실규모 수리모형실험을 이용한 계단 흐름에서의 안전성에 관한 연구)

  • Kim, Myounghwan;Lee, Du Han
    • Ecology and Resilient Infrastructure
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    • v.5 no.4
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    • pp.210-218
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    • 2018
  • In this study, a real-scale stairway model was constructed to analyze the evacuation safety of human life due to the change of flooded stair flow. In the experiment, the water depth and flow velocity at each stage of the stairs were measured and the specific force per unit width was calculated. Using the calculated the specific force per unit width, the evacuation safety of each steps of stairs according to the change of the flooded stair flow was presented. Finally, the depth of water measured by the experiment and the evacuation safety graph of "Ishigaki" by the specific force per unit width were combined to analyze the evacuation safety by depth. As a result, it has been found that evacuation of adult man is difficult without help at the flow depth of 0.20 m or more. And it has been found that evacuation of adult women and elderly men are difficult without help at the flow depth of 0.15 m or more. Finally, it has been found that evacuation of elderly women is difficult without help at depth of 0.13 m or more.

Real-time large-scale hybrid testing for seismic performance evaluation of smart structures

  • Mercan, Oya;Ricles, James;Sause, Richard;Marullo, Thomas
    • Smart Structures and Systems
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    • v.4 no.5
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    • pp.667-684
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    • 2008
  • Numerous devices exist for reducing or eliminating seismic damage to structures. These include passive dampers, semi-active dampers, and active control devices. The performance of structural systems with these devices has often been evaluated using numerical simulations. Experiments on structural systems with these devices, particularly at large-scale, are lacking. This paper describes a real-time hybrid testing facility that has been developed at the Lehigh University NEES Equipment Site. The facility enables real-time large-scale experiments to be performed on structural systems with rate-dependent devices, thereby permitting a more complete evaluation of the seismic performance of the devices and their effectiveness in seismic hazard reduction. The hardware and integrated control architecture for hybrid testing developed at the facility are presented. An application involving the use of passive elastomeric dampers in a three story moment resisting frame subjected to earthquake ground motions is presented. The experiment focused on a test structure consisting of the damper and diagonal bracing, which was coupled to a nonlinear analytical model of the remaining part of the structure (i.e., the moment resisting frame). A tracking indictor is used to track the actuator ability to achieve the command displacement during a test, enabling the quality of the test results to be assessed. An extension of the testbed to the real-time hybrid testing of smart structures with semi-active dampers is described.

A Real Scale Experimental Study for Evaluation of Permissible Shear Stresses on Vegetation Mats (식생매트 허용 소류력 평가를 위한 실규모 실험 연구)

  • Lee, Du Han;Kim, Dong-Hee;Kim, Myounghwan;Rhee, Dong Sop
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.13 no.12
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    • pp.6151-6158
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    • 2012
  • By the activation of environment-friendly river works, application of vegetation mats is increasing, however, evaluation techniques for hydraulic stability of vegetation mats are not presented. This study is conducted to develop the objective test method for vegetation mats. Two kind of vegetation mats are tested by the real scale experiments, and hydraulic quantities are measured and analyzed to evaluate acting shear stresses. Roughness and shear stress are evaluated by 1 D non-uniform model. After each tests, changes in mat surfaces and sub-soil are evaluated, and from these evaluation, 3 types of mat surface damages and 2 types of sub-soil damages are presented. In the study, the case in which some damages in mat surface don't cause loss of sub-soil, is presented to be in the stable condition. Appling this stable condition and acting shear stresses, permissible shear stresses of vegetation mats are evaluated, and the results show that the reinforced mat with wire netting has more permissible shear stress.

Deep-learning-based system-scale diagnosis of a nuclear power plant with multiple infrared cameras

  • Ik Jae Jin;Do Yeong Lim;In Cheol Bang
    • Nuclear Engineering and Technology
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    • v.55 no.2
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    • pp.493-505
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    • 2023
  • Comprehensive condition monitoring of large industry systems such as nuclear power plants (NPPs) is essential for safety and maintenance. In this study, we developed novel system-scale diagnostic technology based on deep-learning and IR thermography that can efficiently and cost-effectively classify system conditions using compact Raspberry Pi and IR sensors. This diagnostic technology can identify the presence of an abnormality or accident in whole system, and when an accident occurs, the type of accident and the location of the abnormality can be identified in real-time. For technology development, the experiment for the thermal image measurement and performance validation of major components at each accident condition of NPPs was conducted using a thermal-hydraulic integral effect test facility with compact infrared sensor modules. These thermal images were used for training of deep-learning model, convolutional neural networks (CNN), which is effective for image processing. As a result, a proposed novel diagnostic was developed that can perform diagnosis of components, whole system and accident classification using thermal images. The optimal model was derived based on the modern CNN model and performed prompt and accurate condition monitoring of component and whole system diagnosis, and accident classification. This diagnostic technology is expected to be applied to comprehensive condition monitoring of nuclear power plants for safety.