• 방사선산업학회지
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• 제2권3호
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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.

• Ecology and Resilient Infrastructure
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• 제5권4호
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• pp.210-218
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• 2018

본 연구에서는 침수된 계단 흐름의 변화에 따른 인명의 대피 안전성을 분석하기 위하여 실규모의 계단 수로 모형을 제작하여 수리 실험을 수행하였다. 실험에서는 계단 각각의 단에서의 수심과 유속을 측정하였으며 이를 이용하여 단위 폭당 비력을 산출하였다. 그리고 산출된 단위 폭당 비력 값을 이용하여 침수된 계단 흐름의 변화에 따른 구간별 대피 안전성을 제시하였다. 실험을 통해 측정된 수심 값과 Ishigaki의 단위 폭당 비력에 따른 대피 안전성 그래프를 결합하여 분석한 결과 계단 흐름 수심 0.20 m 이상에서는 도움 없이 성인 남성의 대피가 어려운 것이 확인되었으며, 수심 0.15 m 이상에서는 성인 여성과 노인 남성이 도움 없이 대피가 어려운 것으로 확인되었다. 노인 여성의 경우 수심 0.13 m 이상에서 도움 없이 대피가 어려운 것으로 나타났다.

• Smart Structures and Systems
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• 제4권5호
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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.

• 한국산학기술학회논문지
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• 제13권12호
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• pp.6151-6158
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• 2012

친환경 하천사업의 활성화로 식생매트의 사용은 증가하고 있으나 수리적 안정성에 대한 평가는 미흡한 실정이다. 본 연구는 호안용 식생매트 제품의 객관적인 수리안정성 시험 기법 개발을 위해 수행하였다. 이를 위해서 식생매트 2종에 대한 실규모 실험을 수행하여 수리량을 측정하고 분석하여 작용 소류력을 계산하였다. 1차원 부정류 모형을 이용하여 최적 조도계수를 결정하고 작용 소류력을 계산하였다. 각 유량의 시험 후에는 매트 표면 및 기반층의 변동 여부를 기록하여 평가하였으며 이에 따라 매트표면의 손상 유형 3가지 및 기반층의 손상 유형 2가지를 제시하였다. 본 연구에서는 식생매트의 표면 변동이 있더라도 하부 기반층의 유실이 발생하지 않는 경우에는 안정한 상태로 제안하였다. 이에 따라 실험체 2종의 허용소류력을 평가하였으며 철망으로 보강된 식생매트가 허용 소류력 측면에서 효과가 있는 것을 확인할 수 있었다.

• Nuclear Engineering and Technology
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• 제55권2호
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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.