• Journal of the Korean Society for Aviation and Aeronautics
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• v.21 no.4
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• pp.47-52
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• 2013

In this paper, limit cycle flutter induced by Hopf bifurcation is studied with nonlinear system analysis approach and observed for the critical slowing down phenomenon. Considering an attractor of the dynamics of a system, when a small perturbation is applied to the system, the dynamics converge toward the attractor at some rate. The critical slowing down means that this recovery rate approaches zero as a parameter of the system varies and the size of the basin of attraction shrinks to nil. Consequently, in the pre-bifurcation regime, the recovery rates decrease as the system approaches the bifurcation. This phenomenon is one of the features used to forecast bifurcation before they actually occur. Therefore, studying the critical slowing down for limit cycle flutter behavior would have potential applicability for forecasting those types of flutter. Herein, modeling and nonlinear system analysis of the 2D airfoil with torsional nonlinearity have been discussed, followed by observation of the critical slowing down phenomenon.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.41-44
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• 2021

In this paper, we propose a monitoring system that can monitor gas leakage concentrations in real time and forecast the amount of gas leaked after one minute. When gas leaks happen, they typically lead to accidents such as poisoning, explosion, and fire, so a monitoring system is needed to reduce such occurrences. Previous research has mainly been focused on analyzing explosion characteristics based on gas types, or on warning systems that sound an alarm when a gas leak occurs in industrial areas. However, there are no studies on creating systems that utilize specific gas explosion characteristic analysis or empirical urban gas data. This research establishes a deep learning model that predicts the gas explosion risk level over time, based on the gas data collected in real time. In order to determine the relative risk level of a gas leak, the gas risk level was divided into five levels based on the lower explosion limit. The monitoring platform displays the current risk level, the predicted risk level, and the amount of gas leaked. It is expected that the development of this system will become a starting point for a monitoring system that can be deployed in urban areas.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.611-614
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• 2009

Understanding the severity of the typhoon-induced storm-surge helps in planning reaction and in preventing further disaster. Natural disasters due to the storm-surge are predictable from accurate observations and forecasts from numerical simulations. What we can do is to make intelligent effort to minimize the loss due to the disaster to the most extent with the technology of early warning, forecast and prevention activity. In this paper, we propose the design of GIS-based Web Service System to visualize the time-varying storm-surge's height and wind field data effectively with 3 different kinds of resolution for predict and prevent storm-surge disasters. This system is one of the efforts to provide the storm-surge forecast service to general public and share two-way more helpful information to coastal resident through the Internet.

• Journal of Korea Water Resources Association
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• v.41 no.3
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• pp.341-351
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• 2008

Since the damage from the torrential rain increases recently due to climate change and global warming, the significance of flood forecasting and warning becomes important in medium and small streams as well as large river. Through the preprocess and main processes for estimating runoff, diverse errors occur and are accumulated, so that the outcome contains the errors in the existing flood forecasting and warning method. And estimating the parameters needed for runoff models requires a lot of data and the processes contain various uncertainty. In order to overcome the difficulties of the existing flood forecasting and warning system and the uncertainty problem, ANFIS(Adaptive Neuro-Fuzzy Inference System) technique has been presented in this study. ANFIS, a data driven model using the fuzzy inference theory with neural network, can forecast stream level only by using the precipitation and stream level data in catchment without using a lot of physical data that are necessary in existing physical model. Time series data for precipitation and stream level are used as input, and stream levels for t+1, t+2, and t+3 are forecasted with this model. The applicability and the appropriateness of the model is examined by actual rainfall and stream level data from 2003 to 2005 in the Tancheon catchment area. The results of applying ANFIS to the Tancheon catchment area for the actual data show that the stream level can be simulated without large error.

• Korean Journal of Agricultural Science
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• v.46 no.4
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• pp.843-856
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• 2019

Real-time flood prediction has an important role in significantly reducing potential damage caused by floods for urban residential areas located downstream of river basins. This paper presents an effective approach for flood forecasting based on the construction of a deep neural network (DNN) model. In addition, this research depends closely on the open-source software library, TensorFlow, which was developed by Google for machine and deep learning applications and research. The proposed model was applied to forecast the flowrate one, two, and three days in advance at the Son Tay hydrological station on the Red River, Vietnam. The input data of the model was a series of discharge data observed at five gauge stations on the Red River system, without requiring rainfall data, water levels and topographic characteristics. The research results indicate that the DNN model achieved a high performance for flood forecasting even though only a modest amount of data is required. When forecasting one and two days in advance, the Nash-Sutcliffe Efficiency (NSE) reached 0.993 and 0.938, respectively. The findings of this study suggest that the DNN model can be used to construct a real-time flood warning system on the Red River and for other river basins in Vietnam.

• Journal of Electrical Engineering and Technology
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• v.13 no.4
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• pp.1697-1704
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• 2018

As a key component of lighting location system (LLS) for lightning warning, the atmospheric electric field measuring is required to have high accuracy. The Conventional methods of the existent electric field measurement meter can only detect the vertical component of the atmospheric electric field, which cannot acquire the realistic electric field in the thunderstorm. This paper proposed a three dimensional (3D) electric field system for atmospheric electric field measurement, which is capable of three orthogonal directions in X, Y, Z, measuring. By analyzing the relationship between the electric field and the relative permittivity of ground surface, the permittivity is calculated, and an efficiency 3D measurement model is derived. On this basis, a three-dimensional electric field sensor and a permittivity sensor are adopted to detect the spatial electric field. Moreover, the elevation and azimuth of the detected target are calculated, which reveal the location information of the target. Experimental results show that the proposed 3D electric field meter has satisfactory sensitivity to the three components of electric field. Additionally, several observation results in the fair and thunderstorm weather have been presented.

• Korean Journal of Agricultural and Forest Meteorology
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• v.4 no.3
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• pp.133-140
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• 2002

Site-specific minimum temperature forecasts are critical in a short-term decision making procedure for preventive measures as well as a long-term strategy such as site selection in fruits industry. Nocturnal cold air pools frequently termed in mountainous areas under anticyclonic systems are very dangerous to the flowering buds in spring over Korea, but the spatial resolution to detect them exceeds the current weather forecast scale. To supplement the insufficient spatial resolution of official forecasts, we developed a GIS - assisted frost risk assesment scheme for using in mountainous areas. Daily minimum temperature data were obtained from 6 sites located in a 2.1 by 2.1 km area with complex topography near the southern edge of Sobaek mountains during radiative cooling nights in spring 2001. A digital elevation model with a 10 m spatial resolution was prepared for the entire study area and the cold air inflow was simulated for each grid cell by counting the number of surrounding cells coming into the processing cell. Primitive temperature surfaces were prepared for the corresponding dates by interpolating the Korea Meteorological Administration's automated observational data with the lapse rate correction. The cell temperature values corresponding to the 6 observation sites were extracted from the primitive temperature surface, and subtracted from the observed values to obtain the estimation error. The errors were regressed to the flow accumulation at the corresponding cells, delineating a statistically significant relationship. When we applied this relationship to the primitive temperature surfaces of frost nights during April 2002, there was a good agreement with the observations, showing a feasibility of site-specific frost warning system development in mountainous areas.

• The Journal of the Korea Contents Association
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• v.10 no.2
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• pp.81-88
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• 2010

This paper describes a development of next generation information remote retrieval and warning system that enables the user to make slope information retrieval remotely for a rockfall and landslide disaster reduction from mobile environments. And this system will be able to warn with a real-time stability condition about the slope which circumference are contiguous in standard user location. Slope information which provides to the user, become the service which upgrades from depth deep information directness will be able to confirm in order from field with applies multimedia style information which is various. In order to retrieve slope information with the wire and wireless internet from the remote place, we used mobile PC carrying is simple. Also this system attached GPS receiver to mobile PC in order to confirm user location as a real-time from the electronic map from field. Specially this system user location divide the safety of the slope which within the area where are fixed in the center are representative with 'safe area', 'collapse area' and 'collapse forecast area' etc. And to indicate with the icon of each other different color simultaneously in the electronic map. With like that reason, this system which sees the user even while moving safety condition about circumferential slope from the electronic map is having the strong point will be able to grasp with a real-time in one eye. Also warning message leads at the case real-time when the collapse will occur in specific slope, to inform to the user. Therefore this system which sees will be able to reduce the disaster which is caused by in landslide a very big strong point and has.

• Tribology and Lubricants
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• v.30 no.3
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• pp.156-167
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• 2014

This paper presents the test results of small dipstick-gage-type engine-oil-deterioration-detection sensor. The measured sensor signal characteristics for the capacitance and temperature are analyzed. The engine oil deterioration condition correlates with the electrical property of the dielectric constant that comprised with physical properties such as TAN (Total Acid Number), TBN (Total Base Number) and viscosity. Several problems encontered during the test of the sensor system are improved. The results of vehicle tests show that the capacitance signal is stable after the engine stops. Therefore, the sensor should start measuring the parameters for monitoring the engine oil condition after the engine stops. The engine is considered to be in a stopped state if the difference between the maximum and minimum values of the oil capacitance measured every 1 min is below 0.02 pF. The key test results in this paper will help in the development of an engine oil change warning algorithm.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.4
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• pp.655-662
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• 2011

SAR(Synthetic Aperture Radar) has the ability to generate high resolution images regardless of a weather condition(e.g. visibility good or poor and day or night, etc.). SAR is considered as one of the most important powers and needs for the future since it has been utilized in a number of important military fields such as early warning, urban defense, missile guidance system, etc. Additionally there are many civilian demands and applications in aviation, traffic control, earth and space explorations, weather forecast etc. This days, the ability to acquire and analyze information is needed to cope with the urgency of global politics and international changes. In this paper, technical survey and development review for SAR systems are investigated to derive the core and immature technologies of domestic defense industry.