• Earthquakes and Structures
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• v.7 no.1
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• pp.17-38
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• 2014

As the desire for high performance buildings increases, it is increasingly evident that engineers require reliable methods for the estimation of seismic demands on both structural and non-structural components. To this extent, improved tools for the prediction of floor spectra would assist in the assessment of acceleration sensitive non-structural and secondary components. Recently, a new procedure was successfully developed and tested for the simplified construction of floor spectra, at various levels of elastic damping, atop single-degree-of-freedom structures. This paper extends the methodology to multi-degree-of-freedom (MDOF) supporting systems responding in the elastic range, proposing a simplified modal combination approach for floor spectra over upper storeys and accounting for the limited filtering of the ground motion input that occurs over lower storeys. The procedure is tested numerically by comparing predictions with floor spectra obtained from time-history analyses of RC wall structures of 2- to 20-storeys in height. Results demonstrate that the method performs well for MDOF systems responding in the elastic range. Future research should further develop the approach to permit the prediction of floor spectra in MDOF systems that respond in the inelastic range.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2011.11a
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• pp.20-27
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• 2011

A system for fine-resolution long-range weather forecast is introduced in this study. The system is basically consisted of a global-scale coupled general circulation model (CGCM) and Weather Research and Forecast (WRF) regional model. The system makes use of a data assimilation method in order to reduce the initial shock or drift that occurs at the beginning of coupling due to imbalance between model dynamics and observed initial condition. The long-range predictions are produced in the system based on a non-linear ensemble method. At the same time, the model bias are eliminated by estimating the difference between hindcast model climate and observation. In this research, the predictability of the forecast system is studied, and it is illustrated that the system can be effectively used for the high resolution long-term weather prediction. Also, using the system, fine-resolution climatological data has been produced with high degree of accuracy. It is proved that the production of agrometeorological variables that are not intensively observed are also possible.

• Journal of Ship and Ocean Technology
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• v.9 no.4
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• pp.23-34
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• 2005

Increased usage of AUVs has led to the development of alternative navigational methods that use the acoustic beacons and dead reckoning. This paper describes a concurrent mapping and localization (CML) scheme that uses range sonars mounted on SNUUV­I, which is a small test AUV developed by Seoul National University. The CML is one of such alternative navigation methods for measuring the environment that the vehicle is passing through. In addition, it is intended to provide relative position of AUV by processing the data from sonar measurements. A technique for CML algorithm which uses several ranging sonars is presented. This technique utilizes an extended Kalman filter to estimate the location of the AUV. In order for the algorithm to work efficiently, the nearest neighbor standard filter is introduced as the algorithm of data association in the CML for associating the stored targets the sonar returns at each time step. The proposed CML algorithm is tested by simulations under various conditions. Experiments in a towing tank for one dimensional navigation are conducted and the results are presented. The results of the simulation and experiment show that the proposed CML algorithm is capable of estimating the position of the vehicle and the object and demonstrates that the algorithm will perform well in the real environment.

• Nuclear Engineering and Technology
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• v.56 no.4
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• pp.1398-1406
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• 2024

The control rod worth is a key safety parameter required to be measured in commercial pressurized water reactors (PWRs). Conventionally, the control rod worth is measured after reaching the critical state, which occupies the considerable time in the zero-power physics test. In this study, an efficient control-rod worth measurement technique has been proposed based on the improved neutron-source multiplication method, which can be implemented with the source-range detector count rates in the subcritical states. Moreover, the noise reduction technique has been adopted to smooth the large fluctuation existing in the original signals. In order to verify the engineering performance of the proposed measurement technique, the measured source-range detector count rates during the rod withdrawal process before reaching critical state in a CNP1000 reactor have been employed. It demonstrated that almost all estimated results of control rod worth satisfy the engineering acceptance criteria, except one control rod with the relative difference over 10 %, which indicates the capability of the proposed method in estimating control rod worth.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.24 no.12
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• pp.1173-1180
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• 2013

High Resolution Range Profile-Jet Engine Modulation imagery first introduced in 2005 carries out radar target recognition by localizing the position of the jet engine installed on the aircraft target. This paper presents a new approach for estimating the jet engine position in the HRRP-JEM image based on the eccentricity of a complex signal. It can effectively evaluate the contribution of the JEM component to the radar received signal in a range bin of the HRRP-JEM image. Therefore, the localization is expected to be performed more quantitatively and reliably by pinpointing the range bin corresponding to the jet engine position where the JEM contribution is maximized. The simulation results of realistic aircraft models validated the effectiveness of the proposed concept.

• Journal of Advanced Navigation Technology
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• v.21 no.5
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• pp.435-442
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• 2017

The runway visual range affected by fog and so on is one of the important indicators to determine whether aircraft can take off and land at the airport or not. In the case of airports where transportation airplanes are operated, major weather forecasts including the runway visual range for local area have been released and provided to aviation workers for recognizing that. This paper proposes a runway visual range estimation model with a deep neural network applied recently to various fields such as image processing, speech recognition, natural language processing, etc. It is developed and implemented for estimating a runway visual range of local airport with a deep neural network. It utilizes the past actual weather observation data of the applied airfield for constituting the learning of the neural network. It can show comparatively the accurate estimation result when it compares the results with the existing observation data. The proposed model can be used to generate weather information on the airfield for which no other forecasting function is available.

• Journal of Ecology and Environment
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• v.45 no.3
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• pp.130-142
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• 2021

Background: Climate change is occurring rapidly around the world, and is predicted to have a large impact on biodiversity. Various studies have shown that climate change can alter the geographical distribution of wild bees. As climate change affects the species distribution and causes range shift, the degree of range shift and the quality of the habitats are becoming more important for securing the species diversity. In addition, those pollinator insects are contributing not only to shaping the natural ecosystem but also to increased crop production. The distributional and habitat quality changes of wild bees are of utmost importance in the climate change era. This study aims to investigate the impact of climate change on distributional and habitat quality changes of five wild bees in northwestern regions of Iran under two representative concentration pathway scenarios (RCP 4.5 and RCP 8.5). We used species distribution models to predict the potential range shift of these species in the year 2070. Result: The effects of climate change on different species are different, and the increase in temperature mainly expands the distribution ranges of wild bees, except for one species that is estimated to have a reduced potential range. Therefore, the increase in temperature would force wild bees to shift to higher latitudes. There was also significant uncertainty in the use of different models and the number of environmental layers employed in the modeling of habitat suitability. Conclusion: The increase in temperature caused the expansion of species distribution and wider areas would be available to the studied species in the future. However, not all of this possible range may include high-quality habitats, and wild bees may limit their niche to suitable habitats. On the other hand, the movement of species to higher latitudes will cause a mismatch between farms and suitable areas for wild bees, and as a result, farmers will face a shortage of pollination from wild bees. We suggest that farmers in these areas be aware of the effects of climate change on agricultural production and consider the use of managed bees in the future.

• The Journal of the Acoustical Society of Korea
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• v.42 no.6
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• pp.511-518
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• 2023

Accurate ranging is one of the key factors in the test and evaluation process of underwater vehicles. In particular, when estimating range using Time of Arrival (ToA) values, signals such as Linear Frequency Modulation (LFM), a chirp signal, are highly applicable due to their correlated nature. However, in a Doppler shift environment with mobility, measurement errors may occur due to the range-Doppler coupling effect. In this paper, we propose a signal that compensates for the distance-Doppler coupling effect to reduce the measurement error of the arrival time value. The proposed signal is constructed by superimposing two types of LFM signals, and the range-Doppler coupling effect can be minimized. Through simulations, it is confirmed that the proposed signal is a way to compensate for the distance-Doppler coupling effect in the distance estimation of underwater mobile bodies, reducing the measurement error of the arrival time value.

• The Journal of the Acoustical Society of Korea
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• v.25 no.6
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• pp.305-311
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• 2006

In this paper the performance of a array invariant method is evaluated for source-range estimation in horizontally stratified shallow water ocean waveguide. The method has advantage of little computationally effort over existing source-localization methods. such as matched field processing or the waveguide invariant and array gain is fully exploited. And. no knowledge of the environment is required except that the received field should not be dominated by purely interference This simple and instantaneous method is applied to simulated acoustic propagation filed for testing range estimation performance. The result of range estimation according to the SNR for the underwater impulsive source with broadband spectrum is demonstrated. The spatial smoothing method is applied to suppress the effect of mutipath propagation by high frequency signal. The result of performance test for range estimation shows that the error rate is within 20% at the SNR above 10dB.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.7B
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• pp.595-605
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• 2012

DV-Hop is one of the well known range-free localization algorithms. The algorithm works well in case of isotropic network since the sensor and anchor nodes are placed in the entire area. However, it results in large errors in case of anisotropic networks where the hop count between nodes is not linearly proportional to the Euclidean distance between them. Hence, we proposed a novel range-free algorithm for anisotropic networks to improve the localization accuracy. In the paper, the Euclidean distance between anchor node and unknown node is estimated by the average hop distance calculated at each hop count with hop count and distance information between anchor nodes. By estimating the unknown location of nodes with the estimated distance estimated by the average hop distance calculated at each hop, the localization accuracy is improved. Simulation results show that the proposed algorithm has more accuracy than DV-Hop.