• Atmosphere
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• 제20권3호
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• pp.287-306
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• 2010

An ensemble Kalman filter (EnKF) with Weather Research and Forecasting (WRF) Model is applied for Typhoon Wukong (200610) to investigate the performance of ensemble forecasts depending on experimental configurations of the EnKF. In addition, the ensemble sensitivity analysis is applied to the forecast and analysis ensembles generated in EnKF, to investigate the possibility of using the ensemble sensitivity analysis as the adaptive observation guidance. Various experimental configurations are tested by changing model error, ensemble size, assimilation time window, covariance relaxation, and covariance localization in EnKF. First of all, experiments using different physical parameterization scheme for each ensemble member show less root mean square error compared to those using single physics for all the forecast ensemble members, which implies that considering the model error is beneficial to get better forecasts. A larger number of ensembles are also beneficial than a smaller number of ensembles. For the assimilation time window, the experiment using less frequent window shows better results than that using more frequent window, which is associated with the availability of observational data in this study. Therefore, incorporating model error, larger ensemble size, and less frequent assimilation window into the EnKF is beneficial to get better prediction of Typhoon Wukong (200610). The covariance relaxation and localization are relatively less beneficial to the forecasts compared to those factors mentioned above. The ensemble sensitivity analysis shows that the sensitive regions for adaptive observations can be determined by the sensitivity of the forecast measure of interest to the initial ensembles. In addition, the sensitivities calculated by the ensemble sensitivity analysis can be explained by dynamical relationships established among wind, temperature, and pressure.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• 제9권4호
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• pp.504-516
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• 1997

Recently scientists and engineers are developing a system to get waste heat of low-temperature level with advanced heat pump, which have not been used up to now. As the reason, it is necessary to examine capability of using waste heat which is raised up in the tunnel of subway out of widely distributed low-temperature waste heat in large cities. Therefore we surveyed thermal environment of the tunnel of subway in $S\check{o}my\check{o}n$, downtown of Pusan, from November 1995 to December 1996 and developed a program to predict the thermal environment of subway on the basis of experimental data and the geometries of tunnels. This paper has proved availability of waste heat of subway when the measured results obtained in subway in the winter time and the simulated results of thermal environment prediction program are compared, as well as has reported results of estimating reliability of the simulation program. As the result, the charateristics of thermal environment in the tunnel of subway in $S\check{o}my\check{o}n$ station in the winter time are to be followed; 1) temperature in the tunnel is about $10^{\circ}C$ higher than outside air temperature, 2) temperature change in the tunnel is less than that in the platform so that we may obtain stable heat source, 3) and when the measured results obtained in subway in the winter time and the simulated results of thermal environment prodiction program is compared, both results show similar tendency. Therefore, we confirm estimating reliability of the simulation program.

• Journal of the Society of Naval Architects of Korea
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• 제35권4호
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• pp.19-26
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• 1998

In this paper, we studied the Similar Ship(SS) concept[1,2] as a method to an experimental and semi-emperical approach for the estimation of hull hydrodynamic forces and hull-propeller-rudder interaction coefficients and used these methods to predict ship's manoeuvrability. The SS concept is adopted to use experimental data of prototype ships for manoeuvrability prediction of a new ship. The SS concept is composed of the key components as follows: existence of experimental data about prototype ship, availability of semi-emperical method for estimating the changes of hull force, a method to correct the prototype ship data. On the basis of these concepts, we attempted to simulate manoeuvrability at ballast and scantling draft conditions by making use of experimental data at full load draft condition and to simulate manoeuvrability of new ships by making use of experimental data for prototype. From present calculation, it was found that the present method can predict the ship's manoeuvrability accurately at early design stage.

• Journal of the Society of Naval Architects of Korea
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• 제57권1호
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• pp.35-44
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• 2020

Propeller cavitation extent, pressure fluctuation induced by cavitation, pressure distribution on propeller blade, total velocity distribution and nominal wake distribution for a MR Taker were computed in both conditions of model test and sea trial using a code STAR-CCM⁺. Then some of the results were compared with model test data at LCT and full-scale measurement (Ahn et al (2014); Kim et al (2014)] in order to confirm the availability of a numerical prediction method and to get the physical insight of local flow around a ship and propeller. The nominal wake distributions computed and measured by LDV velocimeter on the variation of on-coming velocity show the wake contraction characteristics proposed by Hoekstra (1974). The numerical prediction of propeller cavitation extent on a blade angular position and pressure fluctuation level on each location of pressure sensors are very similar with the experimental results.

• Tunnel and Underground Space
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• 제31권1호
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• pp.25-40
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• 2021

As the era of Industry 4.0 arrives, the researches using artificial intelligence in the field of rock engineering as well have increased. For a better understanding and availability of AI, this paper analyzed the types of algorithms and how to apply them to the research papers where AI is applied among domestic and international studies related to tunnels, blasting and mines that are major objects in which rock engineering techniques are applied. The analysis results show that the main specific fields in which AI is applied are rock mass classification and prediction of TBM advance rate as well as geological condition ahead of TBM in a tunnel field, prediction of fragmentation and flyrock in a blasting field, and the evaluation of subsidence risk in abandoned mines. Of various AI algorithms, an artificial neural network is overwhelmingly applied among investigated fields. To enhance the credibility and accuracy of a study result, an accurate and thorough understanding on AI algorithms that a researcher wants to use is essential, and it is expected that to solve various problems in the rock engineering fields which have difficulty in approaching or analyzing at present, research ideas using not only machine learning but also deep learning such as CNN or RNN will increase.

• Journal of Aerospace System Engineering
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• 제15권3호
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• pp.30-44
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• 2021

Experimental investigation of counter-rotating propellers is subject to multiple time and cost constraint because of additional design parameters unlike single propeller. Also, a lot of computing time and resources are required for numerical analysis due to consideration of the interference between the upper and lower propellers. In the present study, numerical simulations were conducted to investigate the hover performance of counter-rotating propellers by using actuator method which is considered to be time-efficient. The accuracy of the present numerical methods was validated by comparing the ANSYS Fluent which is commercial CFD code. The axial spacing and rotational speed were selected as the analysis variables, and the aerodynamic performance was obtained under various conditions. Based on the obtained results, the Figure of Merit (FM) of single propeller and counter-rotating propellers and a prediction factor which enables prediction of counter-rotating propeller performance using a single propeller were derived to evaluate availability of the actuator method.

• Journal of KIISE:Information Networking
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• 제29권4호
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• pp.412-427
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• 2002

This paper proposes a restoration scheme based on mobility learning and prediction in the presence of the failure of mobility databases in mobile communication systems. In mobile communication systems, mobility databases must maintain the current location information of users to provide a fast connection for them. However, the failure of mobility databases may cause some location information to be lost. As a result, without an explicit restoration procedure, incoming calls to users may be rejected. Therefore, an explicit restoration scheme against the failure of mobility databases is needed to guarantee continuous service availability to users. Introducing mobility learning and prediction into the restoration process allows systems to locate users after a failure of mobility databases. In failure-free operations, the movement patterns of users are learned by a Neuro-Fuzzy Inference System (NFIS). After a failure, an inference process of the NFIS is initiated and the users' future location is predicted. This is used to locate lost users after a failure. This proposal differs from previous approaches using checkpoint because it does not need a backup process nor additional storage space to store checkpoint information. In addition, simulations show that our proposal can reduce the cost needed to restore the location records of lost users after a failure when compared to the checkpointing scheme

• Asian-Australasian Journal of Animal Sciences
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• 제11권5호
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• pp.620-633
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• 1998

Methods developed for measuring digestibility and availability of amino acids in feedstuffs used in pig nutrition are reviewed. Digestibility is a proportion of an amino acid in a feed that is absorbed from the digestive tract and should be determined from the difference between the amount of amino acid consumed and passing the distal ileum. Techniques for ileal digesta sampling including various types of cannulas: a re-entrant, T-piece, IPV, IPVC and ileaorectal anastomosis are described and comparisons amongst these methods are presented. Other methodologies like mobile bag technique, in vitro assays and mathematical prediction method are also described. Significance and methodologies for measurement of endogenous nitrogen and amino acids losses at the distal ileum and their effect on the apparent and true nitrogen and amino acid digestibilities in feeds are discussed. Factors influencing the apparent and true amino acid digestibilities such as dry matter intake, protein, fibre and antinutritive compounds content in the diet are discussed. Amino acid bioavailability -the proportion of the total amino acid digested and absorbed in a form utilized in metabolism - measured by the growth assay may differ from its ileal digestibility. Chemical methods for determination of available lysine content in heat treated feeds are evaluated.

• Journal of the Korean GEO-environmental Society
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• 제3권4호
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• pp.11-17
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• 2002

The purpose of this study is the prediction of pollutant loads into Seomjin river watershed using neural networks model. The pollutant loads into river watershed depend upon the water quantity of inflow from the upstream as well as the water quality of the inflow into the river. For the estimation of pollutants into river, a neural networks model which has the features of multi-layered structure and parallel multi-connections is used. The used water quality parameters are BOD, COD and SS into Seomjin river. The results of calibration are satisfactory, and proved the availability of a proposed neural networks model to estimate short-term water quality pollutants into river system.

• Computers and Concrete
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• 제8권5호
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• pp.597-616
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• 2011

With respect to rehabilitation, strengthening and retrofitting of existing and deteriorated columns in buildings and bridges, CFRP sheets have been found effective in enhancing the performance of existing RC columns by wrapping and bonding CFRP sheets externally around the concrete. Concrete columns and piers that are confined by both lateral steel reinforcement and CFRP are sometimes referred to as "hybrid" concrete columns. With the availability of experimental data on concrete columns confined by steel reinforcement and/or CFRP, the study presents modeling using artificial neural networks (ANNs) to predict the compressive strength of hybrid circular RC columns. The prediction of the ultimate confined compressive strength of RC columns is very important especially when this value is used in estimating the capacity of structures. The present ANN model used as parameters for the confining materials the lateral steel ratio (${\rho}_s$) and the FRP volumetric ratio (${\rho}_{FRP}$). The model gave good predictions for three types of confined columns: (a) columns confined with steel reinforcement only, (b) CFRP confined columns, and (c) hybrid columns confined by both steel and CFRP. The model may be used for predicting the compressive strength of existing circular RC columns confined with steel only that will be strengthened or retrofitted using CFRP.