• Journal of The Korean Society For Urban Railway
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• v.6 no.4
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• pp.319-326
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• 2018

The safety interval to prevent collision between trains in a train control system is based on the braking distance according to the emergency braking of the train. The evaluation of the braking performance is based on the longitudinal train dynamics or the commissioning test in the test track, but since the conditions such as the weakening of the adhesion coefficient between the wheel and rail can not all be considered, these conventional methods are not sufficient to design of the train control systems. Therefore, in this study, the Monte Carlo Method (MCM) which can consider various environments is used to analyze braking performance and limitations. The braking model is based on the air braking used in the emergency braking and is modeled to take into account the braking pressure, efficiency, friction coefficient, adhesion condition, and vehicle mass distribution. It is confirmed that braking performance can be improved by controlling the quality of braking device. In addition, the change of the braking performance was confirmed according to the vehicle constituting the train. The results of this study are expected to be used as basic information for designing safety clearance for the train control systems and as a basis for improving the braking performance of railway vehicles.

• Geophysics and Geophysical Exploration
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• v.13 no.1
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• pp.80-87
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• 2010

This study was conducted to develop a reservoir modelling workflow to reproduce the heterogeneous distribution of effective permeability that impacts on the performance of SAGD (Steam Assisted Gravity Drainage), the in-situ bitumen recovery technique in the Athabasca Oil Sands. Lithologic facies distribution is the main cause of the heterogeneity in bitumen reservoirs in the study area. The target formation consists of sand with mudstone facies in a fluvial-to-estuary channel system, where the mudstone interrupts fluid flow and reduces effective permeability. In this study, the lithologic facies is classified into three classes having different characteristics of effective permeability, depending on the shapes of mudstones. The reservoir modelling workflow of this study consists of two main modules; facies modelling and permeability modelling. The facies modelling provides an identification of the three lithologic facies, using a stochastic approach, which mainly control the effective permeability. The permeability modelling populates mudstone volume fraction first, then transforms it into effective permeability. A series of flow simulations applied to mini-models of the lithologic facies obtains the transformation functions of the mudstone volume fraction into the effective permeability. Seismic data contribute to the facies modelling via providing prior probability of facies, which is incorporated in the facies models by geostatistical techniques. In particular, this study employs a probabilistic neural network utilising multiple seismic attributes in facies prediction that improves the prior probability of facies. The result of using the improved prior probability in facies modelling is compared to the conventional method using a single seismic attribute to demonstrate the improvement in the facies discrimination. Using P-wave velocity in combination with density in the multiple seismic attributes is the essence of the improved facies discrimination. This paper also discusses sand matrix porosity that makes P-wave velocity differ between the different facies in the study area, where the sand matrix porosity is uniquely evaluated using log-derived porosity, P-wave velocity and photographically-predicted mudstone volume.

• Geotechnical Engineering
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• v.7 no.2
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• pp.51-66
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• 1991

In the stability analysis of hillside slopes, the roots of vegetation have been considered to act as a soil reinforcement. In order to predict the amount of increase in soil shear resistance, produced by tensile strength of roots that intersect a potential slip surface in hillside slopes, new soil -root interaction models are proposed in this paper. For this purpose, firstly, laboratary teats and in-situ tests wert performed on soil-root systems, and experimental results were compared with a couple of soil-root interaction models which had been proposed by Gray, Waldron, and Wu etc. Based on this comparison, a new soil-root interaction model is proposed. Secondly, a probabilistic soil-root model is proposed based on statistical analysis considering random nature of root distribution, root characteristics, and soil-root interactions. Finally, to examine the effect of this root reinforcement system on stability of hillside slopes, a simple three-dimensional stability analysis was performed, and it was shown that root reinforcement had a significant stabilizing influence on shallow slips rather than deep slips in hillside slopes.

• Journal of the Korea Society for Simulation
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• v.21 no.2
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• pp.1-9
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• 2012

Subterranean termites forage by constructing tunnel networks in soil and encounter food resources during tunnel excavation. Some species of termites can travel up to 150 m underground. They often travel to the surface to find wood cellulose to feed their colony, which in turn causes extensive damage to wooden architecture, such as timber-frame houses. This type of damage has been constantly increasing along with global warming because higher temperatures provide an ecological niche for termites. The damage is closely related to termite territory size and distribution. Recently, as a way to research termite control, the necessity of a mathematical model to simulate termite territory formation in relation to damage has increased. So far, however, few studies have been conducted on the development of a model because it is difficult to quantify or characterize the relationship between territorial behavior and field conditions including complicated environmental factors. In the present study, we suggest a simulation model of the territoriality of the Formosan subterranean termites, Coptotermes formosanus (Shiraki), and Reticulitermes flavipes (Kollar), based on empirical data. The model consists of 2 procedures. One describes tunnel network growth for each colony, and the other represents territoriality based on tunnel-tunnel interactions between different colonies. Using the model, we show changes in territorial competition according to the termination probability of tunnel growth.

• Journal of Wetlands Research
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• v.21 no.1
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• pp.16-26
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• 2019

Wetlands that provide diverse ecosystem services, such as habitat provision and hydrological control of flora and fauna, constitute ecosystems through interaction between wetlands existing in a wetlandscape. Therefore, to evaluate the wetland functions such as resilience, it is necessary to analyze the ecological connectivity that is formed between wetlands which also show hydrologically dynamic behaviors. In this study, by defining wetlands as ecological nodes, we generated ecological networks through the connection of wetlands according to the dispersal model of wetland species. The characteristics of these networks were then analyzed using various network metrics. In the case of the dispersal based on a threshold distance, while a high local clustering is observed compared to the exponential dispersal kernel and heavy-tailed dispersal model, it showed a low efficiency in the movement between wetlands. On the other hand, in the case of the stochastic dispersion model, a low local clustering with high efficiency in the movement was observed. Our results confirmed that the ecological network characteristics are completely different depending on which dispersal model is chosen, and one should be careful on selecting the appropriate model for identifying network properties which highly affect the interpretation of network structure and function.

• Journal of Korean Society of Transportation
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• v.23 no.3 s.81
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• pp.95-108
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• 2005

The purpose of this study is to develop the ITS evaluation model using the Probabilistic Risk Analysis (PRA) methodology and to demonstrate the goodness-of-fit of the large ITS projects through the comparative analysis between DEA and PRA model. The results of this study are summarized below. First, the evaluation mode] using PRA with Monte-Carlo Simulation(MCS) and Latin-Hypercube Sampling(LHS) is developed and applied to one of ITS projects initiated by local government. The risk factors are categorized with cost, benefit and social-economic factors. Then, PDF(Probability Density Function) parameters of these factors are estimated. The log-normal distribution, beta distribution and triangular distribution are well fitted with the market and delivered price. The triangular and uniform distributions are valid in benefit data from the simulation analysis based on the several deployment scenarios. Second, the decision making rules for the risk analysis of projects for cost and economic feasibility study are suggested. The developed PRA model is applied for the Daejeon metropolitan ITS model deployment project to validate the model. The results of cost analysis shows that Deterministic Project Cost(DPC), Deterministic Total Project Cost(DTPC) is the biased percentile values of CDF produced by PRA model and this project need Contingency Budget(CB) because these values are turned out to be less than Target Value(TV;85% value), Also, this project has high risk of DTPC and DPC because the coefficient of variation(C.V) of DTPC and DPC are 4 and 15 which are less than that of DTPC(19-28) and DPC(22-107) in construction and transportation projects. The results of economic analysis shows that total system and subsystem of this project is in type II, which means the project is economically feasible with high risk. Third, the goodness-of-fit of PRA model is verified by comparing the differences of the results between PRA and DEA model. The difference of evaluation indices is up to 68% in maximum. Because of this, the deployment priority of ITS subsystems are changed in each mode1. In results. ITS evaluation model using PRA considering the project risk with the probability distribution is superior to DEA. It makes proper decision making and the risk factors estimated by PRA model can be controlled by risk management program suggested in this paper. Further research not only to build the database of deployment data but also to develop the methodologies estimating the ITS effects with PRA model is needed to broaden the usage of PRA model for the evaluation of ITS projects.

• Journal of the Korean GEO-environmental Society
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• v.13 no.12
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• pp.91-98
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• 2012

In this paper, the behavior of offshore wind turbine(OWT) foundation which is modeled by using existing design method and FEM is compared. When the same type of foundation is designed under the same sea and ground condition, the behavior characteristics with each model are compared. As a result, the member forces between apparent fixity and distributed spring type foundation which consider the ground stiffness are not different markedly, while fixed-base type foundation shows relatively lower member forces, which results in smaller safety margin. In other words, considering ground stiffness is reasonable because soil-pile interaction affects significantly on the analysis result. A case study with a monopile shows significant errors between p-y and FEM model at the head and tip of the pile. Also, it shows that the errors at the tip with diameter increase of the pile is larger. Thus, considering ground characteristics and engineering judgment are necessary in practice. A comparison of reliability analysis between tripod and monopile type foundation on the same condition shows larger probability of failure in monopile type and it indicates that the safety margin of monopile type can be lower.

• Journal of KIISE:Software and Applications
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• v.29 no.3
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• pp.167-179
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• 2002

In this paper, we propose a new acoustic model for characterizing segmental features and an algorithm based upon a general framework of hidden Markov models (HMMs) in order to compensate the weakness of HMM assumptions. The segmental features are represented as a trajectory of observed vector sequences by a polynomial regression function because the single frame feature cannot represent the temporal dynamics of speech signals effectively. To apply the segmental features to pattern classification, we adopted segmental HMM(SHMM) which is known as the effective method to represent the trend of speech signals. SHMM separates observation probability of the given state into extra- and intra-segmental variations that show the long-term and short-term variabilities, respectively. To consider the segmental characteristics in acoustic model, we present segmental-feature HMM(SFHMM) by modifying the SHMM. The SFHMM therefore represents the external- and internal-variation as the observation probability of the trajectory in a given state and trajectory estimation error for the given segment, respectively. We conducted several experiments on the TIMIT database to establish the effectiveness of the proposed method and the characteristics of the segmental features. From the experimental results, we conclude that the proposed method is valuable, if its number of parameters is greater than that of conventional HMM, in the flexible and informative feature representation and the performance improvement.

• The Journal of the Acoustical Society of Korea
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• v.40 no.5
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• pp.530-536
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• 2021

Recently, due to the development of deep learning, end-to-end speech recognition, which directly maps graphemes to speech signals, shows good performance. Especially, among the end-to-end models, conformer shows the best performance. However end-to-end models only focuses on the probability of which grapheme will appear at the time. The decoding process uses a greedy search or beam search. This decoding method is easily affected by the final probability output by the model. In addition, the end-to-end models cannot use external pronunciation and language information due to structual problem. Therefore, in this paper conformer with lexicon transducer is proposed. We compare phoneme-based model with lexicon transducer and grapheme-based model with beam search. Test set is consist of words that do not appear in training data. The grapheme-based conformer with beam search shows 3.8 % of CER. The phoneme-based conformer with lexicon transducer shows 3.4 % of CER.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.2A
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• pp.119-127
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• 2006

In this two-part paper, we consider dynamic resource allocation in orthogonal frequency division multiple access(OFDMA). To reduce the reverse link overhead for channel quality information(CQI) feedback, a set of sub-carriers are tied up to a sub-channel to be used as the unit of CQI feedback, user-multiplexing and the corresponding power/rate allocation. Specifically, we focus on two sub-channel structures, either aggregated or distributed, where the SNR distribution over a sub-channel is modeled as Ricean in general, and the channel quality of a sub-channel is summarized as the mean and variance of channel gain envelop divided by noise standard deviation. Then, we develop a generalized two step channel/resource allocation algorithm, which uses the two statistical measurements, and analyze the spectral efficiency of the OFDMA system in terms of average frequency utilization. An extension to proportional fair algorithm will also be addressed. As confirmed by numerical results, the aggregated structure is preferred especially when intending aggressive link adaptation.