• Journal of the Korean Society of Safety
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• v.33 no.5
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• pp.28-34
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• 2018

Recently, various engineering approaches have been widely used in the accident investigation field to identify the cause of the accident and to predict damage by accident. Computational analysis is the most commonly used method of accident investigation technique. This technique is mainly used to identify the mechanism of the accident generation and to determine the cause when it is difficult to reproduce the situation at the time of the accident or when it is impossible to perform a reproduction experiment. In this study, The computational fluid dynamics analysis for nitrogen asphyxiation accident generated by defect of building structural between diffusion outlet and cooling tower was performed to determine the inflow path of the suffocation gas, death possibility by concentration of suffocation gas and predicted the time of death due to the accident using 3D modeling and FLACS program. We can quantify diffusion concentration of asphyxiation gas and predict mechanism of death occurrence by accident and evaluate the consequence Analysis through this study. In the future, This method can be widely used in the field of gas safety by improving the reliability and validity of the analysis.

• Journal of the Korean Institute of Gas
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• v.18 no.3
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• pp.67-74
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• 2014

Buried natural gas pipelines in densely populated urban areas have serious hazards of property damages and casualties generated by release, dispersion, fire and explosion of gas caused by outside or inside failures. So as to prevent any accident in advance, managers implement danger management based on quantitative risk analysis. In order to evaluate quantitative risk about buried natural gas pipelines, we need calculation for radiant heat and pressure wave caused by calculation for release rate of chemical material, dispersion analysis, fire or explosion modeling through consequence analysis in priority, in this paper, we carry out calculation for release rate of pressured natural gas, radiant heat of fireball based in accident scenario of actual "San Bruno" buried high pressured pipelines through models which CCPS, TNO provide and compare with an actual damage result.

• Journal of the Society of Naval Architects of Korea
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• v.55 no.3
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• pp.215-221
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• 2018

The structural design of offshore installations against explosions has been required to protect vital areas (e.g. control room, worker's area etc.) and minimize the damage from explosion accidents. Because the explosion accident will not only result in significant casualties and economic losses, but also cause serious pollution and damage to surrounding environment and coastal marine ecosystems. Over the past two decades, an incredible efforts was made to develop reliable methods to reduce and manage the explosion risk. Among the methods Quantitative Risk Assessment and Management (QRA&M) is the one of cutting-edge technologies. The explosion risk can be quantitatively assessed by the product of explosion frequency based on probability calculation and consequence analyzed using computer simulations, namely Computational Fluid Dynamics (CFD) and Finite Element Analysis (FEA). However to obtain reliable consequence analysis results by CFD and FEA, uncertainties associate with modeling and simulation are needed to be identified and validated by comparison with experimental data. Therefore, large-scaled explosion test procedure is developed in this study. And developed test procedure can be helpful to obtain precious test data for the validation of consequence analysis using computer simulations, and subsequently allow better assessment and management of explosion risks.

• Proceedings of the KIEE Conference
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• 1990.11a
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• pp.417-420
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• 1990

The conventional quantitative techniques of system analysis are intrinsically unsuited for dealing with humanistic systems. Therefore, the rule based modeling of fuzzy linguistic type has been developed for the analysis of humanistic systems and complex systems and it is very significant for analysis and design of fuzzy logic controller. The activated sludge process is a commonly used method for treating sewage and waste waters. A mathematical tool to build a fuzzy model of the activated sludge process where fuzzy implications and linear reasoning are used is presented in here. A root-mean square error is used as the criterion of the fuzzy model's adequacy to the A.S.P. and the least square method is used for the identification of optimum consequence parameters. A method of modeling of the activated sludge process using its input-output data and simulation results for its application are shown.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.701-706
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• 1998

A design method of rule -based fuzzy modeling is presented for the model identification of complex and nonlinear systems. The proposed rule-based fuzzy modeling implements system structure and parameter identification in the efficient form of " IF..., THEN,," statements. using the theories of optimization and linguistic fuzzy implication rules. The improved complex method, which is a powerful auto-tuning algorithm, is used for tuning of parameters of the premise membership functions in consideration of the overall structure of fuzzy rules. The optimized objective function, including the weighting factors, is auto-tuned for better performance of fuzzy model using training data and testing data. According to the adjustment of each weighting factor of training and testing data, we can construct the optimal fuzzy model from the objective function. The least square method is utilized for the identification of optimum consequence parameters. Gas furance and a sewage treatment proce s are used to evaluate the performance of the proposed rule-based fuzzy modeling.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.2
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• pp.96-105
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• 1997

In this paper, A new design method of fuzzy modeling is presented for the model identification of nonlinear complex systems. The proposed FPNN(Fuzzy Polynomial Neural Network) modeling implements system structure and parameter identification using GMDH(Group Method of Data Handling) method and linguistic fuzzy implication rules from input and output data of processes. In order to identify premise structure and parameter of fuzzy implication rules, GMDH method and regression polynomial fuzzy reasoning method are used and the least square method is utilized for the identification of optimum consequence parameters. Time series data for gas furnace and those for wastewater treatment process are used for the purpose of evaluating the performance of the proposed FPNN modeling. The results show that the proposed method can produce the fuzzy model with higher accuracy than other works achieved previously.

• Journal of the Korea Safety Management & Science
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• v.11 no.2
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• pp.77-85
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• 2009

Considering heat insulation and beautiful sight of construction, making use of exterior panels is increasing. Recently the exterior panels now are weak very much, and so in consequence of the weakness fire spreads rapidly. Compared with internal fire, external vertical fire spread rate goes rapidly and it is extensive in spread range, therefore it is dangerous very much. Accordingly, under present condition of poor standard of exterior panels, it is required to take measure to meet the appropriate situation. In this study, by making use of FDS(Fire Dynamic Simulation) program about external vertical fire of high rise building, fire behavior is searched by computer. It is important that realizing by computer fire modeling about external vertical fire must be included certainly in procedure of fire performance design in the future. In modeling program, FDS version 5 is available, and aluminium composite panel is applied in external panels. In this study, for realizing of actual fire condition, FDS is applied by details of fire scenarios considering influence of wind.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.4
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• pp.692-700
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• 2017

In this paper, we propose the structural design of Interval Type-2 FCM based RBFNN. Proposed model consists of three modules such as condition, conclusion and inference parts. In the condition part, Interval Type-2 FCM clustering which is extended from FCM clustering is used. In the conclusion part, the parameter coefficients of the consequence part are estimated through LSE(Least Square Estimation) and WLSE(Weighted Least Square Estimation). In the inference part, final model outputs are acquired by fuzzy inference method from linear combination of both polynomial and activation level obtained through Interval Type-2 FCM and acquired activation level through Interval Type-2 FCM. Additionally, The several parameters for the proposed model are identified by using differential evolution. Final model outputs obtained through benchmark data are shown and also compared with other already studied models' performance. The proposed algorithm is performed by using Iris and Vehicle data for pattern classification. For the validation of regression problem modeling performance, modeling experiments are carried out by using MPG and Boston Housing data.

• Korean Journal of Construction Engineering and Management
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• v.10 no.2
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• pp.145-154
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• 2009

For developing an Automation equipment in construction, it is a key issue to develop 3D modeling technology which can be used for automatically recognizing environmental objects. Recently, for the development of "Intelligent Excavating System(IES), a research developing the real-time 3D terrain modeling technology has been implemented from 2006 in Korea and a stereo vision system is selected as the optimum technology. However, as a result of performance tests implemented in various earth moving environment, the 3D images obtained by stereo vision included considerable noise. Therefore, in this study, for getting rid of the noise which is necessarily generated in stereo image matching, the noise elimination algorithm of stereo-vision images for 3D terrain modeling was developed. The consequence of this study is expected to be applicable in developing an automation equipments which are used in field environment.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.6_1
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• pp.575-581
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• 2012

In general, various modeling and estimation techniques have been proposed to extract the tropospheric and ionospheric delays from the GPS CORS. In this study, Kalman filter approach is adopted to estimate the tropospheric and ionospheric delays and the proper modeling for the state vector and the variance-covariance matrix for the process noises are performed. The coordinates of reference stations and the zenith wet delays are estimated with the assumption of random walk stochastic process. Also, the first-order Gauss-Markov stochastic process is applied to compute the ionospheric effects. For the evaluation of the proposed modeling technique, Kalman filter algorithm is implemented and the numerical test is performed with the CORS data. The results show that the atmospheric effects can be estimated successfully and, as a consequence, can be used for the generation of VRS data.