• Journal of the Computational Structural Engineering Institute of Korea
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• v.21 no.3
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• pp.211-216
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• 2008

Recently a lot of researches have been conducted on the progressive collapse of structures which is the total collapse of structures initiated by localized damage. Most of the previous studies on the field of progressive collapse have followed deterministic approach without considering uncertainty involved in design variables, which results in unknown reliability of the analysis results. In this study the sensitivity analyses are carried out with design variables such as yield strength, live load, damping ratio, and elastic modulus on the vertical deflection of the joint from which a column is suddenly removed. The Monte Calro simulation, tornado diagram method, and the first order second moment method(FOSM) are applied for the sensitivity study. According to the nonlinear static analysis results, the vertical deflection is most affected by the variation of yield strength of beams. The nonlinear dynamic analyses show that the behaviour of model structures is highly sensitive to variation of the yield strength of beams and the structural damping ratio.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.25 no.2
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• pp.70-78
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• 2013

Plants which are having conditions of high temperature and pressure always are exposed to danger. In order to prevent unexpected accidents, safety management that can effectively and appropriately examine facilities is required in plant operation. RBI(Risk-Based Inspection) technology in API 581 is one of standard management technique for evaluating risk on petroleum plants. There are qualitative and quantitative assessments in RBI methodology. Quantitative evaluation step is complex and required much information, so high-risk facilities in plant are selected firstly by qualitative method. Qualitative RBI is performed by choosing the answer in prepared questionnaire. However, it is difficult to believe thoroughly results from survey including ambiguous information. In this study, the procedure of qualitative RBI analysis with considering probability distribution concept were proposed by using Monte Carlo simulation method in order to increase reliability in spite of uncertain factors. In addition, qualitative risk of cooling system for LNG plant was evaluated using proposed procedure. Although 20 items of total 39 assessment items are applied to uncertain factors, risk section of high probability(89%) were verified. The detailed results were described in manuscript.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.3
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• pp.55-63
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• 2012

Soil properties are not random values which is represented by mean and standard deviation but show spatial correlation. Especially, soils are highly variable in their properties and rarely homogeneous. Thus, the accuracy and reliability of probabilistic analysis results is decreased when using only one random variable as design parameter. In this paper, to consider spatial variability of soil property, one-dimensional random fields of coefficient of consolidation ($C_v$) were generated based on a Karhunen-Loeve expansion. A Latin hypercube Monte Calro simulation coupled with finite difference method for Terzaghi's one dimensional consolidation theory was then used to probabilistic analysis. The results show that the failure probability is smaller when consider spatial variability of $C_v$ than not considered and the failure probability increased when the autocorrelation distance increased. Thus, the uncertainty of soil can be overestimated when spatial variability of soil property is not considered, and therefore, to perform a more accurate probabilistic analysis, spatial variability of soil property needed to be considered.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.4
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• pp.392-397
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• 2014

Recently, there are many researches on active safety system of intelligent vehicle. To reduce the probability of collision caused by driver's inattention and mistakes, the active safety system gives warning or controls the vehicle toward avoiding collision. For the purpose, it is necessary to recognize and analyze circumstances around. In this paper, we will treat the problem about collision risk assessment. In general, it is difficult to calculate the collision risk before it happens. To consider the uncertainty of the situation, Monte Carlo simulation can be employed. However it takes long computation time and is not suitable for practice. In this paper, we apply neural networks to solve this problem. It efficiently computes the unseen data by training the results of Monte Carlo simulation. Furthermore, we propose the features affects the performance of the assessment. The proposed algorithm is verified by applications in various crash scenarios.

• Food Engineering Progress
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• v.13 no.1
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• pp.56-63
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• 2009

The aim of this study was to control the outbreak of food pathogen through quantitative microbial risk assessment (QMRA). We used Monte Calro Simulation (MCS) to predict contamination levels of Staphylococcus aureus on the raw materials, equipments and cook in Japanese restaurant located in Seoul. The result of sensitivity analysis showed that the most significant factor for the outbreak of food pathogen was consumption temperature and storage time. In shrimp and octopus sushi, 'consumption temperature' was the highest sensitivity value of 0.419 followed by 'storage time' of 0.374. To increase safety of sushi, consumers should have sushi as soon as possible after cooking. In sushi 'storage time after cooking' was determined as Critical Control Point (CCP). To determine Control Limit (CL), Scenario Analysis (SA) was carried out. In sushi, SA was carried out using storage time as a unit condition. Safety level of S. aureus was set lower than 5 log CFU/g. After 2 hr 'storage time' the number of S. aureus increased to 3.908 log CFU/g. Therefore, 'storage time' of sushi was set as CL in case of room temperature storage.

• The Journal of the Korea Contents Association
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• v.15 no.7
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• pp.282-288
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• 2015

A monte carlo simulation about shielding material and thickness of the syringe shield for radiation shield was performed. As a result of analysis, high atomic number materials such as tungsten, lead and bismuth have the highest shielding effect. However, $^{18}F$, $^{67}Ga$ and $^{111}In$ show high energy distribution in the region with thin shielding thickness. As the thickness of shielding materials increased, the energy distribution decreased due to reduction of ${\gamma}$-ray. In the case of low atomic number materials, they, showed energy distribution from highest to lowest, were barium sulfate, steel, stainless, iron and copper. Aluminum, plastic, concrete and water showed diverse aspect. they showed relatively high energy distribution because of increased ${\gamma}$-ray that penetrate the shield.

• Journal of the Korea institute for structural maintenance and inspection
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• v.14 no.5
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• pp.119-127
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• 2010

This paper provides a new approach for durability prediction of reinforced concrete structures exposed to carbonation. In this method, the prediction can be updated successively by a Bayes' theorem when additional data are available. The stochastic properties of model parameters are explicitly taken into account in the model. To simplify the procedure of the model, the probability of the durability limit is determined based on the samples obtained from the Latin Hypercube Sampling(LHS) technique. The new method may be very useful in design of important concrete structures and help to predict the remaining service life of existing concrete structures which have been monitored. For using the new method, in which the prior distribution is developed to represent the uncertainties of the carbonation velocity using data of concrete structures(3700 specimens) in Korea and the likelihood function is used to monitor in-situ data. The posterior distribution is obtained by combining a prior distribution and a likelihood function. Efficiency of the LHS technique for simulation was confirmed through a comparison between the LHS and the Monte Calro Simulation(MCS) technique.

• Progress in Medical Physics
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• v.20 no.4
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• pp.290-297
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• 2009

In case of radiation treatment using small field high-energy photon beams, an accurate dosimetry is a challenging task because of dosimetrically unfavorable phenomena such as dramatic changes of the dose at the field boundaries, dis-equilibrium of the electrons, and non-uniformity between the detector and the phantom materials. In this study, the absorbed dose in the phantom was measured by using an ion chamber and a diode detector widely used in clinics. $GAFCHROMIC^{(R)}$ EBT films composed of water equivalent materials was also evaluated as a small field detector and compared with ionchamber and diode detectors. The output factors at 10 cm depth of a solid phantom located 100 cm from the 6 MV linear accelerator (Varian, 6 EX) source were measured for 6 field sizes ($5{\times}5\;cm^2$, $2{\times}2\;cm^2$, $1.5{\times}1.5\;cm^2$, $1{\times}1\;cm^2$, $0.7{\times}0.7\;cm^2$ and $0.5{\times}0.5\;cm^2$). As a result, from $5{\times}5\;cm^2$ to $1.5{\times}1.5\;cm^2$ field sizes, absorbed doses from three detectors were accurately identified within 1%. Wheres, the ion chamber underestimated dose compared to other detectors in the field sizes less than $1{\times}1\;cm^2$. In order to correct the observed underestimation, a convolution method was employed to eliminate the volume averaging effect of an ion chamber. Finally, in $1{\times}1\;cm^2$ field the absorbed dose with a diode detector was about 3% higher than that with the EBT film while the dose with the ion chamber after volume correction was 1% lower. For $0.5{\times}0.5\;cm^2$ field, the dose with the diode detector was 1% larger than that with the EBT film while dose with volume corrected ionization chamber was 7% lower. In conclusion, the possibility of $GAFCHROMIC^{(R)}$ EBT film as an small field dosimeter was tested and further investigation will be proceed using Monte Calro simulation.