• Journal of the Architectural Institute of Korea Structure & Construction
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• v.34 no.2
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• pp.41-48
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• 2018

Carbonation is one of the major detrimental factors to the reinforced concrete structures owing to penetration of atmospheric CO2 through the micro pores, thereby it reduces the durability of the concrete. The maintenance periods and cost for concrete according to the coefficient variation of different finishing materials is documented in literature. However, it is required to carry out the systematic and well planned studies. Therefore, keeping them in mind, surface repair was carried out to the carbonated concrete and the maintenance cost was calculated to measure the durability life after repair with different variable. The deterministic and probabilistic methods were applied for durability and repair cost of the concrete. In the existing deterministic model, the cost of repair materials increases significantly when the concrete structure reaches its service life. In present study using a stochastic model, the maintenance period and cost was evaluated. According to obtained results, there was no significant difference in the number of maintenance of the coefficient variation. The initial durability has a great influence on the maintenance time and cost of the structure. Unlike the deterministic model, the probabilistic cost estimating model reduces the number of maintenance to the target service life expectancy.

• Nuclear Engineering and Technology
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• v.54 no.6
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• pp.2084-2093
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• 2022

Probabilistic safety assessment is widely used to quantify the risks of nuclear power plants and their uncertainties. When the lognormal distribution describes the uncertainties of basic events, the uncertainty of the top event in a fault tree is approximated with the sum of lognormal random variables after minimal cutsets are obtained, and rare-event approximation is applied. As handling complicated analytic expressions for the sum of lognormal random variables is challenging, several approximation methods, especially Monte Carlo simulation, are widely used in practice for uncertainty analysis. In this study, a theoretical approach for analyzing the sum of lognormal random variables using an efficient numerical integration method is proposed for uncertainty analysis in probability safety assessments. The change of variables from correlated random variables with a complicated region of integration to independent random variables with a unit hypercube region of integration is applied to obtain an efficient numerical integration. The theoretical advantages of the proposed method over other approximation methods are shown through a benchmark problem. The proposed method provides an accurate and efficient approach to calculate the uncertainty of the top event in probabilistic safety assessment when the uncertainties of basic events are described with lognormal random variables.

• Phonetics and Speech Sciences
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• v.15 no.1
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• pp.1-7
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• 2023

This study investigated the influences of probabilistic accessibility of the word being produced - as determined by its usage frequency and neighborhood density - on native and high-proficiency L2 speakers' realization of six English monophthong vowels. The native group hyperarticulated the vowels over an expanded acoustic space when the vowel occurred in words with low frequency and high density, supporting the claim that vowel forms are modified in accordance with the probabilistic accessibility of words. However, temporal expansion occurred in words with greater accessibility (i.e., with high frequency and low density) as an effect of low phonotactic probability in low-density words, particularly in attended speech. This suggests that temporal modification in the opposite direction may be part of the phonetic characteristics that are enhanced in communicatively driven focus realization. Conversely, none of these spectral and temporal patterns were found in the L2 group, thereby indicating that even the high-proficiency L2 speakers may not have developed experience-based sensitivity to the modulation of sub-categorical phonetic details indexed with word-level probabilistic information. The results are discussed with respect to how phonological representations are shaped in a word-specific manner for the sake of communicatively driven lexical intelligibility, and what factors may contribute to the lack of native-like sensitivity in L2 speech.

• Journal of Ocean Engineering and Technology
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• v.32 no.4
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• pp.215-221
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• 2018

In this study, the optimal design of a mooring system was carried out. Unlike almost all design methods, which are based on the deterministic method, this study focused on the probabilistic method. The probabilistic method, especially the design of experiment (DOE), could be a good way to cover some of the drawbacks of the deterministic approach. There various parameters for a mooring system, as widely known, including the weight, length, and stiffness of line. Scenarios for the mooring system parameters were produced using the Latin Hypercube Sampling method of the probabilistic approach. Next, a vessel-mooring system coupled analysis was performed in Orcaflex. A total of 50 scenarios were used in this study to optimize the initial design by means of a genetic algorithm. Finally, after determining the optimal process, a reliability analysis was performed to understand the system validity.

• Journal of Korean Society on Water Environment
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• v.25 no.4
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• pp.494-501
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• 2009

Probabilistic Ecological risk assessment (PERA) is extensive approach to qualify and quantify risk on the multi species based on species sensitivity distribution (SSD). As a while, deterministic ecological risk assessment (DERA) considers the comparison of predicted no-effect concentration (PNEC) and predicted exposure concentration (PEC). DERA is used to determine if there is potential risk or no risk, and it doesn't consider the nature variability and the species sensitivity. But PERA can be more realistic and reasonable approach to estimate likelihood or risk. In this study, we compared PERA used in developed countries, and proposed PERA applicable for the Korean water environment. Taxonomic groups were classified as "class" level including Actinopterygill, Branchiopoda, Chlorophyceae, Maxillapoda, Insects, Bivalvia, Gastropoda, Secernentea, Polychaeta, Monocotyldoneae, and Chanophyceae in this study. Statistical extrapolation method (SEM), statistical extrapolation method $_{acutechronicratio}$ ($SEM_{ACR}$) and assessment factor method (AFM) were used to calculate the ecological protective concentration based on qualitative and quantitative levels of taxonomic toxicity data. This study would be useful to establish the PERA for the protection of aquatic ecosystem in Korea.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2017.11a
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• pp.191-192
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• 2017

In response to the economic depression, the demand for fixed rent income has increased according to the easing construction regulations. it caused indiscriminated investment to stakeholders. This leads to oversupply in the multi-family Housing market and increases unsold housing and vacancy rates except specific area such as Gangnam-gu.In order to solve this issue, although studies on the optimization price of apartment houses has been conducted, the study is insufficient regarding on residential officetel. Therefore, the objective is to suggest a basic study on optimal price estimation model development by using probabilistic forecasting method in planning phase. To achieve the objective, first, variables are defined such as expenses, financial costs, income, etc. Second, causal loop diagram is suggested. Third, basic optimization prices estimation model is developed. In the future, this study can be used as one of decision making tools in planning phase of officetel development projects.

• Economic and Environmental Geology
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• v.41 no.6
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• pp.763-771
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• 2008

Uncertainties are pervasive in engineering geological problems. Therefore, the presence of uncertainties and their significance in analysis and design of slopes have been recognized. Since the uncertainties cannot be taken into account by the conventional deterministic approaches in slope stability analysis, the probabilistic analysis has been considered as the primary tool for representing uncertainties in mathematical models. However, some uncertainties are caused by incomplete information due to lack of information, and those uncertainties cannot be handled appropriately by the probabilistic approach. For those uncertainties, the theory of fuzzy sets is more appropriate. Therefore, in this study, fuzzy reliability analysis has been proposed in order to deal with the uncertainties which cannot be quantified in the probabilistic analysis due to the limited information. For the practical example, a slope is selected in this study and both the probabilistic analysis and the fuzzy reliability analysis have been carried out for planar failure. In the fuzzy reliability analysis, the dip angle and internal friction angle of discontinuity are considered as triangular fuzzy numbers since the random properties of the variables cannot be obtained completely under the conditions of limited information. In the study, the fuzzy reliability index and the probabilities of failure are evaluated from fuzzy arithmetic and compared to those from the probabilistic approach using Monte Carlo simulation and point estimate method. The analysis results show that the fuzzy reliability analysis is more appropriate for the condition that the uncertainties arise due to incomplete information.

• Journal of the Korea Institute of Building Construction
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• v.18 no.3
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• pp.295-303
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• 2018

In the DBB delivery system, the design stage and the construction stage are separated. Because of this, design changes frequently occur, and problems such as construction cost overrun, schedule delay, and quality deterioration happen as well. Recently, in the construction industry CM at Risk(CM@R) delivery system, which can systematically solve the above-mentioned problems of DBB delivery system, meet various demands of clients, and overcome the limited cost and period. In the CM@R delivery system, the contractor negotiates for a maximum guaranteed price(GMP) with the client at the design stage, and the CM performer carries out the construction within the GMP. However, uncertainties are inherent in the GMP calculation because the calculation is based on unfinished drawings and documents. In this study, a Probabilistic Earlier GMP Calculation Method by combining a probabilistic tool of Monte Carlo simulation with a case based reasoning is proposed so that the uncertainty in GMP calculation is reflected. After the earlier GMP is calculated, a process to calculate the $2^{nd}$ GMP at the time of around 80 % of detailed deign and to negotiate with the client to fix the final GMP is proposed. The Probabilistic Earlier GMP Calculation Method is verified through the case study. In this study, researchers set the range of GMP through the proposed probabilistic GMP calculation and tried to reduce the risk through negotiation between the client and the CM performer. The proposed method and process would contribute to the successful introduction of CM@R in Korea.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.4
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• pp.505-511
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• 2018

Long term capacity expansion planning has to be carried out to satisfy pre-defined system reliability criterion. For purpose of assessing system reliability, probabilistic simulation technique has been widely adopted. However, the way how to approximate generator outage, especially maintenance outage, in probabilistic simulation scheme can significantly influence on reliability assessment. Therefore, in this paper, 3 different maintenance approximation methods are applied to investigate the quantitative impact of maintenance approximation method on long term capacity expansion planning.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.731-739
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• 1998

The probabilistic relaxation(PR) scheme based on the conditional probability and probability space partition has the important property that when its compatibility coefficient matrix (CCM) has uniform components it can classify m-dimensional probabilistic distribution vectors into different classes. When consistency or inconsistency measures have been defined, the properties of PRs are completely determined by the compatibility coefficients among labels of labeled objects and influence weight among labeled objects. In this paper we study the properties of PR in which both compatibility coefficients and influence weights are uniform, and then a learning rule for such PR system is derived. Experiments have been performed to verify the effectiveness of the learning rule.