• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.41 no.8
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• pp.619-624
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• 2013

To predict the probabilistic service life, statistical factors should be included to consider the uncertainty of parameters. Generally the probabilistic analysis is one of the common methods to account the uncertainty of parameters on the structural failure. In order to apply probabilistic analysis on the deterministic life analysis, it would be necessary to introduce Probability of Failure(PoF) and conduct risk assessment. In this work, we have studied probabilistic risk assessment of aircraft structures by using PoF approach. To achieve this goal, the Bayesian method was utilized to model PoF estimation since this method is known as the proper method to express the uncertainty of parameters. A series of proof tests were also conducted in order to verify the result of PoF estimation. The results from this efforts showed that the PoF estimation model can calculate quantitatively the value of PoF. Furthermore effectiveness of risk assessment approach for the aircraft structures was also demonstrated.

• Journal of the Korean Society of Propulsion Engineers
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• v.22 no.3
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• pp.14-20
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• 2018

An estimation law of air mass flow rate for high speed engine control is presented. The variables of mass estimation equations are modified to measurable variables which can be obtained during flight, and the effectiveness of each variable to the estimation accuracy is evaluated. The equation is modified to a simplified form, and the uncertainty is evaluated. In addition, reference data for the selection of estimation methods is suggested by considering the sensitivity analysis of sensor error.

• The KSFM Journal of Fluid Machinery
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• v.17 no.2
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• pp.24-29
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• 2014

In general, a large-capacity axial flow fan is used for industrial processes or ventilation in a social overhead capital infrastructure. The main characteristics of the large axial-flow fan need a lot of electrical power consumption and operate 24 hours a day, 365 days a year. Since the large axial flow fan consumes several hundreds to thousands kW per hour, both manufacturer and consumer are struggling to select high efficiency products for saving energy and reducing operation cost. Therefore, the performance testing should be accurately conducted in experimental equipments. The performance estimation and uncertainty of measurement of the axial-flow fan gathered from the result from nozzle shaped testing equipments certified with ANSI/AMCA standard and duct shaped testing equipment under the same experimental condition. The experimental results from both facilities have maximum 17% differences in performance evaluation and uncertainty of measurement. As considering that the differences, it is doubt about the reliability of testing result. The test was repeated with the specific term during 12 months because it is important to fully reflect the real conditions and to decide the repeatability of data. The evaluation of duct type testing facilities was failed to get an uncertainty measure. Testing results were previously published. As a series of previous paper, axial fan (∅1690 mm) and duct type testing facilities were fabricated. The purpose of fabricating testing equipment was testing an uncertainty measurement under the controlled environments.

• Tunnel and Underground Space
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• v.13 no.2
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• pp.87-99
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• 2003

Geostatistics is defined as the theory of modeling of regionalized variables and is an efficient and elegant methodology for estimation and uncertainty evaluation from limited spatial sample data. In this study, we have made a theoretical comparison between kriging estimation and geostatistical simulation methods. Kriging methods do not preserve the histogram of original data nor their spatial structure, and also provide only an incomplete measure of uncertainty when compared to the simulation methods. A practical procedure of geostatistical simulation is suggested in this study and the technique is demonstrated through an application, in which it was used to identify the spatial distribution of RMR as well as to evaluate the spatial uncertainty. It is concluded that the geostatistical simulation is the appropriate method to quantify the spatial uncertainty of geotechnical variables such as RMA. Therefore, the results from the simulation can be used as useful information for designer's considerations in decision-making under various geological conditions as well as the related terms of contract.

• Journal of Korea Water Resources Association
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• v.43 no.4
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• pp.337-351
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• 2010

There is a growing dissatisfaction with use of conventional statistical methods for the prediction of extreme events. Conventional methodology for modeling extreme event consists of adopting an asymptotic model to describe stochastic variation. However asymptotically motivated models remain the centerpiece of our modeling strategy, since without such an asymptotic basis, models have no rational for extrapolation beyond the level of observed data. Also, this asymptotic models ignored or overestimate the uncertainty and finally decrease the reliability of uncertainty. Therefore this article provide the research example of the extreme rainfall event and the methodology to reduce the uncertainty. In this study, the Bayesian MCMC (Bayesian Markov Chain Monte Carlo) and the MLE (Maximum Likelihood Estimation) methods using a quadratic approximation are applied to perform the at-site rainfall frequency analysis. Especially, the GEV distribution and Gumbel distribution which frequently used distribution in the fields of rainfall frequency distribution are used and compared. Also, the results of two distribution are analyzed and compared in the aspect of uncertainty.

• Smart Media Journal
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• v.11 no.9
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• pp.9-20
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• 2022

Deep reinforcement learning(RL) is an end-to-end data-driven control method that is widely used in the autonomous driving domain. However, conventional RL approaches have difficulties in applying it to autonomous driving tasks due to problems such as inefficiency, instability, and uncertainty. These issues play an important role in the autonomous driving domain. Although recent studies have attempted to solve these problems, they are computationally expensive and rely on special assumptions. In this paper, we propose a new algorithm MCDT that considers inefficiency, instability, and uncertainty by introducing a method called uncertainty sequence modeling to autonomous driving domain. The sequence modeling method, which views reinforcement learning as a decision making generation problem to obtain high rewards, avoids the disadvantages of exiting studies and guarantees efficiency, stability and also considers safety by integrating uncertainty estimation techniques. The proposed method was tested in the OpenAI Gym CarRacing environment, and the experimental results show that the MCDT algorithm provides efficient, stable and safe performance compared to the existing reinforcement learning method.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11a
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• pp.251-254
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• 2005

In this study vibration transmissibilities of the selected anti-vibration gloves were measured, and the measurement uncertainty was estimated. Since human factors such as palm size, gripping condition and dynamic properties of the hand-arm effect the measurement a lot, it is necessary to know ow much the uncertainty is. This study takes the measurement procedure suggested in ISO 10819. Three subjects Joined at each test and each anti-vibration glove was tested twice per a subject. Average and standard deviation of vibration transmissibility were calculated and uncertainty of them were estimated at 95% confidence level.

• Korean Journal of Veterinary Research
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• v.47 no.2
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• pp.139-145
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• 2007

Measurement uncertainty could play an important role in the assessment of test results in laboratories and industries. We investigated measurement uncertainties possibly included in determination of flubendazole, a benzimidazole anthelmintic, in pork by HPLC. The concentration of flubendazole was 62.69 ng/g in a sample of pork. Uncertainty was estimated in the analytical procedure of flubendazole. A model equation was made for determination of flubendazole in pork. The four uncertainty components such as weight of sample, volume of sample, calibration curve, and recovery were selected to estimate measurement uncertainties. Standard uncertainty was calculated for each component and all the standard uncertainties were combined. The combined standard uncertainty was expanded to a sample population as an expanded uncertainty. The expanded uncertainty was calculated using k value on Student's t-table and effective degrees of freedom from Welch-Satterthwaite formula. The expanded uncertainty was calculated as 3.45 with the combined standard uncertainty, 1.584 6 and the k value, 2.18. The final expression can be ($62.69{\pm}3.45$) ng/g (confidence level 95%, k = 2.18). The uncertainty value might be estimated differently depending on the selection of the uncertainty components. It is difficult to estimate all the uncertainty factors. Therefore, it is better to take several big effecting components instead of many small effecting components.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1432-1435
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• 1997

This paper proposes a fault detection and isolation metho by combining the parameter estimation method[4] with the observer method[2] to use merits of both methods. To verify the performance of the method proposed some simulations applied to remotely piloted vehicle are performed.

• Proceedings of the KSME Conference
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• 2005.11a
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• pp.108.1-108.1
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• 2005