• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 2006년도 춘계학술발표회 논문집(I)
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• pp.462-465
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• 2006

This paper is aimed at proposing the sampling method to reduce variance of statistical parameters in uncertainty analysis of concrete structures. The proposed method is a modification of Latin Hypercube sampling method. This uses specially modified tables of random permutations of rank number. Also, the Spearman coefficient is used to make modified tables. Numerical analysis is carried out to predict the uncertainty of axial shortening in prestressed concrete bridge. The numerical results show that the method is efficient for uncertainty analysis of complex structural system such as prestressed concrete bridges.

• Journal of Forest and Environmental Science
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• 제33권4호
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• pp.295-304
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• 2017

This study compared and analyzed the construction of a land use change matrix for the Intergovernmental Panel on Climate Change's (IPCC) land use, land use change, and forestry area (LULUCF). We used National Forest Inventory (NFI) permanent sample plots (with a sample intensity of 4 km) and permanent sample plots with 500 m sampling intensity. The land use change matrix was formed using the point sampling method, Level-2 Land Cover Maps, and forest aerial photographs (3rd and 4th series). The land use change matrix using the land cover map indicated that the annual change in area was the highest for forests and cropland; the cropland area decreased over time. We evaluated the uncertainty of the land use change matrix. Our results indicated that the forest land use, which had the most sampling, had the lowest uncertainty, while the grassland and wetlands had the highest uncertainty and the least sampling. The uncertainty was higher for the 4 km sampling intensity than for the 500 m sampling intensity, which indicates the importance of selecting the appropriate sample size when constructing a national land use change matrix.

• 한국대기환경학회지
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• 제18권5호
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• pp.355-362
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• 2002

There has been relatively a few studies that focused on evaluation of uncertainty for standard methods by which criteria pollutants are analyzed in ambient air. Especially, uncertainty evaluation has not been made yet for sampling and analysis of airborne NO$_2$. Ambient NO$_2$ has been thought to be a major criteria pollutant worldwide because of the potential of ozone formation as well as of its own toxicity. In this study, we tried to assess uncertainties associated with the every step of sampling and of analytical procedure of Griess-Saltzman method. Quality assurance (QA) and quality control (QC) were also emphasized with the uncertainty characterization. The use of Griess-Saltzman method for ambient NO$_2$ analysis showed very uniform daily concentration distribution with the mean of 10.8 ppb and the standard deviation of 1.08ppb during the sampling period. However, seven daily samples collected at the same sampling time and place exhibited highly different concentration distribution. Therefore, we evaluated uncertainties associated with sampling and analysis through the precise application of ISO Guide. Estimates of expanded uncertainties for a total of 62 samples fell in a relatively broad range of 5.17% to 11.85%. On the other hand. the expanded uncertainties were smaller for the high concentration range of greater than 15ppb.

• Journal of electromagnetic engineering and science
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• 제18권3호
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• pp.169-174
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• 2018

In this paper, we propose an estimation method using multiple in-phase and quadrature (IQ) signals of different frequencies to evaluate the sample-time errors in the sampling oscilloscope. The estimator is implemented by ODRPACK, and a novel iteration scheme is applied to achieve fast convergence without any prior information. Monte-Carlo simulation is conducted to confirm the proposed method. It clearly shows that the multiple IQ approach achieves more accurate results compared to the conventional method. Finally, the criteria for the frequency selection and the signal capture time are investigated.

• Nuclear Engineering and Technology
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• 제42권2호
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• pp.163-174
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• 2010

As pointed out in the OECD BEMUSE Program, when a high computation time is taken to obtain the relevant output values of a complex physical model (or code), the number of statistical samples that must be evaluated through it is a critical factor for the sampling-based uncertainty analysis. Two alternative methods have been utilized to avoid the problem associated with the size of these statistical samples: one is based on Wilks' formula, which is based on simple random sampling, and the other is based on the conventional nonlinear regression approach. While both approaches provide a useful means for drawing conclusions on the resultant uncertainty with a limited number of code runs, there are also some unique corresponding limitations. For example, a conclusion based on the Wilks' formula can be highly affected by the sampled values themselves, while the conventional regression approach requires an a priori estimate on the functional forms of a regression model. The main objective of this paper is to assess the feasibility of the ACE-RSM approach as a complementary method to the Wilks' formula and the conventional regression-based uncertainty analysis. This feasibility was assessed through a practical application of the ACE-RSM approach to the LOFT L2-5 LBLOCA PCT uncertainty analysis, which was implemented as a part of the OECD BEMUSE Phase III program.

• Nuclear Engineering and Technology
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• 제53권3호
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• pp.715-731
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• 2021

Uncertainties are calculated for pressurized water reactor (PWR) spent nuclear fuel (SNF) characteristics. The deterministic code STREAM is currently being used as an SNF analysis tool to obtain isotopic inventory, radioactivity, decay heat, neutron and gamma source strengths. The SNF analysis capability of STREAM was recently validated. However, the uncertainty analysis is yet to be conducted. To estimate the uncertainty due to nuclear data, STREAM is used to perturb nuclear cross section (XS) and resonance integral (RI) libraries produced by NJOY99. The perturbation of XS and RI involves the stochastic sampling of ENDF/B-VII.1 covariance data. To estimate the uncertainty due to modeling parameters (fuel design and irradiation history), surrogate models are built based on polynomial chaos expansion (PCE) and variance-based sensitivity indices (i.e., Sobol' indices) are employed to perform global sensitivity analysis (GSA). The calculation results indicate that uncertainty of SNF due to modeling parameters are also very important and as a result can contribute significantly to the difference of uncertainties due to nuclear data and modeling parameters. In addition, the surrogate model offers a computationally efficient approach with significantly reduced computation time, to accurately evaluate uncertainties of SNF integral characteristics.

• Earthquakes and Structures
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• 제23권4호
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• pp.385-401
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• 2022

Uncertainty quantification is the most important challenge in seismic fragility assessment of structures. The precision increment of the quantification method leads to reliable results but at the same time increases the computational costs and the latter will be so undesirable in cases such as reliability-based design optimization which includes numerous probabilistic seismic analyses. Accordingly, the authors' effort has been put on the development and validation of an approach that has reduced computational cost in seismic fragility assessment. In this regard, it is necessary to apply the appropriate methods for consideration of two categories of uncertainties consisting of uncertainties related to the ground motions and structural characteristics, separately. Also, cable-stayed bridges have been specifically selected because as a result of their complexity and the according time-consuming seismic analyses, reducing the computations corresponding to their fragility analyses is worthy of studying. To achieve this, the fragility assessment of three case studies is performed based on existing and proposed approaches, and a comparative study on the efficiency in the estimation of seismic responses. For this purpose, statistical validation is conducted on the seismic demand and fragility resulting from the mentioned approaches, and through a comprehensive interpretation, sufficient arguments for the acceptable errors of the proposed approach are presented. Finally, this study concludes that the combination of the Capacity Spectrum Method (CSM) and Uniform Design Sampling (UDS) in advanced proposed forms can provide adequate accuracy in seismic fragility estimation at a significantly reduced computational cost.

• Journal of Electrical Engineering and Technology
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• 제10권3호
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• pp.1255-1263
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• 2015

In the previous work, the authors studied the problem of robust discretization of linear time-invariant systems with polytopic uncertainties, where linear matrix inequality (LMI) conditions were developed to find an approximate discrete-time (DT) model of a continuous-time (CT) system with uncertainties in polytopic domain. The system matrices of obtained DT model preserved the polytopic structures of the original CT system. In this paper, we extend the previous approach to solve the problem of robust discretization of polytopic uncertain systems with aperiodic sampling. In contrast with the previous work, the sampling period is assumed to be unknown, time-varying, but contained within a known interval. The solution procedures are presented in terms of unidimensional optimizations subject to LMI constraints which are numerically tractable via LMI solvers. Finally, an example is given to show the validity of the proposed techniques.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 1998년도 가을 학술발표대회 논문집(III)
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• pp.656-661
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• 1998

This paper presents a method of statistical analysis and sensitivity analysis of creep and shrinkage effects in PSC box girder bridges. The statistical and sensitivity analyses are performed by using the numerical simulation of Latin Hypercube sampling. For each sample, the time-dependent structural analysis is performed to produce response data, which are then statistically analyzed. The probabilistic prediction of the confidence limits on long-term effects of creep and shrinkage is then expressed. Three measures are examined to quantify the sensitivity of the outputs to each of the input variables. These are rank correlation coefficient(RCC), partial rank correlation coefficient(PRCC) and standardized rank regression coefficient(SRRC) computed on the ranks of the observations. Probability band widens with time, which indicates an increase of prediction uncertainty with time. The creep model uncertainty factor and the relative humidity appear as the most dominant factors with regard to the model output uncertainty.

• Structural Engineering and Mechanics
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• 제56권2호
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• pp.257-273
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• 2015

Numerical value of correlation between effective parameters in the strength of a structure is as important as its stochastic properties in determining the safety of the structure. In this article investigation is made about the variation of coefficient of correlation between effective parameters in corrosion initiation time of reinforcement and the time of concrete cover cracking in reinforced concrete (RC) structures. Presence of many parameters and also error in measurement of these parameters results in uncertainty in determination of corrosion initiation and the time to crack initiation. In this paper, assuming diffusion process as chloride ingress mechanism in RC structures and considering random properties of effective parameters in this model, correlation between input parameters and predicted time to corrosion is calculated using the Monte Carlo (MC) random sampling. Results show the linear correlation between corrosion initiation time and effective input parameters increases with increasing uncertainty in the input parameters. Diffusion coefficient, concrete cover, surface chloride concentration and threshold chloride concentration have the highest correlation coefficient respectively. Also the uncertainty in the concrete cover has the greatest impact on the coefficient of correlation of corrosion initiation time and the time of crack initiation due to the corrosion phenomenon.