• Geomechanics and Engineering
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• v.12 no.6
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• pp.871-882
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• 2017

Indirect measure of the tensile strength of laboratory samples is an important topic in rock engineering. One of the most important tests, the Brazilian strength test is performed to obtain the tensile strength of rock, concrete and other quasi brittle materials. Because the measurements are provided indirectly and the inspected rock materials may have heterogeneous properties, uncertainty quantification is required for a reliable test evaluation. In addition to the conventional measurement evaluation uncertainty methods recommended by the Guide to the Expression of Uncertainty in Measurement (GUM), such as Taylor's and Monte Carlo Methods, a fuzzy set-based approach is also proposed and resulting uncertainties are discussed. The results showed that when a tensile strength measurement is measured by a laboratory test, its uncertainty can also be expressed by one of the methods presented.

• Journal of the Korea Convergence Society
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• v.4 no.2
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• pp.35-41
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• 2013

Data management with fuzzy entropy and similarity measure were discussed and verified by applying reliable data selection problem. Calculation of certainty or uncertainty for data, fuzzy entropy and similarity measure are designed and proved. Proposed fuzzy entropy and similarity are considered as dissimilarity measure and similarity measure, and the relation between two measures are explained through graphical illustration.Obtained measures are useful to the application of decision theory and mutual information analysis problem. Extension of data quantification results based on the proposed measures are applicable to the decision making and fuzzy game theory.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.4
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• pp.275-280
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• 2010

Verification of efficiency in data management fuzzy entropy and similarity measure were discussed and verified by applying reliable data selection problem and numerical data similarity evaluation. In order to calculate the certainty or uncertainty fuzzy entropy and similarity measure are designed and proved. Designed fuzzy entropy and similarity are considered as dissimilarity measure and similarity measure, and the relation between two measures are explained through graphical illustration. Obtained measures are useful to the application of decision theory and mutual information analysis problem. Extension of data quantification results based on the proposed measures are applicable to the decision making and fuzzy game theory.

• Korean Journal of Food Science and Technology
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• v.53 no.6
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• pp.682-687
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• 2021

The purpose of this study was to validate a high-performance liquid chromatography (HPLC) method for the quantitative analysis of quercetin in various foods. The method was based on HPLC-UV (360 nm). The method was validated using candy, beverage, and sausage which were tested for specificity, linearity, limit of detection (LOD), limit of quantification (LOQ), precision, and accuracy, and the measurement uncertainty was assessed. Matrix-matched calibration was also applied. The calibration curves (0.5-50 mg/L) showed good linearity (r²≥0.9998). LOD and LOQ ranged from 0.15 to 0.31 mg/kg and from 0.44 to 0.93 mg/kg, respectively. The average accuracy and precision at 0.5, 2.5, and 10 mg/kg ranged from 84.3 to 102.0% and 0.7 to 3.0 relative standard deviation (RSD%), respectively. This study confirmed the applicability of the proposed method by applying it to commercial products, such as teas and beverages. Thus, the proposed analytical method is suitable for quantifying quercetin in various foods.

• Journal of the Korean Society of Propulsion Engineers
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• v.22 no.5
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• pp.73-80
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• 2018

At the early stages of development of high-speed propulsion systems, associated uncertainties cannot be easily modeled into probabilistic distributions, owing to the lack of test data, cost, and difficulty of simulating real-flight environments on the ground. To tackle this issue, in this research, the combustion efficiencies of dual-combustion ramjet engines are assumed to have been provided by experts and quantified by evidence theory. Using quantified uncertainty, the inlet area and combustor exit are optimized while satisfying reliability margins of thrust and thermal choking. The result shows a reasonable design of the engine under uncertain circumstances.

• Structural Engineering and Mechanics
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• v.38 no.4
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• pp.503-516
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• 2011

Uncertainty in concrete properties, including concrete modulus of elasticity and modulus of rupture, are predicted by developing a microstructural homogenization model. The homogenization model is developed by analyzing a concrete representative volume element (RVE) using the finite element (FE) method. The concrete RVE considers concrete as a three phase composite material including: cement paste, aggregate and interfacial transition zone (ITZ). The homogenization model allows for considering two sources of variability in concrete, randomly dispersed aggregates in the concrete matrix and uncertain mechanical properties of composite phases of concrete. Using the proposed homogenization technique, the uncertainty in concrete modulus of elasticity and modulus of rupture (described by numerical cumulative probability density function) are determined. Deflection uncertainty of reinforced concrete (RC) beams, propagated from uncertainties in concrete properties, is quantified using Monte Carlo (MC) simulation. Cracked plane frame analysis is used to account for tension stiffening in concrete. Concrete homogenization enables a unique opportunity to bridge the gap between concrete materials and structural modeling, which is necessary for realistic serviceability prediction.

• Nuclear Engineering and Technology
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• v.54 no.2
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• pp.523-531
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• 2022

In order to study the sensitivity and the uncertainty of the Moroccan research reactor TRIGA Mark II, a model of this reactor has been developed in our ERSN laboratory for use with the N-Particle MCNP Monte Carlo transport codes (version 6). In this article, the sensitivities of the effective multiplication factor of this reactor are evaluated using the ENDF/B-VII.0, ENDF/B-VII.1 and JENDL-4.0 libraries and in 44 energy groups, for the cross sections of the fuel (U-235 and U-238) and the moderator (H-1 and O-16). However, the quantification of the uncertainty of the nuclear data is performed using the nuclear code NJOY99 for the generation and processing of covariance matrices. On the one hand, the highest uncertainty deviations, calculated using the ENDFB-VII.1 and JENDL4.0 evaluations, are 2275, 386 and 330 pcm respectively for the reactions U₂₃₅(n, f), $ U_{235}(n\bar{\nu})$ and H₁(n, γ). On the other hand, these differences are very small for the neutron reactions of O-16 and U-238. Regarding the neutron spectra, in CT-mid plane, they are very close for the three evaluations (ENDF/B-VII.0, ENDF/B-VII.1 and JENDL-4.0). These spectra present two peaks (thermal and fission) around the energies 0.05 eV and 1 MeV.

• Nuclear Engineering and Technology
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• v.55 no.4
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• pp.1563-1570
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• 2023

In this study, a DeCART/MIG uncertainty quantification (UQ) analysis code system with a multicorrelated cross section stochastic sampling (S.S.) module was established and verified through the UAM (Uncertainty Analysis in Modeling) and the BEAVRS (Benchmark for Evaluation And Validation of Reactor Simulations) benchmark calculations. For the S.S. calculations, a sample of 500 DeCART multigroup cross section sets for two major actinides, i.e., ²³⁵U and ²³⁸U, were generated by the MIG code and covariance data from the ENDF/B-VII.1 evaluated nuclear data library. In the three pin problems (i.e. TMI-1, PB2, and Koz-6) from the UAM benchmark, the uncertainties in k_inf by the DeCART/MIG S.S. calculations agreed very well with the sensitivity and uncertainty (S/U) perturbation results by DeCART/MUSAD and the S/U direct subtraction (S/U-DS) results by the DeCART/MIG. From these results, it was concluded that the multi-group cross section sampling module of the MIG code works correctly and accurately. In the BEAVRS whole benchmark problems, the uncertainties in the control rod bank worth, isothermal temperature coefficient, power distribution, and critical boron concentration due to cross section uncertainties were calculated by the DeCART/MIG code system. Overall, the uncertainties in these design parameters were less than the general design review criteria of a typical pressurized water reactor start-up case. This newly-developed DeCART/MIG UQ analysis code system by the S.S. method can be widely utilized as uncertainty analysis and margin estimation tools for developing and designing new advanced nuclear reactors.

• Nuclear Engineering and Technology
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• v.36 no.1
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• pp.83-103
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• 2004

The methodological framework of the Level 2 PSA appears to be currently standardized in a formalized fashion, but there have been different opinions on the way the sources of uncertainty are characterized and treated. This is primarily because the Level 2 PSA deals with complex phenomenological processes that are deterministic in nature rather than random processes, and there are no probabilistic models characterizing them clearly. As a result, the probabilistic quantification of the Level 2 PSA CET / APET is often subjected to two sources of uncertainty: (a) incomplete modeling of accident pathways or different predictions for the behavior of phenomenological events and (b) expert-to-expert variation in estimating the occurrence probability of phenomenological events. While a clear definition of the two sources of uncertainty involved in the Level 2 PSA makes it possible to treat an uncertainty in a consistent manner, careless application of these different sources of uncertainty may produce different conclusions in the decision-making process. The primary purpose of this paper is to characterize typical sources of uncertainty that would often be addressed in the Level 2 PSA and to provide a formal guidance for quantifying their impacts on the PSA Level 2 risk results. An additional purpose of this paper is to give a formal approach on how to combine random uncertainties addressed in the Level 1 PSA with subjectivistic uncertainties addressed in the Level 2 PSA.

• Structural Engineering and Mechanics
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• v.32 no.1
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• pp.1-20
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• 2009

The present contribution addresses uncertainty quantification and uncertainty propagation in structural mechanics using stochastic analysis. Presently available procedures to describe uncertainties in load and resistance within a suitable mathematical framework are shortly addressed. Monte Carlo methods are proposed for studying the variability in the structural properties and for their propagation to the response. The general applicability and versatility of Monte Carlo Simulation is demonstrated in the context with computational models that have been developed for deterministic structural analysis. After discussing Direct Monte Carlo Simulation for the assessment of the response variability, some recently developed advanced Monte Carlo methods applied for reliability assessment are described, such as Importance Sampling for linear uncertain structures subjected to Gaussian loading, Line Sampling in linear dynamics and Subset simulation. The numerical example demonstrates the applicability of Line Sampling to general linear uncertain FE systems under Gaussian distributed excitation.