• Earthquakes and Structures
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• v.26 no.4
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• pp.311-326
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• 2024

Transmission tower structures are particularly susceptible to damage and even collapse under strong seismic ground motions. Conventional seismic analyses of transmission towers are usually performed by considering only ground motion uncertainty while ignoring structural uncertainty; consequently, the performance evaluation and failure prediction may be inaccurate. In this context, the present study numerically investigates the seismic responses and failure mechanism of transmission towers by considering multiple sources of uncertainty. To this end, an existing transmission tower is chosen, and the corresponding three-dimensional finite element model is created in ABAQUS software. Sensitivity analysis is carried out to identify the relative importance of the uncertain parameters in the seismic responses of transmission towers. The numerical results indicate that the impacts of the structural damping ratio, elastic modulus and yield strength on the seismic responses of the transmission tower are relatively large. Subsequently, a set of 20 uncertainty models are established based on random samples of various parameter combinations generated by the Latin hypercube sampling (LHS) method. An uncertainty analysis is performed for these uncertainty models to clarify the impacts of uncertain structural factors on the seismic responses and failure mechanism (ultimate bearing capacity and failure path). The numerical results show that structural uncertainty has a significant influence on the seismic responses and failure mechanism of transmission towers; different possible failure paths exist for the uncertainty models, whereas only one exists for the deterministic model, and the ultimate bearing capacity of transmission towers is more sensitive to the variation in material parameters than that in geometrical parameters. This research is expected to provide an in-depth understanding of the influence of structural uncertainty on the seismic demand assessment of transmission towers.

• Proceedings of the KIEE Conference
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• 2002.07a
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• pp.286-288
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• 2002

The rapid development of measurement systems for high power tests makes it possible to measure signals as well as analyze with the help of computer. Also, methods to evaluate such measurement systems are required recently. Uncertainty has been regarding as the most important factor in evaluating the measurement systems. Because of the character of the measurement systems for high power tests. the uncertainty shall be evaluated by each component. If the uncertainty evaluated by each component, it is convenient to evaluate total uncertainty of the measurement systems according to each component setting's combination. In this paper each component of high current measurement system of high power testing Dept. II in Korea Electrotechnology Research Institute is evaluated except sensors such as shunts and CTs. The total uncertainty of the measurement systems can be determined by that of each component including uncertainty of sensors.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.3
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• pp.529-536
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• 2001

We investigate a surface-micromachined capacitive accelerometer with the grid-type electrodes surrounded by a perforated proof-mass frame. An electromechanical analysis of the microaccelerometer has been performed to obtain analytical formulae for natural frequency and output sensitivity response estimation. A set of prototype devices has been designed and fabricated based on a 4-mask surface-micromachining process. The resonant frequency of 5.8$\pm$0.17kHz and the detection sensitivity of 0.28$\pm$0.03mV/g have been measured from the fabricated devices. The parasitic capacitance of the detection circuit with a charge amplifier has been measured as 3.34$\pm$1.16pF. From the uncertainty analysis, we find that the major uncertainty in the natural frequency of the accelerometer comes from the micromachining error in the beam width patterning process. The major source of the sensitivity uncertainty includes uncertainty of the parasitic capacitance, the inter-electrode gap and the resonant frequency, contributing to the overall sensitivity uncertainty in the portions of 75%, 14% and 11%, respectively.

• Journal of Environmental Science International
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• v.20 no.3
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• pp.329-340
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• 2011

The probability concepts mainly used for rainfall or flood frequency analysis in water resources planning are the frequentist viewpoint that defines the probability as the limit of relative frequency, and the unknown parameters in probability model are considered as fixed constant numbers. Thus the probability is objective and the parameters have fixed values so that it is very difficult to specify probabilistically the uncertianty of these parameters. This study constructs the uncertainty evaluation model using Bayesian MCMC and Metropolis -Hastings algorithm for the uncertainty quantification of parameters of probability distribution in rainfall frequency analysis, and then from the application of Bayesian MCMC and Metropolis- Hastings algorithm, the statistical properties and uncertainty intervals of parameters of probability distribution can be quantified in the estimation of probability rainfall so that the basis for the framework configuration can be provided that can specify the uncertainty and risk in flood risk assessment and decision-making process.

• YAKHAK HOEJI
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• v.51 no.3
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• pp.206-213
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• 2007

Recently estimating the uncertainty of an analytical result has become an essential part of quantitative analysis. This study describes the uncertainty of the measurement for the determination of methamphetamine and its major metabolite amphetamine in human hair, The method consists of washing, drying, weighing, incubation and extraction with methanolic HCI solution, clean-up, trifluoroacetyl derivatization, and qualification/quantification of residues by gas chromatography/mass spectrometry (GC/MS). Traceability of measurement was established through traceable standards and calibrated volumetric equipment and measuring instruments. Measurement uncertainty associated with each analyte in real samples was estimated using quality control (QC) data. The main source of combined standard uncertainty comprised two components, which are uncertainties associated with calibration linearity and variations in QC, while those associated with preparation of analytical standards and sample weighing were not so important considering the degree of contribution. Relative combined standard uncertainties associated with the described method ranged for individual analytes from 4.99 to5.03%.

• Journal of Information Processing Systems
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• v.15 no.2
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• pp.331-343
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• 2019

Dynamic thermal rating of the overhead transmission lines is affected by many uncertain factors. The ambient temperature, wind speed and wind direction are the main sources of uncertainty. Measurement uncertainty is an important parameter to evaluate the reliability of measurement results. This paper presents the uncertainty analysis based on Monte Carlo. On the basis of establishing the mathematical model and setting the probability density function of the input parameter value, the probability density function of the output value is determined by probability distribution random sampling. Through the calculation and analysis of the transient thermal balance equation and the steady- state thermal balance equation, the steady-state current carrying capacity, the transient current carrying capacity, the standard uncertainty and the probability distribution of the minimum and maximum values of the conductor under 95% confidence interval are obtained. The simulation results indicate that Monte Carlo method can decrease the computational complexity, speed up the calculation, and increase the validity and reliability of the uncertainty evaluation.

• International journal of steel structures
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• v.18 no.5
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• pp.1508-1524
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• 2018

Hysteretic energy dissipating devices (HEDDs) have been increasingly applied to building construction to improve the seismic performance. The seismic responses of such damped structures are significantly affected by HEDD's structural properties. An accurate investigation on the propagation of HEDD's structural properties is required for reasonable evaluation of the seismic performance of a structure. This study aims to develop simplified methods that can estimate the collective uncertainty-propagation to the seismic response of damped structures employing HEDDs. To achieve this, three- and six-story steel moment-resisting frames were selected and the propagations of the individual HEDD's property-uncertainties were evaluated when they are subjected to various levels of seismic demand. Based on the result of individual uncertainty-propagations, a simplified method is proposed to evaluate the variation of seismic response collectively propagated by HEDD's property-uncertainties and is verified by comparing with the exact collective uncertainty-propagation calculated using the Monte Carlo simulation method. The proposed method, called as a modified SRSS method in this study, is established from a conventional square root of the sum of the squares (SRSS) method with the relative contributions of the individual HEDD's property-uncertainty propagations. This study shows that the modified SRSS method provides a better estimation than the conventional SRSS method and can significantly reduce computational time with reasonable accuracy compared with the Monte Carlo simulation method.

• Nuclear Engineering and Technology
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• v.56 no.7
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• pp.2850-2858
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• 2024

Amidst the uncertainties of climate policy, investing in nuclear energy technology emerges as a sustainable strategy, fostering innovation in a critical sector, while simultaneously addressing urgent environmental concerns and managing budgetary dynamics. Our investigation inspects the asymmetric influence of climate policy uncertainty on nuclear energy technology in the top 10 nations with the highest nuclear energy R&D budgets (Germany, Japan, China, France, USA, UK, India, South Korea, Russia, and Canada). Previous studies adopted panel data methods to evaluate the linkage between climate policy uncertainty and nuclear energy technology. Nonetheless, these investigations overlooked the variability in this association across various countries. Conversely, this investigation introduces an innovative tool, 'Quantile-on-Quantile' to probe this connection merely for every economy. This methodology concedes for a more accurate evaluation, offering a holistic global perspective and delivering tailored insights for individual countries. The findings uncover that climate policy uncertainty significantly reduces nuclear energy technology budgets across multiple quantiles in most selected economies. Additionally, our results highlight the asymmetries in the correlations between our variables across the nations. These findings stress the need for policymakers to conduct thorough assessments and skillfully manage climate policy uncertainty and nuclear energy budgets.

• Proceedings of the Society of Korea Industrial and System Engineering Conference
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• 2002.05a
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• pp.25-30
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• 2002

The problem of qualitative reliability system is very important issue in the digitalized nuclear power plant, because the failure of its system brings about extravagant economic loss, extensive environment destruction, and fatal damage of human. Therefore this study is to develop the reliability evaluation model through the normalized scoring model by the quantitative and qualitative factors considering the advanced safety factors In the Advanced Pressurized water Reactor 1400MWe(APR 1400) under uncertainty Especially, the qualitative factors considering the information and human factors for the systematic and rational justification have been closely analyzed. The reliability evaluation model can be simply applied in real fields in order to minimize the industrial accident and human error in the digitalized nuclear power plant.

• Industrial Engineering and Management Systems
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• v.13 no.1
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• pp.15-28
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• 2014

Evaluation of the implementation and performance of a firm's green supply chain management (GSCM) is an ongoing process. Balanced scorecard is a multi-criteria evaluation concept that highlights implementation and performance measures. The literature on the framework is abundant literature but scarce on how to build a hierarchical framework under uncertainty with dependence relations. Hence, this study proposes a hybrid approach, which includes applied interpretive structural modeling to build a hierarchical structure and uses the analytic network process to analyze the dependence relations. Additionally, this study applies the fuzzy set theory to determine linguistic preferences. Twenty dependence criteria are evaluated for a GSCM implemented firm in Taiwan. The result shows that the financial aspect and life cycle assessment are the most important performance and weighted criteria.