• Smart Structures and Systems
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• v.10 no.4_5
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• pp.485-499
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• 2012

Mode shape expansion is useful in structural dynamic studies such as vibration based structural health monitoring; however most existing expansion methods can not consider the modelling errors in the finite element model and the measurement uncertainty in the modal properties identified from vibration data. This paper presents a reliable approach for expanding mode shapes with consideration of both the errors in analytical model and noise in measured modal data. The proposed approach takes the perturbed force as an unknown vector that contains the discrepancies in structural parameters between the analytical model and tested structure. A regularisation algorithm based on the Tikhonov solution incorporating the L-curve criterion is adopted to reduce the influence of measurement uncertainties and to produce smooth and optimised expansion estimates in the least squares sense. The Canton Tower benchmark problem established by the Hong Kong Polytechnic University is then utilised to demonstrate the applicability of the proposed expansion approach to the actual structure. The results from the benchmark problem studies show that the proposed approach can provide reliable predictions of mode shape expansion using only limited information on the operational modal data identified from the recorded ambient vibration measurements.

• Nuclear Engineering and Technology
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• v.39 no.2
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• pp.133-142
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• 2007

The Electric Power Research Institute (EPRI) demonstrated a method for monitoring the performance of instrument channels in Topical Report (TR) 104965, 'On-Line Monitoring of Instrument Channel Performance.' This paper presents the results of several models originally developed by EPRI to monitor three nuclear plant sensor sets: Pressurizer Level, Reactor Protection System (RPS) Loop A, and Reactor Coolant System (RCS) Loop A Steam Generator (SG) Level. The sensor sets investigated include one redundant sensor model and two non-redundant sensor models. Each model employs an Auto-Associative Kernel Regression (AAKR) model architecture to predict correct sensor behavior. Performance of each of the developed models is evaluated using four metrics: accuracy, auto-sensitivity, cross-sensitivity, and newly developed Error Uncertainty Limit Monitoring (EULM) detectability. The uncertainty estimate for each model is also calculated through two methods: analytic formulas and Monte Carlo estimation. The uncertainty estimates are verified by calculating confidence interval coverages to assure that 95% of the measured data fall within the confidence intervals. The model performance evaluation identified the Pressurizer Level model as acceptable for on-line monitoring (OLM) implementation. The other two models, RPS Loop A and RCS Loop A SG Level, highlight two common problems that occur in model development and evaluation, namely faulty data and poor signal selection

• Journal of Positioning, Navigation, and Timing
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• v.12 no.1
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• pp.51-58
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• 2023

Geofencing supports unmanned aerial vehicle (UAV) operation by defining stay-in and stay-out regions. National Aeronautics and Space Administration (NASA) has developed a prototype of the geofencing function, SAFEGUARD, which prevents stayout region violation by utilizing position estimates. Thus, SAFEGUARD depends on navigation system performance, and the safety risk associated with the navigation system uncertainty should be considered. This study presents a methodology to compute the safety risk assessment-based along-track position error bound under nominal and Global Navigation Satellite Systems (GNSS) failure conditions. A Kalman filter system using pseudorange measurements as well as pseudorange rate measurements is considered for determining the position uncertainty induced by velocity uncertainty. The worst case pseudorange and pseudorange rate fault-based position error bound under the GNSS failure condition are derived by applying a Receiver Autonomous Integrity Monitor (RAIM). Position error bound simulations are also conducted for different GNSS fault hypotheses and constellation conditions with a GNSS/INS integrated navigation system. The results show that the proposed along-track position error bounds depend on satellite geometries caused by UAV attitude change and are reduced to about 40% of those of the single constellation case when using the dual constellation.

• Wind and Structures
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• v.11 no.1
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• pp.51-70
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• 2008

CFD is applied to evaluate pedestrian wind comfort at outdoor platforms in a high-rise apartment building. Model validation is focused on generic building sub-configurations that are obtained by decomposition of the actual complex building geometry. The comfort study is performed during the design stage, which allows structural design changes to be made for wind comfort improvement. Preliminary simulations are performed to determine the effect of different design modifications. A full wind comfort assessment study is conducted for the final design. Structural remedial measures for this building, aimed at reducing pressure short-circuiting, appear to be successful in bringing the discomfort probability estimates down to acceptable levels. Finally, the importance of one of the main sources of uncertainty in this type of wind comfort studies is illustrated. It is shown that the uncertainty about the terrain roughness classification can strongly influence the outcome of wind comfort studies and can lead to wrong decisions. This problem is present to the same extent in both wind tunnel and CFD wind comfort studies when applying the same particular procedure for terrain relation contributions as used in this paper.

• Journal of Coastal Disaster Prevention
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• v.6 no.3
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• pp.111-120
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• 2019

In coastal morphological modelling, there are a number of input factors: wave height, water depth, sand particle size, bed friction coefficients, coastal structures and so forth. Measurements or estimates of these input data may include uncertainties due to errors by the measurement or hind-casting methods. Therefore, it is necessary to consider the uncertainty of each input data and the range of the uncertainty during the evaluation of numerical results. In this study, three uncertainty factors are considered with regard to the prediction of coastal erosion in Ilsan beach located in Ilsan-dong, Ulsan metropolitan city. Those are wave diffraction effect of XBeach model, wave input scenario and the specification of the coastal structure. For this purpose, the values of mean wave direction, significant wave height and the height of the submerged breakwater were adjusted respectively and the followed numerical results of morphological changes are analyzed. There were erosion dominant patterns as the wave direction is perpendicular to Ilsan beach, the higher significant wave height, and the lower height of the submerged breakwater. Furthermore, the rate of uncertainty impacts among mean wave direction, significant wave height and the height of the submerged breakwater are compared. In the study area, the uncertainty influence by the wave input scenario was the largest, followed by the height of the submerged breakwater and the mean wave direction.

• Journal of the Korean Geotechnical Society
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• v.28 no.1
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• pp.17-27
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• 2012

Since geologic data are often sampled at sparse locations, it is important not only to predict attribute values at unsampled locations but also to assess the uncertainty attached to the prediction. In this study the assessment of the local uncertainty of prediction for the thickness of the consolidation layer was performed by using the indicator approach. A conditional cumulative distribution function (ccdf) was first modeled, and then E-type estimates and the conditional variance were computed for the spatial distribution of the thickness of the consolidation layer. These results could be used to estimate the spatial distribution of secondary compression and to assess the local uncertainty of secondary compression for Songdo New City.

• Journal of Korean Society for Atmospheric Environment
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• v.29 no.3
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• pp.275-286
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• 2013

It is well known that exposure to high level of PM (particulate matter) can adversely affect human health. However, little is known about health burden of PM considering the relationship, exposed level of PM, and health level in local communities. And, there is scarcely methodical assessment of uncertainty for application to policies of these assessment results. The scope of this study is divided into two parts: firstly to estimate the death burden of PM10 (particulate matter less then $10{\mu}m$ in diameter) in Seoul metropolitan region, and secondly to evaluate potential uncertainties in these estimates. To estimate the death burden of PM10 in Seoul metropolitan region from 2005~2010, we firstly assessed the relationship between daily mean PM10 and daily death counts in Seoul from 2000~2010, and calculated the death burden of PM10 using BenMAP (Environmental Benefits Mapping and Analysis Program). After that, we identified and characterized uncertainties to substantially influence the results of death burden. The daily mortality risk was increased 1.000227 times (p-value/0.001) associated with $1{\mu}g/m^3$ increase of daily mean PM10 for all ages population, Seoul. And, death burdens of PM10 in Seoul metropolitan region were estimated from 5.51 in 2005 to 5.12 in 2010 per 100,000 people. Finally, we categorized context, model, and input uncertainty and characterized these uncertainties in three dimensions (i.e. location, level, and nature) using uncertainty typology. In our study, we argue that uncertainties need to be identified, assessed, reported and interpreted in order for assessment results to adequately support decision making, such as the establishment of air quality standards based on health burden of air quality.

• Journal of Korean Society of Transportation
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• v.32 no.6
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• pp.694-702
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• 2014

Since Greenhouse Gas Inventory & Research Center (GIR) of Korea was founded in 2010, the annual greenhouse gas inventory reports, one of the collections of GIR's major affairs, have been published from 2012. In the reports many items related to greenhouse gas emission quantities are included, but among them uncertainty values are replaced to basic values which IPCC guideline suggests. Even though IPCC guideline suggests the equations of each Tier level in details, the guideline recommends developing nation's own methodology on uncertainty which is closely related to statistical problems such as the estimation of a probability density function or Monte carlo methods. In the road transportation sector the emissions have been calculated by Tier 1 but the uncertainties have not been reported. This study introduce a bootstrap technique and Monte carlo method to estimates annual emission quantity and uncertainty, given activity data and emission factors such as annual traveled distances, fuel efficiencies and emission coefficients.

• Journal of Environmental Policy
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• v.8 no.3
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• pp.163-180
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• 2009

This study attempts to investigate the preference uncertainty of respondents involved in stating their Willingness to Pay (WTP). For the Contingent Valuation Method (CVM) survey, we employed two approaches using two split samples. The respondents of one sample were given the opportunity to express intensity of preference through Multi-bounded Discrete Choice (MBDC) WTP questions, while those in the other sample were given Dichotomous Choice (DC) WTP questions. By incorporating the two elicited degrees of preference uncertainty into examining the WTP responses, we compared the two approaches. In comparing the DC model with the MBDC model, the mean WTP for the DC model was similar to PRYES in the MBDC Model. We concluded that the MBDC model estimates the various mean WTP while considering the preference uncertainty.

• Journal of Korea Technology Innovation Society
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• v.5 no.1
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• pp.59-71
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• 2002

Risk, or exposure to uncertainty, is an inherent of risk-adjusted discount rate. It is therefore important part factor in the determination of risk-adjusted discount rate. This paper suggests the method to quantify risk and explains the process how to transfer quantified risk into incremental discount rate. The estimates of underlying risks will help determine the size of appropriate risk-adjusted discount rate with logical and scientific way when the technology valuation is made.