• Nuclear Engineering and Technology
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• v.51 no.4
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• pp.968-976
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• 2019

This paper presents a number of verification case studies for a recently developed sensitivity/uncertainty code package. The code package, ROMUSE (Reduced Order Modeling based Uncertainty/Sensitivity Estimator) is an effort to provide an analysis tool to be used in conjunction with reactor core simulators, in particular the Virtual Environment for Reactor Applications (VERA) core simulator. ROMUSE has been written in C++ and is currently capable of performing various types of parameter perturbations and associated sensitivity analysis, uncertainty quantification, surrogate model construction and subspace analysis. The current version 2.0 has the capability to interface with the Design Analysis Kit for Optimization and Terascale Applications (DAKOTA) code, which gives ROMUSE access to the various algorithms implemented within DAKOTA, most importantly model calibration. The verification study is performed via two basic problems and two reactor physics models. The first problem is used to verify the ROMUSE single physics gradient-based range finding algorithm capability using an abstract quadratic model. The second problem is the Brusselator problem, which is a coupled problem representative of multi-physics problems. This problem is used to test the capability of constructing surrogates via ROMUSE-DAKOTA. Finally, light water reactor pin cell and sodium-cooled fast reactor fuel assembly problems are simulated via SCALE 6.1 to test ROMUSE capability for uncertainty quantification and sensitivity analysis purposes.

• Nuclear Engineering and Technology
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• v.54 no.3
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• pp.790-802
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• 2022

Large-scale reactor simulation often requires the use of Monte Carlo calculation techniques to estimate important reactor parameters. One drawback of these Monte Carlo calculation techniques is they inevitably result in some uncertainty in calculated quantities. The present study includes parametric uncertainty quantification (UQ) and sensitivity analysis (SA) on the Advanced Test Reactor Critical (ATRC) facility housed at Idaho National Laboratory (INL) and addresses some complications due to Monte Carlo uncertainty when performing these analyses. This approach for UQ/SA includes consideration of Monte Carlo code uncertainty in computed sensitivities, consideration of uncertainty from directly measured parameters and a comparison of results obtained from brute-force Monte Carlo UQ versus UQ obtained from a surrogate model. These methodologies are applied to the uncertainty and sensitivity of k_eff for two sets of uncertain parameters involving fuel plate geometry and fuel plate composition. Results indicate that the less computationally-expensive method for uncertainty quantification involving a linear surrogate model provides accurate estimations for k_eff uncertainty and the Monte Carlo uncertainty in calculated k_eff values can have a large effect on computed linear model parameters for parameters with low influence on k_eff.

• Journal of Korean Society for Atmospheric Environment
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• v.18 no.4
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• pp.327-334
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• 2002

The work presents sensitivity and uncertainty analysis of 2-compartment model for the evaluation of indoor radon pollution in a house. Effort on the development of such model is directed towards the prediction of the generation and transfer of radon in indoor air released from groundwater. The model is used to estimate a quantitative daily human exposure through inhalation of such radon based on exposure scenarios. However, prediction from the model has uncertainty propagated from uncertainties in model parameters. In order to assess how model predictions are affected by the uncertainties of model inputs, the study performs a quantitative uncertainty analysis in conjunction with the developed model. An importance analysis is performed to rank input parameters with respect to their contribution to model prediction based on the uncertainty analysis. The results obtained from this study would be used to the evaluation of human risk by inhalation associated with the indoor pollution by radon released from groundwater.

• Nuclear Engineering and Technology
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• v.37 no.3
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• pp.245-258
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• 2005

This paper addresses two types of uncertainty: stochastic uncertainty and subjective uncertainty in probabilistic accident consequence assessments. The off-site consequence assessment code OSCAAR has been applied to uncertainty and sensitivity analyses on the individual risks of early fatality and latent cancer fatality in the population outside the plant boundary due to a severe accident. A new stratified meteorological sampling scheme was successfully implemented into the trajectory model for atmospheric dispersion and the statistical variability of the probability distributions of the consequence was examined. A total of 65 uncertain input parameters was considered and 128 runs of OSCAAR with 144 meteorological sequences were performed in the parameter uncertainty analysis. The study provided the range of uncertainty for the expected values of individual risks of early and latent cancer fatality close to the site. In the sensitivity analyses, the correlation/regression measures were useful for identifying those input parameters whose uncertainty makes an important contribution to the overall uncertainty for the consequence. This could provide valuable insights into areas for further research aiming at reducing the uncertainties.

• 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.

• Proceedings of the Korea Concrete Institute Conference
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• 1998.10b
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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.

• Journal of the Korean Society of Safety
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• v.16 no.4
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• pp.160-167
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• 2001

Cracking in connote structures is one of the main issues of structural design next to ensuring the load-bearing capacity. Thermal analysis is used to prevent thermal mucking, but concrete properties are uncertain variable, and analysis results have uncertainty, too. In this study, sensitivity analysis is performed to investigate the effect of conductivity, specific heal and pouring temperature. The results show that lower conductivity and higher specific heat increase the maximum temperature and maximum tensile stress. The structure with internal restraint is mostly influenced by the change of conductivity and specific heat.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.24 no.10
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• pp.1388-1398
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• 2000

A pipe prover is a flowmeter calibrator used in flow measurement field. Gravimetric and volumetric methods were applied to determine the basic volume of the pipe prover. Uncertainty of its basic volume measurement was evaluated in accordance with the procedure recommended by International Organization for Standardization. The combined standard uncertainty of determining the basic volume was estimated from the sensitivity coefficient and the standard uncertainty of independent variables. It was found that the uncertainties of the weighing and volume measurements have dominant influence on that of the basic volume determination. With the quantitative analysis of the sensitivity coefficient, the contribution of the each variable uncertainty to the combined standard uncertainty of the basic volume is shown clearly.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.25 no.4
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• pp.561-571
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• 2001

The standard uncertainty of flowrate measurement is obtained by combining that of independent variables. Gravimetric and volumetric method were applied to determine the flowrate and the standard uncertainties of flowrate measurement by both methods were evaluated in accordance with the procedure recommended by International Organization for Standardization. The combined standard uncertainties of determining the flowrate were estimated from the sensitivity coefficient and the standard uncertainty of independent variables. For practical application, the methods for evaluating and expressing uncertainty in flow measurement were discussed. It was found that the uncertainties of the weighing and time measurement in gravimetric method, the volume and time measurement in volumetric method have dominant influence on that of flowrate measurement. With the quantitative analysis of the sensitivity coefficient, the contribution of the each variable uncertainty to the combined standard uncertainty of flowrate measurement is shown clearly.

• Proceedings of the Korea Water Resources Association Conference
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• 2004.05b
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• pp.1285-1289
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• 2004

Elman Discrete Recurrent Neural Networks Model(EDRNNM) was used to be a suitable short-term hydrological forecasting tool yielding a very high degree of flood stage forecasting accuracy at Musung station of Wi-stream one of IHP representative basins in South Korea. A relative new approach method has recurrent feedback nodes and virtual small memory in the structure. EDRNNM was trained by using two algorithms, namely, LMBP and RBP The model parameters, optimal connection weights and biases, were estimated during training procedure. They were applied to evaluate model validation. Sensitivity analysis test was also performed to account for the uncertainty of input nodes information. The sensitivity analysis approach could suggest a reduction of one from five initially chosen input nodes. Because the uncertainty of input nodes information always result in uncertainty in model results, it can help to reduce the uncertainty of EDRNNM application and management in small catchment.