• The KSFM Journal of Fluid Machinery
• /
• v.11 no.3
• /
• pp.50-55
• /
• 2008

The diverter system is a key component in achieving a high accuracy liquid flow rate standard using a static gravimetric system with a flying start and stop method. The diverter is a moving device used to direct flow alternately along its normal course(by pass) or towards the weighing tank. The time needed for collection into the weighing tank is measured using a timer. So it is important to the diversion period is sufficiently fast and triggering point of timer which is determined the filling time. On this studies show that uncertainty of diverter system for changing diversion speed and triggering point was estimated in accordance with Guide to The Expression of Uncertainty in Measurement(ISO).

• Nuclear Engineering and Technology
• /
• v.52 no.3
• /
• pp.461-468
• /
• 2020

The improvements of the DeCART/MUSAD code system for uncertainty analysis of HTGR neutronic parameters are presented in this paper. The function for quantifying an uncertainty of critical-spectrumweighted few group cross section was implemented using the generalized adjoint B₁ equation solver. Though the changes between the infinite and critical spectra cause a considerable difference in the contribution by the graphite scattering cross section, it does not significantly affect the total uncertainty. To reduce the number of iterations of the generalized adjoint transport equation solver, the generalized adjoint B₁ solution was used as the initial value for it and the number of iterations decreased to 50%. To reflect the implicit uncertainty, the correction factor was derived with the resonance integral. Moreover, an additional correction factor for the double heterogeneity was derived with the effective cross section of the DH region and it reduces the difference from the complete uncertainty. The code system was examined with the MHTGR-350 Ex.II-2 3D core benchmark. The k_eff uncertainty for Ex.II-2a with only the fresh fuel block was similar to that of the block and the uncertainty for Ex.II-2b with the fresh fuel and the burnt fuel blocks was smaller than that of the fresh fuel block.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.49 no.4
• /
• pp.13-22
• /
• 2007

The uncertainty in water quality model predictions is inevitably high due to natural stochasticity, model uncertainty, and parameter uncertainty. An integrated modeling system under uncertainty was described and demonstrated for use in watershed management and receiving-water quality prediction. A watershed model (HSPF), a receiving water quality model (WASP), and a wetland model (NPS-WET) were incorporated into an integrated modeling system (modified-BASINS) and applied to the Hwaseong Reservoir watershed. Reservoir water quality was predicted using the calibrated integrated modeling system, and the deterministic integrated modeling output was useful for estimating mean water quality given future watershed conditions and assessing the spatial distribution of pollutant loads. A Monte Carlo simulation was used to investigate the effect of various uncertainties on output prediction. Without pollution control measures in the watershed, the concentrations of total nitrogen (T-N) and total phosphorous (T-P) in the Hwaseong Reservoir, considering uncertainty, would be less than about 4.8 and 0.26 mg 4.8 and 0.26 mg $L^{-1}$, respectively, with 95% confidence. The effects of two watershed management practices, a wastewater treatment plant (WWTP) and a constructed wetland (WETLAND), were evaluated. The combined scenario (WWTP + WETLAND) was the most effective at improving reservoir water quality, bringing concentrations of T-N and T-P in the Hwaseong Reservoir to less than 3.54 and 0.15 mg ${L^{-1}$, 26.7 and 42.9% improvements, respectively, with 95% confidence. Overall, the Monte Carlo simulation in the integrated modeling system was practical for estimating uncertainty and reliable in water quality prediction. The approach described here may allow decisions to be made based on probability and level of risk, and its application is recommended.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1996.11a
• /
• pp.306-312
• /
• 1996

The performance of the failure detection algorithm may be greatly influenced by the model uncertainty. It is very important to design a robust failure detection system to the model uncertainty. In this paper, a design procedure to generate failure detection algorithm is proposed. The design procedure suggested is based on the concept of the‘threshold selector［1］’. The H$\infty$ control algorithm is used to derive a threshold selector which is robust to the model uncertainty, The threshold selector derived can be used to develop a failure detection system together with the weighted cumulative sum algorithm［3］. Computer simulation study showed that the failure detection system designed for an ISA(Integrated Servo Actuator) system by using the proposed method is robust to the model uncertainty.

• Journal of Power Electronics
• /
• v.4 no.1
• /
• pp.1-11
• /
• 2004

A stable adaptive sensorless speed controller for three-level inverter fed induction motor direct torque control (DTC) system using the radial-basis function network (RBFN) is presented in this paper. Torque ripple in the DTC system for high power induction motor could be drastically reduced with the foregoing researches of switching voltage selection and torque ripple reduction algorithms. However, speed control performance is still influenced by the inherent uncertainty of the system such as parametric uncertainty, external load disturbances and unmodeled dynamics, and its exact mathematical model is much difficult to be obtained due to their strong nonlinearity. In this paper, the inherent uncertainty is approximated on-line by the RBFN, and an additional robust control term is introduced to compensate for the reconstruction error of the RBFN instead of the rich number of rules and additional updated parameters. Control law for stabilizing the system and adaptive laws for updating both of weights in the RBFN and a bounding constant are established so that the whole closed-loop system is stable in the sense of Lyapunov, and the stability proof of the whole control system is presented. Computer simulations as well as experimental results are presented to show the validity and effectiveness of the proposed system.

• Proceedings of the Korea Inteligent Information System Society Conference
• /
• 2001.01a
• /
• pp.325-329
• /
• 2001

This paper tests existence of precautionary saving motive under health uncertainty, using household level panel data from Korea. For this purpose, this paper considers a dynamic health capital model with health uncertainty and derives testable equations for changes in consumption and medical expenditures. Under this framework, households who face future health uncertainty will exhibit precautionary behavior by depressing consumption or increasing investment in health. To test this hypothesis, the paper uses the conditional variance of health as the direct measure of health uncertainty, obtained by estimating a multinomial logit model. Empirical results using the Korean Household Panel Study (KHPS, 1993 - 1997) suggest that Korean elderly households follow the precautionary behavior to insure against future health risk.

• Transactions on Control, Automation and Systems Engineering
• /
• v.1 no.1
• /
• pp.32-43
• /
• 1999

Adaptive robust control scheme is introduced for flexible joint manipulator with nonlinearities and uncertainties. The system does not satisfy the matching condition due to insufficient actuators for each node. The control only relies on the assumption that the bound of uncertainty exists. Thus, the bounded value does not need to be known a prior. The control utilizes the update law by estimating the bound of the uncertainties. The control scheme uses the backstepping method and constructs a state transformation. Also, stability analysis is done for both transformed system and original system.

• Nuclear Engineering and Technology
• /
• v.46 no.5
• /
• pp.619-632
• /
• 2014

The Best Estimate Plus Uncertainty (BEPU) method has been widely used to evaluate the uncertainty of a best-estimate thermal hydraulic system code against a figure of merit. This uncertainty is typically evaluated based on the physical model's uncertainties determined by expert judgment. This paper introduces the application of data assimilation methodology to determine the uncertainty bands of the physical models, e.g., the mean value and standard deviation of the parameters, based upon the statistical approach rather than expert judgment. Data assimilation suggests a mathematical methodology for the best estimate bias and the uncertainties of the physical models which optimize the system response following the calibration of model parameters and responses. The mathematical approaches include deterministic and probabilistic methods of data assimilation to solve both linear and nonlinear problems with the a posteriori distribution of parameters derived based on Bayes' theorem. The inverse problem was solved analytically to obtain the mean value and standard deviation of the parameters assuming Gaussian distributions for the parameters and responses, and a sampling method was utilized to illustrate the non-Gaussian a posteriori distributions of parameters. SPACE is used to demonstrate the data assimilation method by determining the bias and the uncertainty bands of the physical models employing Bennett's heated tube test data and Becker's post critical heat flux experimental data. Based on the results of the data assimilation process, the major sources of the modeling uncertainties were identified for further model development.

• Journal of Institute of Control, Robotics and Systems
• /
• v.18 no.4
• /
• pp.295-301
• /
• 2012

This paper deals with the design of robust DSMC (Discrete-Time Sliding Mode Control) scheme in order to overcome system uncertainty in steering system with mechanically joined structure. The proposed control scheme is one of robust control schemes based on system dynamics. Therefore, system dynamics required is not obtained from physical law but SCM (Signal Compression Method) through experiment in order to avoid complicate mathematical development and save time. However, SCM has a shortcoming that is the limitation of with $2^{nd}$ order linear model which does not include the dynamic of high-frequency band. Thus, considering system uncertainty, DSMC is designed. In addition, to reduce the chattering problem of DSMC, DSMC is derived from the reaching law and the Lyapunov stability condition. It is found that the proposed control scheme has robustness in spite of the perturbation of system uncertainty through computer simulation.

• Proceedings of the KSME Conference
• /
• 2004.11a
• /
• pp.1721-1726
• /
• 2004

Heat rate is a representative index to estimate the performance of turbine cycle in nuclear power plant. Accuracy of heat rate calculation is dependent on the accuracy of measurement for plant status variables. Uncertainty of heat rate can be modeled using uncertainty propagation model. We developed practical estimation model of heat rate uncertainty using the propagation and regression model. The uncertainty model is used in the performance analysis system developed for the operating nuclear power plant.