• Journal of Korea Water Resources Association
• /
• v.42 no.10
• /
• pp.773-783
• /
• 2009

The effects of rainfall input uncertainty on predictions of stream flow are studied based extended GLUE (Generalized Likelihood Uncertainty Estimation) approach. The uncertainty in the rainfall data is implemented by systematic/non-systematic rainfall measurement analysis in Weida catchment, Germany. PDM (Probability Distribution Model) rainfall runoff model is selected for hydrological representation of the catchment. Using general correction procedure and DUE(Data Uncertainty Engine), feasible rainfall time series are generated. These series are applied to PDM in MC(Monte Carlo) and GLUE method; Posterior distributions of the model parameters are examined and behavioural model parameters are selected for simplified GLUE prediction of stream flow. All predictions are combined to develop ensemble prediction and 90 percentile of ensemble prediction, which are used to show the effects of uncertainty sources of input data and model parameters. The results show acceptable performances in all flow regime, except underestimation of the peak flows. These results are not definite proof of the effects of rainfall uncertainty on parameter estimation; however, extended GLUE approach in this study is a potential method which can include major uncertainty in the rainfall-runoff modelling.

• Structural Engineering and Mechanics
• /
• v.81 no.3
• /
• pp.293-303
• /
• 2022

As infrastructure ages and traffic load increases, serious public concerns have arisen for the well-being of bridges. The current health monitoring practice focuses on large-scale bridges rather than short span bridges. However, it is critical that more attention should be given to these behind-the-scene bridges. The relevant information about the construction methods and as-built properties are most likely missing. Additionally, since the condition of a bridge has unavoidably changed during service, due to weathering and deterioration, the material properties and boundary conditions would also have changed since its construction. Therefore, it is not appropriate to continue using the design values of the bridge parameters when undertaking any analysis to evaluate bridge performance. It is imperative to update the model, using finite element (FE) analysis to reflect the current structural condition. In this study, a FE model is established to simulate a concrete culvert bridge in New South Wales, Australia. That model, however, contains a number of parameter uncertainties that would compromise the accuracy of analytical results. The model is therefore updated with a neural network (NN) optimisation algorithm incorporating Monte Carlo (MC) simulation to minimise the uncertainties in parameters. The modal frequency and strain responses produced by the updated FE model are compared with the frequency and strain values on-site measured by sensors. The outcome indicates that the NN model updating incorporating MC simulation is a feasible and robust optimisation method for updating numerical models so as to minimise the difference between numerical models and their real-world counterparts.

• Journal of the Korean Applied Science and Technology
• /
• v.37 no.4
• /
• pp.744-754
• /
• 2020

We investigated the whether endurance exercise and MitoQ intake mediated neuroprotection are associated with mitochondrial function in 1-methyl-4-phenyl-1,2,3,6 tetrahydropyridine(MPTP) -induced mice model of Parkinson's disease. C57BL/6 male mice were randomly assigned to five groups: Normal Conrol(NC, n=10), MPTP Control(MC, n=10), MPTP +MitoQ(MQ, n=10), MPTP + Exercise(ME, n=10) and MPTP + MitoQ + Exercise(MQE, n=10). Exercise intervention groups performed the treadmill exercise for 5days/week for 5 weeks with gradual increase of intensity. MitoQ intake groups consumed the MitoQ at a concentration of 250μmol by dissolving with water during experiment period. Our data demonstrated that ME and MQE group restored MPTP-induced motor dysfunction. In addition, treatment groups(MQ, ME and MQE) increased tyrosine hydroxylase levels, and suppressed the accumulation of α-synuclein levels. Futhermore, treatment groups modulated the mitochondrial function such as upregulated mitochondrial biogenesis, increased antioxidant enzyme, enhanced a anti-apoptotic protein(e.g., BCL2), and reduced a pro-apoptotic protein(e.g., BAX). Taken together, these results suggested that endurance exercise and MitoQ intake-mediated increase in mitochondrial function contributes to improvement of aggravated dopaminergic neuronal, resulting in attenuation of motor function of Parkinson's disease.

• Current Optics and Photonics
• /
• v.5 no.4
• /
• pp.421-430
• /
• 2021

The multifocal multiphoton microscopy (MMM) enables high-speed imaging by the concurrent scanning and detection of multiple foci generated by lenslet array or diffractive optical element. The MMM system mainly suffers from crosstalk generated by scattered emission photons that form ghost images among adjacent channels. The ghost image which is a duplicate of the image acquired in sub-images significantly degrades overall image quality. To eliminate the ghost image, the photon reassignment method was established using maximum likelihood estimation. However, this post-processing method generally takes a longer time than image acquisition. In this regard, we propose a novel strategy for rapid noise reduction in the MMM system based upon Monte-Carlo (MC) simulation. Ballistic signal, scattering signal, and scattering noise of each channel are quantified in terms of photon distribution launched in tissue model based on MC simulation. From the analysis of photon distribution, we successfully eliminated the ghost images in the MMM sub-images. If the priori MC simulation under a certain optical condition is established at once, our simple, but robust post-processing technique will continuously provide the noise-reduced images, while significantly reducing the computational cost.

• Nuclear Engineering and Technology
• /
• v.54 no.1
• /
• pp.30-35
• /
• 2022

In a nuclear reactor, gamma radiation is the dominant energy deposition in non-fuel regions. Heat is generated upon gamma deposition and consequently affects the mechanical and thermal structure of the material. Therefore, the safety of samples should be carefully considered so that their integrity and quality can be retained. To evaluate relevant parameters, an in-core gamma thermometer (GT) was used to measure gamma heating (GH) throughout the operation of the McMaster nuclear reactor (MNR) at four irradiation sites. Additionally, a Monte Carlo reactor physics code (Serpent-2) was utilized to model the MNR with the GT located in the same irradiation sites used in the measurement to verify its predictions against measured GH. This research aids in the development of modeling, calculation, and prediction of the GH utilizing Serpent-2 as well as implementing a new GH measurement at the MNR core. After all uncertainties were quantified for both approaches, comparable GH profiles were observed between the measurements and calculations. In addition, the GH values found in the four sites represent a strong level of radiation based on the distance of the sample from the core. In this study, the maximum and minimum GH values were found at 0.32 ± 0.05 W/g and 0.15 ± 0.02 W/g, respectively, corresponding to 320 Sv/s and 150 Sv/s. These values are crucial to be considered whenever sample is planned to be irradiated inside the MNR core.

• Nuclear Engineering and Technology
• /
• v.54 no.3
• /
• pp.803-810
• /
• 2022

The small modular liquid-metal fast reactor (SMFR) is an important component of advanced nuclear systems. SMFRs exhibit relatively low breeding capability and constraint space for control rod installation. Consequently, control rods are deeply inserted at beginning and are withdrawn gradually to compensate for large burnup reactivity loss in a long lifetime. This paper is committed to investigating the impact of control rod compensation operation on core neutronics characteristics. This paper presents a whole core fine depletion model of long lifetime SMFR using OpenMC and the influence of depletion chains is verified. Three control rod position schemes to simulate the compensation process are compared. The results show that the fine simulation of the control rod compensation process impacts significantly the fuel burnup distribution and absorber consumption. A control rod equivalent position scheme proposed in this work is an optimal option in the trade-off between computation time and accuracy. The control position is crucial for accurate power distribution and void feedback coefficients in SMFRs. The results in this paper also show that the pin level power distribution is important due to the heterogeneous distribution in SMFRs. The fuel burnup distribution at the end of core life impacts the worth of control rods.

• Structural Engineering and Mechanics
• /
• v.83 no.3
• /
• pp.293-304
• /
• 2022

In this work, a novel reliability approach for combined high and low cycle fatigue (CCF) estimation is developed by combining active learning strategy with least squares support vector machines (LS-SVM) (named as ALS-SVM) surrogate model to address the multi-resources uncertainties, including working loads, material properties and model itself. Initially, a new active learner function combining LS-SVM approach with Monte Carlo simulation (MCS) is presented to improve computational efficiency with fewer calls to the performance function. To consider the uncertainty of surrogate model at candidate sample points, the learning function employs k-fold cross validation method and introduces the predicted variance to sequentially select sampling. Following that, low cycle fatigue (LCF) loads and high cycle fatigue (HCF) loads are firstly estimated based on the training samples extracted from finite element (FE) simulations, and their simulated responses together with the sample points of model parameters in Coffin-Manson formula are selected as the MC samples to establish ALS-SVM model. In this analysis, the MC samples are substituted to predict the CCF reliability of turbine blades by using the built ALS-SVM model. Through the comparison of the two approaches, it is indicated that the reliability model by linear cumulative damage rule provides a non-conservative result compared with that by the proposed one. In addition, the results demonstrate that ALS-SVM is an effective analysis method holding high computational efficiency with small training samples to gain accurate fatigue reliability.

• The Journal of Society for e-Business Studies
• /
• v.18 no.2
• /
• pp.257-277
• /
• 2013

Those studies in the field of Management Information Systems and the Success Model of the DeLone and McLean's Information Systems suggest that some factors related to information systems should be developed and operated to affect the performance of the user's personal and companies through the introduction and use of corporate information systems. The purpose of this study is put on searching for some factors which impact on user satisfaction about the customer information management systems of call center. We did conduct on a survey of 539 people who are working as a call center counseling employees as setting up a structural equation model which reflects previous research on working environment and job satisfaction, and modified DeLone and McLean's information system success model. The results of this study are as follows. First, seven of the eleven hypotheses that three quality of the information systems might be affecting working environment, job satisfaction, user satisfaction were adopted Second, we confirmed that the working environment works as a the partial mediation and the quality of services works as a fully mediation between system/information quality and users' satisfaction. The implications of this study are that it is necessary not only to make a good working environment but also to keep improving it in order to boost the operational performance of information systems in the future.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.26 no.1A
• /
• pp.45-54
• /
• 2006

To obtain realistic stress-strain relation in concrete, it is necessary to improve the constitutive model for creep and shrinkage of concrete. This study is made up with predicting model of creep using rheological approach and mathematical development which is solution for phenomenon of concrete creep. Long-term deformation components are combined based on traditional 4-parameters model. Creep deformation is obtained adequately using 4-parameters determined by considering aging effect and microprestress among gels. And coefficient of effective viscosity is able to represent both basic creep and total creep included drying creep. This study attempt to establish mathematical model considering effects of aging, hydration, and variations of pore humidity. It can predict both basic creep and total creep. Values of result between prediction and experiment have greater than correlation factor 99%. Additionally experimental results report bad consentaneity with highway design specification adopting FIB MC 90. Rather than those are similar to FIB MC 90 rev.99.

• Journal of the Korean Statistical Society
• /
• v.36 no.1
• /
• pp.129-148
• /
• 2007

Frailty estimates from the proportional hazards frailty model often lead us to conjecture the heterogeneity in frailty such that the variance of the frailty varies over different covariate groups (e.g. male group versus female group). For such systematic heterogeneity in frailty, we consider a regression model for the variance components in the proportional hazards frailty model, denoted by the MLFM. However, in many cases, the observed data do not show any statistically significant preference between the homogeneous frailty model and the heterogeneous frailty model. In this paper, we propose a Bayesian model averaging procedure with the reversible jump Markov chain Monte Carlo which selects the appropriate model automatically. The resulting regression coefficient estimate ignores the model uncertainty from the frailty distribution in view of Bayesian model averaging (Hoeting et al., 1999). Finally, the proposed model and the estimation procedure are illustrated through the analysis of the kidney infection data in McGilchrist and Aisbett (1991) and a simulation study is implemented.