• Journal of the Korean Statistical Society
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• v.34 no.4
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• pp.331-344
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• 2005

Inference on current data could be more reliable if there exist similar data based on previous studies. Ibrahim and Chen (2000) utilize these data to characterize the power prior. The power prior is constructed by raising the likelihood function of the historical data to the power $a_o$, where $0\;{\le}\;a_o\;{\le}\;1$. The power prior is a useful informative prior in Bayesian inference. However, for model selection or model comparison problems, the propriety of the power prior is one of the critical issues. In this paper, we suggest two joint power priors for the power law process and show that they are proper under some conditions. We demonstrate our results with a real dataset and some simulated datasets.

• Journal of the Korean Data and Information Science Society
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• v.18 no.2
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• pp.535-541
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• 2007

The Non-homogeneous Poisson process is probably the most popular model since it can model systems that are deteriorating or improving. The renewal process is a model that is often used to describe the random occurrence of events in time. But both these models are based on too restrictive assumptions on the effect of the repair action. The Modulated Power Law Process is a suitable model for describing the failure pattern of repairable systems when both renewal-type behavior and time trend are present. In this paper we propose maximum likelihood estimation of the next failure time after the system has experienced some failures, that is, Mean Time Between Failure for the MPLP model.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.10 no.2
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• pp.41-47
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• 2006

The Renewal process and the Non-homogeneous Poisson process (NHPP) process are probably the most popular models for describing the failure pattern of repairable systems. But both these models are based on too restrictive assumptions on the effect of the repair action. For these reasons, several authors have recently proposed point process models which incorporate both renewal type behavior and time trend. One of these models is the Modulated Power Law Process (MPLP). The Modulated Power Law Process is a suitable model for describing the failure pattern of repairable systems when both renewal-type behavior and time trend are present. In this paper we propose Bayes estimation of the next failure time after the system has experienced some failures, that is, Mean Time Between Failure for the MPLP model. Numerical examples illustrate the estimation procedure.

• Computers and Concrete
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• v.29 no.4
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• pp.255-262
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• 2022

The present study investigates the effects of Cattaneo-Christov thermal effects of stagnation point in Walters-B nanofluid flow through lubrication of power-law fluid by taking the slip at the interfacial condition. The impacts of thermophoresis and Brownian motions are further accounted. The fluid impinging orthogonally on the surface is due to power-law slim coating liquid. The generalized newtonian fluid equation is used that obeys the power law constitutive equation to model our problem. The effect of velocity profiles, temperature for different values of n are investigated. The prandtl on the temperature distribution for partial slip and no slip cases is also observed. It is found that for larger values of prandtl number thermal diffusivity of fluid reduces and it enhance the decrease in temperature and boundary layer thickness.

• Journal of Applied Reliability
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• v.9 no.2
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• pp.121-130
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• 2009

The power law process model the Rate of occurrence of failures(ROCOF) with monotonic trend during the operating time. However, the power law process is inappropriate when a non-monotonic trend in the failure data is observed. In this paper we deals with the reliability modeling of the failure process of large and complex repairable system whose rate of occurrence of failures shows the non-monotonic trend. We suggest a sectional model and a change-point test based on the Schwarz information criterion(SIC) to describe the non-monotonic trend. Maximum likelihood is also suggested to estimate parameters of sectional model. The suggested methods are applied to field data from an repairable system.

• Communications for Statistical Applications and Methods
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• v.12 no.2
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• pp.483-496
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• 2005

We consider the power law process which is assumed to have multiple changepoints. We propose a binary segmentation procedure for locating all existing changepoints. We select one model between the no-changepoints model and the single changepoint model by the Bayes factor. We repeat this procedure until no more changepoints are found. Then we carry out a multiple test based on the Bayes factor through the intrinsic priors of Berger and Pericchi (1996) to investigate the system behaviour of failure times. We demonstrate our procedure with a real dataset and some simulated datasets.

• Applied Chemistry for Engineering
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• v.23 no.2
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• pp.204-209
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• 2012

In this study, kinetics data was obtained for steam reforming reaction of ethane over the commercial ruthenium catalyst. The variables of ethane steam reforming were the reaction temperature, partial pressure of ethane, and steam/ethane mole ratio. Parameters for the power rate law kinetic model and the Langmuir-Hinshelwood model were obtained from the kinetic data. Also, sizing of steam reforming reactor was performed by using PRO/II simulator. The reactor size calculated by the power rate law kinetic model was bigger than that of using the Langmuir-Hinshelwood model for the same conversion of ethane. Reactor size calculated by the Langmuir-Hinshelwood model seems to be more suitable for the reactor design because the Langmuir-Hinshelwood model was more consistent with the experimental results.

• Journal of computational fluids engineering
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• v.15 no.4
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• pp.1-8
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• 2010

This article describes the numerical investigation of turbulent blood flow in the stenosed artery bifurcation under periodic acceleration of the human body. Numerical analyses for turbulent blood flow were performed with different magnitude of periodic accelerations using a modified turbulence model which was considering drag reduction of non-Newtonian fluid. The blood was considered to be a non-Newtonian fluid which was based on the power-law viscosity. In order to validate the modified $k-{\varepsilon}$ model, numerical simulations were compared with the standard $k-{\varepsilon}$ model and the Malin's low Reynolds number turbulence model for power-law fluid. As results, the modified $k-{\varepsilon}$ model represents intermediate characteristics between laminar and standard $k-{\varepsilon}$ model, and the modified $k-{\varepsilon}$ model showed good agreements with Malin's verified power law model. Moreover, the computing time and computer resource of the modified $k-{\varepsilon}$ model were reduced about one third than low Reynolds number model including Malin's model.

• Korean Journal of Ecology and Environment
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• v.45 no.4
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• pp.420-443
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• 2012

An Individual-Based Model (IBM) was developed by employing natural and toxic survival rates of individuals to elucidate the community responses of benthic macroin-vertebrates to anthropogenic disturbance in the streams. Experimental models (dose-response and relative sensitivity) and mathematical models (power law and negative exponential distribution) were applied to determinate the individual survival rates due to acute toxicity in stressful conditions. A power law was additionally used to present the natural survival rate. Life events, covering movement, exposure to contaminants, death and reproduction, were simulated in the IBM at the individual level in small (1 m) and short (1 week) scales to produce species abundance distributions (SADs) at the community level in large (5 km) and long (1~2 years) scales. Consequently, the SADs, such as geometric series, log-series, and log-normal distribution, were accordingly observed at severely (Biological Monitoring Working Party (BMWP<10), intermediately (BMWP<40) and weakly (BMWP${\geq}50$) polluted sites. The results from a power law and negative exponential distribution were suitably fitted to the field data across the different levels of pollution, according to the Kolmogorov-Smirnov test. The IBMs incorporating natural and toxic survival rates in individuals were useful for presenting community responses to disturbances and could be utilized as an integrative tool to elucidate community establishment processes in benthic macroin-vertebrates in the streams.

• Journal of the Korean Society of Propulsion Engineers
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• v.16 no.6
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• pp.23-31
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• 2012

Present work deals three families of $SiO_2$ gelling agents which have been used to produce gel fuel based on Kerosene. Jet A-1 is chosen as fuel where power-law rheological model is used to confirm whether or not the gelification is achieved depending on the %wt of gellant. It was confirmed that the produced jelly-like substance have shear-thinning effect, and that its apparent viscosity increases as $SiO_2$ concentration increases. Compared to other gellants, gel with Aerosil(R) R972 fits most to the power-law model, while gels with Silica 230 and Silica 530 deviate from the power-law model. The rheological characteristics behaved differently depending on the mixing method(vortex mixing and manual mixing) when gellant concentration is increased.