• Communications for Statistical Applications and Methods
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• v.4 no.1
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• pp.259-269
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• 1997

Bayesian inference for a record value statistics(RVS) model of nonhomogeneous Poisson process is considered. We seal with Bayesian inference for double exponential, Gamma, Rayleigh, Gumble RVS models using Gibbs sampling and Metropolis algorithm and also explore Bayesian computation and model selection.

• Journal of computational fluids engineering
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• v.18 no.4
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• pp.25-34
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• 2013

A numerical study of a laminar natural convection of the CuO-water nanofluid in a square cavity using the Buongiorno's nonhomogeneous model is presented. All the governing equations including the volume fraction equation are discretized on a cell-centered, non-uniform grid employing the finite-volume method with a primitive variable formulation. Calculations are performed over a range of Rayleigh numbers and volume fractions of the nanopartile. From the computed results, it is shown that both the homogeneous and nonhomogeneous models predict the deterioration of the natural convection heat transfer well with an increase of the volume fraction of nanoparticle at the same Rayleigh number, which was observed in the previous experimental studies. It is also shown that the differences in the computed results of the average Nusselt number at the wall between the homogeneous and nonhomogeneous models are very small, and this indicates that the slip mechanism of the Brown diffusion and thermophoresis effects are negligible in the laminar natural convection of the nanofluid. The degradation of the heat transfer with an increase of the volume fraction of the nanoparticle in the natural convection of nanofluid is due to the increase of the viscosity and the decrease of the thermal expansion coefficient and the specific heat. It is clarified in the present study that the previous controversies between the numerical and experimental studies are owing to the different definitions of the Nusselt number.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.501-504
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• 2008

A non-homogeneous markov model which is able to simulate hourly rainfall series is developed for estimating reliable hydrological variables. The proposed approach is applied to simulate hourly rainfall series in Korea. The simulated rainfall is used to estimate the design rainfall and compared to observations in terms of reproducing underlying distributions of the data to assure model's validation. The model shows that the simulated rainfall series reproduce a similar statistical attribute with observations, and expecially maximum value is gradually increased as number of simulation increase.

• Smart Structures and Systems
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• v.13 no.4
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• pp.659-683
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• 2014

The static analysis of structures with arbitrary cross-section geometry and material lamination via a refined one-dimensional (1D) approach is presented in this paper. Higher-order 1D models with a variable order of expansion for the displacement field are developed on the basis of Carrera Unified Formulation (CUF). Classical Euler-Bernoulli and Timoshenko beam theories are obtained as particular cases of the first-order model. Numerical results of displacement, strain and stress are provided by using the finite element method (FEM) along the longitudinal direction for different configurations in excellent agreement with three-dimensional (3D) finite element solutions. In particular, a layered thin-walled cylinder is considered as first assessment with a laminated conventional cross-section. An atherosclerotic plaque is introduced as a typical structure with arbitrary cross-section geometry and studied for both the homogeneous and nonhomogeneous material cases through the 1D variable kinematic models. The analyses highlight limitations of classical beam theories and the importance of higher-order terms in accurately detecting in-plane cross-section deformation without introducing additional numerical problems. Comparisons with 3D finite element solutions prove that 1D CUF provides remarkable three-dimensional accuracy in the analysis of even short and nonhomogeneous structures with arbitrary geometry through a significant reduction in computational cost.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.49
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• pp.23-31
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• 1999

Bayesian approach using nonhomogeneous Poisson process is considered for modelling software reliability problem. The usefulness of the iterative sampling-based method increases greatly as the dimension of a problem increases. Maximum likelihood estimator and Gibbs estimator are derived. Model selection based on a predictive likelihood is studied. A numerical example is given.

• Journal of Korean Society for Quality Management
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• v.39 no.2
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• pp.170-178
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• 2011

In general, a software fault detection phenonenon is described by a software reliability model based on a nonhomogeneous Poisson process(NHPP). In this paper, we propose a software reliability growth model considering the differences of the software environments in both the testing phase and the operational phase. Also, we consider the problem of determining the optimal release time and the optimal warranty period that minimize the total expected software cost which takes account of periodic software maintenance(e.g. patch, update, etc). Finally, we analyze the sensitivity of the optimal release time and warranty period based on the fault data observed in the actual testing process.

• International Journal of Quality Innovation
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• v.5 no.1
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• pp.1-9
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• 2004

The nonhomogeneous poisson process (NHPP) is often used to model repairable systems that are subject to a minimal repair strategy, with negligible repair times. In this situation, the system can be characterized by its intensity function. There have been many NHPP models according to intensity functions. However, the intensity function of system in use can be changed because of repair or its aging. We consider the single change point model as the modification of the power law process. The shape parameter of its intensity function is changed before and after the change point. We detect the presence of the change point using Bayesian methodology. Some numerical results are also presented.

• Structural Engineering and Mechanics
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• v.58 no.5
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• pp.931-947
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• 2016

The effects of nanotechnology and smartness on the buckling reduction of pipes are the main contributions of present work. For this ends, the pipe is simulated with classical piezoelectric polymeric cylindrical shell reinforced by armchair double walled boron nitride nanotubes (DWBNNTs), The structure is subjected to combined electro-thermo-mechanical loads. The surrounding elastic foundation is modeled with a novel model namely as orthotropic nonhomogeneous Pasternak medium. Using representative volume element (RVE) based on micromechanical modeling, mechanical, electrical and thermal characteristics of the equivalent composite are determined. Employing nonlinear strains-displacements and stress-strain relations as well as the charge equation for coupling of electrical and mechanical fields, the governing equations are derived based on Hamilton's principal. Based on differential quadrature method (DQM), the buckling load of pipe is calculated. The influences of electrical and thermal loads, geometrical parameters of shell, elastic foundation, orientation angle and volume percent of DWBNNTs in polymer are investigated on the buckling of pipe. Results showed that the generated ${\Phi}$ improved sensor and actuator applications in several process industries, because it increases the stability of structure. Furthermore, using nanotechnology in reinforcing the pipe, the buckling load of structure increases.

• Proceedings of the Korean Society for Quality Management Conference
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• 1998.11a
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• pp.277-286
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• 1998

This paper investigates the problem of determining optimal replacement policies for equipment subject to failures with cyclic rates. In many situations, the system failures depend on the operating environmental conditions that vary on time, usually with periodical manners. We use nonhomogeneous Poisson processes whose rate functions exhibit cyclic behavior as well as a long-term evolutionary trend to model the stochastic process of the failures when the rate of occurrence of the failures varies periodically, for example from day to day or between seasons. In this study, we compare optimal policies under the nonhomogeneous process with/without a cyclic component in the failure rate function. The analytical results for various situations are presented along with numerical examples using simulated data.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.5
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• pp.935-944
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• 2023

In this study, the Inverse-type (: Inverse-Exponential, Inverse-Rayleigh) life distribution, which is known to be suitable for reliability research, was applied to a software development cost model based on finite failure NHPP(: Nonhomogeneous Poisson Process), and then the attributes that determine the model's performance were analyzed. Additionally, to evaluate the efficiency of the model, it was compared with the Goel-Okumoto basic model. The performance of the model was analyzed using failure time data, and MLE (: Maximum Likelihood Estimation) was applied to calculate the parameters. In conclusion, first, as a result of analyzing m(t), which determines the development cost, the Inverse-Exponential model was efficient due to its small error in the true value. Second, as a result of analyzing the release time along with the development cost, the Inverse-Rayleigh model was confirmed to be the best. Third, as a result of comprehensive evaluation of the attributes (m(t), cost, and release time) of the proposed model, the Inverse-Rayleigh model had the best performance. Therefore, if software developers can effectively utilize this research data in the early process, they will be able to proactively explore and analyze attributes that affect cost.