• Journal of Mechanical Science and Technology
• /
• v.19 no.6
• /
• pp.1280-1289
• /
• 2005

This paper presents the effects of corrosion environments of failure pressure model for buried pipelines on failure prediction by using a failure probability. The FORM (first order reliability method) is used in order to estimate the failure probability in the buried pipelines with corrosion defects. The effects of varying distribution types of random variables such as normal, lognormal and Weibull distributions on the failure probability of buried pipelines are systematically investigated. It is found that the failure probability for the MB31G model is larger than that for the B31G model. And the failure probability is estimated as the largest for the Weibull distribution and the smallest for the normal distribution. The effect of data scattering in corrosion environments on failure probability is also investigated and it is recognized that the scattering of wall thickness and yield strength of pipeline affects the failure probability significantly. The normalized margin is defined and estimated. Furthermore, the normalized margin is used to predict the failure probability using the fitting lines between failure probability and normalized margin.

• Journal of the Korean Society of Safety
• /
• v.32 no.6
• /
• pp.1-8
• /
• 2017

P-PIE is a program developed to estimate failure probability of pipes and pressure vessels considering fatigue and stress corrosion crack growth. Using the program, crack growth simulation was performed with an initially existing crack in order to examine the effects of initial crack depth distribution on the leak probability of pipes. In the simulation stress corrosion crack growth was considered and several crack depth distribution models were used. From the results it was found that the initial crack depth distribution gives great effect on the leak probability of pipes. The log-normal distribution proposed by Khaleel and Simonen gives lower leak probability compared other exponential distribution models. The effects of the number and the quality of pre-service and in-service inspections on the leak probability were also examined and it was recognized that the number and the quality of pre-service and in-service inspections are also give great effect on the leak probability. In order to reduce the leak probability of pipes in plants it is very important to improve the quality of inspections. When in-service inspection is performed every 10 years and the quality of inspection is above the very good level, the leak probability shows nearly constant value after the first inspection for an initially existing crack.

• Journal of Information Technology Services
• /
• v.4 no.1
• /
• pp.129-139
• /
• 2005

This paper proposes a framework of Operational Risk-based Business Continuity System(ORBCS), and develops protection system for operational risk through operational risk assessment and loss distribution approach based on risk management guideline announced in the basel II. In order to find out financial operational risk, business processes of domestic bank are assorted by seven event factors and eight business activities so that we can construct the system. After we find out KRI(Key Risk Indicator) index, tasks and risks, we calculated risk possibility and expected cost by analyzing quantitative data, questionnaire and qualitative approach for AHP model from the past events. Furthermore, we can assume unexpected cost loss by using loss distribution approach presented in the basel II. Each bank can also assume expected loss distributions of operational risk by seven event factors and eight business activities. In this research, we choose loss distribution approach so that we can calculate operational risk. In order to explain number of case happened, we choose poisson distribution, log-normal distribution for loss cost, and estimate model for Monte-Carlo simulation. Through this process which is measured by operational risk. of ABC bank, we find out that loss distribution approach explains closer unexpected cost directly compared than internal measurement approach, and makes less unexpected cost loss.

• Journal of Mechanical Science and Technology
• /
• v.14 no.4
• /
• pp.380-392
• /
• 2000

A typical production-distribution system consist of three main echelons representing the retailer, distributors, and a factory each with an on-site warehouse. The system is sufficiently general and realistic to represent many industrial situations. However, decision functions and parameters have been selected to apply particularly to the production and distribution of consumer durables. The flows included in the model are materials, orders, and those information flows needed to support the material and order-rate decisions. In this work, a realistic production-distribution system has been used as a basic model, which consists of three sectors: retailer, distributor, and factory. That system is a nonlinear 25th-order continuous system interconnected between the echelons. Using a modern control algorithm, a typical multi-echelon production-distribution system using a dynamic controller is numerically simulated in the nominal plant and in the perturbed plant when the piecewise constant manufacturing decision is limited by a factory manufacturing upper-limit due to capital equipment, manpower, and factory lotsize.

• Computers and Concrete
• /
• v.9 no.3
• /
• pp.179-193
• /
• 2012

The hydration of cement contributes to the performance characteristics of concrete, such as strength and durability. In order to improve the utilization efficiency of cement and its early properties, the particle size distribution (PSD) of cement varies considerably, and the effects of the particle size distribution of cement on the hydration process should be considered. In order to evaluate effects of PSD separately, experiments testing the isothermal heat generated during the hydration of cements with different particle size distributions but the same chemical composition have been carried out. The measurable hydration depth for cement hydration was proposed and deduced based on the experimental results, and a PSD hydration model was developed in this paper for simulating the effects of particle size distribution on the hydration process of cement. First, a reference hydration rate was derived from the isothermal heat generated by the hydration of ordinary Portland cement. Then, the model was extended to take into account the effect of water-to-cement ratio, hereinafter which was referred to as PSD hydration model. Finally, the PSD hydration model was applied to simulate experiments measuring the isothermal heat generated by the hydration of cement with different particle size distributions at different water-to-cement ratios. This showed that the PSD hydration model had simulated the effects of particle size distribution and water-to-cement ratio on the hydration process of cement with satisfactory accuracy.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.33 no.3
• /
• pp.130-136
• /
• 2010

In this study, we propose a new method for generating candidate solutions based on both the Cauchy and the Gaussian probability distributions in order to use the merit of the solutions generated by these distributions. The Cauchy probability distribution has larger probability in the tail region than the Gaussian distribution. Thus, the Cauchy distribution can yield higher probabilities of generating candidate solutions of large-varied variables, which in turn has an advantage of searching wider area of variable space. On the contrary, the Gaussian distribution can yield higher probabilities of generating candidate solutions of small-varied variables, which in turn has an advantage of searching deeply smaller area of variable space. In order to compare and analyze the performance of the proposed method against the conventional method, we carried out experiments using benchmarking problems of real valued functions. From the result of the experiment, we found that the proposed method based on the Cauchy and the Gaussian distributions outperformed the conventional one for most of benchmarking problems, and verified its superiority by the statistical hypothesis test.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.10 no.3
• /
• pp.1-9
• /
• 2014

The inverse Rayleigh model distribution and Rayleigh distribution model were widely used in the field of reliability station. In this paper applied using the finite failure NHPP models in order to growth model. In other words, a large change in the course of the software is modified, and the occurrence of defects is almost inevitable reality. Finite failure NHPP software reliability models can have, in the literature, exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, proposes the inverse Rayleigh and Rayleigh software reliability growth model, which made out efficiency application for software reliability. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on mean square error (MSE) and coefficient of determination($R^2$), for the sake of efficient model, were employed. In order to insurance for the reliability of data, Laplace trend test was employed. In many aspects, Rayleigh distribution model is more efficient than the reverse-Rayleigh distribution model was proved. From this paper, software developers have to consider the growth model by prior knowledge of the software to identify failure modes which can helped.

• Journal of Distribution Science
• /
• v.13 no.3
• /
• pp.5-9
• /
• 2015

Purpose -The purpose of this study was to review and analyze the four major journals of KODISA and all of their published articles of 2014 and to revise and update the existing publication standards and practices in order to improve the overall quality and reputation of these journals. Research design, data, and methodology - This study applied an analytical approach, a case study method, to analyze and examine the published articles and the publication standards and practices of four KODISA journals, JDS (1999), IJIDB (2010), EAJBM (2011), and JAFEB (2014), from their first publication. Results - In 2014, KODISA journals published a total of 171 papers - JDS (122), IJIDB and EAJBM (16 each), and JAFEB (17): 94 articles in general business and 77 articles in economics. Conclusions - KODISA journals continuously revised and updated their publication standards and practices and adopted technological support systems to enable its journals to remain independent and open access in order to ultimately become one of the world's reputable journals.

• Journal of Power System Engineering
• /
• v.14 no.1
• /
• pp.16-21
• /
• 2010

This research focused on the spray and distribution characteristics of urea solution by applying flow visualization techniques and did durability and driver test on injectors as well. The spray characteristics of urea solution was observed by CCD camera. Also, the distribution characteristics of urea solution was evaluated quantitatively as well by using 3D laser scanner equipment. It was considered that it was reasonable to use the injector for gasoline engine in order to inject the urea. The best distribution chart result was observed near 45cm distance difference between catalyst and urea spray injector. As a result of trapped urea distribution chart analysis, optimal pressure and volumetric flow rates of air and urea were derived in order to improve the distribution of Urea. This information may contribute to provide fundamental data in the future.

• The Korean Journal of Applied Statistics
• /
• v.25 no.5
• /
• pp.757-773
• /
• 2012

Traditional value at risk(S-VaR) has a difficulity in predicting the future risk of financial asset prices since S-VaR is a backward looking measure based on the historical data of the underlying asset prices. In order to resolve the deficiency of S-VaR, an economic value at risk(E-VaR) using the risk neutral probability distributions is suggested since E-VaR is a forward looking measure based on the option price data. In this study E-VaR is estimated by assuming the generalized gamma distribution(GGD) as risk neutral density function which is implied in the option. The estimated E-VaR with GGD was compared with E-VaR estimates under the Black-Scholes model, two-lognormal mixture distribution, generalized extreme value distribution and S-VaR estimates under the normal distribution and GARCH(1, 1) model, respectively. The option market data of the KOSPI 200 index are used in order to compare the performances of the above VaR estimates. The results of the empirical analysis show that GGD seems to have a tendency to estimate VaR conservatively; however, GGD is superior to other models in the overall sense.