• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.873-876
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• 2002

This paper presents the effect of internal corrosion, external corrosion, material properties, operation condition, earthquake, traffic load and design thickness in pipeline on the failure prediction using a failure probability model. A nonlinear corrosion is used to represent the loss of pipe wall thickness with time. The effects of environmental, operational, and design random variables such as a pipe diameter, earthquake, fluid pressure, a corrosion rate, a material yield stress and a pipe thickness on the failure probability are systematically investigated using a failure probability model for the corrosion pipeline.

• Proceedings of the Korean Reliability Society Conference
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• 2002.06a
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• pp.403-410
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• 2002

This paper presents the effect of internal corrosion, external corrosion, material properties, operation condition, earthquake, traffic load and design thickness in pipeline on the failure prediction using a failure probability model. A nonlinear corrosion is used to represent the loss of pipe wall thickness with time. The effects of environmental, operational, and design random variables such as a pipe diameter, earthquake, fluid pressure, a corrosion rate, a material yield stress and a pipe thickness on the failure probability are systematically investigated using a failure probability model for the corrosion pipeline.

• Journal of the Korean Statistical Society
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• v.9 no.1
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• pp.97-108
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• 1980

Variance components model appears often in designing experiments including time series data analysis. This paper is investigating the properties of the various procedures in estimating variance components for the two-way random model without interaction under normality. In this age of computer-oriented computations, MINQUE is found to be quite practicla because of the robustness with respect to the design configurations and parameters. Also adjusted AOV type estimation procedure is found to yield superior results over the unadjusted one.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1998.04a
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• pp.157-164
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• 1998

An elasto-plastic stochastic finite element method is developed to evaluate the probability of failure of the underground structure. The Mohr-Coulomb failure criteria is adopted for yield condition. The material properties such as the elastic modulus and the cohesion are assumed to be statistically independent random variables which are modeled as spatial stochastic fields. The displacements around the excavated area and the probability of the failure are examined by varying the coefficient of variance for each variables. It is found that the developed procedure can provide the proper probabilistic information about the failure of the underground structure

• Journal of Korean Society of Steel Construction
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• v.9 no.2 s.31
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• pp.229-235
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• 1997

In order to check the influence of the randomness in yield strengths on the energy dissipation capacity of steel structures, behaviour factors applied for the "Response Spectrum Method" and their distributions are determined in this study with 7 steel framed models. Also 4 artificial accelerograms simulated with a given spectrum are applied to check the influence of the randomness in seismic action on the behviour factor. To execute numerous time-step calculations for the investigation a time-step analysis method is developed and applied after the reliability estimation to determine the action effects.

• Structural Engineering and Mechanics
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• v.59 no.5
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• pp.853-866
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• 2016

This paper examines a methodology for computing the probability of structural failure of reinforced concrete beams subjected to fire. The significant load variables considered are dead load, sustained live load and fire temperature. Resistance is expressed in terms of moment capacity with random variables taken as yield strength of steel, concrete class (or grade of concrete), beam width and depth. The flexural capacity is determined based on the design equations recommended in Indian standard IS456:2000. Simplified method named $500^{\circ}C$ isotherm method detailed in Eurocode 2 is incorporated for fire design. A transient thermal analysis is conducted using finite element software ANSYS$^{(R)}$ Release15. Reliability is evaluated from the initial state to 4h of fire exposure based on the first order reliability method (FORM). A procedure is coded in MATLAB for finding the reliability index. This procedure is validated with available literature. The effect of various parameters like effective cover, yield strength of steel, grade of concrete, distribution of reinforcement bars and aggregate type on reliability indices are studied. Parameters like effective cover of concrete, yield strength of steel has a significant effect on reliability of beams. Different failure modes like limit state of flexure and limit state of shear are checked.

• Journal of Broadcast Engineering
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• v.21 no.6
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• pp.913-919
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• 2016

In this paper, we propose the visual tracking algorithm that takes advantage of multiple random walkers. We first show the tracking method based on support vector machine as [1] and suggest a method that suppresses feature vectors extracted from backgrounds while preserve features vectors from foregrounds. We also show how to discriminate between foregrounds and backgrounds. Learned by reducing influences of backgrounds, support vector machine can clearly distinguish foregrounds and backgrounds from the image whose target objects are similar to backgrounds and occluded by another object. Thus, the algorithm can track target objects well. Furthermore, we introduce a simple method improving tracking speed. Finally, experiments validate that proposed algorithm yield better performance than the state-of-the-art trackers on the widely-used benchmark dataset with high speed.

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.9
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• pp.1387-1399
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• 2020

Objective: The objective of this study was to estimate the genetic parameters and trends for milk, fat, and protein yields in the first three lactations of Thai dairy cattle using a 3-trait,-3-lactation random regression test-day model. Methods: Data included 168,996, 63,388, and 27,145 test-day records from the first, second, and third lactations, respectively. Records were from 19,068 cows calving from 1993 to 2013 in 124 herds. (Co) variance components were estimated by Bayesian methods. Gibbs sampling was used to obtain posterior distributions. The model included herd-year-month of testing, breed group-season of calving-month in tested milk group, linear and quadratic age at calving as fixed effects, and random regression coefficients for additive genetic and permanent environmental effects, which were defined as modified constant, linear, quadratic, cubic and quartic Legendre coefficients. Results: Average daily heritabilities ranged from 0.36 to 0.48 for milk, 0.33 to 0.44 for fat and 0.37 to 0.48 for protein yields; they were higher in the third lactation for all traits. Heritabilities of test-day milk and protein yields for selected days in milk were higher in the middle than at the beginning or end of lactation, whereas those for test-day fat yields were high at the beginning and end of lactation. Genetics correlations (305-d yield) among production yields within lactations (0.44 to 0.69) were higher than those across lactations (0.36 to 0.68). The largest genetic correlation was observed between the first and second lactation. The genetic trends of 305-d milk, fat and protein yields were 230 to 250, 25 to 29, and 30 to 35 kg per year, respectively. Conclusion: A random regression model seems to be a flexible and reliable procedure for the genetic evaluation of production yields. It can be used to perform breeding value estimation for national genetic evaluation in the Thai dairy cattle population.

• Composites Research
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• v.12 no.4
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• pp.42-54
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• 1999

FMLC(Fiber-Metal Laminate Composites) is a new structural material combining thin metal laminate with adhesive fiber prepreg, it nearly include all the advantage of metallic materials, for example: good plasticity, impact resistance, processibility, light weight and excellent fatigue properties. This research studied the optimum design of the FMLC subject to various loading conditions using genetic algorithm. The finite element method based on the shear deformation theory was used for the analysis of FMLC. Tasi-Hill failure criterion and Miser yield criterion were taken as fitness functions of the fiber prepreg and the metal laminate, respectively. The design variables were fiber orientation angles. In genetic algorithm, the tournament selection and the uniform crossover method were used. The elitist model was also used to be effective evolution strategy and the creeping random search method was adopted in order to approach a solution with high accuracy. Optimization results were given for various loading conditions and compared with CFRP(Carbon Fiber Reinforced Plastic). The results show that the FMLC is more excellent than the CFRP in point and uniform loading conditions and it is more stable to unexpected loading because the deviation of failure index is smaller than that of CFRP.

• Journal of the Korean Ceramic Society
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• v.54 no.6
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• pp.506-510
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• 2017

One of the characteristics of polycrystalline graphene that determines its material properties is grain size. Mechanical properties such as Young's modulus, yield strain and tensile strength depend on the grain size and show a reverse Hall-Petch effect at small grain size limit for some properties under certain conditions. While there is agreement on the grain size effect for Young's modulus and yield strain, certain MD simulations have led to disagreement for tensile strength. Song et al. showed a decreasing behavior for tensile strength, that is, a pseudo Hall-Petch effect for the small grain size domain up to 5 nm. On the other hand, Sha et al. showed an increasing behavior, a reverse Hall-Petch effect, for grain size domain up to 10 nm. Mortazavi et al. also showed results similar to those of Sha et al. We suspect that the main difference of these two inconsistent results is due to the different modeling. The modeling of polycrystalline graphene with regular size and (hexagonal) shape shows the pseudo Hall-Petch effect, while the modeling with random size and shape shows the reverse Hall-Petch effect. Therefore, this study is conducted to confirm that different modeling is the main reason for the different behavior of tensile strength of the polycrystalline structures. We conducted MD simulations with models derived from the Voronoi tessellation for two types of grain size distributions. One type is grains of relatively similar sizes; the other is grains of random sizes. We found that the pseudo Hall-Petch effect and the reverse Hall-Petch effect of tensile strength were consistently shown for the two different models. We suspect that this result comes from the different crack paths, which are related to the grain patterns in the models.