• Journal of Welding and Joining
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• v.24 no.4
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• pp.39-49
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• 2006

The austenite grain growth model in low alloyed steel HAZ without precipitates was proposed by analyzing isothermal grain growth behavior. Steels used in this study were designed to investigate the effect of alloying elements. Meanwhile, a systematic procedure was proposed to prevent inappropriate neglect of initial grain size (D0) and misreading both time exponent and activation energy for isothermal grain growth. It was found that the time exponent was almost constant, irrespectively of temperature and alloying elements, and activation energy increased with the addition of alloying elements. From quantification of the effect of alloying elements on the activation energy, an isothermal grain growth model was presented. Finally, combining with the additivity rule, the austenite grain size in the CGHAZ was predicted.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.4
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• pp.71-77
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• 2008

This paper presents a methodology for recovering the industrial radiographic images from the effects of nonlinear distortion. Analytical approach based on the inverse square law and Beer's law is developed in order to improve a mathematic model of nonlinear type. The geometric effect due to dimensions of the radioactive source appeals on the digitized images. The relation that expresses parameters values(angle, position, absorption coefficient, length, width and pixel account) is defined in this model, matching with the sample image. To perform the search for image recovery most similar to the model, a correction procedure is designed. The application of this method on the radiographic images of steel tubes is shown and recovered results are discussed.

• 한국전산유체공학회:학술대회논문집
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• 2008.03b
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• pp.109-112
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• 2008

In this work, a mathematical heat transfer model of a walking-beam type reheating furnace that can predict the formation and growth of the scale layer, which is produced due to oxidative reaction between the furnace oxidizing atmosphere and the steel surface in the reheating furnace, has been developed. The model can also predict the heat flux distribution within the furnace and the temperature distribution in the slab and scale throughout the reheating furnace process by considering the heat exchange between the slab and its surroundings in the furnace, including radiant heat transfer among the slabs, the skids, the hot gases and the furnace wall as well as the gas convection heat transfer in the furnace. Using the model developed in this work, the effects of the scale layer on the heat transfer characteristics and temperature behavior of the slab is investigated. A comparison is also made between the predictions of the present model and the data from an in situ measurement in the furnace, and a reasonable agreement is founded.

• Corrosion Science and Technology
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• v.16 no.2
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• pp.64-68
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• 2017

The interactions between corrosion pits on stainless steel under loading conditions are studied by using a cellular automata model coupled with finite element method at a mesoscopic scale. The cellular automata model focuses on a metal/film/electrolyte system, including anodic dissolution, passivation, diffusion of hydrogen ions and salt film hydrolysis. The Chopard block algorithm is used to improve the diffusion simulation efficiency. The finite element method is used to calculate the stress concentration on the pit surface during pit growth, and the effect of local stress and strain on anodic current is obtained by using the Gutman model, which is used as the boundary conditions of the cellular automata model. The transient current characteristics of the interactions between corrosion pits under different simulation factors including the breakdown of the passive film at the pit mouth and the diffusion of hydrogen ions are analyzed. The analysis of the pit stability product shows that the simulation results are close to the experimental conclusions.

• Earthquakes and Structures
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• v.2 no.2
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• pp.189-206
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• 2011

In this study, the subspace stochastic realization theories (SSR model I and SSR model II) have been applied to a real bridge for estimating its dynamic characteristics (natural frequencies, damping constants, and vibration modes) under ambient vibration. A numerical simulation is carried out for an arch-type steel truss bridge using a white noise excitation. The estimates obtained from this simulation are compared with those obtained from the Finite Element (FE) analysis, demonstrating good agreement and clarifying the excellent performance of this method in estimating the structural dynamic characteristics. Subsequently, these methods are applied to the vibration induced by both strong and weak winds as obtained by remote monitoring of the Kabashima bridge (an arch-type steel truss bridge of length 136 m, and situated in Nagasaki city). The results obtained with this experimental data reveal that more accurate estimates are obtained when strong wind vibration data is used. In contrast, the vibration data obtained from weak wind provides accurate estimates at lower frequencies, and inaccurate accuracy for higher modes of vibration that do not get excited by the wind of lower intensity. On the basis of the identified results obtained using both simulated data and monitored data from a real bridge, it is determined that the SSR model II realizes more accurate results than the SSR model I. In general, the approach investigated in this study is found to provide acceptable estimates of the dynamic characteristics of highway bridges as well as for the vibration monitoring of bridges.

• Computers and Concrete
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• v.23 no.4
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• pp.281-294
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• 2019

The post-fire behavior of structural elements and the cooling process has always been one of the main concerns of the structural engineers. The structures can be cooled at different rates, where they affect the structure's behavior. In the present study, a numerical model has been developed using the Abaqus program to investigate the effect of cooling rate on the post-fire behavior of the CFST column. To verify the model, results of an experimental study performed on CFST columns within a full heating and cooling cycle have been used. In this model, coMParison of the residual strength has been employed in order to examine the behavior of CFST column under different cooling rates. Furthermore, a parametric study was carried out on the strength of steel and concrete, the height of the specimens, the axial load ratio and the cross-sectional shape of the specimen through the proposed model. It was observed that the cooling rate affects the behavior of the column after the fire, and thus the higher the specimen's temperature is, the more effect it has on the behavior. It was also noticed that water cooling had slightly more residual strength than natural cooling. Furthermore, it was recognized from the parametric study, that by increasing the strength of steel and concrete and the load ratio, as well as modifying the cross-sectional shape from circular to square, residual strength of column at the cooling phase was less than that of the heating phase. In addition, with reducing column height, no change was witnessed in the column behavior after the cooling phase.

• Structural Engineering and Mechanics
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• v.68 no.6
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• pp.691-700
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• 2018

Ground granulated blast furnace slag (GGBS) is a by product obtained from iron and steel industries, useful in the design and development of high quality cement paste/mortar and concrete. This paper investigates the applicability of relevance vector machine (RVM) based regression model to predict the compressive strength of various GGBS based concrete mixes. Compressive strength data for various GGBS based concrete mixes has been obtained by considering the effect of water binder ratio and steel fibres. RVM is a machine learning technique which employs Bayesian inference to obtain parsimonious solutions for regression and classification. The RVM is an extension of support vector machine which couples probabilistic classification and regression. RVM is established based on a Bayesian formulation of a linear model with an appropriate prior that results in a sparse representation. Compressive strength model has been developed by using MATLAB software for training and prediction. About 70% of the data has been used for development of RVM model and 30% of the data is used for validation. The predicted compressive strength for GGBS based concrete mixes is found to be in very good agreement with those of the corresponding experimental observations.

• Nuclear Engineering and Technology
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• v.51 no.2
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• pp.561-572
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• 2019

In the design criterion for the nuclear power plant piping system, the limit state of the piping against an earthquake is assumed to be plastic collapse. The failure of a common piping system, however, means the leakage caused by the cracks. Therefore, for the seismic fragility analysis of a nuclear power plant, a method capable of quantitatively expressing the failure of an actual piping system is required. In this study, it was conducted to propose a quantitative failure criterion for piping system, which is required for the seismic fragility analysis of nuclear power plants against critical accidents. The in-plane cyclic loading test was conducted to propose a quantitative failure criterion for steel pipe elbows in the nuclear power plant piping system. Nonlinear analysis was conducted using a finite element model, and the results were compared with the test results to verify the effectiveness of the finite element model. The collapse load point derived from the experiment and analysis results and the damage index based on the stress-strain relationship were defined as failure criteria, and seismic fragility analysis was conducted for the piping system of the BNL (Brookhaven National Laboratory) - NRC (Nuclear Regulatory Commission) benchmark model.

• Corrosion Science and Technology
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• v.19 no.6
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• pp.302-309
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• 2020

This study aimed to predict the pitting corrosion characteristics of AL-6XN super-austenitic steel using multiple linear regression. The variables used in the model are degree of sensitization, temperature, and pH. Experiments were designed and cyclic polarization curve tests were conducted accordingly. The data obtained from the cyclic polarization curve tests were used as training data for the multiple linear regression model. The significance of each factor in the response (critical pitting potential, repassivation potential) was analyzed. The multiple linear regression model was validated using experimental conditions that were not included in the training data. As a result, the degree of sensitization showed a greater effect than the other variables. Multiple linear regression showed poor performance for prediction of repassivation potential. On the other hand, the model showed a considerable degree of predictive performance for critical pitting potential. The coefficient of determination (R2) was 0.7745. The possibility for pitting potential prediction was confirmed using multiple linear regression.

• Steel and Composite Structures
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• v.48 no.5
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• pp.485-498
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• 2023

The need for carbon neutrality in the world strives the construction industry to reduce the use of construction materials. Aiming to this, recycled aggregate concrete (RAC) could be used as it reduces the carbon dioxide emissions. Currently, RAC is mainly used in non-structural members of civil constructions, seldom used in structural members. To broaden its structural use, a new type of composite column, i.e., the square and rectangular RAC filled FRP tubes (CFFTs), has been concerned in this study. The investigation on their axial compressive behavior through physical test and numerical analysis demonstrated that the load-carrying capacity of such column is reduced with the increase of replacement ratio of recycled aggregate and aspect ratio of section but can be improved by the increase of FRP confining stiffness and corner radius, said capacity can be equivalent to their steel reinforced concrete counterparts. At failure, the hoop strain at corner of tube is unexpectedly smaller than that at flat side of the tube although the FRP tube ruptured at its corner first, revealing a premature failure. Besides, a design-oriented stress-strain model of concrete and an analysis-oriented finite element model are proposed to predict the load-strain response of square and rectangular CFFT columns, which facilitates the engineering use of RAC in load-carrying structural members.