• Transactions of Materials Processing
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• v.14 no.1 s.73
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• pp.65-70
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• 2005

A phase mixture model was employed to simulate the deformation behaviour of metallic materials covering a wide grain size range from micrometer to nanometer scale. In this model a polycrystalline material is treated as a mixture of two phases: grain interior phase whose plastic deformation is governed by dislocation and diffusion mechanisms and grain boundary 'phase' whose plastic flow is controlled by a boundary diffusion mechanism. The main target of this study was the effect of grain size on stress and its strain rate sensitivity as well as on the strain hardening. Conventional Hall-Petch behaviour in coarse grained materials at high strain rates governed by the dislocation glide mechanism was shown to be replaced with inverse Hall-Petch behaviour in ultrafine grained materials at low strain rates, when both phases deform predominantly by diffusion controlled mechanisms. The model predictions are illustrated by examples from literature.

• Structural Engineering and Mechanics
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• v.4 no.4
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• pp.425-436
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• 1996

An application of the perturbation method to optimum structural design with random parameters is presented. It is formulated on the basis of the first-order stochastic finite element perturbation method. It also takes into full account the stress, displacement and eigenvalue constraints, together with the rates of change of the random variables. A method for calculating the sensitivity coefficients in regard to the governing equation and the first-order perturbed equation has been derived, by using a direct differentiation approach. A gradient-based nonlinear programming technique is used to solve the problem. The numerical results are specifically noted, where the stiffness parameter and external load are treated as random variables.

• Nuclear Engineering and Technology
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• v.52 no.3
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• pp.614-620
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• 2020

In a previous study, delayed hydride cracking (DHC) assessment of pressurized water reactor (PWR) spent fuel during dry storage using the threshold stress intensity factor (K_IH) was performed. However, there were a few limitations in the analysis of the cladding properties, such as oxide thickness and mechanical properties. In this study, those models were modified to include test data for irradiated materials, and the cladding creep model was introduced to improve the reliability of the DHC assessment. In this study, DHC susceptibility of PWR spent fuel during dry storage depending on the axial elevation was evaluated with the improved assessment methodology. In addition, the sensitivity of affecting parameters such as fuel burnup, hydride thickness, and crack aspect ratio are presented.

• Proceedings of the Korean Geotechical Society Conference
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• 2005.03a
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• pp.1324-1334
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• 2005

This study investigated the applicability of the Artificial Neural Network (ANN) technique for prediction of tunnel behavior. For training data collection, a series of finite element analyses were conducted for actual tunnel project site. Using the data, optimimzed ANNs were developed through a sensitivity study on internal parameters. The developed ANNs can make tunneling related predictions such as tunnel crown settlement, shotcrete lining stress, ground surface settlement, and groundwater inflow rate. The results indicated that the developed ANNs can be used as an effective and efficient tool for tunnelling related prediction in practical tunneling situations.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.8
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• pp.1822-1831
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• 1995

A general formulation of the design optimization problem with the random parameters is presented here. The formulation is based on the stochastic finite element second-order perturbation method ; it takes into full account of the stress and displacement constraints together with the rates of change of the random variables. A method of direct differentiation for calculating the sensitivity coefficients in regard to the governing equation and the second-order perturbed equation is derived. A gradient-based nonlinear programming technique is used to solve the problem. The numerical results are specifically noted, where the stiffness parameter and external load are treated as random variables.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.23 no.11 s.170
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• pp.1896-1903
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• 1999

The basic requirements to improve the joints quality of tube-to-tubesheet for heat exchangers are to obtain high residual contact pressures between the tubes and the tubesheet as well as low residual stresses in the transition zone of the tubes. The residual contact pressures and residual stresses which govern the joint quality are influenced by parameters such as material properties, geometric dimension of tube and tubesheet and expansion pressures. There are two types of tube layout patterns, triangular and square, which are frequently used for heat exchangers. The purpose of the present work is to examine the superior tube layout patterns considering the joints quality by comparing numerical results from sensitivity analyses which were performed for both of tube layout patterns.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.347-351
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• 1997

A micromachined piezoelectic cantilever transducer,which works both as a microphone and as a microspeaker,has been fabricated and tested. The 2000*2000*3.mu.m .sap2. cantilever has oxide(ZnO)piezoelectric thin film on a supporting layer of low-pressure chemical-vapor-deposited(LPCVD)low-stress siliconnitride. A highlight of the fabrication process which may also be relevant for other micromachined stuctures is the technique for producing a flat,multilayer cantilever. The measured microphone sensitivity is fairly constant at 2 mV/.mu.bar in the low frequency range and rise to 20 mV/.mu.bar at the lowest resonant frequency of 890 Hz. The 2 mV/.mu.bar sensitivity is the highest report to data for a microphone with a micromachined diaphragm. When measured into a 2 cm/sap3 coupler with 4V (zero-park)drive,the microspeaker output sound pressure level(SPL) is 75 dB at 890 Hz. It increases to approximately 100dB SPL at 4.8kHz with 6V(zero-park)drive. The measured microphone frequency response agrees well with the results of an ABAQUS simulation.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.11
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• pp.1341-1346
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• 2009

In this paper, the technique to reinforce the durability performance of structure using the sensitivity information for the frame structure is applied. The fatigue life calculation for the frame structure is performed from the quasi-static and transient analysis and the characteristics of two methods are compared for the fatigue analysis. Then the reinforcement technique is applied. First, some design variables related to the locations of fatigue failure is selected. Then sensitivities of fatigue life at fracture points with respect to the variation of design variables are calculated and the vector composed of gaps between the target life and initial life cycles is calculated. If the number of fatigue fracture points is same as the number of design variables, the variations of the design variables are calculated from the linear algebraic equation. If not, the variations of the design variables are calculated from the optimization formulation with the constraints.

• Computers and Concrete
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• v.9 no.3
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• pp.215-226
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• 2012

This article employs Support Vector Machine (SVM) for determination of fracture parameters critical stress intensity factor ($K^s_{Ic}$) and the critical crack tip opening displacement ($CTOD_c$) of concrete. SVM that is firmly based on the theory of statistical learning theory, uses regression technique by introducing ${\varepsilon}$-insensitive loss function has been adopted. The results are compared with a widely used Artificial Neural Network (ANN) model. Equations have been also developed for prediction of $K^s_{Ic}$ and $CTOD_c$. A sensitivity analysis has been also performed to investigate the importance of the input parameters. The results of this study show that the developed SVM is a robust model for determination of $K^s_{Ic}$ and $CTOD_c$ of concrete.

• 한국터널공학회:학술대회논문집
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• 2005.04a
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• pp.105-116
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• 2005

This study investigated the applicability of the Artificial Neural Network(ANN) technique for prediction of tunnel behavior. For training data collection, a series of finite element analyses were conducted for actual tunnel project site. Using the data, optimimzed ANNs were developed through a sensitivity study on internal parameters. The developed ANNs can make tunneling related predictions such as tunnel crown settlement, shotcrete lining stress, ground surface settlement, and groundwater inflow rate. The results indicated that the developed ANNs can be used as an effective and efficient tool for tunnelling related prediction in practical tunneling situations.