• Proceedings of the KSR Conference
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• 2011.05a
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• pp.1085-1091
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• 2011

The dynamic stability of railway vehicle has been one of the important issues in railway safety. The dynamic simulator has been used in the study about the dynamic stability of railway vehicle and wheel/rail interface. Especially, a small scale simulator has been widely used in the fundamental study in the laboratory instead of full scale roller rig which is not cost effective and inconvenient to achieve diverse design parameters. But the technique for the design of the small scale simulator for the fundamental study about the dynamic characteristics of the wheel-rail system and the bogie system has not been well developed in Korea. Therefore, the research about the development of the small scale simulator and the bogie has been conducted. This paper presents the design of the small-scaled derailment simulator and the example design case of a small scale bogie. The simulator could be used in the study about the effect of diverse parameters such as attack angle, wheelbase and cant on dynamic behavior of the bogie and the safety parameter such as derailment coefficient and critical speed.

• Advances in concrete construction
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• v.1 no.4
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• pp.289-304
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• 2013

A reliable concrete constitutive material model is critical for an accurate numerical analysis simulation of reinforced concrete structures under extreme dynamic loadings including impact or blast. However, the formulation of concrete material model is challenging and entails numerous input parameters that must be obtained through experimentation. This paper presents a damage scale analytical model to characterize concrete material for its pre- and post-peak behavior. To formulate the damage scale model, statistical regression and finite element analysis models were developed leveraging twenty existing experimental data sets on concrete compressive strength. Subsequently, the proposed damage scale analytical model was implemented in the finite element analysis simulation of a reinforced concrete pier subjected to vehicle impact loading and the response were compared to available field test data to validate its accuracy. Field test and FEA results were in good agreement. The proposed analytical model was able to reliably predict the concrete behavior including its post-peak softening in the descending branch of the stress-strain curve. The proposed model also resulted in drastic reduction of number of input parameters required for LS-DYNA concrete material models.

• Transactions of the Korean Society of Automotive Engineers
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• v.14 no.6
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• pp.127-136
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• 2006

Prediction of diesel particulate filtration is typically made by virtue of modeling of particulate matter(PM) collection. The model is closed with filtration parameters reflecting all small scale phenomena associated with PM trapping, and these parameters are to be traced back by inversely analyzing large-scale empirical data-the pressure drop histories. Included are soot cake permeability, soot cake density, soot density in the porous filter wall, and percolation constant. In the present study, a series of single channel DPF experiment is conducted, pressure histories are inversely analyzed, and the essential filtration parameters are deducted by DPF filtration model formulated with non-linear description of soot cake regression. Sensitivity analyses of model parameters are also made. Results showed that filtration transients are significantly altered by the extent of percolation constant, and the soot density in the porous filter wall is controlling the filtration qualities in deep-bed filtration regime. In addition, effect of soot particle size on filtration quality is distinct in a period of soot cake regime.

• Structural Engineering and Mechanics
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• v.43 no.3
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• pp.371-394
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• 2012

Accurate finite element (FE) models are needed in many applications of Civil Engineering such as health monitoring, damage detection, structural control, structural evaluation and assessment. Model accuracy depends on both the model structure (the form of the equations) and the model parameters (the coefficients of the equations), and can be generally improved through that process of experimental reconciliation known as model updating. However, modelling errors, including (i) errors in the model structure and (ii) errors in parameters excluded from adjustment, may bias the solution, leading to an updated model which replicates measurements but lacks physical meaning. In this paper, an application of ambient-vibration-based model updating to a large-scale benchmark prototype of a building structure is reported in which both types of error are met. The error in the model structure, originating from unmodelled secondary structural elements unexpectedly working as resonant appendages, is faced through a reduction of the experimental modal model. The error in the model parameters, due to the inevitable constraints imposed on parameters to avoid ill-conditioning and under-determinacy, is faced through a multi-model parameterization approach consisting in the generation and solution of a multitude of models, each characterized by a different set of updating parameters. Results show that modelling errors may significantly impair updating even in the case of seemingly simple systems and that multi-model reasoning, supported by physical insight, may effectively improve the accuracy and robustness of calibration.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1998.04a
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• pp.291-300
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• 1998

This paper demonstrates how ambient vibration measurements at a limited number of locations can be effectively utilized to estimate parameters of a finite element model of a large-scale structural system involving a large number of elements. System identification using ambient vibration measurements presents a challenge requiring the use of special identification techniques, which ran deal with very small magnitudes of ambient vibration contaminated by noise without the knowledge of input farces. In the present study, the modal parameters such as natural frequencies, damping ratios, and mode shapes of the structural system were estimated by means of appropriate system identification techniques including the random decrement method. Moreover, estimation of parameters such as the stiffness matrix of the finite element model from the system response measured by a limited number of sensors is another challenge. In this study, the system stiffness matrix was estimated by using the quadratic optimization involving the computed and measured modal strain energy of the system, with the aid of a sensitivity relationship between each element stiffness and the modal parameters established by the second order inverse modal perturbation theory. The finite element models thus identified represent the actual structural system very well, as their calculated dynamic characteristics satisfactorily matched the observed ones from the ambient vibration test performed on a large-scale structural system subjected primarily to ambient wind excitations. The dynamic models identified by this study will be used for design of an active mass damper system to be installed on this structure fer suppressing its wind vibration.

• Nuclear Engineering and Technology
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• v.42 no.6
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• pp.690-703
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• 2010

Sampling based uncertainty analysis was carried out to quantify uncertainty in predictions of best estimate code RELAP5/MOD3.2 for a thermal hydraulic test (10% hot leg break LOCA) performed in the Large Scale Test Facility (LSTF) as a part of an IAEA coordinated research project. The nodalisation of the test facility was qualified for both steady state and transient level by systematically applying the procedures led by uncertainty methodology based on accuracy extrapolation (UMAE); uncertainty analysis was carried out using the Latin hypercube sampling (LHS) method to evaluate uncertainty for ten input parameters. Sixteen output parameters were selected for uncertainty evaluation and uncertainty band between $5^{th}$ and $95^{th}$ percentile of the output parameters were evaluated. It was observed that the uncertainty band for the primary pressure during two phase blowdown is larger than that of the remaining period. Similarly, a larger uncertainty band is observed relating to accumulator injection flow during reflood phase. Importance analysis was also carried out and standard rank regression coefficients were computed to quantify the effect of each individual input parameter on output parameters. It was observed that the break discharge coefficient is the most important uncertain parameter relating to the prediction of all the primary side parameters and that the steam generator (SG) relief pressure setting is the most important parameter in predicting the SG secondary pressure.

• Geomechanics and Engineering
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• v.24 no.4
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• pp.359-370
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• 2021

Joint roughness is combination of primary and secondary roughness. Ordinarily primary roughness is a geostatistical part of a joint surface that has a periodic nature but secondary roughness or unevenness is a statistical part of that which have a random nature. Using roughness generating algorithms is a useful method for evaluation of joint roughness. In this paper after determining geostatistical parameters of the joint profile, were presented two roughness generating algorithms using Mount-Carlo method for evaluation of primary (GJRGAP) and secondary (GJRGAS) roughness. These based on geostatistical parameters (range and sill) and statistical parameters (standard deviation of asperities height, SDH, and standard deviation of asperities angle, SDA) for generation two-dimensional joint roughness profiles. In this study different geostatistical regions were defined depending on the range and SDH. As SDH increases, the height of the generated asperities increases and asperities become sharper and at a specific range (a specific curve) relation between SDH and SDA is linear. As the range in GJRGAP becomes larger (the base of the asperities) the shape of asperities becomes flatter. The results illustrate that joint profiles have larger SDA with increase of SDH and decrease of range. Consequencely increase of SDA leads to joint roughness parameters such Z2, Z3 and RP increases. The results showed that secondary roughness or unevenness has a great influence on roughness values. In general, it can be concluded that the shape and size of asperities are appropriate parameters to approach the field scale from the laboratory scale.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.1
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• pp.15-21
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• 2015

In support vector machine, the values of parameters included in kernels affect strongly generalization ability. It is often difficult to determine appropriate values of those parameters in advance. It has been observed through our studies that the burden for deciding the values of those parameters in support vector regression can be reduced by utilizing ensemble learning. However, the straightforward application of the method to large scale problems is too time consuming. In this paper, we propose a method in which the original data set is decomposed into a certain number of sub data set in order to reduce the burden for parameter tuning in support vector regression with large scale data sets and imbalanced data set, particularly.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.11
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• pp.92-102
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• 1990

A new method for determining the motion parameters (scale, rotation, translation) of 2-D image is introduced. It employs Hough transform that maps the straight lines in the input image to the points in the Hough space (HS). This method makes use of the relations between the motion of an object in input image and the translations of peak points in the HS and thus derives relating equations about motion parameters especially when scale changes are involved. The derived equations make is efficient and simple to estimate motion parameters of input image, even if the scale parameter of input image is varied. Performance of this approach on an aircraft image is provided in detail in the presence of noise.

• Journal of Astronomy and Space Sciences
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• v.20 no.3
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• pp.163-174
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• 2003

The motion of 3C 120 Jet relative to the core is reasonably uniform and the VLBI scale jet connects outwards to a VLA ~ 100kpc scale. We measured the jet width variation from the center and found some indication of a power law which indicates the jet expands roughly with a constant opening angle and a constant flow velocity, $V_{f}{\cong}c$, from subparsec scales to ~ 100 kpc. With such a constant flow velocity and based on other physical parameters deduced from observed emission characteristics of the jet, we have established an equipartition jet model which might accommodate the basic parameters of the jet on subparsec scales, with which one can fit the radio intensities over all the scale of the jet even to ~100 kpc.