• Earthquakes and Structures
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• v.21 no.5
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• pp.551-562
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• 2021

In this study, the generalized intensity measure (IM) named I_Npg is analyzed. The recently proposed proxy of the spectral shape named N_pg is the base of this intensity measure, which is similar to the traditional N_p based on the spectral shape in terms of pseudo-acceleration; however, in this case the new generalized intensity measure can be defined through other types of spectral shapes such as those obtained with velocity, displacement, input energy, inelastic parameters and so on. It is shown that this IM is able to increase the efficiency in the prediction of nonlinear behavior of structures subjected to earthquake ground motions. For this work, the efficiency of two particular cases (based on acceleration and velocity) of the generalized I_Npg to predict the peak floor acceleration demands on steel frames under 30 earthquake ground motions with respect to the traditional spectral acceleration at first mode of vibration Sa(T₁) is compared. Additionally, a 3D reinforced concrete building and an irregular steel frame is used as a basis for comparison. It is concluded that the use of velocity and acceleration spectral shape increase the efficiency to predict peak floor accelerations in comparison with the traditional and most used around the world spectral acceleration at first mode of vibration.

• Geomechanics and Engineering
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• v.36 no.4
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• pp.355-366
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• 2024

The original elastoplastic Hardening Soil model is formulated actually partly under hexagonal pyramidal Mohr-Coulomb failure criterion, and can be only used in specific stress paths. It must be completely generalized under Mohr-Coulomb criterion before its usage in engineering practice. A set of generalized constitutive equations under this criterion, including shear and volumetric yield surfaces and hardening laws, is proposed for Hardening Soil model in principal stress space. On the other hand, a Mohr-Coulumb type yield surface in principal stress space comprises six corners and an apex that make singularity for the normal integration approach of constitutive equations. With respect to the isotropic nature of the material, a technique for processing these singularities by means of Koiter's rule, along with a transforming approach between both stress spaces for both stress tensor and consistent stiffness matrix based on spectral decomposition method, is introduced to provide such an approach for developing generalized Hardening Soil model in finite element analysis code ABAQUS. The implemented model is verified in comparison with the results after the original simulations of oedometer and triaxial tests by means of this model, for volumetric and shear hardenings respectively. Results from the simulation of oedometer test show similar shape of primary loading curve to the original one, while maximum vertical strain is a little overestimated for about 0.5% probably due to the selection of relationships for cap parameters. In simulation of triaxial test, the stress-strain and dilation curves are both in very good agreement with the original curves as well as test data.

• Journal of the Korean GEO-environmental Society
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• v.4 no.2
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• pp.77-91
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• 2003

The Hoek-Brown failure criterion for rock masses developed first in 1980 is widely accepted and has been applied in a variety of rock engineering problems including slope analyses. The failure criterion was modified over the years because rock mass strength by the original failure criterion in 1980 was overestimated. The modified failure criterion, named Generalized Hoek-Brown Failure Criterion, was proposed with a new classification called the Geological Strength Index(GSI) in 1994. Generally, Hoek-Brown failure criterion is applied in numerical analyses of rock mass behaviors using equivalent Mohr-Coulomb parameters estimated by linear regression method. But these parameters estimated by this method have some inaccuracies to be applied and to be incorporated into numerical models and limit equilibrium programs. The most important issue is that this method cannot take account of non-linear characteristics of Hoek-Brown criterion, therefore, equivalent Mohr-Coulomb parameters is used as constant values regardless of field stress distribution in rock masses. In this study, the numerical analysis on rock slope stability considering non-linear characteristics of Hoek-Brown failure criterion was carried out. Futhermore, by the latest Hoek-Brown failure criterion in 2002, the revised estimating method of equivalent Mohr-Coulomb parameters was applied and rock mass damage criterion is introduced to account for the strength reduction due to stress relaxation and blast damge in slope stability.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.2
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• pp.122-133
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• 2021

Cultivar parameter calibration can be affected by the reliability of the input data to a crop growth model. In South Korea, two sets of weather stations, which are included in the automated synoptic observing system (ASOS) or the automatic weather system (AWS), are available for preparation of the weather input data. The objectives of this study were to estimate the cultivar parameter using those sets of weather data and to compare the uncertainty of these parameters. The cultivar parameters of CERES-Rice model for Shindongjin cultivar was calibrated using the weather data measured at the weather stations included in either ASO S or AWS. The observation data of crop growth and management at the experiment farms were retrieved from the report of new cultivar development and research published by Rural Development Administration. The weather stations were chosen to be the nearest neighbor to the experiment farms where crop data were collected. The Generalized Likelihood Uncertainty Estimation (GLUE) method was used to calibrate the cultivar parameters for 100 times, which resulted in the distribution of parameter values. O n average, the errors of the heading date decreased by one day when the weather input data were obtained from the weather stations included in AWS compared with ASO S. In particular, reduction of the estimation error was observed even when the distance between the experiment farm and the ASOS stations was about 15 km. These results suggest that the use of the AWS stations would improve the reliability and applicability of the crop growth models for decision support as well as parameter calibration.

• Korean Journal of Optics and Photonics
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• v.16 no.5
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• pp.446-449
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• 2005

In a directional coupler, the design process requires repeated calculation of the characteristics of every changed structure, because it is generally difficult to expect the extinction ratio to be optimized over the entire variation of design parameters. In this paper, we systematically simulated the extinction ratio as a function of the design parameters, and analyzed the general tendency of that characteristic. In other words, we could find the generalized extinction ratio curve if the separation distance is normalized by the waveguide width. Here, the extinction ratio is shown to be increased as the normalized frequency (v) and the ratio (d) of the separation distance over the waveguide width were increased. For various structures with same ratio d, all corresponding extinction ratio curves as a function of v coincide with each other. We showed the usefulness of the generalized extinction ratio curve by applying it to the design and the fabrication of 1310/l550 nm demultiplexer, as it was convenient to design a shorter directional coupler with targeted extinction ratio from this curve.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.3B
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• pp.259-267
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• 2009

Generalized Extreme Value (GEV) distribution is recommended for flood frequency and extreme rainfall distribution in many country. L-moment method is the most common estimation procedure for the GEV distribution. In this study, the relationships between the cross-site correlations between extreme events and the cross-correlation of estimators of L-moment ratios (L-moment Coefficient of Variation (L-CV) and L-moment Coefficient of Skewness (L-CS)) for data generated from GEV distribution were derived by Monte Carlo simulation. Those relationships were fit to the simple power function. In this Monte Carlo simulation, GEV+ distribution were employed wherein unrealistic negative values were excluded. The simple power models provide accurate description of the relationships between cross-correlation of data and cross-correlation of L-moment ratios. Estimated parameters and accuracies of the power functions were reported for different GEV distribution parameters combinations. Moreover, this study provided a description about regional regression approach using Generalized Least Square (GLS) regression method which require the cross-site correlation among L-moment estimators. The relationships derived in this study allow regional GLS regression analyses of both L-CV and L-CS estimators that correctly incorporate the cross-correlation among GEV L-moment estimators.

• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.4
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• pp.121-133
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• 2015

The TANK model has been widely used in rainfall-runoff modeling due to its simplicity of concept and computation while achieving forecast accuracy. A major barrier to the model application is to determine parameter values for ungauged watersheds, leading to the need of a method for the parameter estimation. The objective of this study was to develop regression equations for estimating the 3th TANK model parameters considering their variations for the ungauged watersheds. Thirty watersheds of dam sites and stream stations were selected for this study. A genetic algorithm was used to optimize TANK model parameters. Watershed characteristics used in this study include land use percent, watershed area, watershed length, and watershed average slope. Generalized equations were derived by correlating to the optimized parameters and the watershed characteristics. The results showed that the TANK model, with the parameters determined by the developed regression equations, performed reasonably with 0.60 to 0.85 of Nash-Sutcliffe efficiency for daily runoff. The developed regression equations for the TANK model can be applied for the runoff simulation particularly for the ungauged watersheds, which is common for upstream of agricultural reservoirs in Korea.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.7
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• pp.754-764
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• 2016

To understand and analyze SNS(Social Network Service) two important classes of networks, small-world and scale-free networks have gained a lot of research interests. In this study, a generalized network generation method is developed, which can produce small-world network, scale-free network, or network with the properties of both small-world and scale-free by controlling two input parameters. By tuning one parameter we can represent the small-world property and by tuning the other one we can represent both scale-free and small-world properties. For the network measures to represent small-world and scale-free properties clustering coefficient, average shortest path distance and power-law property are used. Using the model proposed in this study we can have more clear understanding about relationships between small-world network and scale-free network. Using numerical examples we have verified the effects of two parameters on clustering coefficient, average shortest path distance and power-law property. Through this investigation it can be shown that small-world network, scale-free network or both can be generated by tuning two input parameters properly.

• Journal of Korea Water Resources Association
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• v.42 no.10
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• pp.773-783
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• 2009

The effects of rainfall input uncertainty on predictions of stream flow are studied based extended GLUE (Generalized Likelihood Uncertainty Estimation) approach. The uncertainty in the rainfall data is implemented by systematic/non-systematic rainfall measurement analysis in Weida catchment, Germany. PDM (Probability Distribution Model) rainfall runoff model is selected for hydrological representation of the catchment. Using general correction procedure and DUE(Data Uncertainty Engine), feasible rainfall time series are generated. These series are applied to PDM in MC(Monte Carlo) and GLUE method; Posterior distributions of the model parameters are examined and behavioural model parameters are selected for simplified GLUE prediction of stream flow. All predictions are combined to develop ensemble prediction and 90 percentile of ensemble prediction, which are used to show the effects of uncertainty sources of input data and model parameters. The results show acceptable performances in all flow regime, except underestimation of the peak flows. These results are not definite proof of the effects of rainfall uncertainty on parameter estimation; however, extended GLUE approach in this study is a potential method which can include major uncertainty in the rainfall-runoff modelling.

• Journal of Korean Society of Disaster and Security
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• v.13 no.4
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• pp.25-36
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• 2020

An increasing frequency and intensity of natural disasters have been observed due to climate change. To better prepare for these, the MOIS (ministry of the interior and safety) announced a comprehensive plan for minimizing damages associated with natural disasters, including drought and heavy snowfall. The spatial-temporal pattern of snowfall is greatly influenced by temperature and geographical features. Heavy snowfalls are often observed in Gangwon-do, surrounded by mountains, whereas less snowfall is dominant in the southern part of the country due to relatively high temperatures. Thus, snow depth data often contains zeros that can lead to difficulties in the selection of probability distribution and estimation of the parameters. A generalized mixture distribution approach to a maximum snow depth series over the southern part of Korea (i.e., Changwon, Tongyeoung, Jinju weather stations) are located is proposed to better estimate a threshold (𝛿) classifying discrete and continuous distribution parts. The model parameters, including the threshold in the mixture model, are effectively estimated within a Bayesian modeling framework, and the uncertainty associated with the parameters is also provided. Comparing to the Daegwallyeong weather station, It was found that the proposed model is more effective for the regions in which less snow depth is observed.