• Computers and Concrete
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• v.34 no.3
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• pp.307-328
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• 2024

The concrete damage plasticity (CDP) model is widely used to simulate concrete behaviour using either implicit or explicit analysis methods. To effectively execute the models and resolve convergence issues in implicit analysis, activating the viscosity parameter of this material model is a common practice. Despite the frequent application of implicit analysis to analyse concrete structures with the CDP model, the viscosity parameter significantly varies among available models and lacks consistency. The adjustment of the viscosity parameter at the element/structural level disregards its indirect impact on the material. Therefore, the accuracy of the numerical model is confined to the validated range and might not hold true for other values, often explored in parametric studies subsequent to validations. To address these challenges and develop a unified numerical model for varied conditions, a quasi-static analysis using the explicit solver was conducted in this study. Fifteen thick flat plates tested under load control with different geometries and different eccentric loads were considered to verify the accuracy of the model. The study first investigated various concrete material behaviours under compression and tension as well as the concrete tensile strength to identify the most reliable models from previous methodologies. The study compared the results using both implicit and explicit analysis. It was found that, in implicit analysis, the viscosity parameter should be as low as 0.0001 to avoid affecting material properties. However, at the structural level, the optimum value may need adjustment between 0.00001 to 0.0001 with changing geometries and loading type. This observation raises concerns about further parametric study if the specific value of the viscosity parameter is used. Additionally, activating the viscosity parameter in load control simulations confirmed its inability to capture the peak load. Conversely, the unified explicit model accurately simulated the behaviour of the test specimens under varying geometries, load eccentricities, and column sizes. This study recommends restricting implicit solutions to the viscosity values proposed in this research. Alternatively, for highly nonlinear problems under load control simulation, explicit analysis stands as an effective approach, ensuring unified parameters across a wide range of applications without convergence problems.

• Journal of the Korean Data and Information Science Society
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• v.18 no.1
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• pp.11-16
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• 2007

Since the seminal work of Engle (1982), many researchers and practitioners have developed ARCH-type models to deal with volatility modelling, which, for instance, is crucial to perform the task of derivative pricing, measuring risk, and risk hedging. In this paper, we base the GARCH(1,1) model to analyze the KOSPI200 data, and perform the CUSUM test for detecting parameter changes in the GARCH model. It is shown that the data suffers from a parameter change.

• Structural Engineering and Mechanics
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• v.65 no.5
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• pp.505-511
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• 2018

Recently, a new foundation model called "Dynamic foundation model" was proposed for the dynamic analysis of structures on the foundation. This model includes a linear elastic spring, shear layer, viscous damping and the special effects of mass density parameter of foundation during vibration. However, the relationship of foundation property parameters with the experimental parameter of the influence of foundation mass also has not been established in previous research. Hence, the purpose of the paper presents a simple experimental model in order to establish relationships between foundation properties such as stiffness, depth of foundation and experimental parameter of the influence of foundation mass. The simple experimental model is described by a steel plate connected with solid rubber layer as a single degree of freedom system including an elastic spring connected with lumped mass. Based on natural circular frequencies of the experimental models determined from FFT analysis plots of the time history of acceleration data, the experimental parameter of the influence of foundation mass is obtained and the above relationships are also discussed.

• Geomechanics and Engineering
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• v.21 no.4
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• pp.349-356
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• 2020

Rock brittleness, which is closely related to the failure modes, plays a significant role in the design and construction of many rock engineering applications. However, the brittle-ductile failure transition is mostly ignored by the current statistical damage constitutive model, which may misestimate the failure strength and failure behaviours of intact rock. In this study, a new statistical damage model considering rock brittleness is proposed for brittle to ductile behaviour of rocks using brittleness index (BI). Firstly, the statistical constitutive damage model is reviewed and a new statistical damage model considering failure mode transition is developed by introducing rock brittleness parameter-BI. Then the corresponding damage distribution parameters, shape parameter m and scale parameter F₀, are expressed in terms of BI. The shape parameter m has a positive relationship with BI while the scale parameter F₀ depends on both BI and ε_e. Finally, the robustness and correctness of the proposed damage model is validated using a set of experimental data with various confining pressure.

• Journal of Korean Society of Forest Science
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• v.95 no.5
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• pp.569-579
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• 2006

This study focuses on the application of multi-criteria performance measures based on the concept of equifinality to the calibration of the rainfall-runoff model TOPMODEL in a small deciduous forest catchment. The performance of each parameter set was evaluated by six performance measures, individually, and each set was identified as a behavioral or non-behavioral parameter set by a given behavioral acceptance threshold. Many behavioral parameter sets were scattered throughout the parameter space, and the range of model behavior and the sensitivity for each parameter varied considerably between the different performance measures. Sensitivity was very high in some parameters, and varied depending on the kind of performance measure as well. Compatibilities of behavioral parameter sets between different performance measures also varied, and very few parameter sets were selected to be used in making god predictions for all performance measures. Since different behavioral parameter sets with different likelihood weights were obtained for each performance measure, the decision on which performance measure to be used may be very important to achieve the goal of study. Therefore, one or more suitable performance measures should be selected depending on the environment and the goal of a study, and this may lead to decrease model uncertainty.

• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.2721-2731
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• 2018

This study purposes to derive the predictive model for the cold tolerance of Brassica napus, using the data collected in the Tree Breeding Lab of Gyeongsang National University during July and August of 2016. Three Brassica napus samples were treated at each of low temperatures from $4^{\circ}C$ to $-12^{\circ}C$ by decrement of $4^{\circ}C$, step by step, and electrolyte leakage levels were measured at each stage. Electrolyte leakages were observed tangibly from $-4^{\circ}C$. We tried to fit the six nonlinear regression models to the electrolyte leakage data of Brassica napus: 3-parameter logistic model, baseline logistic model, 4-parameter logistic model, (4-1)-parameter logistic model, 3-parameter Gompertz model, and (3-1)-parameter Gompertz model. The baseline levels of the electrolyte leakage estimated by these models were 4.81%, 4.07%, 4.19%, 4.07%, 4.55%, and 0%, respectively. The estimated median lethal temperature, LT50, were $-5.87^{\circ}C$, $-6.31^{\circ}C$, $-6.05^{\circ}C$, $-6.35^{\circ}C$, $-4.98^{\circ}C$, and $-5.15^{\circ}C$, respectively. We compared and discussed the measures of goodness of fit to select the appropriate nonlinear regression model.

• Journal of Power Electronics
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• v.16 no.3
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• pp.1004-1011
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• 2016

The inaccurate model parameters in the predictive current control of surface-mounted permanent magnet synchronous motor (SMPMSM) affect the current dynamic response and steady-state error. This paper presents a model parameter correction algorithm based on the relationship between the errors of model parameters and the static errors of dq-axis current. In this correction algorithm, the errors of inductance and flux are corrected in two steps. Resistance is ignored. First, the proportional relations between inductance and d-axis static current errors are utilized to correct the error of model inductance. Second, the flux is corrected by utilizing the proportional relations between flux and q-axis static current errors under the condition that inductance is corrected. An experimental study with a 100 W SMPMSM is performed to validate the proposed algorithm.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.503-506
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• 2003

In this paper, we present the results of parameter estimation for do-dc converter model by system identification. The parameter estimation for dc-dc converter aims at the diagnosis of its operating status. we applied the system identification method for parameter estimation. For verification of estimated parameter, we compare bode plot of estimated system transfer function and measurement results of HP4194 instrument.

• Magazine of the Korean Society of Agricultural Engineers
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• v.32 no.E
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• pp.47-58
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• 1990

Abstract A regionalized daily streamflow model using a modified retention parameter in the SCS method was developed to predict the daily streamflow of a natural series for Korean watersheds. Model verification showed that it is possible to use the model for extending short period records in a gaged watershed or for predicting daily streamflow in any ungaged watershed, with reasonable accuracy by simply inputing the name of the watershed boundary, the watershed size, the latitude and longitude of the watershed, and the daily areal rainfall.

• Journal of the Korean Data and Information Science Society
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• v.10 no.2
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• pp.465-472
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• 1999

We considered a bootstrap method for constructing confidenc intervals for a one parameter model using multinomial sampling. The convergence rates or the proposed bootstrap method are calculated for model-based maximum likelihood estimators(MLE) using multinomial sampling. Monte Carlo simulation was used to compare the performance of bootstrap methods with normal approximations in terms of the average coverage probability criterion.