• Coupled systems mechanics
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• v.4 no.4
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• pp.337-364
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• 2015

In this paper we present methodology for parameters identification of constitutive model which is able to present behavior of a connection between two members in a structure. Such a constitutive model for frame connections can be cast in the most general form of the Timoshenko beam, which can present three failure modes. The first failure mode pertains to the bending in connection, which is defined as coupled plasticity-damage model with nonlinear softening. The second failure mode is seeking to capture the shearing of connection, which is defined as plasticity with linear hardening and nonlinear softening. The third failure mode pertains to the diffuse failure in the members; excluding it leads to linear elastic constitutive law. Theoretical formulation of this Timoshenko beam model and its finite element implementation are presented in the second section. The parameter identification procedure that will allow us to define eighteen unknown parameters is given in Section 3. The proposed methodology splits identification in three phases, with all details presented in Section 4 through three different examples. We also present the real experimental results. The conclusions are stated in the last section of the paper.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.136-136
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• 2022

This study investigates the possibility of coupling empirical mode decomposition (EMD) for runoff prediction from machine learning (ML) models. Here, support vector regression (SVR) and convolutional neural network (CNN) were considered for ML algorithms. Precipitation (P), minimum temperature (Tmin), maximum temperature (Tmax) and their intrinsic mode functions (IMF) values were used for input variables at a monthly scale from Jan. 1973 to Dec. 2020 in the Grand river basin, Canada. The support vector machine-recursive feature elimination (SVM-RFE) technique was applied for finding the best combination of predictors among input variables. The results show that the proposed method outperformed the individual performance of SVR and CNN during the training and testing periods in the study area. According to the correlation coefficient (R), the EMD-SVR model outperformed the EMD-CNN model in both training and testing even though the CNN indicated a better performance than the SVR before using IMF values. The EMD-SVR model showed higher improvement in R value (38.7%) than that from the EMD-CNN model (7.1%). It should be noted that the coupled models of EMD-SVR and EMD-CNN represented much higher accuracy in runoff prediction with respect to the considered evaluation indicators, including root mean square error (RMSE) and R values.

• Coupled systems mechanics
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• v.12 no.6
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• pp.519-530
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• 2023

This paper presents a mathematical model suitable for the calculation of laminated glass, i.e. glass plates combined with an interlayer material. The model is based on a beam differential equation for each glass plate and a separate differential equation for the slip in the interlayer. In addition to slip, the model takes into account prestressing force in the interlayer. It is possible to combine the two contributions arbitrarily, which is important because the glass sheet fabrication process changes the stiffness of the interlayer in ways that are not easily predictable and could introduce prestressing of varying magnitude. The model is suitable for reformulation into an inverse procedure for calculation of the relevant parameters. Model consisting of a system of differential-algebraic equations, proved too stiff for cases with the thin interlayer. This novel approach covers the full range of possible stiffnesses of layered glass sheets, i.e., from zero to infinite stiffness of the interlayer. The comparison of numerical and experimental results contributes to the validation of the model.

• Journal of Soil and Groundwater Environment
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• v.10 no.5
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• pp.52-60
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• 2005

The conceptual model of under-sampled study area will include a great amount of uncertainty. In this study, we investigate the applicability of Markov chain model in a spatial domain as a tool for minimizing the uncertainty arose from the lack of data. A new formulation is developed to generalize the previous two-dimensional coupled Markov chain model, which has more versatility to fit any computational sequence. Furthermore, the computational algorithm is improved to utilize more conditioning information and reduce the artifacts, such as the artificial parcel inclination, caused by sequential computation. A generalized 20 coupled Markov chain (GCMC) is tested through applying a hypothetical soil map to evaluate the appropriateness as a substituting model for conventional geostatistical models. Comparing to sequential indicator model (SIS), the simulation results from GCMC shows lower entropy at the boundaries of indicators which is closer to real soil maps. For under-sampled indicators, however, GCMC under-estimates the presence of the indicators, which is a common aspect of all other geostatistical models. To improve this under-estimation, further study on data fusion (or assimilation) inclusion in the GCMC is required.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.25 no.4
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• pp.312-326
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• 2021

The prey-predator model is one of the most influential mathematical models in ecology and evolutionary biology. In this study, we considered a modified prey-predator model, which describes the rate of change for each species. The effects of modifications to the classical prey-predator model are investigated here. The conditions required for the existence of the first integral and the stability of the fixed points are studied. In particular, it is shown that the first integral exists only for a subset of the model parameters, and the phase portraits around the fixed points exhibit physically relevant phenomena over a wide range of the parameter space. The results show that adding coupling terms to the classical model widely expands the dynamics with great potential for applicability in real-world phenomena.

• Coupled systems mechanics
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• v.10 no.6
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• pp.521-544
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• 2021

In this work, we present the development of a 3D lattice-type model at microscale based upon the Voronoi-cell representation of material microstructure. This model can capture the coupling between mechanic and electric fields with non-linear constitutive behavior for both. More precisely, for electric part we consider the ferroelectric constitutive behavior with the possibility of domain switching polarization, which can be handled in the same fashion as deformation theory of plasticity. For mechanics part, we introduce the constitutive model of plasticity with the Armstrong-Frederick kinematic hardening. This model is used to simulate a complete coupling of the chosen electric and mechanics behavior with a multiscale approach implemented within the same computational architecture.

• Proceedings of the Korean Quaternary Association Conference
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• 2004.11a
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• pp.37-43
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• 2004

The response of the CCCma coupled climate model to the imposition of LGM conditions is investigated. The global mean SAT and SST decrease by about $10^{\circ}C$ and $5.6^{\circ}C$ in the coupled model. Tropical SST decreases by $6.5^{\circ}C$, whereas CLIMAP reconstructions suggest that the tropics cool by only about $1.7^{\circ}C$, although the larger tropical cooling is consistent with the more recent proxy estimates. With the incorporation of a full ocean component, the coupled model gives a realistic spatial SST pattern, capturing features associated with ocean dynamics that are seen in the CLIMAP reconstructions. The larger decrease of the surface temperature in the model is associated with a reduction in global precipitation rate (about 15%). The tropical Pacific warm pool retreats to the west and a mean La $Ni\tilde{n}a$-like response is simulated with less precipitation over the central Pacific and more in the western tropical Pacific. The more arid ocean climate in the LGM results in an increase in SSS almost everywhere. This is particularly the case in the Arctic Ocean where large SSS increase is due to a decrease in river discharge to the Arctic Ocean associated with the accumulation of snow over the ice sheet, but in the North Atlantic by contrast SSS decreases markedly. This remarkable reduction of SSS in the North Atlantic is attributed to an increase in fresh water supply by an increase in discharges from the Mississippi and Amazon rivers and an increase in P-E over the North Atlantic ocean itself. The discharges increase in association with the wetter LGM climate south of the Laurentide ice sheet and in South America. The fresh water capping of the northern North Atlantic results in a marked reduction of deep convection and consequently a marked weakening of the North Atlantic overturning circulation. In the LGM, the maximum overturning stream function associated with the NADW formation decreases by about 60% relative to the control run, while in the Southern Ocean, oceanic convection is stronger in the LGM due to reduced stratification associated with an increase in SSS and a decrease in SST and the overturning stream function associated with the formation of AABW and the outflow increases substantially.

• The Proceeding of the Korean Institute of Electromagnetic Engineering and Science
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• v.6 no.3
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• pp.80-90
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• 1995

The scattering parameters of a microstrip single line, a right-angle bend and a coupled line are calculated using the multiport network model for the frequency range from 1 to 18 GHz. The single line is analyzed using the planar waveguide model. The right-angle bend is broken into two rectangular segments, and each segment is analyzed in a similar fashion as the single line. Impedance matrices corresponding to the two segments are combined by the segmentation method. In the analysis of elec- tromagnetic coupling of the coupled line, a new method is employed resulting in much less computation time than those previous methods involving Green's functions. A good agreement between the numerical results for the three structures and those from SuperCompact reveals the usefulness of the multiport network medel in analyzing complicated mirostrip single and coupled line discontinuities.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.155-155
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• 2018

Uncertainty in flood forecasting using a coupled meteorological and hydrological model is arisen from various sources, especially the uncertainty comes from the inaccuracy of Quantitative Precipitation Forecasts (QPFs). In order to improve the capability of flood forecast, the uncertainty estimation and mitigation are required to perform. This study is conducted to investigate and reduce such uncertainty. First, ensemble QPFs are generated by using Monte - Carlo simulation, then each ensemble member is forced as input for a hydrological model to obtain ensemble streamflow prediction. Likelihood measures are evaluated to identify feasible member. These members are retained to define upper and lower limits of the uncertainty interval and assess the uncertainty. To mitigate the uncertainty for very short lead time, a blending method, which merges the ensemble QPFs with radar-based rainfall prediction considering both qualitative and quantitative skills, is proposed. Finally, blending bias ratios, which are estimated from previous time step, are used to update the members over total lead time. The proposed method is verified for the two flood events in 2013 and 2016 in the Yeonguol and Soyang watersheds that are located in the Han River basin, South Korea. The uncertainty in flood forecasting using a coupled Local Data Assimilation and Prediction System (LDAPS) and Sejong University Rainfall - Runoff (SURR) model is investigated and then mitigated by blending the generated ensemble LDAPS members with radar-based rainfall prediction that uses McGill algorithm for precipitation nowcasting by Lagrangian extrapolation (MAPLE). The results show that the uncertainty of flood forecasting using the coupled model increases when the lead time is longer. The mitigation method indicates its effectiveness for mitigating the uncertainty with the increases of the percentage of feasible member (POFM) and the ratio of the number of observations that fall into the uncertainty interval (p-factor).

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2000.04b
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• pp.150-155
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• 2000

In this study, deformation analysis for solid-liquid coupled structure has been performed using explicit finite element program In order to model the behavior of liquid, SPH (Smooth Particle Hydrodynamics) algorithm was adopted. Crash test and simulation for the hydro-type impact energy absorber were given as an example of industrial application. The obtained good correlation between the test results and simulation reveals that the proposed method could be used effectively for the structural analysis of solid-liquid coupled problems