• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.494-498
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• 1996

Three fuzzy input space partitoining methods, which are grid, tree, and scatter method, are mainly used until now. These partition methods represent good performance in the modeling of the linear system and nonlinear system with independent modeling variables. But in the case of the nonlinear system with the coupled modeling variables, there should be many fuzzy rules for acquiring the exact fuzzy model. In this paper, it shows that the fuzzy model is acquired using transformed modeling vector by linear transformation of the modeling vector.

• Steel and Composite Structures
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• v.48 no.4
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• pp.367-383
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• 2023

A coupled wall consists of two or more reinforced concrete (RC) shear walls (SWs) connected by RC coupling beams (CBs) or steel CBs (hybrid-coupled walls). To fill the gap in the literature on the plastic hinge length of coupled walls, including coupled and hybrid-coupled shear walls, a parametric study using experimentally validated numerical models was conducted considering the axial stress ratio (ASR) and coupling ratio (CR) as the study variables. A total of sixty numerical models, including both coupled and hybrid-coupled SWs, have been developed by varying the ASR and CR within the ranges of 0.027-0.25 and 0.2-0.5, respectively. A detailed analysis was conducted in order to estimate the ultimate drift, ultimate capacity, curvature profile, yielding height, and plastic hinge length of the models. Compared to hybrid-coupled SWs, coupled SWs possess a relatively higher capacity and curvature. Moreover, increasing the ASR changes the walls' behavior to a column-like member which decreases the walls' ultimate drift, ductility, curvature, and plastic hinge length. Increasing the CR of the coupled SWs increases the walls' capacity and the risk of abrupt shear failure but decreases the walls' ductility, ultimate drift and plastic hinge length. However, CR has a negligible effect on hybrid-coupled walls' ultimate drift and moment, curvature profile, yielding height and plastic hinge length. Lastly, using the obtained results two equations were derived as a function of CR and ASR for calculating the plastic hinge length of coupled and hybrid-coupled SWs.

• Structural Engineering and Mechanics
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• v.20 no.6
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• pp.695-712
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• 2005

Hybrid coupled shear walls in tall buildings are known as efficient structural systems to provide lateral resistance to wind and seismic loads. Multiple hybrid coupled shear walls throughout a tall building should be joined to provide additional coupling action to resist overturning moments caused by the lateral loading. This can be done using a coupling beam which connects two shear walls. In this study, experimental studies on the hybrid coupled shear wall were carried out. The main test variables were the ratios of coupling beam strength to connection strength. Finally, this paper provides background for rational design guidelines that include a design model to behave efficiently hybrid coupled shear walls.

• Coupled systems mechanics
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• v.7 no.1
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• pp.5-25
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• 2018

A fully-coupled thermodynamic-based transient finite element formulation is proposed in this article for electric, magnetic, thermal and mechanic fields interactions limited to the linear case. The governing equations are obtained from conservation principles for both electric and magnetic flux, momentum and energy. A full-interaction among different fields is defined through Helmholtz free-energy potential, which provides that the constitutive equations for corresponding dual variables can be derived consistently. Although the behavior of the material is linear, the coupled interactions with the other fields are not considered limited to the linear case. The implementation is carried out in a research version of the research computer code FEAP by using 8-node isoparametric 3D solid elements. A range of numerical examples are run with the proposed element, from the relatively simple cases of piezoelectric, piezomagnetic, thermoelastic to more complicated combined coupled cases such as piezo-pyro-electric, or piezo-electro-magnetic. In this paper, some of those interactions are illustrated and discussed for a simple geometry.

• Transactions of Materials Processing
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• v.28 no.3
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• pp.159-166
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• 2019

Electromagnetic forming (EMF) simulations consider 3-dimensionally coupled electromagnetic-mechanical phenomenon using LS-DYNA, therefore the calculation cost is normally expensive. In this study, a sensitivity analysis in regard to the simulation variables affecting the calculation time was carried out. The EMF experiments were conducted to form an elliptically protruding shape on a high-strength steel sheet, and it was predicted using LS-DYNA simulation. In this particular EMF simulation case, the effect of several simulation variables, viz., element size, contact condition, EM-time step interval, and re-calculation number of the EM matrices, on the shape of elliptical protrusion and the total calculation time was analyzed. As a result, reasonable values of the simulation variables between the simulation precision and calculation time were proposed, and the EMF experiments with respect to the charging voltages were successfully predicted.

• Proceedings of the Korean Geotechical Society Conference
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• 2010.09a
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• pp.808-812
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• 2010

A great deal of attention is focused on coupled Thermo-Hydro-Mechanical (THM) behavior of multiphase porous media in diverse geo-mechanical and geo-environmental areas. This paper presents general governing equations for coupled THM processes in unsaturated porous media. Coupled partial differential equations are derived from 3 mass balances equations (solid, water, and air), energy balance equation, and force equilibrium equation. Finite element code is developed from the Galerkin formulation and time integration of these governing equations for 4 main variables (displacement $\underline{u}$, gas pressure $P_g$, liquid pressure $P_l$), and temperature T). The code is validated with theoretical solutions for linear material with simple boundary conditions.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.21 no.12
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• pp.1063-1070
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• 2008

The performance of an acoustic transducer is determined by the effects of many design variables, and mostly the influences of these design variables are not linearly independent of each other. To achieve the optimal performance of an acoustic transducer, we must consider the cross-coupled effects of the design variables. In this study, the variation of the performances of underwater acoustic transducer in relation to its structural variables was analyzed. In addition, the new optimal design scheme of an acoustic transducer that could reflect not only individual but also all the cross-coupled effects of multiple structural variables, and could determine the detailed geometry of the transducer with great efficiency and rapidity was developed. The validation of the new optimal design scheme was verified by applying the optimal structure design of a flextensional transducer which are the most common use for high power underwater acoustic transducer. With the finite element analysis(FEA), we analyzed the variation of the resonance frequency, sound pressure, and working depth of a flextensional transducer in relation to its design variables. Through statistical multiple regression analysis of the results, we derived functional forms of the resonance frequency, sound pressure, and working depth in terms of the design variables. By applying the constrained optimization technique, Sequential Quadratic Programming Method of Phenichny and Danilin(SQP-PD), to the derived function, we designed and verified the optimal structure of the Class IV flextensional transducer that could provide the highest sound pressure level and highest working depth at a given operation frequency of 1 kHz.

• 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.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.2
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• pp.109-117
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• 2004

Optimization has been successfully applied to systems with a single discipline. As many disciplines are involved in coupled fashion, MDO (multidisciplinary design optimization) technology has been developed. MDO algorithms are trying to solve the coupled aspects generated from interdisciplinary relationship. In a general MDO algorithms, a large design problem is decomposed into small ones which can be easily solved. Although various methods have been proposed for MDO, the research is still in the early stage. This research proposes a new MDO method which is named as MDOIS (Multidisciplinary Design Optimization Based on Independent Subspaces). Many real engineering problems consist of physically separate components and they can be independently designed. The inter-relationship occurs through coupled physics. MDOIS is developed for such problems. In MDOIS, a large system is decomposed into small subsystems. The coupled aspects are solved via system analysis which solves the coupled physics. The algorithm is mathematically validated by showing that the solution satisfies the Karush-Kuhn-Tucker condition.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.519-524
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• 2005

A numerical process to simulate SiO2 dry etching with inductively coupled C2F6 plasmas has been constructed using a commercial CFD code as a first step to design a run-to-run control system. The simulator was tuned to reasonably predict the reactive ion etching behavior and used to investigate the effects of plasma operating variables on the etch rate and uniformity. The relationship between the operating variables and the etching characteristics was mathematically modeled through linear regression for future run-to-run control system design.