• Journal of Magnetics
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• v.19 no.4
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• pp.315-322
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• 2014

In this work, Artificial Neural Network (ANN) was used to model the dynamic behavior of ferromagnetic hysteresis derived from performing the mean-field analysis on the Ising model. The effect of field parameters and system structure (via coordination number) on dynamic critical points was elucidated. The Ising magnetization equation was drawn from mean-field picture where the steady hysteresis loops were extracted, and series of the dynamic critical points for constructing dynamic phase-diagram were depicted. From the dynamic critical points, the field parameters and the coordination number were treated as inputs whereas the dynamic critical temperature was considered as the output of the ANN. The input-output datasets were divided into training, validating and testing datasets. The number of neurons in hidden layer was varied in structuring ANN network with highest accuracy. The network was then used to predict dynamic critical points of the untrained input. The predicted and the targeted outputs were found to match well over an extensive range even for systems with different structures and field parameters. This therefore confirms the ANN capabilities and indicates the ANN ability in modeling the ferromagnetic dynamic hysteresis behavior for establishing the dynamic-phase-diagram.

• Structural Engineering and Mechanics
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• v.5 no.4
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• pp.355-368
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• 1997

Fiber reinforced plastic (FRP) rods are used as reinforcement (prestressed or not) to concrete. FRP composites can also be combined with steel to form hybrid reinforcing rods that take advantage of the properties of both materials. In order to effectively utilize these rods, their bond behavior with concrete must be understood. The objective of this study is to characterize and model the bond behavior of hybrid FRP rods made with epoxy-impregnated aramid or poly-vinyl alcohol FRP skins directly braided onto a steel core. The model closely examines the split failure of the concrete by quantifying the relationship between slip of the rods resulting transverse stress field in concrete. The model is used to derive coefficients of friction for these rods and, from these, their development length requirements. More testing is needed to confirm this model, but in the interim, it may serve as a design aide, allowing intelligent decisions regarding concrete cover and development length. As such, this model has helped to explain and predict some experimental data from concentric pull-out tests of hybrid FRP rods.

• Interaction and multiscale mechanics
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• v.2 no.4
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• pp.375-396
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• 2009

In the present work, the elasto-viscoplastic behavior, interactions between grains, and the texture evolution in polycrystalline materials subjected to finite deformations are modeled using a multiscale analysis procedure within a finite element framework. Computational homogenization is used to relate the grain (meso) scale to the macroscale. Specifically, a polycrystal is modeled by a material representative volume element (RVE) consisting of an aggregate of grains, and a periodic distribution of such unit cells is considered to describe material behavior locally on the macroscale. The elastic behavior is defined by a hyperelastic potential, and the viscoplastic response is modeled by a simple power law complemented by a work hardening equation. The finite element framework is based on a Lagrangian formulation, where a kinematic split of the deformation gradient into volume preserving and volumetric parts together with a three-field form of the Hu-Washizu variational principle is adopted to create a stable finite element method. Examples involving simple deformations of an aluminum alloy are modeled to predict inhomogeneous fields on the grain scale, and the macroscopic effective stress-strain curve and texture evolution are compared to those obtained using both upper and lower bound models.

• Computers and Concrete
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• v.21 no.5
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• pp.593-605
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• 2018

A nonlinear finite element modeling approach is developed to assess the behavior of a dowel bar embedded on a single concrete block substrate, subjected to monotonic loading. In this approach, a discrete representation of the steel reinforcing bar is considered, using beam finite elements with nonlinear material behavior. The bar is connected to the concrete embedment through nonlinear Winkler spring elements. This modeling approach can only be used if a new constitutive model is developed for the spring elements, to simulate the deformability and strength of the concrete substrate. To define this constitutive model, an extensive literature review was conducted, as well as 3 experimental tests, in order to select the experimental data which can be used in the calibration of the model. Based on this data, an empirical model was established to predict the global dowel response, for a wide range of bar diameters and concrete strengths. This empirical model provided the information needed for calibration of the nonlinear Winkler spring model, valid for dowel displacements up to 4 mm. This new constitutive model is composed by 5 stages, in order to reproduce the concrete substrate response.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.6
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• pp.615-621
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• 2014

The Addiction problems have been became a social problem; the social efforts continue to solve these problems. One of those efforts, we need to establish a mathematical modeling for an addictive model to perform analysis of behavior by using this modeling. We need to process the research that can be judged before and after addictive status with result of the behavior analysis. We have to process an observation of transition from before to after addictive status. According to those necessary, this paper proposed the physical exercise model that is composed by novel second order system, which consisted of Spring-Damper-Mass system with equivalence in order to evolve an addictive equation for physical exercise. This paper also is analyzed by the behaviors for those the addictive equation of physical exercise.

• Geomechanics and Engineering
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• v.21 no.1
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• pp.35-51
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• 2020

In this study, the seismic response analysis of embankment dams was investigated through numerical modeling. The seismic behavior of dams under main earthquake records and wavelet-based records were studied. Earthquake records were decomposed using de-noising method (DNM) and down-sampling method (DSM) up to five levels. In decomposition process, low and high frequencies of the main earthquake record were separated into two signals. Acceleration response, spectral acceleration, and Fourier amplitude spectrum at the crest of embankment dams under different decomposition levels were evaluated. The seismic behavior under main and decomposed earthquake records was compared. The results indicate an acceptable agreement between the seismic responses of embankment dams under wavelet-based decomposed records and main earthquake motions. Dynamic analyses show that the DNM-based decomposed earthquake records have a better performance compared to DSM-based records. DNM-based records up to level 4 and DSM-based records up to level 2 have a high accuracy in assessment of seismic behavior of embankment dams. The periods corresponding to the maximum values of acceleration spectra and the frequencies corresponding to the maximum values of Fourier amplitude spectra of embankment dam crest under main and decomposed records are in good agreement. The results demonstrate that the main earthquake records can be replaced by wavelet-based decomposed records in seismic analysis of embankment dams.

• Proceedings of the KIEE Conference
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• 2005.07b
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• pp.1722-1724
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• 2005

The focus of this paper is to develop a mathematical model for investigating the dynamic performance of a polymer electrolyte membrane fuel cell. The model in this work is based on physical laws having clear significance in replicating the fuel cell system and can easily be used to set up different operational strategies. Simulation results display the transient behavior of the voltage within each single cell, and also within a number of such single cells combined into a fuel cell stack system. A linear as well as a nonlinear analysis of the polymer electrolyte membrane fuel cell system(PEMFC) has been discussed in order to present a complete and comprehensive view of this kind of modeling. Also, a comparison of the two kinds of analysis has been performed. Finally, the various characteristics of the fuel cell system are plotted in order to help us understand its dynamic behavior. Results indicate that there is a considerable amount of error in the modeling process if we use a linear model of the fuel cell. Thus, the nonlinearities present in the fuel cell system should be taken into account in order to obtain a better understanding of the dynamic behavior of the fuel cell system.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.10
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• pp.985-989
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• 2010

The near future smart ubiquitous computing oriented system will have to provide the optimal (right) service through interactions between users and the system. To provide the right services what the user needs, we should choose the user-centered development for reflecting the user needs, but not the developer-centered development. To do this, we proposed User Behavior Analysis Based Needs Extraction Method [1]. In this paper, we propose Object Extraction and Modeling Method from the user requirements with Fillmore's Case Grammar.

• Nuclear Engineering and Technology
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• v.53 no.9
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• pp.3100-3111
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• 2021

Numerical modeling for the safety-related equipment used in a nuclear power plant (i.e., cabinet facilities) plays an essential role in seismic risk assessment. A full finite element model is often time-consuming for nonlinear time history analysis due to its computational modeling complexity. Thus, this study aims to generate a simplified model that can capture the nonlinear behavior of the electrical cabinet. Accordingly, the distributed plasticity approach was utilized to examine the stiffness-degradation effect caused by the local buckling of the structure. The inherent dynamic characteristics of the numerical model were validated against the experimental test. The outcomes indicate that the proposed model can adequately represent the significant behavior of the structure, and it is preferred in practice to perform the nonlinear analysis of the cabinet. Further investigations were carried out to evaluate the seismic behavior of the cabinet under the influence of the constitutive law of material models. Three available models in OpenSees (i.e., linear, bilinear, and Giuffre-Menegotto-Pinto (GMP) model) were considered to provide an enhanced understating of the seismic responses of the cabinet. It was found that the material nonlinearity, which is the function of its smoothness, is the most effective parameter for the structural analysis of the cabinet. Also, it showed that implementing nonlinear models reduces the seismic response of the cabinet considerably in comparison with the linear model.

• Journal of Convergence for Information Technology
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• v.11 no.6
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• pp.24-32
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• 2021

Recently, ransomware attacks have been infected through various channels such as e-mail, phishing, and device hacking, and the extent of the damage is increasing rapidly. However, existing known malware (static/dynamic) analysis engines are very difficult to detect/block against novel ransomware that has evolved like Advanced Persistent Threat (APT) attacks. This work proposes a method for modeling ransomware malicious behavior based on graph databases and detecting novel multi-complex malicious behavior for ransomware. Studies confirm that pattern detection of ransomware is possible in novel graph database environments that differ from existing relational databases. Furthermore, we prove that the associative analysis technique of graph theory is significantly efficient for ransomware analysis performance.