• 산업공학
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• 제25권3호
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• pp.300-308
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• 2012

For convenient business process modeling we propose a mathematical approach to obtain appropriate process structures. In this paper, we define business process structural constraints, on which basis, using Social Network Analysis (SNA), we analyze the frequency of handover occurrences among performers in social network. We here present, therefrom, a new, mathematical approach to business process modeling that proceeds by identifying the social relations among activities.

• 한국연소학회지
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• 제2권1호
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• pp.39-51
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• 1997

A review of probability density function(PDF) methodology and direct numerical simulation for the purpose of modeling turbulent combustion are presented in this study where particular attention is focused on the modeling problem of turbulent molecular mixing term appearing in PDF transport equation. Existing mixing models results were compared to those evaluated by direct numerical simulation in a turbulent premixed medium with finite rate chemistry in which the initial scalar field is composed of pockets of partially burnt gases to simulate autoignition. Two traditional mixing models, the least mean square estimations(LMSE) and Curl#s model are examined to see their prediction capability as well as their modeling approach. Test calculations report that the stochastically based Curl#s approach, though qualitatively demonstrates some unphysical behaviors, predicts scalar evolutions which are found to be in good agreement with statistical data of direct numerical simulation.

• 한국IT서비스학회지
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• 제12권3호
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• pp.311-321
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• 2013

In the community of software engineering, diverse modeling languages are used for representing all relevant information in the form of models. Also many different models such as business model, business process model, product models, interface models etc. are generated through software life cycles. In this situation, models need to be integrated for enterprise integration and enhancement of software productivity. Researchers propose rebuilding models by a specific modeling language, using a intemediate modeling language and using common reference for model integration. However, in the current approach it requires a lot of cost and time to integrate models. Also it is difficult to identify common objects from several models and to update objects in the repository of common model objects. This paper proposes software model integration using metadata model based on Linked data. We verify the effectiveness of the proposed approach through a case study.

• 소성∙가공
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• 제21권6호
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• pp.366-371
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• 2012

Atomistic simulations have become useful tools for exploring new insights in materials science, but the length and time scale that can be handled with atomistic simulations are seriously limiting their practical applications. In order to make meaningful quantitative predictions, atomistic simulations are necessarily combined with higher-scale modeling. The present research is thus concerned with the development of a multi-scale model and its application to the prediction of the mechanical properties of body-centered cubic(BCC) iron with an emphasis on the coupling of atomistic molecular dynamics with meso-scale discrete dislocation dynamics modeling. In order to achieve predictive multi-scale simulations, it is necessary to properly incorporate atomistic details into the meso-scale approach. This challenge is handled with the proposed hierarchical information passing strategy from atomistic to meso-scale by obtaining material properties and dislocation mobility. Finally, this fundamental and physics-based meso-scale approach is employed for quantitative predictions of the mechanical response of single crystal iron.

• Biotechnology and Bioprocess Engineering:BBE
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• 제11권1호
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• pp.67-71
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• 2006

This paper compares regression and neural network modeling approaches to predict competitive biosorption equilibrium data. The regression approach is based on the fitting of modified Langmuir-type isotherm models to experimental data. Neural networks, on the other hand, are non-parametric statistical estimators capable of identifying patterns in data and correlations between input and output. Our results show that the neural network approach outperforms traditional regression-based modeling in correlating and predicting the simultaneous uptake of copper and cadmium by a microbial biosorbent. The neural network is capable of accurately predicting unseen data when provided with limited amounts of data for training. Because neural networks are purely data-driven models, they are more suitable for obtaining accurate predictions than for probing the physical nature of the biosorption process.

• Journal of Information Processing Systems
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• 제18권1호
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• pp.130-145
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• 2022

Games are widely used in many fields, but not all games are successful. Then what makes games successful? The question gave us the motivation of this paper, which is to identify critical factors for successful games with topic modeling technique. It is supposed that game reviews written by experts sit on abundant insights and topics of how games succeed. To excavate these insights and topics, latent Dirichlet allocation, a topic modeling analysis technique, was used. This statistical approach provided words that implicate topics behind them. Fifty topics were inferred based on these words, and these topics were categorized by stimulation-response-desiregoal (SRDG) model, which makes a streamlined flow of how players engage in video games. This approach can provide game designers with critical factors for successful games. Furthermore, from this research result, we are going to develop a model for immersive game experiences to explain why some games are more addictive than others and how successful gamification works.

• Nuclear Engineering and Technology
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• 제56권1호
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• pp.141-146
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• 2024

Station blackout (SBO) risk is one of the most significant contributors to nuclear power plant risk. In this paper, the sequence probability formulas derived by the convolution approach are compared with those derived by the conventional event tree/fault tree (ET/FT) approach for the SBO situation in which emergency diesel generators fail to start. The comparison identifies what makes the ET/FT approach more conservative and raises the issue regarding the mission time of a turbine-driven auxiliary feedwater pump (TDP), which suggests a possible modeling improvement in the ET/FT approach. Monte Carlo simulations with up-to-date component reliability data validate the convolution approach. The sequence probability of an alternative alternating current diesel generator (AAC DG) failing to start and the TDP failing to operate owing to battery depletion contributes most to the SBO risk. The probability overestimation of the scenario in which the AAC DG fails to run and the TDP fails to operate owing to battery depletion contributes most to the SBO risk overestimation determined by the ET/FT approach. The modification of the TDP mission time renders the sequence probabilities determined by the ET/FT approach more consistent with those determined by the convolution approach.

• 한국산학기술학회논문지
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• 제11권6호
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• pp.2219-2224
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• 2010

증강현실 기반의 콘텐츠를 제작하는 데에는 많은 시간과 비용이 필요할 뿐만 아니라 컴퓨터공학, 가상현실, 증강현실, 3차원 그래픽스, 컴퓨터 시각과 같은 여러 분야에 숙련된 기술자의 도움이 필요하다. 이 논문에서는 증강현실 콘텐츠 제작의 어려움을 3가지로 분석하였으며, 이러한 어려움을 해결하기 위한 정형화된 저작 기법을 제안하고 있다. 제안된 기법은 원래 실시간 임베디드 시스템의 모델링을 위한 도구인 Statecharts를 기반으로 하였는데, 자동화된 저작도구로의 적용을 고려하여 증강현실 콘텐츠를 위한 Statecharts의 의미론(semantics)을 제시하고 있으며 상호작용 모델링에서 가장 중요한 이벤트를 정의하고 있다.

• Smart Structures and Systems
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• 제13권4호
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• pp.685-709
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• 2014

Carbon nanotubes are due to their outstanding mechanical properties destined for a wide range of possible applications. Since the knowledge of the material behavior is vital regarding the possible applications, experimental and theoretical studies have been conducted to investigate the properties of this promising material. The aim of the present research is the calculation of mechanical properties and of the mechanical behavior of single wall carbon nanotubes (SWCNTs). The numerical simulation was performed on basis of a molecular mechanics approach. Within this approach two different issues were taken into account: (i) the nanotube geometry and (ii) the modeling of the covalent bond. The nanotube geometry is captured by two different approaches, the roll-up and the exact polyhedral model. The covalent bond is modeled by a structural molecular mechanics approach according to Li and Chou. After a short introduction in the applied modeling techniques, the results for the Young's modulus for several SWCNTs are presented and are discussed extensively. The obtained numerical results are compared to results available in literature and show an excellent agreement. Furthermore, deviations in the geometry stemming from the different models are given and the resulting differences in the numerical findings are shown. Within the investigation of the deformation mechanisms occurring in SWCNTs, the basic contributions of each individual covalent bond are considered. The presented results of this decomposition provide a deeper understanding of the governing deformation mechanisms in SWCNTs.

• Steel and Composite Structures
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• 제28권1호
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• pp.111-121
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• 2018

It has been argued that fracture energy of composite laminates depends on their thickness and number of layers. In this paper a modified direct energy balance approach (DEBA) has been developed to evaluate the mode-II shear fracture energy for E-glass/Epoxy laminates from finite element model at an arbitrary thickness. This approach considers friction and damage/plasticity deformations using cohesive zone modeling (CZM) and nonlinear finite element modeling. The presence of compressive stress and resulting friction was argued to be a possible cause for the thickness dependency of fracture energy. In the finite element modeling, CZM formulation has been developed with bilinear cohesive constitutive law combined with friction consideration. Also ply element have been developed with shear plastic damage model. Modified direct energy balance approach has been proposed for estimation of mode-II shear fracture energy. Experiments were performed on laminates of glass epoxy specimens for characterization of material parameters and determination of mode-II fracture energies for different thicknesses. Effect of laminate thickness on fracture energy of transverse crack tension (TCT) and end notched flexure (ENF) specimens has been numerically studied and comparison with experimental results has been made. It is shown that the developed numerical approach is capable of estimating increase in fracture energy due to size effect.