• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1995.03a
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• pp.211-223
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• 1995

The purpose of the present study is to examine shearing mechanism through rigidplastic finite element analysis. Difficulties arise in simulating shearing process due tothe narrow shear band formation andlackof proper fracture resolve these difficulties by using adaptive mesh generation crriterion. The simulation results are obtained for various punch clearances and these are compared with existing experimental results. It is shown that FEM simulation technique can be used to further understand the shearing mechanism.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1999.03b
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• pp.39-44
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• 1999

Hydroforming is a forming process enabling circular metal tubes to be produced in complex cross sections along curved axial paths With the availability of advanced machine design and control They offer advantages over stamped sheet metal in lower tooling cost and structural mass The technology is relatively new so that there is no large knowledge base to assist the fundamentals of tube hydroforming technology. The purpose of this paper is found that adaptive bending condition and contact condition for bended part has uniform thickness distribution.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2004.10a
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• pp.79-82
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• 2004

In this study, a new refinement technique for 3-dimensional hexahedral element mesh is proposed, which is aimed at the control of mesh density. With the proposed scheme the mesh is refined adaptively to the elemental error which is estimated by 'a posteriori' error estimator based on the energy norm. A desired accuracy of an analysis i.e. a limit of error defines the new desired mesh density map on the current mesh. To obtain the desired mesh density, the refinement procedure is repeated iteratively until no more elements to be refined exist. In the algorithm, at first the regions of mesh to be refined are defined and, then, the zero-thickness element layers are inserted into the interfaces between the regions. All the meshes in the regions, in which the zero-thickness layers are inserted, are to be regularized in order to improve the shape of the slender elements on the interfaces. This algorithm is tested on a simple shape of 2-d quadrilateral element mesh and 3-d hexahedral element mesh. A numerical example of elastic deformation of a plate with a hole shows the effectiveness of the proposed refinement scheme.

• Advances in nano research
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• v.17 no.2
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• pp.109-124
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• 2024

In the era of smart manufacturing, precise prediction of springback-a common issue in ultra-thin sheet metal forming- and forming limits are critical for ensuring high-quality production and minimizing waste. This paper presents a novel approach that leverages the Internet of Things (IoT) and Artificial Neural Networks (ANN) to enhance springback and forming limits prediction accuracy. By integrating IoT-enabled sensors and devices, real-time data on material properties, forming conditions, and environmental factors are collected and transmitted to a central processing unit. This data serves as the input for an ANN model, which is trained with crystal plasticity simulations and experimental data to predict springback with high precision. Our proposed system not only provides continuous monitoring and adaptive learning capabilities but also facilitates real-time decision-making in manufacturing processes. Experimental results demonstrate significant improvements in prediction accuracy compared to traditional methods, highlighting the potential of IoT and ANN integration in advancing smart manufacturing. This approach promises to revolutionize quality control and operational efficiency in the industry, paving the way for more intelligent and responsive manufacturing systems.

• Coupled systems mechanics
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• v.8 no.1
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• pp.71-93
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• 2019

Finite element simulations of solid mechanics problems often involve the use of Non-Confirming Meshes (NCM) to increase accuracy in capturing nonlinear behavior, including damage and plasticity, in part of a solid domain without an undue increase in computational costs. In the presence of material nonlinearity and plasticity, higher-order variables are often needed to capture nonlinear behavior and material history on non-conforming interfaces. The most popular formulations for coupling non-conforming meshes are dual methods that involve the interpolation of a traction field on the interface. These methods are subject to the Ladyzhenskaya-Babuska-Brezzi (LBB) stability condition, and are therefore limited in their implementation with the higher-order elements needed to capture nonlinear material behavior. Alternatively, the enriched discontinuous Galerkin approach (EDGA) (Haikal and Hjelmstad 2010) is a primal method that provides higher order kinematic fields on the interface, and in which interface tractions are computed from local finite element estimates, therefore facilitating its implementation with nonlinear material models. The inclusion of higher-order interface variables, however, presents the issue of preserving material history at integration points when a increase in integration order is needed. In this study, the enriched discontinuous Galerkin approach (EDGA) is extended to the case of small-deformation plasticity. An interface-driven Gauss-Kronrod integration rule is proposed to enable adaptive enrichment on the interface while preserving history-dependent material data at existing integration points. The method is implemented using classical J2 plasticity theory as well as the pressure-dependent Drucker-Prager material model. We show that an efficient treatment of interface variables can improve algorithmic performance and provide a consistent approach for coupling non-conforming meshes in inelasticity.

• IMMUNE NETWORK
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• v.23 no.1
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• pp.5.1-5.28
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• 2023

Th cell lineage determination and functional specialization are tightly linked to the activation of lineage-determining transcription factors (TFs) that bind cis-regulatory elements. These lineage-determining TFs act in concert with multiple layers of transcriptional regulators to alter the epigenetic landscape, including DNA methylation, histone modification and threedimensional chromosome architecture, in order to facilitate the specific Th gene expression programs that allow for phenotypic diversification. Accumulating evidence indicates that Th cell differentiation is not as rigid as classically held; rather, extensive phenotypic plasticity is an inherent feature of T cell lineages. Recent studies have begun to uncover the epigenetic programs that mechanistically govern T cell subset specification and immunological memory. Advances in next generation sequencing technologies have allowed global transcriptomic and epigenomic interrogation of CD4+ Th cells that extends previous findings focusing on individual loci. In this review, we provide an overview of recent genome-wide insights into the transcriptional and epigenetic regulation of CD4+ T cell-mediated adaptive immunity and discuss the implications for disease as well as immunotherapies.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1994.10a
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• pp.64-73
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• 1994

An updated Lagrangian finite element analysis with automatic remeshing scheme is applied to the three-dimensional hot extrusion through landless square dies. In the remeshing procedure, it is very difficult that the meshes are generated automatically with consideration of physical characteristics. In the presented study, the mesh generation is accomplished by modular concept. The generated meshes by modular concept have advantages, especially for three-dimensional problems, such as economized computational time and consideration of physical characteristic. In the problem, orifice shapes of square die are divided into two for the extrusion of solid sections. The orifice adaptive modules are developed for each type and the numerical examples are carried out for each type.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1995.03a
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• pp.162-169
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• 1995

An improved nonparametric tool description based on successive refined monparametric patches is proposed and therlated criterion for refinement is also discussed . In the proposed sheme, any required order of tool surface conformity can be achieved by employing successive refinements accoring to the suggested criterion. By using the suggested adaptive tool refinement technique based on the nonparametric patch tool description, the locally refined nonparametric tool surface with economic memory size and sufficient accuracy as well as with favorable charateristics for contact treatment can be obtained directly form the parametric patch related with commerical CAD system. Computation is carried out for a chosen complex sheet forming example of an actual autobody panel in order to verify the validity and the efficiency of the developed tool surface description.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2002.02a
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• pp.26-33
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• 2002

Die Factory follows typical order adaptive manufacturing, and delaying delivery affects directly product development of customer, Manufacturing Management System is tried to comply with the appointed date of delivery. It acquires running signal from NC milling, calculates manufacturing results, and offers the basic data to manage the operation ratio. Thus it offers Production data necessary to accomplish the objective of progress improvement for Unmanned Manufacturing. Manufacturing Management System runs on Web Environment, and is composed of electronic work order, operation ratio data acquisition and totaling module.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.5
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• pp.102-108
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• 1996

Adaptive resonance theory (ART2) characterized by its built-in mechanism of handling the stability-plasticity switching and by the adaptive learning without forgetting informations learned in the past, is based on an unsupervised template matching. We propose an improved tow-stage learning algorithm for aRT2: the original unsupervised learning followed by a new supervised learning. Each of the output nodes, after the unsupervised learning, is labeled according to the category informations to reinforce the template pattern associated with the target output node belonging to the same category some dominant classes from exhausting a finite number of template patterns in ART2 inefficiently. Experimental results on a set of 2545 FLIR images show that the ART2 trained by the two-stage learning algorithm yields better accuracy than the original ART2, regardless of th esize of the network and the methods of evaluating the accuracy. This improvement shows the effectiveness of the two-stage learning process.