• The Korean Journal of Physiology and Pharmacology
• /
• v.23 no.1
• /
• pp.63-70
• /
• 2019

We aimed to propose a novel computational approach to predict the electromechanical performance of pre- and post-mitral valve cerclage annuloplasty (MVCA). Furthermore, we tested a virtual estimation method to optimize the left ventricular basement tightening scheme using a pre-MVCA computer model. The present model combines the three-dimensional (3D) electromechanics of the ventricles with the vascular hemodynamics implemented in a lumped parameter model. 3D models of pre- and post-MVCA were reconstructed from the computed tomography (CT) images of two patients and simulated by solving the electromechanical-governing equations with the finite element method. Computed results indicate that reduction of the dilated heart chambers volume (reverse remodeling) appears to be dependent on ventricular stress distribution. Reduced ventricular stresses in the basement after MVCA treatment were observed in the patients who showed reverse remodeling of heart during follow up over 6 months. In the case who failed to show reverse remodeling after MVCA, more virtual tightening of the ventricular basement diameter than the actual model can induce stress unloading, aiding in heart recovery. The simulation result that virtual tightening of the ventricular basement resulted in a marked increase of myocardial stress unloading provides in silico evidence for a functional impact of MVCA treatment on cardiac mechanics and post-operative heart recovery. This technique contributes to establishing a pre-operative virtual rehearsal procedure before MVCA treatment by using patient-specific cardiac electromechanical modeling of pre-MVCA.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.41 no.4
• /
• pp.248-255
• /
• 2018

Ensuring the quality of molds is one of the major issues in mass production. In general, securing the quality of the molds is achieved by repeating grinding and die spotting after machining the molds based on engineer's decision. However, this heuristic method is affected by the engineer's skill and working environment. Therefore, a lot of time and resources are needed in order to ensure quality. In this study, ensuring the quality of molds using grinding map which is generated using automatic measurement is proposed. An automatic measuring system based on CMM (Coordinate Measuring Machine) is developed for measuring the molds. This system generates the measurement path automatically using the 3D CAD model of products. CAD (ComputerAided-Design), CAM (Computer-Aided-Manufacturing), and CAQ (Computer-Aided-Quality) technology is integrated using DMIS (Dimensional Measuring Interface Standard) format in the automatic measuring system. After measuring the molds, a grinding map is generated using the gap between the CAD model and measured values of mold. The grinding map displays the machining tendency and the required amount of grinding with values on a 3D map. Therefore, the quality of molds can be ensured with exactness and quickness based on the grinding map. This study shows that integrating the planning, measuring, and analyzing based on computer technology can solve the problem of quality assurance of mold using the proposed method, therefore the productivity can be increased.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2014.05a
• /
• pp.241-244
• /
• 2014

In this paper, we apply the learning of the mobile robot insect augmented reality Digilog Book. In the era of electronic, book written in paper space just have moved to virtual reality space. The virtual reality, constraints spatial and physical, in the real world, it is a technique that enables to experience indirectly situation not experienced directly as user immersive experience type interface. Applied to the learning robot Digilog Book that allows the fusion of paper analog and digital content, using the augmented reality technology, to experience various interactions. Apply critical elements moving, three-dimensional images and animation to enrich the learning, for easier block assembly, designed to grasp more easily rank order between the blocks. Anywhere at any time, is capable of learning of the robot in Digilog Book to be executed by the mobile phone in particular.

• Applied Microscopy
• /
• v.49
• /
• pp.3.1-3.7
• /
• 2019

Graphene, which is one of the most promising materials for its state-of-the-art applications, has received extensive attention because of its superior mechanical properties. However, there is little experimental evidence related to the mechanical properties of graphene at the atomic level because of the challenges associated with transferring atomically-thin two-dimensional (2D) materials onto microelectromechanical systems (MEMS) devices. In this study, we show successful dry transfer with a gel material of a stable, clean, and free-standing exfoliated graphene film onto a push-to-pull (PTP) device, which is a MEMS device used for uniaxial tensile testing in in situ transmission electron microscopy (TEM). Through the results of optical microscopy, Raman spectroscopy, and TEM, we demonstrate high quality exfoliated graphene on the PTP device. Finally, the stress-strain results corresponding to propagating cracks in folded graphene were simultaneously obtained during the tensile tests in TEM. The zigzag and armchair edges of graphene confirmed that the fracture occurred in association with the hexagonal lattice structure of graphene while the tensile testing. In the wake of the results, we envision the dedicated preparation and in situ TEM tensile experiments advance the understanding of the relationship between the mechanical properties and structural characteristics of 2D materials.

• Journal of the Korea Convergence Society
• /
• v.10 no.4
• /
• pp.139-145
• /
• 2019

This paper investigated the strength and stiffness of composite truss unit structures. The model used is a core-filled model combining the Kagome model and the cube truss model. The material properties used for the analysis are 304 stainless steel with elastic modulus of 193 GPa and yield stress of 215 MPa. The theoretical equation is derived from the relative elasticity relation of Gibson - Ashby ratio, the analysis was performed using Deform 3D, a commercial tool. In conclusion, the relative elasticity for this unit model correlates with 1.25 times the relative density and constant coefficient, elasticity is inversely proportional to pore size. The relative compressive strength has a correlation with relative density of 1.25 times. Proof of this is a real experiment, the derived theoretical relationship should further consider mechanical behavior such as bending and buckling. In the future, it is hoped that the research on the elasticity and the stress according to the structure of the three-dimensional space will be continued.

• Structural Engineering and Mechanics
• /
• v.78 no.4
• /
• pp.485-496
• /
• 2021

So far analytical methods on collapse assessment of three-dimensional (3-D) steel frames have mainly focused on a single-column-removal scenario. However, the collapse of the Federal Building in the US due to car bomb explosion indicated that the loss of multiple columns may occur in the real structures, wherein the structures are more vulnerable to collapse. Meanwhile, the General Services Administration (GSA) in the US suggested that the removal of side columns of the structure has a great possibility to cause collapse. Therefore, this paper analytically deals with the robustness of 3-D steel frames in a two-side-column-removal (TSCR) scenario. Analytical method is first proposed to determine the collapse resistance of the frame during this column-removal procedure. The reliability of the analytical method is verified by the finite element results. Moreover, a design-based methodology is proposed to quickly assess the robustness of the frame due to a TSCR scenario. It is found the analytical method can reasonably predict the resistance-displacement relationship of the frame in the TSCR scenario, with an error generally less than 10%. The parametric numerical analyses suggest that the slab thickness mainly affects the plastic bearing capacity of the frame. The rebar diameter mainly affects the capacity of the frame at large displacement. However, the steel beam section height affects both the plastic and ultimate bearing capacity of the frame. A case study on a six-storey steel frame shows that the design-based methodology provides a conservative prediction on the robustness of the frame.

• Nuclear Engineering and Technology
• /
• v.54 no.8
• /
• pp.3059-3072
• /
• 2022

A Jacobian-Free Newton Krylov Two-Nodal Coarse Mesh Finite Difference algorithm based on Nodal Expansion Method (NEM_TNCMFD_JFNK) is successfully developed and proposed to solve the three-dimensional (3D) and multi-group reactor physics models. In the NEM_TNCMFD_JFNK method, the efficient JFNK method with the Modified Incomplete LU (MILU) preconditioner is integrated and applied into the discrete systems of the NEM-based two-node CMFD method by constructing the residual functions of only the nodal average fluxes and the eigenvalue. All the nonlinear corrective nodal coupling coefficients are updated on the basis of two-nodal NEM formulation including the discontinuity factor in every few newton steps. All the expansion coefficients and interface currents of the two-node NEM need not be chosen as the solution variables to evaluate the residual functions of the NEM_TNCMFD_JFNK method, therefore, the NEM_TNCMFD_JFNK method can greatly reduce the number of solution variables and the computational cost compared with the JFNK based on the conventional NEM. Finally the NEM_TNCMFD_JFNK code is developed and then analyzed by simulating the representative PWR MOX/UO₂ core benchmark, the popular NEACRP 3D core benchmark and the complicated full-core pin-by-pin homogenous core model. Numerical solutions show that the proposed NEM_TNCMFD_JFNK method with the MILU preconditioner has the good numerical accuracy and can obtain higher computational efficiency than the NEM-based two-node CMFD algorithm with the power method in the outer iteration and the Krylov method using the MILU preconditioner in the inner iteration, which indicates the NEM_TNCMFD_JFNK method can serve as a potential and efficient numerical tool for reactor neutron diffusion analysis module in the JFNK-based multiphysics coupling application.

• Wind and Structures
• /
• v.34 no.6
• /
• pp.483-497
• /
• 2022

Three-dimensional (3D) computational fluid dynamics (CFD) analysis of flow around a hipped-roof building representative of UK inland conditions are conducted. Unsteady simulations are performed using three variations of the k-ϵ RANS turbulence model namely, the Standard, Realizable, and RNG models, and their predictive capability is measured against current European building standards. External pressure coefficients and wind loading are found through the BS 6399-2:1997 standard (obsolete) and the current European standards (BS EN 1991-1-4:2005 and A1:20101). The current European standard provides a more conservative wind loading estimate compared to its predecessor and the k-ϵ RNG model falls within 15% of the value predicted by the current standard. Surface shear stream-traces and Q-criterion were used to analyze the flow physics for each model. The RNG model predicts immediate flow separation leading to the creation of vortical structures on the hipped-roof along with a larger separation region. It is observed that the Realizable model predicts the side vortex to be a result of both the horseshoe vortex and the flow deflected off it. These model-specific aerodynamic features present the most disparity between building standards at leeward roof locations. Finally, pedestrian comfort and safety criteria are studied where the k-ϵ Standard model predicts the most ideal pedestrian conditions and the Realizable model yields the most conservative levels.

• Steel and Composite Structures
• /
• v.41 no.5
• /
• pp.761-773
• /
• 2021

This study presents a 3D non-linear finite element (FE) assessment of dynamic soil-structure interaction (SSI). The numerical investigation has been performed on the time domain through a Finite Element (FE) system, while considering the nonlinear behavior of soil and the multi-directional nature of genuine seismic events. Later, the FE outcomes are analyzed to the recorded in-situ free-field and structural movements, emphasizing the numerical model's great result in duplicating the observed response. In this work, the soil response is simulated using an isotropic hardening elastic-plastic hysteretic model utilizing HSsmall. It is feasible to define the non-linear cycle response from small to large strain amplitudes through this model as well as for the shift in beginning stiffness with depth that happens during cyclic loading. One of the most difficult and unexpected tasks in resolving soil-structure interaction concerns is picking an appropriate ground motion predicted across an earthquake or assessing the geometrical abnormalities in the soil waves. Furthermore, an artificial neural network (ANN) has been utilized to properly forecast the non-linear behavior of soil and its multi-directional character, which demonstrated the accuracy of the ANN based on the RMSE and R² values. The total result of this research demonstrates that complicated dynamic soil-structure interaction processes may be addressed directly by passing the significant simplifications of well-established substructure techniques.

• Current Optics and Photonics
• /
• v.7 no.3
• /
• pp.237-247
• /
• 2023

In middle- and long-distance imaging systems, due to the atmospheric turbulence caused by temperature, wind speed, humidity, and so on, light waves propagating in the air are distorted, resulting in image-quality degradation such as geometric deformation and fuzziness. In remote sensing, astronomical observation, and traffic monitoring, image information loss due to degradation causes huge losses, so effective restoration of degraded images is very important. To restore images degraded by atmospheric turbulence, an image-restoration method based on improved compound multibranch feature fusion (CMFNetPro) was proposed. Based on the CMFNet network, an efficient channel-attention mechanism was used to replace the channel-attention mechanism to improve image quality and network efficiency. In the experiment, two-dimensional random distortion vector fields were used to construct two turbulent datasets with different degrees of distortion, based on the Google Landmarks Dataset v2 dataset. The experimental results showed that compared to the CMFNet, DeblurGAN-v2, and MIMO-UNet models, the proposed CMFNetPro network achieves better performance in both quality and training cost of turbulent-image restoration. In the mixed training, CMFNetPro was 1.2391 dB (weak turbulence), 0.8602 dB (strong turbulence) respectively higher in terms of peak signal-to-noise ratio and 0.0015 (weak turbulence), 0.0136 (strong turbulence) respectively higher in terms of structure similarity compared to CMFNet. CMFNetPro was 14.4 hours faster compared to the CMFNet. This provides a feasible scheme for turbulent-image restoration based on deep learning.