• Title/Summary/Keyword: Physically based simulations

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Analysis and Evaluation for Constraint Enforcement System (제한 시스템의 분석 및 평가)

  • Hong, Min;Park, Doo-Soon;Choi, Yoo-Joo
    • Journal of the Korea Society for Simulation
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    • v.18 no.2
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    • pp.57-64
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    • 2009
  • Stable and effective constraint enforcement system is one of the crucial components for physically-based dynamic simulations. This paper presents analysis and evaluation for traditional constraint enforcement systems(Lagrange Multiplier method, Baumgarte stabilization method, Post-stabilization method, Implicit constraint enforcement method, Fast projection method) to provide a guideline to users who need to integrate a suitable constraint enforcement system into their dynamic simulations. The mathematical formulations for traditional constraint enforcement systems are presented in this paper. This paper describes a summary of evaluation which consists of constraint error comparison, computational cost, and dynamic behavior analysis to verify the efficiency of each traditional constraint enforcement system.

Modeling of CNTs and CNT-Matrix Interfaces in Continuum-Based Simulations for Composite Design

  • Lee, Sang-Hun;Shin, Kee-Sam;Lee, Woong
    • Korean Journal of Materials Research
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    • v.20 no.9
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    • pp.478-482
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    • 2010
  • A series of molecular dynamic (MD), finite element (FE) and ab initio simulations are carried out to establish suitable modeling schemes for the continuum-based analysis of aluminum matrix nanocomposites reinforced with carbon nanotubes (CNTs). From a comparison of the MD with FE models and inferences based on bond structures and electron distributions, we propose that the effective thickness of a CNT wall for its continuum representation should be related to the graphitic inter-planar spacing of 3.4${\AA}$. We also show that shell element representation of a CNT structure in the FE models properly simulated the carbon-carbon covalent bonding and long-range interactions in terms of the load-displacement behaviors. Estimation of the effective interfacial elastic properties by ab initio simulations showed that the in-plane interfacial bond strength is negligibly weaker than the normal counterpart due to the nature of the weak secondary bonding at the CNT-Al interface. Therefore, we suggest that a third-phase solid element representation of the CNT-Al interface in nanocomposites is not physically meaningful and that spring or bar element representation of the weak interfacial bonding would be more appropriate as in the cases of polymer matrix counterparts. The possibility of treating the interface as a simply contacted phase boundary is also discussed.

Enhanced Second-order Implicit Constraint Enforcement for Dynamic Simulations

  • Hong, Min;Welch, Samuel W.J.;Jung, Sun-Hwa;Choi, Min-Hyung;Park, Doo-Soon
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.2 no.1
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    • pp.51-62
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    • 2008
  • This paper proposes a second-order implicit constraint enforcement method which yields enhanced controllability compared to a first-order implicit constraints enforcement method. Although the proposed method requires solving a linear system twice, it yields superior accuracy from the constraints error perspective and guarantees the precise and natural movement of objects, in contrast to the first-order method. Thus, the proposed method is the most suitable for exact prediction simulations. This paper describes the numerical formulation of second-order implicit constraints enforcement. To prove its superiority, the proposed method is compared with the firstorder method using a simple two-link simulation. In this paper, there is a reasonable discussion about the comparison of constraints error and the analysis of dynamic behavior using kinetic energy and potential energy.

Visualization of Vector Fields from Density Data Using Moving Least Squares Based on Monte Carlo Method (몬테카를로 방법 기반의 이동최소제곱을 이용한 밀도 데이터의 벡터장 시각화)

  • Jong-Hyun Kim
    • Journal of the Korea Computer Graphics Society
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    • v.30 no.2
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    • pp.1-9
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    • 2024
  • In this paper, we propose a new method to visualize different vector field patterns from density data. We use moving least squares (MLS), which is used in physics-based simulations and geometric processing. However, typical MLS does not take into account the nature of density, as it is interpolated to a higher order through vector-based constraints. In this paper, we design an algorithm that incorporates Monte Carlo-based weights into the MLS to efficiently account for the density characteristics implicit in the input data, allowing the algorithm to represent different forms of white noise. As a result, we experimentally demonstrate detailed vector fields that are difficult to represent using existing techniques such as naive MLS and divergence-constrained MLS.

A Study on the Generation of Datasets for Applied AI to OLED Life Prediction

  • CHUNG, Myung-Ae;HAN, Dong Hun;AHN, Seongdeok;KANG, Min Soo
    • Korean Journal of Artificial Intelligence
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    • v.10 no.2
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    • pp.7-11
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    • 2022
  • OLED displays cannot be used permanently due to burn-in or generation of dark spots due to degradation. Therefore, the time when the display can operate normally is very important. It is close to impossible to physically measure the time when the display operates normally. Therefore, the time that works normally should be predicted in a way other than a physical way. Therefore, if you do computer simulations based on artificial intelligence, you can increase the accuracy of prediction by saving time and continuous learning. Therefore, if we do computer simulations based on artificial intelligence, we can increase the accuracy of prediction by saving time and continuous learning. In this paper, a dataset in the form of development from generation to diffusion of dark spots, which is one of the causes related to the life of OLED, was generated by applying the finite element method. The dark spots were generated in nine conditions, such as 0.1 to 2.0 ㎛ with the size of pinholes, the number was 10 to 100, and 50% with water content. The learning data created in this way may be a criterion for generating an artificial intelligence-based dataset.

Enhanced FFD-AABB Collision Algorithm for Deformable Objects

  • Jeon, JaeHong;Choi, Min-Hyung;Hong, Min
    • Journal of Information Processing Systems
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    • v.8 no.4
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    • pp.713-720
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    • 2012
  • Unlike FEM (Finite Element Method), which provides an accurate deformation of soft objects, FFD (Free Form Deformation) based methods have been widely used for a quick and responsive representation of deformable objects in real-time applications such as computer games, animations, or simulations. The FFD-AABB (Free Form Deformation Axis Aligned Bounding Box) algorithm was also suggested to address the collision handling problems between deformable objects at an interactive rate. This paper proposes an enhanced FFD-AABB algorithm to improve the frame rate of simulation by adding the bounding sphere based collision test between 3D deformable objects. We provide a comparative analysis with previous methods and the result of proposed method shows about an 85% performance improvement.

Dynamic Control of Redundant Manipulators based on the Minors of Jacobian Matrix (쟈코비안 행렬의 마이너(Minor)에 기초한 여유자유도 로봇의 동력학적 제어)

  • Chung, W.J.;Chung, W.K.;Youm, Y.
    • Proceedings of the KIEE Conference
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    • 1991.07a
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    • pp.767-770
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    • 1991
  • For the control of redundant manipulators, conventional dynamic control methods of local torque optimization showed the instability which resulted in physically unrealizable torque requirements. In this paper, a new dynamic control method which is based on the concept of aspects is proposed. The proposed method starts with the basic understanding of the minors in the Jacobian matrix. It was shown by computer simulations that the proposed method demonstrates a drastic reduction of torque loadings at the joints in the tracking motion of a long trajectory, and thus guarantees the stability of joint torque.

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Analytical Threshold Voltage Modeling of Surrounding Gate Silicon Nanowire Transistors with Different Geometries

  • Pandian, M. Karthigai;Balamurugan, N.B.
    • Journal of Electrical Engineering and Technology
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    • v.9 no.6
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    • pp.2079-2088
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    • 2014
  • In this paper, we propose new physically based threshold voltage models for short channel Surrounding Gate Silicon Nanowire Transistor with two different geometries. The model explores the impact of various device parameters like silicon film thickness, film height, film width, gate oxide thickness, and drain bias on the threshold voltage behavior of a cylindrical surrounding gate and rectangular surrounding gate nanowire MOSFET. Threshold voltage roll-off and DIBL characteristics of these devices are also studied. Proposed models are clearly validated by comparing the simulations with the TCAD simulation for a wide range of device geometries.

Key-Frame Based Real-Time Fluid Simulations (키-프레임 기반 실시간 유체 시뮬레이션)

  • Ryu, Ji-Hyun;Park, Sang-Hun
    • Journal of Korea Multimedia Society
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    • v.9 no.11
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    • pp.1515-1528
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    • 2006
  • Systems for physically based fluid animation have developed rapidly in the visual special effects industry and can make very high quality images. However, in the real-time application fields such as computer game, the simulation speed is more critical issue than image quality. This paper presents a real-time method for animating fluid using programmable graphics pipeline. We show that once two key-frames are given, the technique can interactively generate a sequence of images changing from the source key-frame to the target.

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Improving the Subject Independent Classification of Implicit Intention By Generating Additional Training Data with PCA and ICA

  • Oh, Sang-Hoon
    • International Journal of Contents
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    • v.14 no.4
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    • pp.24-29
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    • 2018
  • EEG-based brain-computer interfaces has focused on explicitly expressed intentions to assist physically impaired patients. For EEG-based-computer interfaces to function effectively, it should be able to understand users' implicit information. Since it is hard to gather EEG signals of human brains, we do not have enough training data which are essential for proper classification performance of implicit intention. In this paper, we improve the subject independent classification of implicit intention through the generation of additional training data. In the first stage, we perform the PCA (principal component analysis) of training data in a bid to remove redundant components in the components within the input data. After the dimension reduction by PCA, we train ICA (independent component analysis) network whose outputs are statistically independent. We can get additional training data by adding Gaussian noises to ICA outputs and projecting them to input data domain. Through simulations with EEG data provided by CNSL, KAIST, we improve the classification performance from 65.05% to 66.69% with Gamma components. The proposed sample generation method can be applied to any machine learning problem with fewer samples.