• 드라이브 ㆍ 컨트롤
• /
• 제20권4호
• /
• pp.9-16
• /
• 2023

This paper analyzed a drainage tower used to drain water in flooded areas. Multi-body dynamics simulation was used to analyze the dynamic behavior of the drainage tower. Structural analysis, flexible-body dynamic analysis, and rigid body dynamic analysis were done to study the maximum Von-Mises stress of the drainage tower. The results showed that the maximum Von-Mises stress occurs at the turn table, and it decreases when the angle of the boom is increased. Also, the rate of the change of angle affects the maximum stress so that the maximum stress changes more when the angular velocity of the boom increases. Based on the rigid body dynamic analysis and the theoretical analysis results, the centrifugal force from the angular velocity makes the difference in the maximum stress at the turn table because of the difference in their direction. Consequently, it was concluded that the centrifugal force should be considered when designing construction machinerythat can rotate.

• Interaction and multiscale mechanics
• /
• 제3권3호
• /
• pp.235-255
• /
• 2010

This paper investigates the heat equation for domains subjected to an internal source with a sharp spatial gradient. The solution is first approximated using linear finite elements, and sufficiently small time-step sizes to yield stable simulations. The main area of interest is then in the ability to approximate the solution using Generalized Finite Elements, and again explore the time-step limitations required for stable simulations. Both high order elements, as well as elements with special enrichments are used to generate solutions. When compared to linear finite elements, the high order elements deliver better accuracy at a given level of mesh refinement, but do not offer an increase in critical time-step size. When special enrichment functions are used, the solution can be approximated accurately on very coarse meshes, while yielding solutions which are both accurate and computationally efficient. The major conclusion of interest is that the significantly larger element size yields larger allowable time-step sizes while still maintaining stability of the time-stepping algorithm.

• 디자인학연구
• /
• 제17권4호
• /
• pp.141-148
• /
• 2004

본 논문은 스텝 애니메이션에서 표현되어지는 감성을 정의하고, 스텝 관련 감성 자극 요소들을 추출 측정, 분석하여 스텝의 직관적인 감성 표현을 정량화시키는 것을 목적으로 하고 있다. 실험 방법으로는 스텝 관련 27개의 감성 표현 어휘와 36개의 샘플 스텝 동영상의 상관관계를 설문 조사하였다. 통합된 데이터를 수량화 이론 III류를 이용하여 스텝의 감성적 멘털구조를 2차원 평면화 하였다. 이를 분석한 결과, 감성 스텝은 가로의 자신감 축과 세로의 안정감 축으로 형성되어 있음을 밝혀내었다. 감성 스텝의 2차원 분포도를 분석한 결과, <자신감, 불안감 쪽> 2사분면과 <자신감, 안정감 쪽> 3사분면은 데이터가 풍부한 반면 <소심함, 불안감 쪽> 1사분면과 <소심함, 안정감 쪽> 4사분면의 데이터 분포가 희박함을 보여주었다. 이러한 그래프 분석을 통해 불안감이 느껴지면서 소심한 감성과 안정감이 느껴지는 소심한 캐릭터의 감성은 스텝만으로 표현하기에는 난해한 감성 표현임을 파악할 수 있었다. 감성에 영향을 미치는 스텝의 신체 물리적 요소로는 <스텝의 간격> <스텝의 속도> <골반(Y축)의 움직임 각도> <팔 스윙 폭> <척추(x축)의 움직임 각도> <신체의 기울기> 6가지로 선정하여 분석하였다. 그 결과 <스텝의 속도>와 <신체의 기울기>가 스텝의 감성 자극에 가장 큰 영향을 미치는 요소임을 밝혀낼 수 있었다. 본 연구를 통해 캐릭터의 미묘한 감성 상태를 스텝 애니메이션에 자연스럽게 표현해 내는 과정에 있어 애니메이터들의 주관적인 가성 표현들을 객관화, 정량화시키고자 하였으며 향후 이 데이터들을 활용한 멀티컨텐츠의 적용을 목표로 하고 있다.

• 한국전산유체공학회:학술대회논문집
• /
• 한국전산유체공학회 1998년도 추계 학술대회논문집
• /
• pp.13-18
• /
• 1998

The practical use of the particle image velocimetry(PIV), a whole-field velocity measurement method, requires the use of fast, reliable, computer-based methods for tracking velocity vectors. The full search block matching, the most widely studied and applied technique both in area of PIV and Image Coding and Compression, is computationally costly. Many less expensive alternatives have been proposed mostly in the area of Image Coding and Compression. Among others, TSS, NTSS, HPM are introduced for the past PIV analysis, and found to be successful. But, these algorithms are based on small dynamic range, 7 pixels/frame in maximum displacement. To analyze the images with large displacement, Even and Odd field image separation and a simple version of multi-resolution hierarchical procedures are introduced in this paper. Comparison with other algorithms are summarized. A Results of application to the turbulent backward step flow shows the improvement of new algorithm.

• Nuclear Engineering and Technology
• /
• 제51권1호
• /
• pp.104-115
• /
• 2019

Since the Fukushima Daiichi accident, there has been an emphasis on the risk resulting from multi-unit accidents. Human reliability analysis (HRA) is one of the important issues in multi-unit probabilistic safety assessment (MUPSA). Hence, there is a need to properly identify all the human and organizational factors relevant to a multi-unit incident scenario in a nuclear power plant (NPP). This study identifies and categorizes the human and organizational factors relevant to a multi-unit incident scenario of NPPs based on a review of relevant literature. These factors are then analyzed to ascertain all possible unit-to-unit interactions that need to be considered in the multi-unit HRA and the pattern of interactions. The human and organizational factors are classified into five categories: organization, work device, task, performance shaping factors, and environmental factors. The identification and classification of these factors will significantly contribute to the development of adequate strategies and guidelines for managing multi-unit accidents. This study is a necessary initial step in developing an effective HRA method for multiple NPP units in a site.

• 한국IT서비스학회지
• /
• 제7권1호
• /
• pp.117-130
• /
• 2008

Multi-attribute risk assessments provide a useful framework for systematic quantitative risk assessment that the security manager can use to prioritize security requirements and threats. In the first step, the security managers identify the four significant outcome attributes(lost revenue, lost productivity, lost customer, and recovery cost). Next. the security manager estimates the frequency and severity(three points estimates for outcome attribute values) for each threat and rank the outcome attributes according to AHP(Analytic Hierarchy Process). Finally, we generate the threat index by using muiti-attribute function and make sensitivity analysis with simulation package(Crystal Ball). In this paper, we show how multi-attribute risk analysis techniques from the field of security risk management can be used by security managers to prioritize their organization's threats and their security requirements, eventually they can derive threat index. This threat index can help security managers to decide whether their security investment is consistent with the expected risks. In addition, sensitivity analysis allows the security manager to explore the estimates to understand how they affect the selection.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제14권4호
• /
• pp.1579-1602
• /
• 2020

In the design of production system, buffer capacity allocation is a major step. Through polymorphism analysis of production capacity and production capability, this paper investigates a buffer allocation optimization problem aiming at the multi-stage production line including unreliable machines, which is concerned with maximizing the system theoretical production rate and minimizing the system state entropy for a certain amount of buffers simultaneously. Stochastic process analysis is employed to establish Markov models for repairable modular machines. Considering the complex structure, an improved vector UGF (Universal Generating Function) technique and composition operators are introduced to construct the system model. Then the measures to assess the system's multi-state reliability and structural complexity are given. Based on system theoretical production rate and system state entropy, mathematical model for buffer capacity optimization is built and optimized by a specific genetic algorithm. The feasibility and effectiveness of the proposed method is verified by an application of an engine head production line.

• Journal of Advanced Marine Engineering and Technology
• /
• 제32권4호
• /
• pp.585-595
• /
• 2008

Process design of multi-stage forging for a bolt with nonaxisymmetric washer cam has been studied by using finite element method. For shape complexity of the bolt, it is impossible to manufacture in a single stage forging. To design multi-stage forging for the bolt the forging load and fiber flow of each step have been analyzed by using commercial finite element code DEFORM-3D. Simulated results have been compared with experimental ones. Multi-stage forging process has been designed with four stages. The workpiece should be eccentric shape until third forging stage. And then bolt head and washer of eccentrical shape is created in last stage. As a results, It was predicted that shape of product would be good and effective strain would be uniformly distributed in the product. Also, it was predicted whether defects would exist or not by reviewing the fiber flow.

• Journal of Computing Science and Engineering
• /
• 제5권1호
• /
• pp.1-18
• /
• 2011

As the first step toward real-time multi-core computing, this paper presents a novel approach to bounding the worst-case performance for threads running on multi-core processors with shared L2 instruction caches. The idea of our approach is to compute the worst-case instruction access interferences between different threads based on the program control flow information of each thread, which can be statically analyzed. Our experiments indicate that the proposed approach can reasonably estimate the worst-case shared L2 instruction cache misses by considering the inter-thread instruction conflicts. Also, the worst-case execution time (WCET) of applications running on multi-core processors estimated by our approach is much better than the estimation by simply assuming all L2 instruction accesses are misses.

• 한국멀티미디어학회논문지
• /
• 제21권12호
• /
• pp.1467-1472
• /
• 2018

For the problem that the face image of surveillance video cannot be accurately identified due to the low resolution, this paper proposes a low resolution face recognition solution based on convolutional neural network model. Convolutional Neural Networks (CNN) model for multi-scale input The CNN model for multi-scale input is an improvement over the existing "two-step method" in which low-resolution images are up-sampled using a simple bi-cubic interpolation method. Then, the up sampled image and the high-resolution image are mixed as a model training sample. The CNN model learns the common feature space of the high- and low-resolution images, and then measures the feature similarity through the cosine distance. Finally, the recognition result is given. The experiments on the CMU PIE and Extended Yale B datasets show that the accuracy of the model is better than other comparison methods. Compared with the CMDA_BGE algorithm with the highest recognition rate, the accuracy rate is 2.5%~9.9%.