• Title/Summary/Keyword: baseline properties

검색결과 123건 처리시간 0.027초

Standard sand for geotechnical engineering and geoenvironmental research in Nigeria: Igbokoda sand

  • Ojuri, Oluwapelumi O.;Fijabia, David O.
    • Advances in environmental research
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    • 제1권4호
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    • pp.305-321
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    • 2012
  • This study entails establishing reference standard sand in Nigeria for engineering and geoenvironmental research work. Sands from four geographical locations in southwestern Nigeria were examined for baseline geotechnical and mineralogical properties. A total of sixteen sand samples were collected. The samples were air dried and subjected to tests in accordance with standard specifications. The tests carried out were: specific gravity, grain size analysis, moisture content, bulk density, porosity, void ratio, chemical analysis, X-ray diffraction and Differential Thermal Analysis. The properties of the samples were compared with a standard (Ottawa sand in Illinois of the United States) in order to find out which of the four samples selected from southwestern Nigeria could serve as standard baseline sand. The results show that Igbokoda sand has geotechnical and mineralogical characteristics closest to Ottawa sand. It was therefore concluded that Igbokoda sand could be used as a standard baseline sand for research work in southwestern Nigeria and other parts of Nigeria since it needs little processing to bring it to the same level as standard baseline sand, like the Ottawa sand.

Gaussian mixture model for automated tracking of modal parameters of long-span bridge

  • Mao, Jian-Xiao;Wang, Hao;Spencer, Billie F. Jr.
    • Smart Structures and Systems
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    • 제24권2호
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    • pp.243-256
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    • 2019
  • Determination of the most meaningful structural modes and gaining insight into how these modes evolve are important issues for long-term structural health monitoring of the long-span bridges. To address this issue, modal parameters identified throughout the life of the bridge need to be compared and linked with each other, which is the process of mode tracking. The modal frequencies for a long-span bridge are typically closely-spaced, sensitive to the environment (e.g., temperature, wind, traffic, etc.), which makes the automated tracking of modal parameters a difficult process, often requiring human intervention. Machine learning methods are well-suited for uncovering complex underlying relationships between processes and thus have the potential to realize accurate and automated modal tracking. In this study, Gaussian mixture model (GMM), a popular unsupervised machine learning method, is employed to automatically determine and update baseline modal properties from the identified unlabeled modal parameters. On this foundation, a new mode tracking method is proposed for automated mode tracking for long-span bridges. Firstly, a numerical example for a three-degree-of-freedom system is employed to validate the feasibility of using GMM to automatically determine the baseline modal properties. Subsequently, the field monitoring data of a long-span bridge are utilized to illustrate the practical usage of GMM for automated determination of the baseline list. Finally, the continuously monitoring bridge acceleration data during strong typhoon events are employed to validate the reliability of proposed method in tracking the changing modal parameters. Results show that the proposed method can automatically track the modal parameters in disastrous scenarios and provide valuable references for condition assessment of the bridge structure.

Estimating the Mixture of Proportional Hazards Model with the Constant Baseline Hazards Function

  • Kim Jong-woon;Eo Seong-phil
    • 한국신뢰성학회:학술대회논문집
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    • 한국신뢰성학회 2005년도 학술발표대회 논문집
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    • pp.265-269
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    • 2005
  • Cox's proportional hazards model (PHM) has been widely applied in the analysis of lifetime data, and it can be characterized by the baseline hazard function and covariates influencing systems' lifetime, where the covariates describe operating environments (e.g. temperature, pressure, humidity). In this article, we consider the constant baseline hazard function and a discrete random variable of a covariate. The estimation procedure is developed in a parametric framework when there are not only complete data but also incomplete one. The Expectation-Maximization (EM) algorithm is employed to handle the incomplete data problem. Simulation results are presented to illustrate the accuracy and some properties of the estimation results.

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Structural model updating of the Gageocho Ocean Research Station using mass reallocation method

  • Kim, Byungmo;Yi, Jin-Hak
    • Smart Structures and Systems
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    • 제26권3호
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    • pp.291-309
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    • 2020
  • To study oceanic and meteorological problems related to climate change, Korea has been operating several ocean research stations (ORSs). In 2011, the Gageocho ORS was attacked by Typhoon Muifa, and its structural members and several observation devices were severely damaged. After this event, the Gageocho ORS was rehabilitated with 5 m height to account for 100-yr extreme wave height, and the vibration measurement system was equipped to monitor the structural vibrational characteristics including natural frequencies and modal damping ratios. In this study, a mass reallocation method is presented for structural model updating of the Gageocho ORS based on the experimentally identified natural frequencies. A preliminary finite element (FE) model was constructed based on design drawings, and several of the candidate baseline FE models were manually built, taking into account the different structural conditions such as corroded thickness. Among these candidate baseline FE models, the most reasonable baseline FE model was selected by comparing the differences between the identified and calculated natural frequencies; the most suitable baseline FE model was updated based on the identified modal properties, and by using the pattern search method, which is one of direct search optimization methods. The mass reallocation method is newly proposed as a means to determine the equivalent mass quantities along the height and in a floor. It was found that the natural frequencies calculated based on the updated FE model was very close to the identified natural frequencies. In conclusion, it is expected that these results, which were obtained by updating a baseline FE model, can be useful for establishing the reference database for jacket-type offshore structures, and assessing the structural integrity of the Gageocho ORS.

모델링 오차를 고려한 신경망 기법 기반 손상추정방법 (Neural Networks-Based Damage Detection for Bridges Considering Errors in Baseline Finite Element Models)

  • Lee, Jong-Jae;Yun, Chung-Bang;Lee, Jong-Won;Jung, Hie-Young
    • 한국전산구조공학회:학술대회논문집
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    • 한국전산구조공학회 2003년도 봄 학술발표회 논문집
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    • pp.382-387
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    • 2003
  • In this paper, a neural networks-based damage detection method using the modal properties is presented, which can effectively reduce the effect of the modeling errors in the baseline finite element model from which the training patterns for the networks are to be generated. The differences or the ratios of the mode shape components between before and after damage are used as the input to the neural networks in this method, since they are found to be less sensitive to the modeling errors than the mode shapes themselves. Results of laboratory test on a simply supported bridge model and field test on a bridge with multiple girders confirm the applicability of the present method.

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저온과 고온 환경 하에서 카본/에폭시 복합재의 기계적 물성 평가 (Evaluation of Mechanical Properties of Carbon/Epoxy Composites Under In situ Low- and High-Temperature Environments)

  • 임재문;신광복;황태경
    • 대한기계학회논문집A
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    • 제39권6호
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    • pp.567-573
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    • 2015
  • 본 논문은 저온과 고온 환경 하에서 카본/에폭시 복합재의 기계적 물성 변화를 평가하는데 목적을 두고 있다. 기계적 물성 변화 평가는 환경 챔버와 전기로를 이용하여 $-40^{\circ}C$에서 $220^{\circ}C$까지의 온도에 대해 섬유방향과 섬유 직각방향의 인장 물성, 면내 전단 물성 그리고 층간전단강도에 대해 평가를 수행하였다. $-40^{\circ}C$ 저온환경에서의 기계적 물성은 상온에서의 물성보다 증가하는 것을 확인하였다. 섬유방향 물성은 온도가 증가함에 따라 물성저하가 서서히 발생하였으나, 섬유직각방향 물성, 면내전단 물성 그리고 층간전단강도는 $140^{\circ}C$ 이상의 온도에서 수지의 유리전이로 인해 급격한 물성저하가 발생하는 것을 확인하였다. $100^{\circ}C$ 환경에서 섬유 직각방향 인장물성 증가의 직접적인 원인은 수지의 후경화로 인한 현상으로 판단된다.

함산소 물질이 혼합된 디젤연료의 분무특성 (Spray Characteristics of Diesel Fuel with Oxygenates)

  • 류근영;하종석;노수영
    • 한국분무공학회지
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    • 제6권3호
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    • pp.38-44
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    • 2001
  • The effect of four diesel fuels with oxygenated agents fuels on spray properties from plain-orifice atomizer was investigated. The oxygenates evaluated were diglyme, MTBE, DEE and DMM and were blended in weights of 5, 10, 15, 20 and 30% in a baseline diesel fuel. The physical properties such as surface tension, density and viscosity are also measured for each blended oxygenated fuels. It was found that changes in physical properties of fuels considered are enough to influence spray properties, i.e. spray angle, spray tip penetration and mean drop size. Spray properties were measured by PMAS(particle motion analysis system) which is employing a point measurement technology. Spray angle increased with increase in oxygenate content. The effect, however, was not great in the higher blend level. The oxygenated fuels produced more shorter spray tip penetration than diesel fuels. SMD was decreased with the increase in blending percent. SMD for DMM and DEE are represented 10.33 and 3.41% decreasing rates respectively. It was found that changes in spray characteristics of oxygenated fuel were easily large enough to impact pollutant emissions. It was clear from this study that spray characteristics of oxygenated fuel is one of possible cause of reducing pollutant emissions. It was clear from this study that spray characteristics of oxygenated fuel is one of possible cause of reducing pollutant emissions from diesel engines when oxygenated fuels is applied.

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Association of epicardial adipose tissue with metabolic risk factors on cardiovascular outcomes: serial coronary computed tomography angiography study

  • Sungjoon Park;Dong Eun Kim;Su Min Kim;JungMin Choi;Sang Joon Park;Hae-Young Lee;Eun Ju Chun
    • The Korean journal of internal medicine
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    • 제39권2호
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    • pp.283-294
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    • 2024
  • Background/Aims: Epicardial adipose tissue (EAT) shares pathophysiological properties with other visceral fats and potentially triggers local inflammation. However, the association of EAT with cardiovascular disease (CVD) is still debatable. The study aimed to observe the changes and associations in EAT and risk factors over time, as well as to investigate whether EAT was associated with CVD. Methods: A total of 762 participants from Seoul National University Hospital (SNUH) and SNUH Gangnam Center were included in this study. EAT was measured using coronary computed tomography angiography. Results: Baseline EAT level was positively associated with body mass index (BMI), calcium score, atherosclerotic cardiovascular disease (ASCVD) 10-year risk score, glucose, triglycerides (TG)/high-density lipoprotein (HDL), but not with total cholesterol, low-density lipoprotein (LDL). At follow-up, EAT levels increased in all groups, with low EAT groups demonstrating a significant increase in EAT per year. Change in EAT was associated with a change in BMI, TG/HDL, and glucose, while changes in LDL, calcium score, and ASCVD 10-year risk score were not associated. Although calcium score and ASCVD 10-year risk score were associated with CVD events, baseline information of EAT, baseline EAT/body surface area, or EAT change was not available. Conclusions: Metabolic risks, e.g., BMI, TG/HDL, and glucose, were associated with EAT change per year, whereas classical CVD risks, e.g., LDL, calcium score, and ASCVD 10-year risk score, were not. The actual CVD event was not associated with EAT volume, warranting future studies combining qualitative assessments with quantitative ones.

조음자질을 이용한 한국인 학습자의 영어 발화 자동 발음 평가 (Automatic pronunciation assessment of English produced by Korean learners using articulatory features)

  • 류혁수;정민화
    • 말소리와 음성과학
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    • 제8권4호
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    • pp.103-113
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    • 2016
  • This paper aims to propose articulatory features as novel predictors for automatic pronunciation assessment of English produced by Korean learners. Based on the distinctive feature theory, where phonemes are represented as a set of articulatory/phonetic properties, we propose articulatory Goodness-Of-Pronunciation(aGOP) features in terms of the corresponding articulatory attributes, such as nasal, sonorant, anterior, etc. An English speech corpus spoken by Korean learners is used in the assessment modeling. In our system, learners' speech is forced aligned and recognized by using the acoustic and pronunciation models derived from the WSJ corpus (native North American speech) and the CMU pronouncing dictionary, respectively. In order to compute aGOP features, articulatory models are trained for the corresponding articulatory attributes. In addition to the proposed features, various features which are divided into four categories such as RATE, SEGMENT, SILENCE, and GOP are applied as a baseline. In order to enhance the assessment modeling performance and investigate the weights of the salient features, relevant features are extracted by using Best Subset Selection(BSS). The results show that the proposed model using aGOP features outperform the baseline. In addition, analysis of relevant features extracted by BSS reveals that the selected aGOP features represent the salient variations of Korean learners of English. The results are expected to be effective for automatic pronunciation error detection, as well.

다단계 베이스라인 네트워크에서의 분산 라우팅 제어 방법에 관한 연구 (On a Distributed Routing Control Scheme in Multistage Baseline Networks)

  • 손유익;안광선
    • 대한전자공학회논문지
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    • 제26권6호
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    • pp.15-22
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    • 1989
  • 본 논문은 다단계 베이스라인 네트워크에서 네트워크의 제어를 스위칭 소자들에 분산시키는 라우팅 방법에 대해서 다룬다. 여기서 사용된 라우팅 방법은 목적지 주소의 이진표현을 라우팅 택으로 사용하는 목적지 택 라우팅 방법을 채택하였다. 주어진 네트워크의 구조적 특성을 이용하여, 하나의 시작지 주소로 부터 임의의 목적지 주소로 전송이 가능한 분산 알고리듬을 제안하였다. 제안된 알고리듬의 성능분석은 컴퓨터를 시뮬레이션을 통하여 수행되었으며 그 결과를 시간 복잡도 면에서 다른 방법과 비교하였다.

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