• Title/Summary/Keyword: normal behavior model

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Compressive Creep Behavior of Fruits

  • Kim, M.S.;Park, J.M.
    • Proceedings of the Korean Society for Agricultural Machinery Conference
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    • 1993.10a
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    • pp.1329-1339
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    • 1993
  • Creep tests were performed to determine the nonlinear viscoelastic properties of apples and pears with the creep experiment apparatus designed in this study. Compressive creep characteristics of fruits were tested at two kinds of storage conditions, four periods of storage and three levels of initial stress. Ten replications were made at each treatment combination. The creep behavior of the fruits could be well described by the nonlinear viscoelastic model as a function of initial stress and time. however, for each level of initial stress applied, the compressive behavior of the samples was satisfactorily represented by Burger's model. For all sample fruits, the longer the samples was stored, the higher the instantaneous elastic strain was observed, and the creep progressed at a high rate. These phenomena were even more remarkable on the fruit stored at the normal temperature storage rather than at the low temperature storage.

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Improvement of Steam Generator Model for DSNP with Two-Region Tube Bundle Model for CANDU Transient Simulation (2영역 튜브모텔을 고려한 CANDU 시뮬레이션용 DSNP 증기발생기 모델 개선)

  • Cheon, Im-Jae;Seung, Seo-Jae
    • Proceedings of the Korea Society for Energy Engineering kosee Conference
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    • 1994.11a
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    • pp.135-140
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    • 1994
  • An improved steam generator model has been developed for the DSNP simulation of normal operational transient behavior of CANDU nuclear power plant. For more realistic prediction of steam generator behavior during transient, tube bundle region is divided into two separate control volumes, subcooled region and saturated region, and the variation of thermal hydraulic properties in the control volume is accounted for more realistic estimates of outlet enthalpy of each control volume. Test results for typical CANDU operational transient case show reasonable transient behavior of steam generator with overall CANDU operation and improved operational characteristics of steam generator with power variation.

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Aiding the operator during novel fault diagnosis

  • Yoon, Wan-C.;Hammer, John-M.
    • Journal of the Ergonomics Society of Korea
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    • v.6 no.1
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    • pp.9-24
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    • 1987
  • The design and philosophy are presented for an intelligent aid for a hyman operator who must diagnose a novel fault in a physical system. A novel fault is defined as one that the operator has not experienced in either real system operation or training. When the operator must diagnose a novel fault, deep reasoning about the behavior of the system components is required. To aid the human operator in this situation, four aiding approaches which provide useful information are proposed. The aiding information is generated by a qualitative, component-level model of the physical system. Both the aid and the human are able to reason causally about the system in a cooperative search for a diagnosis. The aiding features were designed to help the hyman's use of his/her mental model in predicting the normal system behavior, integrating the observations into the actual system behavior, or finding discrepancies between the two. The aid can also have direct access to the operator's hypotheses and run a hypothetical system model. The different aiding approaches will be evaluated by a series of experiments.

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Experimental comparability between steam and normal curing methods on tensile behavior of RPC

  • Guo, Min;Gao, Ri
    • Advances in concrete construction
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    • v.11 no.4
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    • pp.347-356
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    • 2021
  • To address the limitation of the commonly used steam curing of reactive powder concrete (SC-RPC) in engineering, a preparation technology of normal curing reactive powder concrete (NC-RPC) is proposed. In this study, an experimental comparative research on the mechanical properties of NC-RPC and SC-RPC under uniaxial tension is conducted. Under the premise of giving full play to the ultra-high performance of RPC, the paper tries to explore whether normal curing can replace steam curing. The results show that various mechanical indexes of NC-RPC (e.g., tensile strength, ultimate tensile strain, elastic modulus and deformation performance) could basically reach the mechanical index values in steam curing at 28d age, some performance is even better at a longer age. So it affirms the feasibility of normal curing. In this paper, the influence of normal curing age on the tensile properties of RPC is discussed, and the relationship between each index and age is introduced in detail. Based on the experimental data, the tensile mechanism of RPC is analyzed theoretically, and two kinds of tensile constitutive models for RPC are proposed, one is curvilinear model, and another one is polygonal line model. The validity of the two models is further verified by the test results of others.

Development of a 3D thermohydraulic-neutronic coupling model for accident analysis in research miniature neutron source reactor (MNSR)

  • Ahmadi, M.;Rabiee, A.;Pirouzmand, A.
    • Nuclear Engineering and Technology
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    • v.51 no.7
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    • pp.1776-1783
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    • 2019
  • To accurately analyze the accidents in nuclear reactors, a thermohydraulic-neutronic coupling calculation is required to solve fluid dynamics and nuclear reactor kinetics equations in fine cells simultaneously and evaluate the local effects of neutronic and thermohydraulic parameters on each other. In the present study, a 3D thermohydraulic-neutronic coupling model is developed, validated and then applied for Isfahan MNSR (Miniature Neutron Source reactor) safety analysis. The proposed model is developed using FLUENT software and user defined functions (UDF) are applied to simulate the neutronic behavior of MNSR. The validation of the proposed model is first evaluated using 1mk reactivity insertion experiment into Isfahan MNSR core. Then, the developed coupling code is applied for a design basis accident (DBA) scenario analysis with the insertion of maximum allowed cold core reactivity of 4 mk. The results show that the proposed model is able to predict the behavior of the reactor core under normal and accident conditions with a good accuracy.

Fatigue Life Prediction for High Strength AI-alloy under Variable Amplitude Loading (변동하중하에서 고강도 알루미늄 합금의 피로수명 예측)

  • Sim, Dong-Seok;Kim, Gang-Beom;Kim, Jeong-Gyu
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.24 no.8 s.179
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    • pp.2074-2082
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    • 2000
  • In this study, to investigate and to predict the crack growth behavior under variable amplitude loading, crack growth tests are conducted on 7075-T6 aluminum alloy. The loading wave forms are generated by normal random number generator. All wave forms have same average and RMS(root mean square) value, but different standard deviation, which is to vary the maximum load in each wave. The modified Forman's equation is used as crack growth equation. Using the retardation coefficient D defined in previous study, the load interaction effect is considered. The variability in crack growth process is described by the random variable Z which was obtained from crack growth tests under constant amplitude loading in previous work. From these, a statistical model is developed. The curves predicted by the proposed model well describe the crack growth behavior under variable amplitude loading and agree with experimental data. In addition, this model well predicts the variability in crack growth process under variable amplitude loading.

An Intelligent Emotion Recognition Model Using Facial and Bodily Expressions

  • Jae Kyeong Kim;Won Kuk Park;Il Young Choi
    • Asia pacific journal of information systems
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    • v.27 no.1
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    • pp.38-53
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    • 2017
  • As sensor technologies and image processing technologies make collecting information on users' behavior easy, many researchers have examined automatic emotion recognition based on facial expressions, body expressions, and tone of voice, among others. Specifically, many studies have used normal cameras in the multimodal case using facial and body expressions. Thus, previous studies used a limited number of information because normal cameras generally produce only two-dimensional images. In the present research, we propose an artificial neural network-based model using a high-definition webcam and Kinect to recognize users' emotions from facial and bodily expressions when watching a movie trailer. We validate the proposed model in a naturally occurring field environment rather than in an artificially controlled laboratory environment. The result of this research will be helpful in the wide use of emotion recognition models in advertisements, exhibitions, and interactive shows.

Measuring COVID-19 Effects on World and National Stock Market Returns

  • KHANTHAVIT, Anya
    • The Journal of Asian Finance, Economics and Business
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    • v.8 no.2
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    • pp.1-13
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    • 2021
  • Previous studies have found the significant adverse effects of coronavirus disease 2019 (COVID-19) on stock returns and volatility. The effects varied with the confirmed cases and deaths. However, the extent of the effects have never been measured exactly. This study proposes a measurement model for the COVID-19 effects. In the proposed model, stock returns in the COVID-19 period are weighted averages of pre-COVID-19 normal returns and COVID-19-induced returns. The effects are measured by the contributing weights of the COVID-19-induced returns. Kalman filtering is used to estimate the model for the world and Chinese markets, in combination with 10 markets - five most affected countries (United States, India, Brazil, Russia, and France) and five best recovering countries (Hong Kong, Australia, Singapore, Thailand, and South Korea). The sample returns are daily, obtained from the closing Morgan Stanley global investable market indexes. The full period is from September 24, 2018, to October 30, 2020, whereas the COVID-19 period is from November 18, 2019, to October 30, 2020. The contributing weights are significant and close to 100% for all markets. The COVID-19-induced returns replace the pre-COVID-19 normal returns; they are negatively auto-correlated and highly volatile. The COVID-19-induced returns are new normal returns in the COVID-19 period.

Stochastic Finite Element Analysis for Rock Caverns Considering the Effect of Discontinuities (불연속면의 영향을 고려한 암반동굴의 확률유한요소해석)

  • 최규섭;황신일;이경진
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 1996.10a
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    • pp.95-102
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    • 1996
  • In this study, a stochastic finite element model is proposed with a view to consider the uncertainty of physical properties of discontinuous rock mass in the analysis of structural behavior on underground caverns. In so doing, the LHS(Latin Hypercube sampling) technique has been applied to make up weak points of the Crude Monte Carlo technique. Concerning the effect of discontinuities, a joint finite element model is used that is known to be superior in explaining faults, cleavage, things of that nature. To reflect the uncertainty of material properties, the variables such as the the elastic modulus, the poisson's ratio, the joint shear stiffness, and the joint normal stiffness have been used, all of which can be applicable through normal distribution, log-normal distribution, and rectangulary uniform distribution. The validity of the newly developed computer program has been confirmed in terms of verification examples. And, the applicability of the program has been tested in terms of the analysis of the circular cavern in discontinuous rock mass.

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An Anomalous Behavior Detection Method Using System Call Sequences for Distributed Applications

  • Ma, Chuan;Shen, Limin;Wang, Tao
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.2
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    • pp.659-679
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    • 2015
  • Distributed applications are composed of multiple nodes, which exchange information with individual nodes through message passing. Compared with traditional applications, distributed applications have more complex behavior patterns because a large number of interactions and concurrent behaviors exist among their distributed nodes. Thus, it is difficult to detect anomalous behaviors and determine the location and scope of abnormal nodes, and some attacks and misuse cannot be detected. To address this problem, we introduce a method for detecting anomalous behaviors based on process algebra. We specify the architecture of the behavior detection model and the detection algorithm. The anomalous behavior detection and analysis demonstrate that our method is a good discriminator between normal and anomalous behavior characteristics of distributed applications. Performance evaluation shows that the proposed method enhances efficiency without security degradation.