• Title/Summary/Keyword: models & modeling

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Nonlinear Dynamic Analysis of RC Frames Based on Constitutive Models of Constituent Materials (재료의 구성모델에 따른 철근콘크리트 골조의 비선형 동적거동 특성 차이에 관한 연구)

  • Heo, YeongAe;Kang, Thomas H.K.
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.17 no.4
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    • pp.1-8
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    • 2013
  • Constitutive modeling of constituent materials is very important for reinforced concrete (RC) frames. Cyclic constitutive behavior of unconfined concrete, confined concrete and reinforcing steel should be well defined in fiber-based discretization of RC sections. This study performs nonlinear dynamic analyses of RC frame structures to investigate the sensitivity of seismic behavior of such frames to different constitutive models of constituent materials. The study specifically attempts to examine confinement effects in concrete modeling and degrading effects in steel modeling, which substantially affects the monotonic, cyclic and seismic responses of RC members and frames. Based on the system level analysis, it is shown that the response of non-ductile frames is less sensitive to confined concrete models while the modeling of reinforcing steel is quite influential to the inelastic response of both non-ductile and ductile frames.

International case study comparing PSA modeling approaches for nuclear digital I&C - OECD/NEA task DIGMAP

  • Markus Porthin;Sung-Min Shin;Richard Quatrain;Tero Tyrvainen;Jiri Sedlak;Hans Brinkman;Christian Muller;Paolo Picca;Milan Jaros;Venkat Natarajan;Ewgenij Piljugin;Jeanne Demgne
    • Nuclear Engineering and Technology
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    • v.55 no.12
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    • pp.4367-4381
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    • 2023
  • Nuclear power plants are increasingly being equipped with digital I&C systems. Although some probabilistic safety assessment (PSA) models for the digital I&C of nuclear power plants have been constructed, there is currently no specific internationally agreed guidance for their modeling. This paper presents an initiative by the OECD Nuclear Energy Agency called "Digital I&C PSA - Comparative application of DIGital I&C Modelling Approaches for PSA (DIGMAP)", which aimed to advance the field towards practical and defendable modeling principles. The task, carried out in 2017-2021, used a simplified description of a plant focusing on the digital I&C systems important to safety, for which the participating organizations independently developed their own PSA models. Through comparison of the PSA models, sensitivity analyses as well as observations throughout the whole activity, both qualitative and quantitative lessons were learned. These include insights on failure behavior of digital I&C systems, experience from models with different levels of abstraction, benefits from benchmarking as well as major contributors to the core damage frequency and those with minor effect. The study also highlighted the challenges with modeling of large common cause component groups and the difficulties associated with estimation of key software and common cause failure parameters.

Comparison of Head-related Transfer Function Models Based on Principal Components Analysis (주성분 분석법을 이용한 머리전달함수 모형화 기법의 성능 비교)

  • Hwang, Sung-Mok;Park, Young-Jin;Park, Youn-Sik
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.18 no.6
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    • pp.642-653
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    • 2008
  • This study deals with modeling of head-related transfer functions(HRTFs) using principal components analysis(PCA) in the time and frequency domains. Four PCA models based on head-related impulse responses(HRIRs), complex-valued HRTFs, augmented HRTFs, and log-magnitudes of HRTFs are investigated. The objective of this study is to compare modeling performances of the PCA models in the least-squares sense and to show the theoretical relationship between the PCA models. In terms of the number of principal components needed for modeling, the PCA model based on HRIR or augmented HRTFs showed more efficient modeling performance than the PCA model based on complex-valued HRTFs. The PCA model based on HRIRs in the time domain and that based on augmented HRTFs in the frequency domain are shown to be theoretically equivalent. Modeling performance of the PCA model based on log-magnitudes of HRTFs cannot be compared with that of other PCA models because the PCA model deals with log-scaled magnitude components only, whereas the other PCA models consider both magnitude and phase components in linear scale.

A Comparative Study on HSI and MaxEnt Habitat Prediction Models: About Prionailurus bengalensis (HSI와 MaxEnt를 통한 삵의 서식지 예측 모델 비교 연구)

  • Yoo, Da-Young;Lim, Tai-Yang;Kim, Whee-Moon;Song, Won-Kyong
    • Journal of the Korean Society of Environmental Restoration Technology
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    • v.24 no.5
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    • pp.1-14
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    • 2021
  • Excessive development and urbanization have destroyed animal, plant, habitats and reduced biodiversity. In order to preserve species diversity, habitat prediction studies are have been conducted at home and overseas using various modeling techniques. This study was conducted to suggest optimal habitat modeling research by comparing HSI and MaxEnt, which are widely used among habitat modeling techniques. The study was targeted on the endangered species of Prionailurus bengalensis in nearby areas (5460.35km2) including Cheonan City, and the same data were used for analysis to compare those models. According to the HSI analysis, Prionailurus bengalensis's habitat probability was 74.65% for less than 0.5 and 25.34% for more than 0.5 and the top 30% were forest (99.07%). MaxEnt's analysis showed that 56.22% of those below 0.5 and 43.79% of those above 0.5 were found to have a high explanatory power of 78.3% of AUC. The Paired Wilcoxn test, which evaluated the significance of thoes models, confirmed that the mean difference between the two models was statistically significant (p<0.05). Analysis of the differences in the results of those models using the matrix table shows that score 24.43% HSI and MaxEnt was accordance,12.44% of the 0.0 to 0.2 section, 7.22% of the 0.2 to 0.4 section, 2.73% of the 0.4 to 0.6 section, 1.96% of the 0.6 to 0.8, and 0.08% of the 0.9 to 1.0. To verify where the score difference appears, the result values of those models were reset to values from 1 to 5 and overlaid. Overlapping analysis resulted in 30.26% of the Strongly agree values, 56.77% of the agree values, and 11.92% of the Disagree values. The places where the difference in scores occurs were analyzed in the order of forest (45.23%), agricultural land (34.57%), and urbanization area (7.65%). This confirmed that the analysis of the same target species within the same target site also has differences in forecasts depending on the modelling method. Therefore, a novel analysis method combining the advantages of each modeling in habitat prediction studies should be developed, and future study may be used to select Prionailurus bengalensis and species-protected areas and species protection areas in the future. Further research is judged to require higher accuracy studies through the use of various modeling techniques and on-site verification.

General problem solver를 이용한 intelligent LP 모형화에 대한 연구

  • 박성주;권오병
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 1991.10a
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    • pp.469-474
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    • 1991
  • Recent interests in intelligent LP modeling aim to support MS/OR-naive users to be able to apply LP models to practical problems without the expert knowledges required. For more generalized LP modeling, a GPS(General Problem Solver)-based approach is suggested in this paper. It identifies modeling process as a means-ends analysis process. In view of this approach, a) we first divide the knowledges into domain specific assertive knowledges(state) and procedural knowledges about LP modeling(operator and macro) for model-domain independence, b) and then generate LP model according to the difference resolution techniques.

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Towards A Better Understanding of Space Debris Environment

  • Hanada, Toshiya
    • International Journal of Aerospace System Engineering
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    • v.3 no.1
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    • pp.5-9
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    • 2016
  • This paper briefly introduces efforts into space debris modeling towards a better understanding of space debris environment. Space debris modeling mainly consists of debris generation and orbit propagation. Debris generation can characterize and predict physical properties of fragments originating from explosions or collisions. Orbit propagation can characterize, track, and predict the behavior of individual or groups of space objects. Therefore, space debris modeling can build evolutionary models as essential tools to predict the stability of the future space debris populations. Space debris modeling is also useful and effective to improve the efficiency of measurements to be aware of the present environment.

Residual spatial autocorrelation in macroecological and biogeographical modeling: a review

  • Gaspard, Guetchine;Kim, Daehyun;Chun, Yongwan
    • Journal of Ecology and Environment
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    • v.43 no.2
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    • pp.191-201
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    • 2019
  • Macroecologists and biogeographers continue to predict the distribution of species across space based on the relationship between biotic processes and environmental variables. This approach uses data related to, for example, species abundance or presence/absence, climate, geomorphology, and soils. Researchers have acknowledged in their statistical analyses the importance of accounting for the effects of spatial autocorrelation (SAC), which indicates a degree of dependence between pairs of nearby observations. It has been agreed that residual spatial autocorrelation (rSAC) can have a substantial impact on modeling processes and inferences. However, more attention should be paid to the sources of rSAC and the degree to which rSAC becomes problematic. Here, we review previous studies to identify diverse factors that potentially induce the presence of rSAC in macroecological and biogeographical models. Furthermore, an emphasis is put on the quantification of rSAC by seeking to unveil the magnitude to which the presence of SAC in model residuals becomes detrimental to the modeling process. It turned out that five categories of factors can drive the presence of SAC in model residuals: ecological data and processes, scale and distance, missing variables, sampling design, and assumptions and methodological approaches. Additionally, we noted that more explicit and elaborated discussion of rSAC should be presented in species distribution modeling. Future investigations involving the quantification of rSAC are recommended in order to understand when rSAC can have an adverse effect on the modeling process.

Development of GUI System for Coupling of Multi-Dimensional Hydraulic Models (다차원수리모형을 이용한 연계모의 GUI시스템 개발)

  • Ahn, Jung Min;Lyu, Siwan
    • Journal of Wetlands Research
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    • v.14 no.3
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    • pp.353-363
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    • 2012
  • In order to operate the hydraulic structures efficiently for reducing flood damage after 4 Major River Restoration Project, it is essential to obtain enough hydraulic information with certain reliability. A coupled modeling system, providing spatial hydraulic information, for multi-dimensional hydraulic models was developed to complement 1-D hydraulic modeling. Developed system can offers spatial and grid unit information as well as line and section unit information from 1-D modeling. It is considered that the coupled modeling system can be used to provide various kinds of hydraulic information for river management and treatment.

Modeling and Verification Methodology for Context-awareness Service using Colored Petri-Net (Colored Petri-Net을 이용한 상황인식 서비스의 모델링과 검증 방법)

  • Han, Seung-Wok;Youn, Hee-Yong
    • Journal of KIISE:Software and Applications
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    • v.36 no.4
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    • pp.283-290
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    • 2009
  • Context-awareness is one of the key features of ubiquitous paradigm. A methodology that is specifying the relationships between the contexts and services needs to be developed to intelligently and sensitively deal with dynamic environment. The existing models on context-aware modeling are difficult to verify the correctness of models with respect to timeliness. In this paper we propose an approach which includes timing constraint in the relations of the context model, and verify its effectiveness using colored Petri-Net. Moreover, a context-modeling toolkit including context-awareness engine and simulator is developed to support agent-based context-aware service. The effectiveness of the proposed methodology is demonstrated using an example of Usilvercare.

Object-oriented Modeling for Broadband Network Simulation (광대역 통신망 시뮬레이션을 위한 객체지향 모델링)

  • 이영옥
    • Journal of the Korea Society for Simulation
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    • v.3 no.1
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    • pp.151-165
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    • 1994
  • Broadband network based on the Asynchronous Transfer Mode(ATM) concept are becoming the target technology for the emerging Broadband Integrated Services Digital Network(B-ISDN). Since B-ISDN is very complex and requites a great amount of investment, optimum design and performance analysis of such systems are very important. Simulation can be widely used to analyze and examine the broadband network behavior. However, for the complicated system like broadband networks it is extremely difficult and time-consuming to develop a complete model for simulation. In this paper, an object-oriented modeling approach for the broadband network simulation is presented for the effective and efficient modeling. Object-oriented approaches can provide a good structuring capability for complicated simulation models and facilitate the development of reusable and extensible simulation models. We have developed an object-oriented model which consists of object model and behavior model. In the object mode., the components of the broadband network and both constant bit rate(CBR) and variable bit rate(VBR) traffic types of call level, burst level, and cell level are modeled as object classes. In the behavior model, the dynamic features for each object class are represented using the state transition diagram. It has been shown by illustration that objectoriented modeling is an effective tool for modeling the complicated B-ISDN.

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