• Title/Summary/Keyword: Deterministic models

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Evaluation of Probabilistic Fracture Mechanics for Reactor Pressure Vessel under SBLOCA (소규모 냉각재 상실사고하의 원자로 압력용기에 대한 확률론적 파괴역학 평가)

  • Kim, Jong Wook;Lee, Gyu Mahn;Kim, Tae Wan
    • Transactions of the Korean Society of Pressure Vessels and Piping
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    • v.4 no.2
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    • pp.13-19
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    • 2008
  • In order to predict a remaining life of a plant, it is necessary to select the components that are critical to the plant life. The remaining life of those components shall be evaluated by considering the aging effect of materials used as well as numerous factors. However, when evaluating reliability of nuclear structural components, some problems are quite formidable because of lack of information such as operating history, material property change and uncertainty in damage models. Accordingly, if structural integrity and safety are evaluated by the deterministic fracture mechanics approach, it is expected that the results obtained are too conservative to perform a rational evaluation of plant life. The probabilistic fracture mechanics approaches are regarded as appropriate methods to rationally evaluate the plant life since they can consider various uncertainties such as sizes and shapes of cracks and degradation of material strength due to the aging effects. The objective of this study is to evaluate the structural integrity for a reactor pressure vessel under the small break loss of coolant accident by applying the deterministic and probabilistic fracture mechanics. The deterministic fracture mechanics analysis was performed using the three dimensional finite element model. The probabilistic integrity analysis was based on the Monte Carlo simulation. The selected random variables are the neutron fluence on the vessel inside surface, the content of copper, nickel, and phosphorus in the reactor pressure vessel material, and initial RTNDT.

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A Numerical Study of Smoke Movement for the Three Types of Atrium Fires using PISO Algorithm (PISO 알고리즘을 이용한 세 가지 형태의 아트리움 공간에서 화재 발생시 연기 거동에 대한 수치해석적 연구)

  • 정진용;유홍선;김성찬
    • Fire Science and Engineering
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    • v.13 no.1
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    • pp.21-30
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    • 1999
  • In this paper, the smoke filling process for the three types of atrium spaces are simulated u using the two types of deterministic fire model; zone models and field models. The zone models u used are the FffiST, CFAST, and CCFM.VENTS m떠els develo야퍼 at the Building and Fire R Research Laboratories, NIST, USA and the NBTC one-room model of FIR.ECAIι delveloped at C CSffiO, Austr;외ia. The field models used are the fire field model developed by W. K Chow and a a self-developed Sl\1EP(Smoke Movement Estimating Program) based on computational fluid d dynamics the$\alpha$1es. The results pn려icted by the two approaches are very similar. The field model u using SIl\1PLE algorithm or SIl\1PLER algorithm requires much more computing time compared w with the use of Sl\1EP using PISO algorithm.

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Research on Application of SIR-based Prediction Model According to the Progress of COVID-19 (코로나-19 진행에 따른 SIR 기반 예측모형적용 연구)

  • Hoon Kim;Sang Sup Cho;Dong Woo Chae
    • Journal of Information Technology Applications and Management
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    • v.31 no.1
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    • pp.1-9
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    • 2024
  • Predicting the spread of COVID-19 remains a challenge due to the complexity of the disease and its evolving nature. This study presents an integrated approach using the classic SIR model for infectious diseases, enhanced by the chemical master equation (CME). We employ a Monte Carlo method (SSA) to solve the model, revealing unique aspects of the SARS-CoV-2 virus transmission. The study, a first of its kind in Korea, adopts a step-by-step and complementary approach to model prediction. It starts by analyzing the epidemic's trajectory at local government levels using both basic and stochastic SIR models. These models capture the impact of public health policies on the epidemic's dynamics. Further, the study extends its scope from a single-infected individual model to a more comprehensive model that accounts for multiple infections using the jump SIR prediction model. The practical application of this approach involves applying these layered and complementary SIR models to forecast the course of the COVID-19 epidemic in small to medium-sized local governments, particularly in Gangnam-gu, Seoul. The results from these models are then compared and analyzed.

A Deterministic Model for Optimal Pricing Decisions with Price-Driven Substitution (가격차에 의해 발생하는 수요대체효과를 고려한 정태적 최적가격결정 모형 수립)

  • Kim, Sang-Won
    • Journal of the Korean Operations Research and Management Science Society
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    • v.33 no.1
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    • pp.1-17
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    • 2008
  • Market segmentation is a key strategic factor in increasing the expected profits, especially in the practice of revenue management. A manufacturing firm should manage both manufacturing quantities and pricing decisions over its segmented markets to maximize the expected profits, setting different price for each different segment. Also, market segments should be kept separate in order to prevent demand leakages between different market segments. In fact, even though the markets for different products are firmly segmented, it is not easy to keep separate segmentation because many products might be substitutable by customer buying behavior. That is, customers respond to price changes by purchasing other market's products instead of purchasing the originally requested products, which causes demand substitution effect ; This kind of substitution is referred to as price-driven substitution. Therefore, decisions on optimal prices should take into account the differences in customers' valuation of the different products. We consider a deterministic model for deciding optimal prices in the presence of price-driven substitution, and we compare both symmetrical-and asymmetrical-type demand substitutions between two segmented markets. The objective of this study is to develop analytical and numerical models to examine the impact of price-driven substitution on the optimal price levels and the total expected profits.

SYSTEM RELIABILITY-BASED EVALUATION OF BRIDGE SYSTEM REDUNDANCY AND STRENGTH (체계신뢰성에 기초한 교량의 시스템여용성 및 저항강도 평가)

  • 조효남;이승재;임종권
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 1993.10a
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    • pp.240-247
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    • 1993
  • The precise prediction of reserved carrying capacity of bridge as a system is extremely difficult especially when the bridges are highly redundant and significantly deteriorated or damaged. This paper is intended to propose a new approach for the evaluation of reserved system carrying capacity of bridges in terms of equivalent system-strength, which may be defined as a bridge system-strength corresponding to the system reliability of the bridge. This can be derived from an inverse process based on the concept of FOSM form of system reliability index. It may be emphasized that this approach is very useful for the evaluation of the deterministic system redundancy and reserve strength which are measured in terms of either probabilistic system redundancy factor and reserve factor or deterministic system redundancy factor and reserve factor. The system reliability of bridges is formulated as a parallel-series model obtained from the FAM(Failure Mode Approach) based on the major failure mechanisms. AFOSM and IST methods are used for the reliability analysis of the proposed models. The proposed approach and method for the system redundancy and reserve safety/strength are applied to the safety assessment of actual RC and steel box-girder bridges. The results of the evaluation of reserved system safety or bridge system-strength in terms of the system redundancy and the system safety/strength are significantly different from those of element reliability-based or conventional methods.

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Nonlinear finite element analysis of reinforced concrete corbels at both deterministic and probabilistic levels

  • Strauss, Alfred;Mordini, Andrea;Bergmeister, Konrad
    • Computers and Concrete
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    • v.3 no.2_3
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    • pp.123-144
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    • 2006
  • Reinforced concrete corbels are structural elements widely used in practical engineering. The complex response of these elements is described in design codes in a simplified manner. These formulations are not sufficient to show the real behavior, which, however, is an essential prerequisite for the manufacturing of numerous elements. Therefore, a deterministic and probabilistic study has been performed, which is described in this contribution. Real complex structures have been modeled by means of the finite element method supported primarily by experimental works. The main objective of this study was the detection of uncertainties effects and safety margins not captured by traditional codes. This aim could be fulfilled by statistical considerations applied to the investigated structures. The probabilistic study is based on advanced Monte Carlo simulation techniques and sophisticated nonlinear finite element formulations.

A fuzzy residual strength based fatigue life prediction method

  • Zhang, Yi
    • Structural Engineering and Mechanics
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    • v.56 no.2
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    • pp.201-221
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    • 2015
  • The fatigue damage problems are frequently encountered in the design of civil engineering structures. A realistic and accurate fatigue life prediction is quite essential to ensure the safety of engineering design. However, constructing a reliable fatigue life prediction model can be quite challenging. The use of traditional deterministic approach in predicting the fatigue life is sometimes too dangerous in the real practical designs as the method itself contains a wide range of uncertain factors. In this paper, a new fatigue life prediction method is going to be proposed where the residual strength is been utilized. Several cumulative damage models, capable of predicting the fatigue life of a structural element, are considered. Based on Miner's rule, a randomized approach is developed from a deterministic equation. The residual strength is used in a one to one transformation methodology which is used for the derivation of the fatigue life. To arrive at more robust results, fuzzy sets are introduced to model the parameter uncertainties. This leads to a convoluted fuzzy based fatigue life prediction model. The developed model is illustrated in an example analysis. The calculated results are compared with real experimental data. The applicability of this approach for a required reliability level is also discussed.

PD-DESYNC: Practical and Deterministic Desynchronization in Wireless Sensor Networks

  • Hyun, Sang-Hyun;Kim, Geon;Yang, Dongmin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.8
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    • pp.3880-3899
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    • 2019
  • Distributive desynchronization algorithms based on pulse-coupled oscillator (PCO) models have been proposed for achieving collision-free wireless transmissions. These algorithms do not depend on a global clock or infrastructure overheads. Moreover, they gradually converge to fair time-division multiple access (TDMA) scheduling by broadcasting a periodic pulse signal (called a 'firing') and adjusting the next firing time based on firings from other nodes. The time required to achieve constant spacing between phase neighbors is estimated in a closed form or via stochastic modeling. However, because these algorithms cannot guarantee the completion of desynchronization in a short and bounded timeframe, they are not practical. Motivated by the limitations of these methods, we propose a practical solution called PD-DESYNC that provides a short and deterministic convergence time using a flag firing to indicate the beginning of a cycle. We demonstrate that the proposed method guarantees the completion of desynchronization within three cycles, regardless of the number of nodes. Through extensive simulations and experiments, we confirm that PD-DESYNC not only outperforms other algorithms in terms of convergence time but also is a practical solution.

Micromechanical investigation for the probabilistic behavior of unsaturated concrete

  • Chen, Qing;Zhu, Zhiyuan;Liu, Fang;Li, Haoxin;Jiang, Zhengwu
    • Computers and Concrete
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    • v.26 no.2
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    • pp.127-136
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    • 2020
  • There is an inherent randomness for concrete microstructure even with the same manufacturing process. Meanwhile, the concrete material under the aqueous environment is usually not fully saturated by water. This study aimed to develop a stochastic micromechanical framework to investigate the probabilistic behavior of the unsaturated concrete from microscale level. The material is represented as a multiphase composite composed of the water, the pores and the intrinsic concrete (made up by the mortar, the coarse aggregates and their interfaces). The differential scheme based two-level micromechanical homogenization scheme is presented to quantitatively predict the concrete's effective properties. By modeling the volume fractions and properties of the constituents as stochastic, we extend the deterministic framework to stochastic to incorporate the material's inherent randomness. Monte Carlo simulations are adopted to reach the different order moments of the effective properties. A distribution-free method is employed to get the unbiased probability density function based on the maximum entropy principle. Numerical examples including limited experimental validations, comparisons with existing micromechanical models, commonly used probability density functions and the direct Monte Carlo simulations indicate that the proposed models provide an accurate and computationally efficient framework in characterizing the material's effective properties. Finally, the effects of the saturation degrees and the pore shapes on the concrete macroscopic probabilistic behaviors are investigated based on our proposed stochastic micromechanical framework.

Technical Reviews on Ecosystem Modeling Approach and its Applicability in Ecosystem-Based Coastal Management in Saemangeum Offshore and Geum River Estuary (생태계기반 연안관리를 위한 생태모델 개발방향에 대한 기술적 검토 - 새만금 외해역 및 금강 하구역 사례)

  • Kim, Hae-Cheol;Kim, Yong Hoon;Chang, Won-Keun;Ryu, Jongseong
    • Journal of the Korean Society for Marine Environment & Energy
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    • v.18 no.3
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    • pp.233-244
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    • 2015
  • Marine ecosystem modelling has become a more widely used decision-making tool in coastal ecosystem-based management. However, it is not trivial to develop a well calibrated/validated model with potential applicability and practicality because understanding ecological processes with complexities is a pre-requisite for developing robust ecosystem models and this accompanies a great deal of well coordinated efforts among field-going ecologists, laboratory scientists, modelers, stake-holders and managers. This report aims to provide a brief introduction on two different approaches in marine ecological models: deterministic (mechanistic) and stochastic (statistical) approach. We also included definitions, historical overview of past researches, case studies, and contextual suggestions for coastal management in Korea. A long list of references this report included in this study might be used as an introductory material for those who wish to enter ecosystem modelling field.