• Title/Summary/Keyword: stochastic modeling

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EXPLORING NOVEL APPROACHES FOR ESTIMATING FRACTIONAL STOCHASTIC PROCESSES THROUGH PRACTICAL APPLICATIONS

  • NABIL LAICHE;LAID GASMI;RAMAN VINOTH;HALIM ZEGHDOUDI
    • Journal of applied mathematics & informatics
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    • v.42 no.2
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    • pp.223-235
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    • 2024
  • In this paper, our primary focus revolves around the examination of a set of fractional stochastic models. Through our investigation, we can establish the presence of a solution and its distinctiveness. Additionally, we employ a moment-based algorithm to estimate the coefficients within these models and provide evidence that these estimations maintain their asymptotic characteristics. To support this claim, we conduct experimental studies using simulations and numerical examples.

Uncertainty quantification of PWR spent fuel due to nuclear data and modeling parameters

  • Ebiwonjumi, Bamidele;Kong, Chidong;Zhang, Peng;Cherezov, Alexey;Lee, Deokjung
    • Nuclear Engineering and Technology
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    • v.53 no.3
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    • pp.715-731
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    • 2021
  • Uncertainties are calculated for pressurized water reactor (PWR) spent nuclear fuel (SNF) characteristics. The deterministic code STREAM is currently being used as an SNF analysis tool to obtain isotopic inventory, radioactivity, decay heat, neutron and gamma source strengths. The SNF analysis capability of STREAM was recently validated. However, the uncertainty analysis is yet to be conducted. To estimate the uncertainty due to nuclear data, STREAM is used to perturb nuclear cross section (XS) and resonance integral (RI) libraries produced by NJOY99. The perturbation of XS and RI involves the stochastic sampling of ENDF/B-VII.1 covariance data. To estimate the uncertainty due to modeling parameters (fuel design and irradiation history), surrogate models are built based on polynomial chaos expansion (PCE) and variance-based sensitivity indices (i.e., Sobol' indices) are employed to perform global sensitivity analysis (GSA). The calculation results indicate that uncertainty of SNF due to modeling parameters are also very important and as a result can contribute significantly to the difference of uncertainties due to nuclear data and modeling parameters. In addition, the surrogate model offers a computationally efficient approach with significantly reduced computation time, to accurately evaluate uncertainties of SNF integral characteristics.

Propagation of radiation source uncertainties in spent fuel cask shielding calculations

  • Ebiwonjumi, Bamidele;Mai, Nhan Nguyen Trong;Lee, Hyun Chul;Lee, Deokjung
    • Nuclear Engineering and Technology
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    • v.54 no.8
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    • pp.3073-3084
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    • 2022
  • The propagation of radiation source uncertainties in spent nuclear fuel (SNF) cask shielding calculations is presented in this paper. The uncertainty propagation employs the depletion and source term outputs of the deterministic code STREAM as input to the transport simulation of the Monte Carlo (MC) codes MCS and MCNP6. The uncertainties of dose rate coming from two sources: nuclear data and modeling parameters, are quantified. The nuclear data uncertainties are obtained from the stochastic sampling of the cross-section covariance and perturbed fission product yields. Uncertainties induced by perturbed modeling parameters consider the design parameters and operating conditions. Uncertainties coming from the two sources result in perturbed depleted nuclide inventories and radiation source terms which are then propagated to the dose rate on the cask surface. The uncertainty analysis results show that the neutron and secondary photon dose have uncertainties which are dominated by the cross section and modeling parameters, while the fission yields have relatively insignificant effect. Besides, the primary photon dose is mostly influenced by the fission yield and modeling parameters, while the cross-section data have a relatively negligible effect. Moreover, the neutron, secondary photon, and primary photon dose can have uncertainties up to about 13%, 14%, and 6%, respectively.

Internal Property and Stochastic Deterioration Modeling of Total Pavement Condition Index for Transportation Asset Management (도로자산관리를 위한 포장종합평가지수의 속성과 변화과정의 모델링)

  • HAN, Daeseok;DO, Myungsik;KIM, Booil
    • International Journal of Highway Engineering
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    • v.19 no.5
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    • pp.1-11
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    • 2017
  • PURPOSES : This study is aimed at development of a stochastic pavement deterioration forecasting model using National Highway Pavement Condition Index (NHPCI) to support infrastructure asset management. Using this model, the deterioration process regarding life expectancy, deterioration speed change, and reliability were estimated. METHODS : Eight years of Long-Term Pavement Performance (LTPP) data fused with traffic loads (Equivalent Single Axle Loads; ESAL) and structural capacity (Structural Number of Pavement; SNP) were used for the deterioration modeling. As an ideal stochastic model for asset management, Bayesian Markov multi-state exponential hazard model was introduced. RESULTS:The interval of NHPCI was empirically distributed from 8 to 2, and the estimation functions of individual condition indices (crack, rutting, and IRI) in conjunction with the NHPCI index were suggested. The derived deterioration curve shows that life expectancies for the preventive maintenance level was 8.34 years. The general life expectancy was 12.77 years and located in the statistical interval of 11.10-15.58 years at a 95.5% reliability level. CONCLUSIONS : This study originates and contributes to suggesting a simple way to develop a pavement deterioration model using the total condition index that considers road user satisfaction. A definition for level of service system and the corresponding life expectancies are useful for building long-term maintenance plan, especially in Life Cycle Cost Analysis (LCCA) work.

Importance of the Temporal Variability of Rainfall Statistics in Stochastic Rainfall Modeling (추계강우모형에서의 강우통계의 시간적 변동성 연구)

  • Kim, Dong-Kyun;Lee, Jin-Woo;Cho, Yong-Sik
    • 한국방재학회:학술대회논문집
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    • 2010.02a
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    • pp.51.2-51.2
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    • 2010
  • A novel approach of Poisson cluster stochastic rainfall generator was validated in its ability to reproduce important rainfall and watershed response characteristics at 104 locations of the United States. The suggested novel approach - The Hybrid Model(THM), as compared to the traditional ones, has an additional function to account for the year-to-year variability of rainfall statistics. The two-sample Kolmogorov-Smirnov test was used to see how well THM and traditional approach of Poisson cluster rainfall model reproduce the distribution of the following hydrologic variables: monthly maximum rainfall depths with 1, 3, 6, 12, and 24 hour duration, monthly maximum flow peaks at the virtual watersheds with Curve Number of 50, 60, 70, 80 and 90; and monthly runoff depths at the same virtual watersheds. In all of the testing variables, THM significantly outperformed the traditional approach. This result indicates that the year-to-year variability of rainfall statistics contains important information about the characteristics of rainfall processes that were not considered by the conventional approach of Poisson cluster rainfall modeling and that further considering it in rainfall simulation will enhance the performance of the rainfall models.

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Baleen Whale Sound Synthesis using a Modified Spectral Modeling (수정된 스펙트럴 모델링을 이용한 수염고래 소리 합성)

  • Jun, Hee-Sung;Dhar, Pranab K.;Kim, Cheol-Hong;Kim, Jong-Myon
    • The KIPS Transactions:PartB
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    • v.17B no.1
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    • pp.69-78
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    • 2010
  • Spectral modeling synthesis (SMS) has been used as a powerful tool for musical sound modeling. This technique considers a sound as a combination of a deterministic plus a stochastic component. The deterministic component is represented by the series of sinusoids that are described by amplitude, frequency, and phase functions and the stochastic component is represented by a series of magnitude spectrum envelopes that functions as a time varying filter excited by white noise. These representations make it possible for a synthesized sound to attain all the perceptual characteristics of the original sound. However, sometimes considerable phase variations occur in the deterministic component by using the conventional SMS for the complex sound such as whale sounds when the partial frequencies in successive frames differ. This is because it utilizes the calculated phase to synthesize deterministic component of the sound. As a result, it does not provide a good spectrum matching between original and synthesized spectrum in higher frequency region. To overcome this problem, we propose a modified SMS that provides good spectrum matching of original and synthesized sound by calculating complex residual spectrum in frequency domain and utilizing original phase information to synthesize the deterministic component of the sound. Analysis and simulation results for synthesizing whale sounds suggest that the proposed method is comparable to the conventional SMS in both time and frequency domain. However, the proposed method outperforms the SMS in better spectrum matching.

Receding Horizon FIR Parameter Estimation for Stochastic Systems

  • Lee, Kwan-Ho;Han, Soo-Hee;Lee, Changhun;Kwon, Wook-Hyun
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.159.1-159
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    • 2001
  • A new time-domain FIR parameter estimation called the receding horizon least square estimation (RHLSE) is suggested for stochastic systems by combining the well known least square estimation with the receding horizon strategy. It can be always obtained without the requirement of any \textit{a priori} information about the horizon initial parameter. A fast algorithm for the suggested estimation is also presented which is remarkable in the view of computational advantage and simple implementation. It is shown that the proposed estimation is robust against temporary modeling uncertainties due to their FIR structure through simulation studies.

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Real Time Turbulent Gas Modeling By Using Stochastic Model (추계 모델을 이용한 실시간에서의 난류 기체 모델링)

  • 서완종;박찬모
    • Proceedings of the Korean Information Science Society Conference
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    • 1998.10c
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    • pp.627-629
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    • 1998
  • 본 논문에서는 파티클 시스템(Particel System)을 이용한 실시간 기체 모델링 알고리즘을 제시한다. 일반적으로 그래픽스 분야에서, 주요한 자연현상의 하나인 기체의 운동은 수학적으로 복잡한 모델을 사용하여 그 모델링이 매우 복잡하였다. 따라서 빠른 구현시간을 얻기 위해서는 고성능의 컴퓨터가 요구되어왔다. 이 알고리즘에서는 물리학에서 수학적으로 정의된, 기체의 움직임에 적용되는 요소 각각을 추계 모델(Stochastic Model)로 다시 재 정의하여 기체 입자각각에 적용시켜 계산과정을 간단히 하였다. 따라서 일반적으로 사용되는 연구용 컴퓨터시스템에서도 실시간 애니메이션의 구현이 가능하다.

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Finite element fracture reliability of stochastic structures

  • Lee, J.C.;Ang, A.H.S.
    • Structural Engineering and Mechanics
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    • v.3 no.1
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    • pp.1-10
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    • 1995
  • This study presents a methodology for the system reliability analysis of cracked structures with random material properties, which are modeled as random fields, and crack geometry under random static loads. The finite element method provides the computational framework to obtain the stress intensity solutions, and the first-order reliability method provides the basis for modeling and analysis of uncertainties. The ultimate structural system reliability is effectively evaluated by the stable configuration approach. Numerical examples are given for the case of random fracture toughness and load.

Power Management SRN Modeling based on Adaptive Timeout (적응적 타임아웃 기반 전력관리 SRN 모델링)

  • Ro, Cheul-Woo;Kim, Kyung-Min
    • The Journal of the Korea Contents Association
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    • v.8 no.1
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    • pp.300-307
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    • 2008
  • Power management (PM) depends on the power state transition and system workload. The system model is composed of corresponding stochastic models of the power state and system queue. In this paper, stochastic models which can handle various PM techniques are developed. SRN (Stochastic Reward Nets), an extended Petri-Net, has facilities that represent system queue and various modelling functions. The SRN is employed for developing PM models. An adaptive timeout PM model is also introduced and the power consumption and performance of this model are compared with other existing PM techniques models such as greedy and N-Policy techniques.