• Title/Summary/Keyword: Probability density function approach

검색결과 121건 처리시간 0.028초

A Lagrangian Based Scalar PDF Method for Turbulent Combustion Models

  • Moon, Hee-Jang;Borghi, Roland
    • Journal of Mechanical Science and Technology
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    • 제18권8호
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    • pp.1470-1478
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    • 2004
  • In this paper, a new 'presumed' Probability Density Function (PDF) approach coupled with a Lagrangian tracking method is proposed for turbulent combustion modeling. The test and the investigation of the model are conducted by comparing the model results with DNS data for a premixed flame subjected in a decaying turbulent field. The newly constructed PDF, which incorporates the instantaneous chemical reaction term, demonstrates consistent improvement over conventional assumed PDF models. It has been found that the time evolution of the mean scalar, the variance and the mean reaction rate are strongly influenced by a parameter deduced by a Lagrangian equation which takes into account explicitly the local reaction rate. Tests have been performed for a moderate Damkohler number, and it is expected the model may cover a broader range of Damkohler number. The comparison with the DNS data demonstrates that the proposed model may be promising and affordable for implementation in a moment-equation solver.

A homogenization approach for uncertainty quantification of deflection in reinforced concrete beams considering microstructural variability

  • Kim, Jung J.;Fan, Tai;Reda Taha, Mahmoud M.
    • Structural Engineering and Mechanics
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    • 제38권4호
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    • pp.503-516
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    • 2011
  • Uncertainty in concrete properties, including concrete modulus of elasticity and modulus of rupture, are predicted by developing a microstructural homogenization model. The homogenization model is developed by analyzing a concrete representative volume element (RVE) using the finite element (FE) method. The concrete RVE considers concrete as a three phase composite material including: cement paste, aggregate and interfacial transition zone (ITZ). The homogenization model allows for considering two sources of variability in concrete, randomly dispersed aggregates in the concrete matrix and uncertain mechanical properties of composite phases of concrete. Using the proposed homogenization technique, the uncertainty in concrete modulus of elasticity and modulus of rupture (described by numerical cumulative probability density function) are determined. Deflection uncertainty of reinforced concrete (RC) beams, propagated from uncertainties in concrete properties, is quantified using Monte Carlo (MC) simulation. Cracked plane frame analysis is used to account for tension stiffening in concrete. Concrete homogenization enables a unique opportunity to bridge the gap between concrete materials and structural modeling, which is necessary for realistic serviceability prediction.

피로하중을 받는 구조물의 결함분포에 대한 확률론적 해석 (Probabilistic Analysis of Flaw Distribution on Structure Under Cyclic Load)

  • 곽상록;최영환;김효정
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2003년도 춘계학술대회
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    • pp.604-609
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    • 2003
  • Flaw geometries, applied stress, and material properties are major input variables for the fracture mechanics analysis. Probabilistic approach can be applied for the consideration of uncertainties within these input variables. But probabilistic analysis requires many assumptions due to the lack of initial flaw distributions data. In this study correlations are examined between initial flaw distributions and in-service flaw distributions on structures under cyclic load. For the analysis, LEFM theories and Monte Carlo simulation are applied. Result shows that in-service flaw distributions are determined by initial flaw distributions rather than fatigue crack growth rate. So initial flaw distribution can be derived from in-service flaw distributions.

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주파수영역 손상식별 SI 기법에 적응할 최적센서 위치결정법 (Determination of Optimal Sensor Locations for Modal System Identification-based Damage Detection on Structures)

  • 권순정;신수봉;박영환
    • 한국전산구조공학회:학술대회논문집
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    • 한국전산구조공학회 2003년도 봄 학술발표회 논문집
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    • pp.95-102
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    • 2003
  • To define an analytical model for a structural system or to assess damage in the system, system identification(SI) methods have been developed and widely applied. The paper presents a method of determining optimal sensor location(OSL) based on the maximum likelihood approach, which is applicable to modal SI methods. To estimate unknown parameters reliably, it is necessary that the information provided by the experiment should be maximized. By applying the Cramer-Rao inequality, a Fisher information matrix in terms of the probability density function of measurements is obtained from a lower bound of the estimation error. The paper also proposes a scheme of determining of OSL on damaged structures by using maximum strain energy factor. Simulation studies have carried out to investigate the proposed OSL algorithm for both undamaged and damaged structures.

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확률론적 방법을 이용한 교류 고속철도 시스템의 고조파 해석 (Harmonics Analysis of AC High Speed Railroad(HSR) System using Probabilistic Approach)

  • 송학선;이준경;김진오;김형철
    • 한국철도학회:학술대회논문집
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    • 한국철도학회 2005년도 춘계학술대회 논문집
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    • pp.782-787
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    • 2005
  • Magnitude of generated harmonic currents along with the operation of AC traction has nonlinear characteristics, and generated harmonic currents for high speed traction are more and more in high speed railroad(HSR) systems, especially. This paper presents probabilistic approximation method for the harmonic currents analysis about the operating speed of AC traction. To use probabilistic method for HSR system, probability density function(PDF) for collected operating speed based measure data is calculated. Mean and variance of harmonic currents of single traction are obtained based on the operating speed PDF and electrical traction model. The results of Monte Carlo Simulation(MCS) are in well accordance with the experimental and analytic methods. The harmonics of different number of trainloads are systematically investigated. It is assessed by the total demand distortion(TDD) for the HSR system.

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마르코프 과정을 이용한 공차 최적화 (Tolerance Optimization with Markov Chain Process)

  • Lee, Jin-Koo
    • 한국공작기계학회논문집
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    • 제13권2호
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    • pp.81-87
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    • 2004
  • This paper deals with a new approach to tolerance optimization problems. Optimal tolerance allotment problems can be formulated as stochastic optimization problems. Most schemes to solve the stochastic optimization problems have been found to exhibit difficulties in multivariate integration of the probability density function. As a typical example of stochastic optimization the optimal tolerance allotment problem has the same difficulties. In this stochastic model, manufacturing system is represented by Gauss-Markov stochastic process and the manufacturing unit availability is characterized for realistic optimization modeling. The new algorithm performed robustly for a large deviation approximation. A significant reduction in computation time was observed compared to the results obtained in previous studies.

Constraining Cosmological Parameters with Gravitational Lensed Quasars in the Sloan Digital Sky Survey

  • Han, Du-Hwan;Park, Myeong-Gu
    • 천문학회보
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    • 제39권1호
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    • pp.34-34
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    • 2014
  • We investigate the constraints on the matter density ${\Omega}m$ and the cosmological constant ${\Omega}{\Lambda}$ using the gravitational lensed QSO (Quasi Stellar Object) systems from the Sloan Digital Sky Survey (SDSS) by analyzing the distribution of image separation. The main sample consists of 16 QSO lens systems with measured source and lens redshifts. We use a lensing probability that is simply defined by the gaussian distribution. We perform the curvature test and the constraints on the cosmological parameters as the statistical tests. The statistical tests have considered well-defined selection effects and adopt parameter of velocity dispersion function. We also applied the same analysis to Monte-Carlo generated mock gravitational lens samples to assess the accuracy and limit of our approach. As the results of these statistical tests, we find that only the excessively positively curved universe (${\Omega}m+{\Omega}{\Lambda}$ > 1) are rejected at 95% confidence level. However, if the informations of the galaxy as play a lens are measured accurately, we confirm that the gravitational lensing statistics would be the most powerful tool.

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Walking Beam형 열연 재가열로의 3차원 수치해석 (Three Dimensional Numerical Analysis of the Walking Beam Type of a Hot Roll Reheat Furnace)

  • 김종규;허강열;김일태
    • 한국전산유체공학회:학술대회논문집
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    • 한국전산유체공학회 1999년도 춘계 학술대회논문집
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    • pp.199-204
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    • 1999
  • Three dimensional numerical analysis for the turbulent reactive flow and radiative heat transfer in the walking beam type of a reheat furnace in POSCO has been carried out by the industrial code FLUENT. Computations an based on the conservation equations of mass, momentum, energy and species with the $k-{\varepsilon}$ turbulence model and mixture fraction/PDF(Probability Density Function) approach for the combustion rate. Radiative heat transfer is computed by the discrete ordinates radiation model in combination with the weighted-sum-of-gray-gas model for the absorption coefficient of gas medium. The predicted temperture distribution in the reheat furnace and energy flow fractions are in reasonable agreement with the measurement data.

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Structural Vibration Control Technique using Modified Probabilistic Neural Network

  • Chang, Seong-Kyu;Kim, Doo-Kie
    • 한국전산구조공학회논문집
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    • 제23권6호
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    • pp.667-673
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    • 2010
  • Recently, structures are becoming longer and higher because of the developments of new materials and construction techniques. However, such modern structures are more susceptible to excessive structural vibrations which cause deterioration in serviceability and structural safety. A modified probabilistic neural network(MPNN) approach is proposed to reduce the structural vibration. In this study, the global probability density function(PDF) of MPNN is reflected by summing the heterogeneous local PDFs automatically determined in the individual standard deviation of each variable. The proposed algorithm is applied for the vibration control of a three-story shear building model under Northridge earthquake. When the control results of the MPNN are compared with those of conventional PNN to verify the control performance, the MPNN controller proves to be more effective than PNN methods in decreasing the structural responses.

SAMPLE-SPACING 방법에 의한 상호정보의 추정 (Sample-spacing Approach for the Estimation of Mutual Information)

  • 허문열;차운옥
    • 응용통계연구
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    • 제21권2호
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    • pp.301-312
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    • 2008
  • 상호정보(mutual information: MI)는 설명변수의 목적변수에 대한 예측정도를 나타내는 척도로서, 목적변수에 대한 설명 변수의 중요도 순위를 구하거나 목적 변수를 잘 설명해주는 설명변수의 집합을 구하는 변수선택문제에 유용하게 사용된다. 본 논문에서는 연속형 설명변수와 범주형 목적변수로 구성된 데이터로부터 결합확률분포를 추정하지 않고도 MI 추정량을 구할 수 있는 Sample-spacing 방법에 대한 연구를 수행하였다. 몬테 칼로 모의 실험과 실제데이터에 대한 실험결과, MI 추정을 위해 Sample-spacing 방법을 사용할 때 m = 1을 사용하면 충분히 신뢰할만한 결과를 얻을 수 있다는 것을 알 수 있었다.