• Smart Structures and Systems
• /
• 제29권2호
• /
• pp.321-336
• /
• 2022

Model uncertainty is a key factor that could influence the accuracy and reliability of numerical model-based analysis. It is necessary to acquire an appropriate updating approach which could search and determine the realistic model parameter values from measurements. In this paper, the Bayesian model updating theory combined with the transitional Markov chain Monte Carlo (TMCMC) method and K-means cluster analysis is utilized in the updating of the structural model parameters. Kriging and polynomial chaos expansion (PCE) are employed to generate surrogate models to reduce the computational burden in TMCMC. The selected updating approaches are applied to three structural examples with different complexity, including a two-storey frame, a ten-storey frame, and the national stadium model. These models stand for the low-dimensional linear model, the high-dimensional linear model, and the nonlinear model, respectively. The performances of updating in these three models are assessed in terms of the prediction uncertainty, numerical efforts, and prior information. This study also investigates the updating scenarios using the analytical approach and surrogate models. The uncertainty quantification in the Bayesian approach is further discussed to verify the validity and accuracy of the surrogate models. Finally, the advantages and limitations of the surrogate model-based updating approaches are discussed for different structural complexity. The possibility of utilizing the boosting algorithm as an ensemble learning method for improving the surrogate models is also presented.

• Structural Engineering and Mechanics
• /
• 제57권2호
• /
• pp.369-387
• /
• 2016

In this work, random homogenization analysis for the effective thermal properties of a three-dimensional composite material with unidirectional fibers is presented by combining the equivalent inclusion method with Random Factor Method (RFM). The randomness of the micro-structural morphology and constituent material properties as well as the correlation among these random parameters are completely accounted for, and stochastic effective thermal properties as thermal expansion coefficients as well as their correlation are then sought. Results from the RFM and the Monte-Carlo Method (MCM) are compared. The impact of randomness and correlation of the micro-structural parameters on the random homogenized results is revealed by two methods simultaneously, and some important conclusions are obtained.

• 한국수자원학회:학술대회논문집
• /
• 한국수자원학회 2010년도 학술발표회
• /
• pp.610-614
• /
• 2010

지구온난화에 따른 이상기후 현상으로 불확실성에 대한 고려가 더욱 중요해진 지금 설계빈도의 무조건적인 상향조정에 의존하기보다는 추계학적 방법을 도입한 수문량의 확충 및 매개변수의 불확실성을 고려하기 위한 연구가 활발히 진행중이다. 본 연구에서는 강우발생의 불확실성을 반영하여 제내지에서의 침수 범위를 GIS상에서 검토하기 위해 log-ratio 방법, Johnson 시스템, 직교변환을 활용한 다변량 Monte Carlo 기법으로 추계학적 시간에 따른 강우변동을 생성하였다. 생성된 강우변동 결과를 토대로 수문분석, 홍수위 분석 등을 실시하고 FLUMEN 모형을 적용하여 해당유역에 대한 홍수범람시 침수범위를 산정하였다. 본 연구결과는 실제 강우의 불확실성을 반영하고 있어 시 공간적 강우특성이 반영된 유역별 주민대피지도, 홍수위험지도 등을 제작하는데 활용될 수 있을 것으로 기대된다.

• 설비공학논문집
• /
• 제12권1호
• /
• pp.83-94
• /
• 2000

The performance of a turbomolecular pump(TMP) in both molecular and transition flow regions is predicted by the numerical solutions of the Boltzmann equation obtained by the direct simulation Monte Carlo method. The compression characteristics of the TMP are investigated for a wide range of the Knudsen number( Kn ). The maximum compression ratios strongly depend on Kn in transition region, while do they weakly on Kn in free molecular flow region. The present numerical results of the single blade row in both molecular and transition regions are used to predict the overall performance of a TMP, which has three kinds of blade with 24-rows.

• 한국전산구조공학회:학술대회논문집
• /
• 한국전산구조공학회 1993년도 가을 학술발표회논문집
• /
• pp.207-215
• /
• 1993

With the aid of finite element method, this paper deals with the problem of structural response variability of transmission tower subjected to the spatial variability of material properties, Young's modulus herein. The spatial variability of material property are modeled as two-dimensional stochastic field which has an isotropic auto-correlation function. Response variability has been computed based on two numerical techniques, such as the Neumann expansion method in conjunction with the Monte Carlo simulation method. The results by these numerical methods are compared with those by the deterministic approach.

• Nuclear Engineering and Technology
• /
• 제36권1호
• /
• pp.1-11
• /
• 2004

Two approximate methods for a cosmic radiation shielding calculation in low earth orbits were developed and assessed. Those are a sectoring method and a chord-length distribution method. In order to simulate a change in cosmic radiation environments along the satellite mission trajectory, IGRF model and AP(E)-8 model were used. When the approximate methods were applied, the geometrical model of satellite structure was approximated as one-dimensional slabs, and a pre-calculated dose-depth conversion function was introduced to simplify the dose calculation process. Verification was performed with mission data of KITSAT-1 and the calculated results were also compared with detailed 3-dimensional calculation results using Monte Carlo calculation. Dose results from the approximate methods were conservatively higher than Monte Carlo results, but were lower than experimental data in total dose rate. Differences between calculation and experimental data seem to come from the AP-8 model, for which it is reported that fluxes of proton are underestimated. We confirmed that the developed approximate method can be applied to commercial satellite shielding calculations. It is also found that commercial products of semi-conductors can be damaged due to total ionizing dose under LEO radiation environment. An intensive shielding analysis should be taken into account when commercial devices are used.

• Nuclear Engineering and Technology
• /
• 제56권10호
• /
• pp.4390-4396
• /
• 2024

The response of an anti-Compton phoswich detector to gamma rays was investigated using Monte-Carlo method, and the pulses from different crystal cases, including gamma deposition only in the LaBr3(Ce) or CsI(Tl) crystal and coincidence in both crystals, were analyzed. A novel pulse discrimination method for gamma deposition events based on wavelet transform analysis, called SSD (Scale Shape Discrimination), was developed in this study. Compared to the traditional PSD (Pulse Shape Discrimination) method, SSD has the advantage of transforming one-dimensional pulses in the time-domain into two-dimensional time-frequency spectra, providing the more useful features for pulse discrimination. The performances of the Compton suppression and Full-energy peak loss using PSD and SSD methods was studied. The results show that the Compton suppression factor I_PSD = 5.12 and I_SSD = 5.32, and FEP loss factor PL_PSD = 0.0554 and PL_SSD = 0.0587. Meanwhile, the influences of the cutoff values for pulse discrimination on the results of I and PL with different method were analyzed.

• Geomechanics and Engineering
• /
• 제25권1호
• /
• pp.17-30
• /
• 2021

This paper develops a convenient approach for deterministic and probabilistic evaluations of tunnel face stability using support vector machine classifiers. The proposed method is comprised of two major steps, i.e., construction of the training dataset and determination of instance-based classifiers. In step one, the orthogonal design is utilized to produce representative samples after the ranges and levels of the factors that influence tunnel face stability are specified. The training dataset is then labeled by two-dimensional strength reduction analyses embedded within OptumG2. For any unknown instance, the second step applies the training dataset for classification, which is achieved by an ad hoc Python program. The classification of unknown samples starts with selection of instance-based training samples using the k-nearest neighbors algorithm, followed by the construction of an instance-based SVM-KNN classifier. It eventually provides labels of the unknown instances, avoiding calculate its corresponding performance function. Probabilistic evaluations are performed by Monte Carlo simulation based on the SVM-KNN classifier. The ratio of the number of unstable samples to the total number of simulated samples is computed and is taken as the failure probability, which is validated and compared with the response surface method.

• 한국지반공학회논문집
• /
• 제25권12호
• /
• pp.13-25
• /
• 2009

본 연구에서는 확률론적 해석에 지반의 공간적 변동성을 고려하기 위한 해석 절차를 제시하였다. 제안된 방법은 한계평형법을 이용하는 결정론적 해석방법을 지반정수의 불확실성과 공간적 변동성을 고려할 수 있도록 확률론적 사면안정 해석으로 확장한다. 개발된 방법은 랜덤유한요소해석법과 같이 미리 임계파괴면을 가정하지 않으면서도 계산시간을 단축할 수 있다는 장점이 있다. 지정된 입력 확률분포함수와 자기상관함수를 따르는 2차원의 랜덤필드를 생성하기 위하여 Karhunen-Lo$\grave{e}$ve 전개법을 사용하였으며, 생성된 랜덤필드를 이용하여 확률론적 응답을 얻기 위해 Monte Carlo 시뮬레이션을 수행하였다. 개발된 해석기법의 적용성을 검토하고 지반정수의 공간적 변화가 확률론적 안정해석에 미치는 영향을 검토하기 위해 예제해석을 수행하였으며, 해석결과는 제안된 방법이 지반물성의 공간적 변동성에 따른 다양한 사면파괴 형태를 확률론적 사면안정 해석에 효과적으로 고려할 수 있음을 보여준다.

• 한국지반공학회논문집
• /
• 제24권8호
• /
• pp.111-123
• /
• 2008

지반공학 문제는 많은 불확실한 요인을 내포한다. 이러한 불확실성 중 일부는 해석 수행과정에 필요한 지반 물성의 변동성과 관련이 있다. 본 연구에서는 지반물성의 공간적 변동성을 고려한 확률론적 해석을 수행할 수 있는 절차를 제시하였다. 제시된 방법은 유한차분 해석기법과 랜덤필드 이론을 확률론적 해석기법에 통합하게 된다. 지정된 입력 확률분포함수와 자기상관함수를 따르는 non-Gaussian 랜덤필드를 생성하기 위하여 Karhunen-$Lo{\grave{e}}ve$ 전개법을 사용하였다. 생성된 랜덤필드를 이용하여 확률론적 응답을 얻기 위해 Monte Carlo 시뮬레이션을 수행하였다. 지반의 공간적인 변동성에 기인하는 불확실성의 효과를 연구하기 위하여 대상 기초의 침하량과 지지력에 대한 일련의 해석을 수행하였다. 해석결과는 지반공학 문제에서 불확실성을 고려할 수 있는 관점을 제시하며 확률론적 평가의 결과에 미치는 지반물성의 공간적 변동성의 중요성을 보여준다.