• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 2006년도 춘계 학술발표회 논문집(II)
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• pp.181-184
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• 2006

Traditional durability analysis is not possible to provide a controlled durability and long-term performance of concrete structures. Recently, research works have shown that probabilistic approach based on the theory of structural reliability, would be very valuable for durability analysis. In this study, the probabilistic durability analysis based on a Monte Carlo Simulation was carried out using sample data selected from detailed field investigation. The probabilistic properties of some design variables, such as diffusion coefficients of concrete and surface chloride concentration, were newly determined using some experimental data. By applying a probabilistic durability analysis to an integral structural design, the durability performance of concrete structures would be remarkably improved.

• 한국지반환경공학회 논문집
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• 제10권7호
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• pp.111-115
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• 2009

국내에서는 지반의 설계응답스펙럼을 확률론적으로 생성한 지진재해도와 결정론적으로 유도된 지진계수를적용하여 생성한다. 지진재해도와 지진계수는 호환되지 않지만, 현 설계기준은 이런 근본적인 비호환성을 무시하고 있다. 지진재해도와 지진계수를 동일한 확률론적 기반에서 생성한다면 이와 같은 문제를 극복할 수 있지만, 기존의 방법으로는 지진계수를 확률론적으로 생성할 수 없다. 본 논문에서는 동반논문에서 신(新) PSHA의 결과물로써 생성된 지진기록을 입력지진파로 활용하여 1차원 등가선형 지반응답 해석을 수행하였으며 이의 결과를 기반으로 등재해스펙트럼을 생성하였다. 등재해스펙트럼의 또 한가지 장점은 지반물성치의 불확실성과 임의성이 과학적으로 고려되었다는 점이다. 등재해스펙트럼은 나아가 확률론적인 지진계수를 도출하는데 활용되었다. 확률론적인 지진계수를 내진설계기준에서 제시된 지진계수를 비교한 결과, 확률론적으로 계산된 지진계수는 결정론적으로 계산된 결과와 상당한 차이가 있는 것으로 나타났다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2005년도 춘계학술대회 논문집
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• pp.1682-1685
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• 2005

System algorithms estimated by deterministic input may occur the error between predicted and actual output. Especially, actual system can't predict the exact outputs due to uncertainty and tolerance of input parameters. A single output to a set of inputs has a limited value without the variation. Hence, we should consider various scatters caused by the load assessment, material characteristics, stress analysis and manufacturing methods in order to perform the robust design or estimate the reliability of structure. The system design with uncertainty should perform the probabilistic structural optimization with the statistical response and the reliability. This method calculated the probability distributions of the characteristics such as stress by combining stress analysis, response surface methodology and Monte-Carlo Method and got the probabilistic sensitivity. The sensitivity of structural response with respect to inconstant design variables was estimated by fracture probability. Therefore, this paper proposed the probabilistic reliability design method for fracture of uncorved freight end beam and the design criteria by fracture probability.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2006년도 정기 학술대회 논문집
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• pp.275-282
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• 2006

System algorithms estimated by deterministic input may occur the error between predicted and actual output. Especially, actual system can't predict the exact outputs due to uncertainty and tolernce of input parameters. A single output to a set of inputs has a limited value without the variation. Hence, we should consider various scatters caused by the load assessment, material characteristics, stress analysis and manufacturing methods in order to perform the robust design or etimate the reliability of structure. The system design with uncertainty should perform the probabilistic structural optimization with the statistical response and the reliability. This method calculated the probability distributions of the characteristics such as stress by combining stress analysis, response surface methodology and Monte Carlo simulation and got the probabilistic sensitivity. The sensitivity of structural response with respect to in constant design variables was estimated by fracture probability. Therefore, this paper proposed the probabilistic reliability design method for fracture of uncorved freight end beam and the design criteria by fracture probability.

• International Journal of Railway
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• 제6권2호
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• pp.45-52
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• 2013

Railway construction needs vast soil investigation for its infrastructure foundation designs along the planned railway path to identify the design parameters for stability and serviceability checks. The soil investigation data are usually classified and grouped to decide design input parameters per each construction section and budget estimates. Deterministic design method which most civil engineer and practitioner are familiar with has a clear limitation in construction/maintenance budget control, and occasionally produced overdesigned or unsafe design problems. Instead of using a batch type analysis with predetermined input parameters, data population collected from site soil investigation and design load condition can be statistically estimated for the mean and variance to present the feature of data distribution and optimized with a best fitting probability function. Probabilistic approach using entire feature of design input data enables to predict the worst, best and most probable cases based on identified ranges of soil and load data, which will help railway designer select construction method to save the time and cost. This paper introduces two Monte Carlo simulations actually applied on estimation of retaining wall external stability and long term settlement of organic soil in soil investigation area for a recent high speed railway project.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2008년도 정기 학술대회
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• pp.65-70
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• 2008

The capacity spectrum method (CSM) is a deterministic seismic analysis approach wherein the expected seismic response of a structure is established as the intersection of the demand and capacity curves. Recently, there are a few studies about a probabilistic CSM where uncertainties in design factors such as material properties, loads, and ground motion are being considered. However, researches show that soil-structure interaction also affects the seismic responses of structures. Thus, their uncertainties should also be taken into account. Therefore, this paper presents a probabilistic approach of using the CSM for seismic analysis considering uncertainties in soil properties. For application, a reinforced concrete bridge column structure is employed as a test model. Considering the randomness of the various design parameters, the structure's probability of failure is obtained. Monte Carlo importance sampling is used as the tool to assess the structure's reliability when subjected to earthquakes. In this study, probabilistic CSM with and without consideration of soil uncertainties are compared and analyzed. Results show that the analysis considering soil structure interaction yields to a greater probability of failure, and thus can lead to a more conservative structural design.

• Geomechanics and Engineering
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• 제18권6호
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• pp.595-603
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• 2019

A modified model combining Kriging and Monte Carlo method (MC) is proposed for probabilistic estimation of tunnel face stability in this paper. In the model, a novel uniform design is adopted to train the Kriging, instead of the existing active learning function. It has advantage of avoiding addition of new training points iteratively, and greatly saves the computational time in model training. The kinematic approach of limit analysis is employed to define the deterministic computational model of face failure, in which the Hoek-Brown failure criterion is introduced to account for the nonlinear behaviors of rock mass. The trained Kriging is used as a surrogate model to perform MC with dramatic reduction of calls to actual limit state function. The parameters in Hoek-Brown failure criterion are considered as random variables in the analysis. The failure probability is estimated by direct MC to test the accuracy and efficiency of the proposed probabilistic model. The influences of uncertainty level, correlation relationship and distribution type of random variables are further discussed using the proposed approach. In summary, the probabilistic model is an accurate and economical alternative to perform probabilistic stability analysis of tunnel face excavated in spatially random Hoek- Brown media.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1991년도 가을 학술발표회 논문집
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• pp.57-62
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• 1991

For the purpose of developing the method for efficiently calculating the design sensitivity and the reliability for the complicated structure such as ship structure, the probabilistic finite element method is introduced to formulate the deterministic design sensitivity analysis method and incorporated with the second moment reliability methods such as MVFOSM, AFOSM and SORM. Also, the probabilistic design sensitivity analysis needed in the reliability-based design is performed. The reliability analysis is carried out for the initial yielding failure, in which the derivative derived in the deterministic desin sensitivity is used. The present PFEM-based reliability method shows good agreement with Monte Carlo method in terms with the variance of response and the associated probability of failure even at the first or first few iteration steps. The probabilistic design sensitivity analysis evaluates explicitly the contribution of each random variable to probability of failure. Further, the reliability index variation can be easily predicted by the variation of the mean and the variance of the random variables.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2006년도 춘계 학술발표회 논문집
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• pp.1148-1154
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• 2006

Composite discharge capacity tests and smear effect tests are carried out to estimate the parameters for the reliability-based design of vertical drain method. Also the probabilistic and deterministic solutions of radial consolidation theory are presented. It compared to the result of reliability-based design and that of deterministic design using the tested and estimated parameters. The results indicated that the drain spacing is larger the deterministic method than the probabilistic method because the former is not considered the uncertainties in the properties of soil. The divergence of methods is dependent on the probability of achieving target degree of consolidation by a given time and the coefficient of variation(COV) of the coefficient of horizontal consolidation$(c_h)$.

• 한국안전학회지
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• 제25권6호
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• pp.186-196
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• 2010

It has been well known that traffic accidents occur under combined functional contributions of drivers, vehicles and road facilities, and that evaluation of safety levels for a specific road section or point is generally much complicated. Additionally, most of traffic accidents occur randomly implicating it is necessary to be evaluated in terms of probability theory. Thus, the evaluation model which reflects various characteristics and probabilistic distributions of traffic accidents has been necessary. The present paper provides a reliability based model with variables of probabilistic operating speeds and design speeds together which have been individually explaining associated characteristics in traffic accidents. Consequently, the model made it possible for speed management and road improvement projects to be evaluated in a common index. Application studies were performed in three cases. Through the studies, couples of facts were identified that the model successfully considered the probabilistic operating speeds and design speeds together and that then, the model evaluated road safety alternatives relatively which are complicatedly characterized and differently located.