• Smart Structures and Systems
• /
• 제33권1호
• /
• pp.17-26
• /
• 2024

The new metro crossing the existing metro will cause the settlement or floating of the existing structures, which will have safety problems for the operation of the existing metro and the construction of the new metro. Therefore, it is necessary to monitor and predict the settlement of the existing metro caused by the construction of the new metro in real time. Considering the complexity and uncertainty of metro settlement, a Gaussian Prior Bayesian Emulator (GPBE) probability prediction model based on Bayesian optimization (BO) is proposed, that is, BO-GPBE. Firstly, the settlement monitoring data are analyzed to get the influence of the new metro on the settlement of the existing metro. Then, five different acquisition functions, that is, expected improvement (EI), expected improvement per second (EIPS), expected improvement per second plus (EIPSP), lower confidence bound (LCB), probability of improvement (PI) are selected to construct BO model, and then BO-GPBE model is established. Finally, three years settlement monitoring data were collected by structural health monitoring (SHM) system installed on Nanjing Metro Line 10 are employed to demonstrate the effectiveness of BO-GPBE for forecasting the settlement.

• 한국지반공학회논문집
• /
• 제24권10호
• /
• pp.83-91
• /
• 2008

현장계측 자료를 이용하여 연약지반의 향후 침하거동을 예측하는 기존의 방법들은 모두 즉시재하 조건을 가정하고 개발된 방법으로써 실제로는 연약지반의 안정성 등을 고려하여 점증재하가 이루어지는 현장에 적용하기에는 많은 제약이 있다. 본 연구에서는 연약층의 두께, 성토하중 크기, 선행압밀하중, 배수거리, 성토속도 등의 다양한 영향인자를 고려하였으며 점증재하가 완료된 이후의 지반개량 기간에도 지속적으로 예측 정확도를 높일 수 있는 계측기반 침하거동 예측기법을 개발하였다. 점증재하 과정에서의 예측방법과 성토완료 이후의 예측방법이 개발되었으며, 성토 완료 이후의 예측방법은 기하학적 보정을 이용한 정확도 향상기법과 확률론적 보정을 이용한 정확도 향상기법 두 가지를 제안하였다. 대형압밀시험 결과를 이용한 예측기법의 적용성 검증 결과, 기존의 예측기법을 적용할 수 없는 점증재하 초기에도 비교적 적은 데이터를 이용하여 상당히 높은 정확도를 가지고 침하거동을 예측할 수 있었다. 또한, 성토완료이후에도 기존 예측기법과 제안된 방법의 비교, 분석 결과 최종침하량과 RMSE에서 모두 제안된 방법이 기존의 예측기법에 비하여 우수한 예측결과를 보였다.

• 대한토목학회논문집
• /
• 제28권6C호
• /
• pp.349-358
• /
• 2008

본 연구에서는 고베 공항 해저 충적 점토를 대상으로 한 신뢰성 침하 해석을 위해 각종 입력 물성치의 불확실성을 확률 통계 이론에 근거하여 조사하였고, Terzaghi 압밀 방정식을 목적 함수로 AFOSM 법을 적용하여 파괴 확률을 정식화하였다. 신뢰성 해석 결과, 목표침하량을 평균침하량 ${\pm}10%,\;{\pm}25%$로 설정한 경우, 발생확률은 각각 30~50%, 60%~90%로 나타났다. 이는 대상 지반의 확률변수의 변동계수가 과거의 연구보고 범위 내에 있음을 고려할 때, 목적함수로 Terzaghi 압밀방정식을 이용한 경우 침하량의 허용 오차 범위는 평균침하량 ${\pm}10%$가 적절할 것으로 사료된다. 또한, 감도 분석 결과 해석에 크게 영향을 미치는 인자는 압축 계수, 모델, 압밀 항복 응력의 불명확성으로 나타났다. 이는 정밀도가 높은 사전 침하량의 예측을 위해서는 현장의 응력 변형 조건을 충실하게 반영한 시험을 수행하여 신뢰도가 높은 물성치를 구하는 것이 매우 중요한 것임을 설명한다.

• 한국지반공학회지:지반
• /
• 제13권6호
• /
• pp.107-122
• /
• 1997

본 논문에서는 점성토 지반에서의 실드 터널 시공에 따른 지표 침하 예측 기법을 제시하였다. 예측 기법을 개발하기 위해 실드 터널의 시공과정을 모사할 수 있는 3차원 유한요소해석기법을 이용하여 매개변수 변환 연구를 수행하였으며, 해석 결과를 이용하여 지반 거동메카니즘을 고찰하고 지반 거동과 영향 요소와의 관계를 나타내는 데이터 베이스를 구축 하였다. 구축된 데이터 베이스에 대한 다중 회귀분석을 통해 막장 상부에서의 지표 침하비와 변곡점의 위치를 결정하는 반경험식을 개발하고 이를 기존의 정규확률분포함수와 접목시켜 횡단면 및 종단면 지표 침하 형상을 예측하는 기법을 제안하였다. 제안된 예측 기법은 유효요소 해석 결과 및 현장 계측 자료와의 비교를 통해 그 타당성이 입증되었으며, 따라서 제시된 예측 기법은 본 연구에서 고려한 경계조건과 유사한 조건에서 효율적으로 적용될 수 있을 것으로 판단된다.

• Geomechanics and Engineering
• /
• 제2권1호
• /
• pp.57-69
• /
• 2010

A major consideration in the design of tunnels in urban areas is the prediction of the ground movements and surface settlements associated with the tunneling operations. Excessive ground movements can damage adjacent building and utilities. In this paper, a neural network model is used to predict the maximum surface settlement, based on instrumented results from three separate EPB tunneling projects in Singapore. This paper demonstrates that by coupling the trained neural network model to a spreadsheet optimization technique, the reliability assessment of the settlement serviceability limit state can be carried out using the first-order reliability method. With this method, it is possible to carry out sensitivity studies to examine the effect of the level of uncertainty of each parameter uncertainty on the probability that the serviceability limit state has been exceeded.

• 한국정밀공학회지
• /
• 제21권1호
• /
• pp.173-180
• /
• 2004

This paper presents the effect of varying boundary conditions such as ground subsidence, internal pressure and temperature variation for buried pipelines on failure prediction by using a failure probability model. The first order Taylor series expansion of the limit state function incorporating with von-Mises failure criteria is used in order to estimate the probability of failure mainly associated with three cases of ground subsidence. Using stresses on the buried pipelines, we estimate the probability of pipelines with von-Mises failure criterion. The effects of varying random variables such as pipe diameter, internal pressure, temperature, settlement width, load for unit length of pipelines, material yield stress and pipe thickness on the failure probability of the buried pipelines are systematically studied by using a failure probability model for the pipeline crossing ground subsidence regions which have different soil properties.

• 한국정밀공학회:학술대회논문집
• /
• 한국정밀공학회 2003년도 춘계학술대회 논문집
• /
• pp.1557-1560
• /
• 2003

This paper presents the effect of varying boundary conditions such as ground subsidence on failure prediction of buried pipelines. The first order Taylor series expansion of the limit state function is used in order to estimate the probability of failure associated with three cases of ground subsidence. We estimate the distribution of stresses imposed on the buried pipelines by varying boundary conditions and calculate the probability of pipelines with von-Mises failure criterion. The effects of random variables such as pipe diameter, internal pressure, temperature, settlement width, load for unit length of pipelines, material yield stress and thickness of pipeline on the failure probability of the buried pipelines are also systematically studied by using a failure probability model for the pipeline crossing a ground subsidence region.

• Steel and Composite Structures
• /
• 제47권1호
• /
• pp.91-102
• /
• 2023

To study the evaluation standard and control limit of mortar filling layer void length, in this paper, the train sub-model was developed by MATLAB and the track-bridge sub-model considering the mortar filling layer void was established by ANSYS. The two sub-models were assembled into a train-track-bridge coupling dynamic model through the wheel-rail contact relationship, and the validity was corroborated by the coupling dynamic model with the literature model. Considering the randomness of fastening stiffness, mortar elastic modulus, length of mortar filling layer void, and pier settlement, the test points were designed by the Box-Behnken method based on Design-Expert software. The coupled dynamic model was calculated, and the support vector regression (SVR) nonlinear mapping model of the wheel-rail system was established. The learning, prediction, and verification were carried out. Finally, the reliable probability of the amplification coefficient distribution of the response index of the train and structure in different ranges was obtained based on the SVR nonlinear mapping model and Latin hypercube sampling method. The limit of the length of the mortar filling layer void was, thus, obtained. The results show that the SVR nonlinear mapping model developed in this paper has a high fitting accuracy of 0.993, and the computational efficiency is significantly improved by 99.86%. It can be used to calculate the dynamic response of the wheel-rail system. The length of the mortar filling layer void significantly affects the wheel-rail vertical force, wheel weight load reduction ratio, rail vertical displacement, and track plate vertical displacement. The dynamic response of the track structure has a more significant effect on the limit value of the length of the mortar filling layer void than the dynamic response of the vehicle, and the rail vertical displacement is the most obvious. At 250 km/h - 350 km/h train running speed, the limit values of grade I, II, and III of the lengths of the mortar filling layer void are 3.932 m, 4.337 m, and 4.766 m, respectively. The results can provide some reference for the long-term service performance reliability of the ballastless track-bridge system of HRS.