• International Journal of Concrete Structures and Materials
• /
• v.5 no.1
• /
• pp.29-33
• /
• 2011

This article employs Least Square Support Vector Machine (LSSVM) for determination of fracture parameters of concrete: critical stress intensity factor ($K_{Ic}^s$) and the critical crack tip opening displacement ($CTOD_c$). LSSVM that is firmly based on the theory of statistical learning theory uses regression technique. The results are compared with a widely used Artificial Neural Network (ANN) Models of LSSVM have been developed for prediction of $K_{Ic}^s$ and $CTOD_c$, and then a sensitivity analysis has been performed to investigate the importance of the input parameters. Equations have been also developed for determination of $K_{Ic}^s$ and $CTOD_c$. The developed LSSVM also gives error bar. The results show that the developed model of LSSVM is very predictable in order to determine fracture parameters of concrete.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.13 no.3
• /
• pp.305-319
• /
• 2000

Numerical solution lot frictional contact problems of nonlinearly deformable bodies having large deformation is presented. The contact conditions on the possible contact points are expressed by using the contact error vector, and the iterative scheme is used to reduce the contact error vector monotonically toward zero. At each iteration the solution consists of two steps : The first step is to revise the contact force by using the contact error vector given by the previous geometry, and the second step is to compute the displacement and the contact error vector by solving the equilibrium equation with the contact force given at the first step. Convergence of the iterative scheme to the correct solution is analyzed, and the numerical simulations we performed with a rigid-plastic membrane and a nonlinear elastic beam.

• The Journal of Engineering Geology
• /
• v.20 no.4
• /
• pp.371-380
• /
• 2010

A three-dimensional finite element analysis was performed to predict the location of a fault zone ahead of a tunnel face based on convergence displacement. Geometrical models for the numerical analysis were developed based on the possible geometric intersection between the fault zone and the tunnel. Fifteen fault models were generated from combinations of faults with five different strikes (at $15^{\circ}$ intervals) and three dips (vertical, $45^{\circ}$ and $-45^{\circ}$) relative to the tunnel route. The displacements on the crown and side walls were calculated and analyzed using a vector orientation approach. As a result, nine representative prediction charts were developed, showing location and orientation of the fault zone based on convergence displacement.

• Journal of the Korean Geotechnical Society
• /
• v.19 no.6
• /
• pp.189-206
• /
• 2003

During tunnel excavation in urban area a systematic monitoring is important for the purpose of determination of support type and quantity, as well as for the control of stability of both surface structures and the tunnel itself due to the frequently, and in many cases, abruptly changing ground condition. In Austria absolute displacement monitoring methods have replaced relative displacement measurements by geodetic methods to a large extent. Prompt detection of weak ground ahead of the tunnel face as well as better adjustment of excavation and support to the geotechnical conditions is possible with the help of the improved methods of data evaluation on sites. Deformation response of the ground to excavation starts ahead of the tunnel face, therefore, the deformation and state of the tunnel advance core is the key factor of the whole deformation process after excavation. In other words, the rigidity and state of the advance core play a determining role in the stability of both surface structures and the tunnel itself. This paper presents the results from detailed three-dimensional numerical studies, exploring vertical displacements, vector orientations and extrusions on tunnel face during the progressive advancement for the shallow tunnel in various geotechnical conditions.

• Geomechanics and Engineering
• /
• v.28 no.5
• /
• pp.505-520
• /
• 2022

In recent years, geotextile-encased gravel columns (usually called stone columns) have become a popular method to increasing soil shear strength, decreasing the settlement, acceleration of the rate of consolidation, reducing the liquefaction potential and increasing the bearing capacity of foundations. The behavior of improved loose base-soil with gravel columns under shear loading and the shear stress-horizontal displacement curves got from large scale direct shear test are of great importance in understanding the performance of this method. In the present study, by performing 36 large-scale direct shear tests on sandy base-soil with different fine-content of zero to 30% in both not improved and improved with gravel columns, the effect of the presence of gravel columns in the loose soils were investigated. The results were used to predict the shear stress-horizontal displacement curve of these samples using support vector machines (SVM). Variables such as the non-plastic fine content of base-soil (FC), the area replacement ratio of the gravel column (Arr), the geotextile encasement and the normal stress on the sample were effective factors in the shear stress-horizontal displacement curve of the samples. The training and testing data of the model showed higher power of SVM compared to multilayer perceptron (MLP) neural network in predicting shear stress-horizontal displacement curve. After ensuring the accuracy of the model evaluation, by introducing different samples to the model, the effect of different variables on the maximum shear stress of the samples was investigated. The results showed that by adding a gravel column and increasing the Arr, the friction angle (ϕ) and cohesion (c) of the samples increase. This increase is less in base-soil with more FC, and in a proportion of the same Arr, with increasing FC, internal friction angle and cohesion decreases.

• Structural Engineering and Mechanics
• /
• v.77 no.2
• /
• pp.151-165
• /
• 2021

This paper aims to present a novelty damage detection method to identify damage locations by the simultaneous use of both the energy and displacement damage indices. Using this novelty method, the damaged location and even the damaged floor are accurately detected. As a first method, a combination of the instantaneous frequency energy index (EDI) and the structural acceleration responses are used. To evaluate the first method and also present a rapid assessment method, the Displacement Damage Index (DDI), which consists of the error reliability (β) and Normal Probability Density Function (NPDF) indices, are introduced. The innovation of this method is the simultaneous use of displacement-acceleration responses during one process, which is more effective in the rapid evaluation of damage patterns with velocity vectors. In order to evaluate the effectiveness of the proposed method, various damage scenarios of the ASCE benchmark problem, and the effects of measurement noise were studied numerically. Extensive analyses show that the rapid proposed method is capable of accurately detecting the location of sparse damages through the building. Finally, the proposed method was validated by experimental studies of a six-story steel building structure with single and multiple damage cases.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.19 no.3
• /
• pp.237-244
• /
• 2001

On this study, a 50-years-old earth dam was measured by the static method of GPS for deformation monitoring. The reference network was measured by the vector between points in twice times and the monitored points were observed in four times at test field, i.e. an embankment which was restored by mortar, In addition, gross errors in the measurement were estimated and eliminated by data snooping method and random errors were adjusted by least square method. Finally, the amount of displacement was estimated from variance-covariance matrix. Also, precision of points were showed by the confidence ellipse(95%), and the amount of displacement was figured.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2002.04a
• /
• pp.369-376
• /
• 2002

The stochastic analysis of semi-infinite domain is presented using the weighted integral method, which is improved to include the higher order terms in expanding the displacement vector. To improve the weighted integral method, the Lagrangian remainder is taken into account in the expansion of the status variable with respect to the mean value of the random variables. In the resulting formulae only the 'proportionality coefficients' are introduced in the resulting equation, therefore no additional computation time and memory requirement is needed. The equations are applied in analyzing the semi-infinite domain. The results obtained by the improved weighted integral method are reasonable and are in good agreement with those of the Monte Carlo simulation. To model the semi-infinite domain, the Bettess's infinite element is adopted, where the theoretical decomposition of the strain-displacement matrix to calculate the deviatoric stiffness of the semi-infinite domains is introduced. The calculated value of mean and the covariance of the displacement are revealed to be larger than those given by the finite domain assumptions which is thought to be rational and should be considered in the design of structures on semi-infinite domains.

• Earthquakes and Structures
• /
• v.18 no.2
• /
• pp.163-170
• /
• 2020

Floor acceleration plays a major role in the seismic design of nonstructural components and equipment supported by structures. Large floor acceleration may cause structural damage to or even collapse of buildings. For precision instruments in high-tech factories, even small floor accelerations can cause considerable damage in this study. Six P-wave parameters, namely the peak measurement of acceleration, peak measurement of velocity, peak measurement of displacement, effective predominant period, integral of squared velocity, and cumulative absolute velocity, were estimated from the first 3 s of a vertical ground acceleration time history. Subsequently, a new predictive algorithm was developed, which utilizes the aforementioned parameters with the floor height and fundamental period of the structure as the new inputs of a support vector regression model. Representative earthquakes, which were recorded by the Structure Strong Earthquake Monitoring System of the Central Weather Bureau in Taiwan from 1992 to 2016, were used to construct the support vector regression model for predicting the peak floor acceleration (PFA) of each floor. The results indicated that the accuracy of the predicted PFA, which was defined as a PFA within a one-level difference from the measured PFA on Taiwan's seismic intensity scale, was 96.96%. The proposed system can be integrated into the existing earthquake early warning system to provide complete protection to life and the economy.

• 한국지구물리탐사학회:학술대회논문집
• /
• 2011.10a
• /
• pp.45-47
• /
• 2011