• Journal of Korea Water Resources Association
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• v.39 no.6 s.167
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• pp.503-510
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• 2006

Riverbank filtration is a natural process, using alluvial aquifers to remove contaminants and pathogens in river water for the production of drinking water. Back analysis which minimizes the objective function that is typically the sum of squares of the differences between the calculated and measured quantities is used for the estimation of aquifer parameters. In this study, transmissivity is back-analysed using the BFGS (Broyden-Fletcher-Goldfarb-Shanno) scheme for optimization. MOC is used to obtain calculated groundwater level. The developed inverse model was applied to Dae-san, Chang-won city where riverbank filtration is being undertaken. The model showed good convergence behavior for different groundwater conditions. The performance of the model was better than a widely-used commercial software package in terms of error between calculated and observed groundwater level.

• Journal of the Korean Geotechnical Society
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• v.18 no.1
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• pp.71-78
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• 2002

This paper presents a back-calculation technique leer the prediction of the behavior of earth wall inserted in multi-layered soil deposit. The soil properties are back-calculated from the measured displacement at each construction stage and the behavior of earth wall far the next construction stage is predicted using back-calculated soil properties. For multi-layered soil deposit, the back-calculation would be very difficult due to the increase in the number of variables. In this study, to solve this difficulty, the back-calculation was performed successively from the lowest layer to the upper layers. An efficient elasto-plastic beam-column analysis was used for forward analysis to minimize the computation time of iterative back-calculation procedure. The coefficients of subgrade reaction and lateral earth pressure necessary for the formation of p-y curve were selected as back calculation variables, and to minimize the effect of abnormal behavior of the wall which might be caused by any unexpected action during construction, the difference between measured displacement increment and computed displacement increment at each construction stages is used as the objective function of optimization. The constrained sequential linear programming was used for the optimization technique to found values of variables minimizing the objective function. The proposed method in this study was verified using numerically generated data and measured field data.

• Geophysics and Geophysical Exploration
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• v.22 no.4
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• pp.186-194
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• 2019

Deterministic optimization, commonly used to find the geophysical inverse solutions, have its limitation that it cannot find the proper solution since it might converge into the local minimum. One of the solutions to this problem is to use global optimization based on a stochastic approach, among which a large number of particle swarm optimization (PSO) applications have been introduced. In this paper, I developed a geophysical inversion algorithm applying PSO method for the layered-earth resistivity inversion of the small-loop electromagnetic (EM) survey data and carried out numerical inversion experiments on synthetic datasets. From the results, it is confirmed that the PSO inversion algorithm could increase the inversion success rate even when attempting the inversion of small-loop EM survey data from which it might be difficult to find a best solution by applying the Gauss-Newton inversion algorithm.

• Geotechnical Engineering
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• v.9 no.1
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• pp.21-30
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• 1993

To know the importance of soil paramters which are used to estimate the deformation and porepressure of soil, the sensitivity for soil parameters in elastic analysis is analyzed. Using the consolidation teat results of several cohesive soils, soil parameters are estimated by back analysis method, and from the parameters the deformations and porepressures of the soil are estimated by elastic analysis, In elastic analysis for soil-deformation and porepressure, the sensitivity for the Young's modulus is large, and the esimation of Young's modulus is more important in pro- portion to the size of stress. Using the measured results during initial short period in small stress, the soil parameters can be correctly estimated by back analysis method. To decrease the iteration number in back analysis and to get the better paramters, the initial measurements in more nodes are required and the more accurate initial measurements are required.

• Journal of the Korea institute for structural maintenance and inspection
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• v.16 no.5
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• pp.121-128
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• 2012

In this paper, nonlinear analysis for reinforced concrete structure for power transmission line is performed by considering the characteristics of the failure, which are depend on loading conditions and concrete material models. On the numerical evaluation for the failure behavior, the finite element analysis is applied. For the concrete material model, microplane model based on concrete damage is introduced. However, to describe the crack bridging effect of long and short fiber of steel fiber reinforced concrete (SFRC), tensile softening model is suggested and applied for SFRC. An numerical results by finite element technique are compared with the experiment results for box culvert specimen. Comparing on the experimental and analytical results, validity and reliability of numerical analysis are investigated.

• Journal of the Society of Disaster Information
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• v.15 no.4
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• pp.570-577
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• 2019

Purpose: The purpose of this study is to develop a system that enables quick on-site response using real-time decision-making by sharing the results of measurement and management performed in the field for safe temporary construction. Method: It is possible to take preemptive responses during construction by identifying the safety factors of construction conditions from measurement results and determining the risk factors such as soil properties and variability of climate change that can occur during construction by simultaneously using the back analysis method reflected in the measurement system and structural review. Result: we developed a back analysis algorithm of the SUNEX program to cope with the discrepancies between the design results and measured results due to inconsistency between site conditions and design properties, unexpected loads, and outdoor environment. The process of matching the measurement result with the analysis result can be confirmed in the safety management system. Conclusion: Gateway was used to communicate with real-time measurement results and safety management system program. It was made possible to preemptively respond to risk factors that may occur in the field.

• Journal of the Korean Geotechnical Society
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• v.35 no.4
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• pp.27-35
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• 2019

This study confirmed the applicability to the field of geotechnical engineering for relatively complicated space and many target design variables in back analysis. The Sharan's equation and the Blum's method were used for the tunnel field and the retaining wall as a model for the multi-variate problem of geotechnical engineering. Optimization methods are generally divided into a deterministic method and a stochastic method. In this study, Simulated Annealing Method (SA) was selected as a deterministic method and Differential Evolution Algorithm (DEA) and Particle Swarm Optimization Method (PSO) were selected as stochastic methods. The three selected optimization methods were compared by applying a multi-variate model. The problem of deterministic method has been confirmed in the multi-variate back analysis of geotechnical engineering, and the superiority of DEA can be confirmed. DEA showed an average error rate of 3.12% for Sharan's solution and 2.23% for Blum's problem. The iteration number of DEA was confirmed to be smaller than the other two optimization methods. SA was confirmed to be 117.39~167.13 times higher than DEA and PSO was confirmed to be 2.43~6.91 times higher than DEA. Applying a DEA to the multi-variate back analysis of geotechnical problems can be expected to improve computational speed and accuracy.

• Journal of Korean Tunnelling and Underground Space Association
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• v.14 no.4
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• pp.357-374
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• 2012

Considerable uncertainties are included in ground properties used for tunnel designs due to the limited investigation and tests. In this study, a back analysis was performed to find optimal ground properties based on artificial neural network using both face mapping data and convergence measurement data. First of all, the rock class of a study tunnel is determined from face mapping data. Then the possible ranges of ground properties were selected for each rock class through a literature review on the previous studies and utilized to establish more precise learning data. To find an optimal training model, a sensitivity analysis was also conducted by varying the number of hidden layers and the number of nodes more minutely than the previous study. As a result of this study, more accurate ground properties could be obtained. Therefore it was confirmed that the accuracy of the results could be increased by making use of not only convergence measurement data but also face mapping data in tunnel back analyses using artificial neural network. In future, it is expected that the methodology suggested in this study can be used to estimate ground properties more precisely.

• Journal of Korean Tunnelling and Underground Space Association
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• v.14 no.1
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• pp.37-53
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• 2012

There is considerable uncertainty in ground properties used in tunnel designs. In this study, a back analysis was performed to find optimal ground properties based on the artificial neural network facility of MATLAB program of using tunnel monitoring data. Total 81 data were constructed by changing elastic modulus and coefficient of lateral pressure which have great influence on tunnel convergence. A sensitivity analysis was conducted to establish an optimal training model by varying the number of hidden layers, the number of nodes, learning rate, and momentum. Meanwhile, the optimal training model was selected by comparing MSE (Mean Squared Error) and coefficient of determination ($R^2$) and was used to find the correct elastic moduli of layers and the coefficient of lateral pressure. In future, it is expected that the suggested method of this study can be applied to determine the optimum tunnel support pattern under given ground conditions.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.13 no.4
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• pp.199-208
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• 1993

Using several soil parameters which are obtained from the PI-experimental formulas and the back analysis method, the elastic analysis, the elasto-plastic analysis and the elasto-viscoplastic analysis for soil deformation are executed. Comparing the results with those of consolidation test, the indirect estimation method for soil parameters and the suitability of constitutive models are studied. The elastic analysis using back analysis result and the elasto-plastic analysis using the perconsolidation test. The elasto-viscoplastic analysis disagrees with the results of meability coefficient obtained from back analysis are the nearest to the results of the consolidation test. It is inferred that elasto-viscoplastic model is not adequate to the soil of which plasticity index is low.