• Geomechanics and Engineering
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• v.2 no.4
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• pp.253-280
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• 2010

A new prediction model is derived for the uplift capacity of suction caissons using a hybrid method coupling genetic programming (GP) and simulated annealing (SA), called GP/SA. The predictor variables included in the analysis are the aspect ratio of caisson, shear strength of clayey soil, load point of application, load inclination angle, soil permeability, and loading rate. The proposed model is developed based on well established and widely dispersed experimental results gathered from the literature. To verify the applicability of the proposed model, it is employed to estimate the uplift capacity of parts of the test results that are not included in the modeling process. Traditional GP and multiple regression analyses are performed to benchmark the derived model. The external validation of the GP/SA and GP models was further verified using several statistical criteria recommended by researchers. Contributions of the parameters affecting the uplift capacity are evaluated through a sensitivity analysis. A subsequent parametric analysis is carried out and the obtained trends are confirmed with some previous studies. Based on the results, the GP/SA-based solution is effectively capable of estimating the horizontal, vertical and inclined uplift capacity of suction caissons. Furthermore, the GP/SA model provides a better prediction performance than the GP, regression and different models found in the literature. The proposed simplified formulation can reliably be employed for the pre-design of suction caissons. It may be also used as a quick check on solutions developed by more time consuming and in-depth deterministic analyses.

• Journal of the Korean Institute of Gas
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• v.21 no.3
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• pp.61-69
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• 2017

The commercial development of unconventional gas is pursued in North America because it is more feasible owing to the technology required to improve productivity. Shale reservoir have low permeability and gas production can be carried out through cracks generated by hydraulic fracturing. The decline rate during the initial production period is high, but very low latter on, there are significant variations from the initial production behavior. Therefore, in the prediction of the production rate using deterministic decline curve analysis(DCA), it is not possible to consider the uncertainty in the production behavior. In this study, production rate of the Eagle Ford shale is predicted by Arps Hyperbolic and Modified SEPD. To minimize the uncertainty in predicting the Estimated Ultimate Recovery(EUR), Monte Carlo simulation is used to multi-wells analysis. Also, kernel density function is applied to determine probability distribution of decline curve factors without any assumption.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.2
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• pp.159-169
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• 2019

Objective: Models for genomic selection assume that the reference population is an unselected population. However, in practice, genotyped individuals, such as progeny-tested bulls, are highly selected, and the reference population is created after preselection. In dairy cattle, the intensity of selection is higher in males than in females, suggesting that cows can be added to the reference population with less bias and loss of accuracy. The objective is to develop formulas applied to any genomic prediction studies or practice with preselected animals as reference population. Methods: We developed formulas for calculating the reliability and bias of genomically enhanced breeding values (GEBV) in the reference population where individuals are preselected on estimated breeding values. Based on the formulas presented, deterministic simulation was conducted by varying heritability, preselection percentage, and the reference population size. Results: The number of bulls equal to a cow regarding the reliability of GEBV was expressed through a simple formula for the reference population consisting of preselected animals. The bull population was vastly superior to the cow population regarding the reliability of GEBV for low-heritability traits. However, the superiority of reliability from the bull reference population over the cow population decreased as heritability increased. Bias was greater for bulls than cows. Bias and reduction in reliability of GEBV due to preselection was alleviated by expanding reference population. Conclusion: Cows are easier in expanding reference population size compared with bulls and alleviate bias and reduction in reliability of GEBV of bulls which are highly preselected than cows by expanding the cow reference population.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6C
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• pp.349-358
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• 2008

In performing the reliability analysis for predicting the settlement with time of alluvial clay layer at Kobe airport, the uncertainties of geotechnical properties were examined based on the stochastic and probabilistic theory. By using Terzaghi's consolidation theory as the objective function, the failure probability was normalized based on AFOSM method. As the result of reliability analysis, the occurrence probabilities for the cases of the target settlement of ${\pm}10%,\;{\pm}25%$ of the total settlement from the deterministic analysis were 30~50%, 60%~90%, respectively. Considering that the variation coefficients of input variable are almost similar as those of past researches, the acceptable error range of the total settlement would be expected in the range of 10% of the predicted total settlement. As the result of sensitivity analysis, the factors which affect significantly on the settlement analysis were the uncertainties of the compression coefficient Cc, the pre-consolidation stress Pc, and the prediction model employed. Accordingly, it is very important for the reliable prediction with high reliability to obtain reliable soil properties such as Cc and Pc by performing laboratory tests in which the in-situ stress and strain conditions are properly simulated.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.2 s.233
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• pp.277-283
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• 2005

Kriging model is widely used as design analysis and computer experiment (DACE) model in the field of engineering design to accomplish computationally feasible design optimization. In general, kriging model has been applied to many engineering applications as an interpolation model because it is usually constructed from deterministic simulation responses. However, when the responses include not only global nonlinearity but also numerical error, it is not suitable to use Kriging model that can distort global behavior. In this research, generalized kriging model that can represent both interpolation and regression is proposed. The performances of generalized kriging model are compared with those of interpolating kriging model for numerical function with error of normal distribution type and trigonometric function type. As an application of the proposed approach, the response of a simple dynamic model with numerical integration error is predicted based on sampling data. It is verified that the generalized kriging model can predict a noisy response without distortion of its global behavior. In addition, the influences of maximum likelihood estimation to prediction performance are discussed for the dynamic model.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.12 no.3
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• pp.173-180
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• 1992

A feature typical of natural rivers is the bend. The purpose of this study is to examine hydraulic and morphometric characteristics in channel bend reach by the deterministic approach. Cross section shape factor, "As" is suggested for a new cahracteristic factor of channel bend reach analysis. The variation of this new factor along the river reach showed the location of the concentration of the force due to the current all over the reach, that is curved or not. Some general meander factors are used for correlation with new factor suggested, and the applicability of "As" is verified. The range R/W values are concentrated 2~4, the meanning of this value can be regarded to the warning for bank erosion or breaking. And this paper dealt with prediction of cross section bed shape variation.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1997.10a
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• pp.145-154
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• 1997

The results of optimum design by the deterministic approach adopted in the current design codes depend upon the safety levels of the applied code. But, it is now generally recognized that structural problems are nondeterministic and, consequently, that engineering optimum design must cope with uncertainties. Therefore, it is not an overstatement to affirm that the combination of reliability-based design procedures and optimization techniques is the only means of providing a powerful tool to obtain a practical optimum design solution. In the paper, reliability based optimum design procedure as a rational approach to optimum structural design is presented. The design constraints are formulated based on the ASD, LRFD and reliability theories. The reliability analysis is based on an advanced first-order second moment approach. Uncertainties in the structural strength and loading due to inherent variability as well as modeling and prediction errors are included in failure due to combined bending and shear. For the realistic reliability-based optimization of continuous steel box girder bridges, interactive non-linear limit state model is formulated based on the von Mises's combined stress yield criterion. Comparative results are presented when the ASD criteria are used for the optimum design of a structure under reliability constraints. In addition, this study comparatively shows the results of the optimum design for various criteria of design codes.

• Journal of Environmental Science International
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• v.8 no.6
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• pp.661-667
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• 1999

Estimating dimensions of attractors are the most basic tools to analyze properties of chaotical dynamic systems. In this paper, we estimate correlation dimensions of meteorological variables, such as wind speed (v) and temperature (T) observed in Kimhae International Airport when the land-sea breeze circulation is appeared and find low non-integer values that reflect the deterministic chaos characterizing the dynamics. We compare the results with the correlation dimensions of 2-dimensional model that is calculated by finite element method. Though the correlation dimensions of the calculated wind speed ( v) are less than those of the observed wind speed ( v), we can suggest that the land-sea breeze circulation has not a unique mechanism. The land-sea breeze phenomenon is a complicated dynamics, which is constructed with various scale motions of atmosphere. In further research, we hope to find more accurate dynamics of land-sea breeze through wide observations and using of more sophisticated prediction models.

• Earthquakes and Structures
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• v.8 no.3
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• pp.681-697
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• 2015

Iran as one of the countries located on the Alpine-Himalayan seismic belt has recently experienced a few number of catastrophic earthquakes. A well-known index of how buildings are affected by earthquakes is through assessment of probable Peak Ground Acceleration (PGA) and structures' response spectra. In this research, active faults around Kerman and Birjand, two major cities in eastern parts of Iran, have been considered. Seismic catalogues are gathered to categorize effects of surrounding faults on seismicity of the region. These catalogues were further refined with respect to time and space based on Knopoff-Gardner algorithm in order to increase statistical independency of events. Probabilistic Seismic Hazard Analysis (PSHA) has been estimated for each of cities regarding 50, 100, 200 and 500 years of structures' effective life-span. These results subsequently have been compared with Deterministic Seismic Hazard Analysis (DSHA). It has been observed that DSHA not necessarily suggests upper bound of PSHA results. Furthermore, based on spectral Ground Motion Prediction Equations (GMPEs), Uniform Hazard Spectra (UHS) and spectral acceleration were provided for 2% and 10% levels of probability of exceedance. The results show that increasing source-to-site distance leads to spectral acceleration reduction regarding each fault. In addition, the spectral acceleration rate of variation would increase if the source-to-site distance decreases.

• Earthquakes and Structures
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• v.8 no.4
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• pp.915-934
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• 2015

Within the context of Structural Health Monitoring (SHM), it is often the case that structural systems are described by uncertainty, both with respect to their parameters and the characteristics of the input loads. For the purposes of system identification, efficient modeling procedures are of the essence for a fast and reliable computation of structural response while taking these uncertainties into account. In this work, a reduced order metamodeling framework is introduced for the challenging case of nonlinear structural systems subjected to earthquake excitation. The introduced metamodeling method is based on Nonlinear AutoRegressive models with eXogenous input (NARX), able to describe nonlinear dynamics, which are moreover characterized by random parameters utilized for the description of the uncertainty propagation. These random parameters, which include characteristics of the input excitation, are expanded onto a suitably defined finite-dimensional Polynomial Chaos (PC) basis and thus the resulting representation is fully described through a small number of deterministic coefficients of projection. The effectiveness of the proposed PC-NARX method is illustrated through its implementation on the metamodeling of a five-storey shear frame model paradigm for response in the region of plasticity, i.e., outside the commonly addressed linear elastic region. The added contribution of the introduced scheme is the ability of the proposed methodology to incorporate uncertainty into the simulation. The results demonstrate the efficiency of the proposed methodology for accurate prediction and simulation of the numerical model dynamics with a vast reduction of the required computational toll.