• Geomechanics and Engineering
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• v.25 no.1
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• pp.17-30
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• 2021

This paper develops a convenient approach for deterministic and probabilistic evaluations of tunnel face stability using support vector machine classifiers. The proposed method is comprised of two major steps, i.e., construction of the training dataset and determination of instance-based classifiers. In step one, the orthogonal design is utilized to produce representative samples after the ranges and levels of the factors that influence tunnel face stability are specified. The training dataset is then labeled by two-dimensional strength reduction analyses embedded within OptumG2. For any unknown instance, the second step applies the training dataset for classification, which is achieved by an ad hoc Python program. The classification of unknown samples starts with selection of instance-based training samples using the k-nearest neighbors algorithm, followed by the construction of an instance-based SVM-KNN classifier. It eventually provides labels of the unknown instances, avoiding calculate its corresponding performance function. Probabilistic evaluations are performed by Monte Carlo simulation based on the SVM-KNN classifier. The ratio of the number of unstable samples to the total number of simulated samples is computed and is taken as the failure probability, which is validated and compared with the response surface method.

• Geomechanics and Engineering
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• v.34 no.6
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• pp.597-609
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• 2023

One of the applicable methods for the stabilization of soil walls is the nailing system which consists of tensile struts. The stability and safety of soil nail wall systems are influenced by the geometrical parameters of the nailing system. Generally, the determination of nailing parameters in order to achieve optimal performance of the nailing system for the safety of soil walls is defined in the framework of optimization problems. Also, according to the various uncertainty in the mechanical parameters of soil structures, it is necessary to evaluate the reliability of the system as a probabilistic problem. In this paper, the optimal design of the nailing system is carried out in deterministic and probabilistic cases using meta-heuristic and reliability-based design optimization methods. The colliding body optimization algorithm and first-order reliability method are used for optimization and reliability analysis problems, respectively. The objective function is defined based on the total cost of nails and safety factors and reliability index are selected as constraints. The mechanical properties of the nailing system are selected as design variables and the mechanical properties of the soil are selected as random variables. The results show that the reliability of the optimally designed soil nail system is very sensitive to uncertainty in soil mechanical parameters. Also, the design results are affected by uncertainties in soil mechanical parameters due to the values of safety factors. Reliability-based design optimization results show that a nailing system can be designed for the expected level of reliability and failure probability.

• KIEAE Journal
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• v.14 no.5
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• pp.5-12
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• 2014

Building has been deteriorated gradually owing to geographic, physical complex and other factors. School living condition has a key role to improve the learning ability, life attitude and qualifications to adopt to social life. Therefore, it is important for school environment to keep the living condition. Repair time and scope of school facilities are required to maintain the function and performance to plan the long term repair. But there are little information about the school maintenance such as repair time and function. In this paper, it aimed at providing the service life to suggest the repair time and scope in the roof-proofing and floor finishing which used the three estimation method in probabilistic approach. The service life has a key role to decide the repair time and to make the plan for the repair maintenance. Results of this study are as follows ; First, the 1st repair time were taken through three methods in probabilistic and deterministic functions to eliminate the estimation bias. Second, the service life is suggested 36 years of an elementary school, 34 years of a middle school and 41 years of a high school. Third, the service life of a floor finishing is 43 years of an elementary, 39 years of a middle school and 41 years of a high school. The above study could not include the detailed information about the materials and repair works. Therefore it needs a further study to reflect the detailed information and to make a repair strategy.

• The Journal of the Acoustical Society of Korea
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• v.43 no.2
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• pp.200-206
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• 2024

Computing music similarity is an indispensable component in developing music search service. This paper proposes a relevance weight of each chromagram vector for cover song identification in computing a music similarity function in order to boost identification accuracy. We derive a music similarity function using the relevance weight based on the probabilistic relevance model, where higher relevance weights are assigned to less frequently-occurring discriminant chromagram vectors while lower weights to more frequently-occurring ones. Experimental results performed on two cover music datasets show that the proposed music similarity improves the cover song identification performance.

• Earthquakes and Structures
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• v.2 no.3
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• pp.279-295
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• 2011

This paper develops a probabilistic methodology for the seismic reliability analysis of structures with random properties. The earthquake loading is assumed to be described in terms of response spectra. The proposed methodology takes advantage of the response spectra and thus does not require explicit dynamic analysis of the actual structure. Uncertainties in the structural properties (e.g. member cross-sections, modulus of elasticity, member strengths, mass and damping) as well as in the seismic load (due to uncertainty associated with the earthquake load specification) are considered. The structural reliability is estimated by determining the failure probability or the reliability index associated with a performance function that defines safe and unsafe domains. The structural failure is estimated using a performance function that evaluates whether the maximum displacement has been exceeded. Numerical illustrations of reliability analysis of elastic and elastic-plastic single-story frame structures are presented first. The extension of the proposed method to elastic multi-degree-of-freedom uncertain structures is also studied and a solved example is provided.

• Structural Engineering and Mechanics
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• v.71 no.6
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• pp.739-749
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• 2019

This article deals with the application of reliability analysis for determining the safety of simply supported beam under the uniformly distributed load. The uncertainties of the existing methods were taken into account and hence reliability analysis has been adopted. To accomplish this aim, Generalized Regression Neural Network (GRNN), Extreme Learning Machine (ELM) and Gaussian Process Regression (GPR) models are developed. Reliability analysis is the probabilistic style to determine the possibility of failure free operation of a structure. The application of probabilistic mathematics into the quantitative aspects of a structure and improve the qualitative aspects of a structure. In order to construct the GRNN, ELM and GPR models, the dataset contains Modulus of Elasticity (E), Load intensity (w) and performance function (${\delta}$) in which E and w are inputs and ${\delta}$ is the output. The achievement of the developed models was weighed by various statistical parameters; one among the most primitive parameter is Coefficient of Determination ($R^2$) which has 0.998 for training and 0.989 for testing. The GRNN outperforms the other ELM and GPR models. Other different statistical computations have been carried out, which speaks out the errors and prediction performance in order to justify the capability of the developed models.

• Journal of the Earthquake Engineering Society of Korea
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• v.12 no.3
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• pp.1-10
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• 2008

The seismic performance of a structure designed without consideration of seismic loading can be effectively enhanced through seismic rehabilitation. The appropriate level of rehabilitation should be determined based on the decision criteria that minimize the anticipated earthquake-related losses. To estimate the anticipated losses, seismic risk analysis should be performed considering the probabilistic characteristics of the hazard and the structural damage. This study presents the decision procedure in which the probabilistic seismic demand model is utilized for the effective estimation and minimization of the total seismic losses through seismic rehabilitation. The probability density function and the cumulative distribution function of the structural damage for a specified time period are established in a closed form, and are combined with the loss functions to derive the expected seismic loss. The procedure presented in this study could be effectively used for making decisions on the seismic rehabilitation of structural systems.

• Korean Journal of Construction Engineering and Management
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• v.10 no.2
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• pp.102-110
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• 2009

The cost for maintenance of bridge structures such as repair or reinforcement is increasing. In addition, the efforts for inspection of bridge structures is becoming more important since the proper repair or reinforcement should be performed to save the maintenance cost and ensure the safety for public infrastructure. Therefore, it is studied on this paper to estimate the repair or reinforcement cycles using probabilistic approach for the steel-box girders of bridge superstructure. In addition, a computer simulation program is uniquely developed based on probabilistic approach to calculate the cycles derived from the function of age of bridge and performance rating curve which were previously studied. In order to ensure the reliability of results and appropriateness of the model, statistical analyses were performed. Also, the results were compared and proved to be similar with ones from previous statistical data related to the repair or reinforcement cycles. The results from this study is expected to be useful for the determination of proper time to repair or reinforce the bridge structure and raise the safetyness of bridge structure in advance.

• Food Science of Animal Resources
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• v.32 no.1
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• pp.62-67
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• 2012

This study calculated kinetic parameters of Escherichia coli O157:H7 and developed a probabilistic model to estimate growth probabilities of E. coli O157:H7 on polyethylene cutting boards as a function of temperature and time. The surfaces of polyethylene coupons ($3{\times}5$ cm) were inoculated with E. coli O157:H7 NCCP11142 at 4 Log $CFU/cm^2$. The coupons were stored at 13 to $35^{\circ}C$ for 12 h, and cell counts of E. coli O157:H7 were enumerated on McConkey II with sorbitol agar every 2 h. Kinetic parameters (maximum specific growth rate, Log $CFU/cm^2/h$; lag phase duration, h; lower asymptote, Log $CFU/cm^2$; upper asymptote, Log $CFU/cm^2$) were calculated with the modified Gompertz model. Of 56 combinations (temperature${\times}$time), the combinations that had ${\geq}$0.5 Log $CFU/cm^2$ of bacterial growth were designated with the value of 1, and the combinations that had increases of <0.5 Log $CFU/cm^2$ were given the value 0. These growth response data were fitted to the logistic regression to develop the model predicting probabilities of E. coli O157:H7 growth. Specific growth rate and growth data showed that E. coli O157:H7 cells were grown at $28-35^{\circ}C$, but there were no obvious growth of the pathogen below $25^{\circ}C$. Moreover, the developed probabilistic model showed acceptable performance to calculate growth probability of E. coli O157:H7. Therefore, the results should be useful in determining upper limits of working temperature and time, inhibiting E. coli O157:H7 growth on polyethylene cutting board.

• Steel and Composite Structures
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• v.24 no.3
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• pp.369-382
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• 2017

This study investigates the reliability of the performance levels of moment resisting steel frames subjected to lateral loads such as wind and earthquake. The reliability assessment has been performed with respect to three performance levels: serviceability, damageability, and ultimate limit states. A four-story moment resisting frame is used as a typical example. In the reliability assessment the uncertainties in the loadings and in the capacity of the frame have been considered. The wind and earthquake loads are assumed to have lognormal distribution, and the frame resistance is assumed to have a normal distribution. In order to obtain an appropriate limit state function a linear relation between the loading and the deflection is formed. For the reliability analysis an algorithm has been developed for determination of limit state functions and iterations of the first order reliability method (FORM) procedure. By the method presented herein the multivariable analysis of a complicated reliability problem is reduced to an S-R problem. The procedure for iterations has been tested by a known problem for the purpose of avoiding convergence problems. The reliability indices for many cases have been obtained and also the effects of the coefficient of variation of load and resistance have been investigated.