• Tunnel and Underground Space
• /
• v.20 no.1
• /
• pp.39-48
• /
• 2010

The present study developed a program which can assess the reliability of tunnel support systems based on a probability-based method. The developed program uses FLAC2D as a solver, and can automatically execute all the processes, associated with numerical and probabilistic analysis. Since a numerical analysis, which models the ground, requires a significant calculation time, it is actually impossible to apply simulation-based methods to probabilistic assessment on the reliability of tunnel support systems. Therefore, the present study used a point estimate method, which is efficient for probabilistic analysis since the method can significantly reduce the number of samples when compared with the simulation-based method. The developed program was applied to a tunnel project, and the results were compared with those through a deterministic approach. From the comparison, it was identified that a probabilistic approach can quantitatively assess the reliability of tunnel support systems based on probability of failure and can be used as a tool for decision making in tunnel support designs.

• Journal of the Korean Recycled Construction Resources Institute
• /
• v.4 no.2
• /
• pp.172-179
• /
• 2016

For an evaluation of service life in RC(Reinforced Concrete) structures, deterministic method and probabilistic method considering random variables of design parameters are usually adopted. In the work, surface chloride contents which vary with distance from sea shore and height are investigated from the previous research literature surveys, and they are considered for service life estimation. Through the analysis, the probabilistic method shows much lower results, which is due to variations of design parameters and very low intended durability failure. In the deterministic method, the structures within 250m and higher than 60m are evaluated to be free from chloride attack. In the probabilistic method, those higher than 60m in all the region and higher than 40m and 250m from sea shore are evaluated to satisfy the service life.

• Earthquakes and Structures
• /
• v.10 no.2
• /
• pp.389-408
• /
• 2016

Recently, seismic hazard analysis has become a very significant issue. New systems and available data have been also developed that could help scientists to explain the earthquakes phenomena and its physics. Scientists have begun to accept the role of uncertainty in earthquake issues and seismic hazard analysis. However, handling the existing uncertainty is still an important problem and lack of data causes difficulties in precisely quantifying uncertainty. Ground Motion Prediction Equation (GMPE) values are usually obtained in a statistical method: regression analysis. Each of these GMPEs uses the preliminary data of the selected earthquake. In this paper, a new fuzzy method was proposed to select suitable GMPE at every intensity (earthquake magnitude) and distance (site distance to fault) according to preliminary data aggregation in their area using ${\alpha}$ cut. The results showed that the use of this method as a GMPE could make a significant difference in probabilistic seismic hazard analysis (PSHA) results instead of selecting one equation or using logic tree. Also, a practical example of this new method was described in Iran as one of the world's earthquake-prone areas.

• Journal of Communications and Networks
• /
• v.18 no.5
• /
• pp.818-825
• /
• 2016

Network management and anomaly detection are challenges in high-speed networks due to the high volume of packets that has to be analysed. Flow-based analysis is a scalable method which reduces the high volume of network traffic by dividing it into flows. As sampling methods are extensively used in flow generators such as NetFlow, the impact of sampling on the performance of flow-based analysis needs to be investigated. Monitoring using sampled traffic is a well-studied research area, however, the impact of sampling on flow-based anomaly detection is a poorly researched area. This paper investigates flow sampling methods and shows that these methods have negative impact on flow-based anomaly detection. Therefore, we propose an efficient probabilistic flow sampling method that can preserve flow traffic distribution. The proposed sampling method takes into account two flow features: Destination IP address and octet. The destination IP addresses are sampled based on the number of received bytes. Our method provides efficient sampled traffic which has the required traffic features for both flow-based anomaly detection and monitoring. The proposed sampling method is evaluated using a number of generated flow-based datasets. The results show improvement in preserved malicious flows.

• Structural Engineering and Mechanics
• /
• v.47 no.3
• /
• pp.361-381
• /
• 2013

A Bayesian probabilistic method is proposed for online estimation of the process noise and measurement noise parameters for Kalman filter. Kalman filter is a well-known recursive algorithm for state estimation of dynamical systems. In this algorithm, it is required to prescribe the covariance matrices of the process noise and measurement noise. However, inappropriate choice of these covariance matrices substantially deteriorates the performance of the Kalman filter. In this paper, a probabilistic method is proposed for online estimation of the noise parameters which govern the noise covariance matrices. The proposed Bayesian method not only estimates the optimal noise parameters but also quantifies the associated estimation uncertainty in an online manner. By utilizing the estimated noise parameters, reliable state estimation can be accomplished. Moreover, the proposed method does not assume any stationarity condition of the process noise and/or measurement noise. By removing the stationarity constraint, the proposed method enhances the applicability of the state estimation algorithm for nonstationary circumstances generally encountered in practice. To illustrate the efficacy and efficiency of the proposed method, examples using a fifty-story building with different stationarity scenarios of the process noise and measurement noise are presented.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.52 no.12
• /
• pp.705-712
• /
• 2003

In this paper, we propose new unified methodologies of reliability and its cost evaluation in power distribution systems. The unified method means that the proposed reliability approaches consider both conventional evaluation factor, i.e. sustained interruptions and additional ones, i.e. momentary interruptions and voltage sags. Because the three voltage quality phenomena generally originate from the outages on distribution systems, the basic and additional reliability indices are summarized considering the fault clearing mechanism. The proposed unified method is divided into the reliability evaluation for calculating the reliability indices and reliability cost evaluation for assessing the damage of customer. The analytic and probabilistic methodologies are presented for each unified reliability and its cost evaluation. The time sequential Monte Carlo technique is used for the probabilistic method. The proposed DVL(Demand Varying Load) model is added to the reliability cost evaluation substituting the average load model. The proposed methods are tested using the modified RBTS(Roy Billinton Test System) form and historical reliability data of KEPCO(Korea Electric Power Corporation) system. The daily load profile of the each customer type in domestic are gathered for the DVL model. Through the case studies, it is verified that the proposed methods can be effectively applied to the distribution systems for more detail reliability assessment than conventional approaches.

• Journal of the Korean Geotechnical Society
• /
• v.27 no.10
• /
• pp.93-104
• /
• 2011

In this paper, a numerical procedure of probabilistic steady seepage analysis that considers the spatial variability of soil permeability is presented. The procedure extends the deterministic analysis based on the finite element method to a probabilistic approach that accounts for the uncertainties and spatial variation of the soil permeability. Two-dimensional random fields are generated based on a Karhunen-Lo$\grave{e}$ve expansion in a fashion consistent with a specified marginal distribution function and an autocorrelation function. A Monte Carlo simulation is then used to determine the statistical response based on the random fields. A series of analyses were performed to verify the application potential of the proposed method and to study the effects of uncertainty due to the spatial heterogeneity on the seepage behavior of soil foundation beneath water retaining structure with a single sheet pile wall. The results showed that the probabilistic framework can be used to efficiently consider the various flow patterns caused by the spatial variability of the soil permeability in seepage assessment for a soil foundation beneath water retaining structures.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.1
• /
• pp.21-40
• /
• 2018

In this paper, we propose the distributed robust beamforming design scheme in cognitive two-way amplify-and-forward (AF) relay networks with imperfect channel state information (CSI). Assuming the CSI errors follow a complex Gaussian distribution, the objective of this paper is to design the robust beamformer which minimizes the total transmit power of the collaborative relays. This design will guarantee the outage probability of signal-to-interference-plus-noise ratio (SINR) beyond a target level at each secondary user (SU), and satisfies the outage probability of interference generated on the primary user (PU) above the predetermined maximum tolerable interference power. Due to the multiple CSI uncertainties in the two-way transmission, the probabilistic constrained optimization problem is intractable and difficult to obtain a closed-form solution. To deal with this, we reformulate the problem to the standard form through a series of matrix transformations. We then accomplish the problem by using the probabilistic approach based on two sorts of Bernstein-type inequalities and the worst-case approach based on S-Procedure. The simulation results indicate that the robust beamforming designs based on the probabilistic method and the worst-case method are both robust to the CSI errors. Meanwhile, the probabilistic method can provide higher feasibility rate and consumes less power.

• Korean Journal of Construction Engineering and Management
• /
• v.8 no.5
• /
• pp.71-79
• /
• 2007

It is common that the analysis of VE/LCC is performed in design phase of quay wall structures. The analysis is mainly executed based on experience and engineering sense of expert considering the selection of construction method, construction and maintenance cost. Recently there are increasing demands on the analysis that includes uncertainty and vulnerability of input parameters, for this purpose, fuzzy reliability based probabilistic VE/LCC analysis model for quay wall structures is suggested. In VE/LCC analysis for quay wall structures, the application of probabilistic analysis method give very similar results compare with those of deterministic analysis method. It is anticipated that the methodology proposed in this paper can also be utilized in the design and maintenance phase of other facilities where decision making is made for the probabilistic life cycle cost and value analysis.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.49 no.4
• /
• pp.195-198
• /
• 2000

This paper illustrates a new method for constructing composite power system effective load duration curve(CMELDC) at load points. The main concept of proposed method is that the CMELDC can be obtain from convolution integral processing of the outage probabilistic distribution function of not supplied power and the load duration curve given at each load point. The effective load duration curve (ELDC) at HLI plays an important part in probabilistic production simulation, reliability evaluation, outage cost assessment and power supply margins assesment for power system planning and operation. And also, the CMELDC at HLII will extend the application areas of outage cost assessment and reliability evaluation at each load point. The CMELDC at load points using the Monte Carlo method and a DC load flow constrained LP have already been developed by authors. The effective load concept at HLII, however, has not been introduced sufficiently in last paper although the concept is important. In this paper, the main concept of the effective load at HLII which is proposed in this study is defined in details as the summation of the original load and the probabilistic loads caused by the forced outage of generators and transmission lines at this load point. The outage capacity probabilistic distribution function at HLII can be obtained by combining the not supplied powers and the probabilities of the not supplied powers at this load point. It si also expected that the proposed CMELDC can be applied usefully to research areas such as reliability evaluation, probabilistic production cost simulation and analytical outage cost assessment, etc. at HLII in future. The characteristics and effectiveness of this methodology are illustrated by case study of IEEE-RTS.