• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.4
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• pp.39-46
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• 2012

The objectives of this study is intended to analyze stresses using the boundary element method and probability analysis for agricultural structure. Loads and material properties are an important factor when analyzing the structure. Until now, designing structure, loads and material properties are applied deterministic value. However, load and material properties involve uncertainties due to those change probabilistic and deterministic methods could not consider uncertainties. To solve these problems, the reliability analysis based on probability properties scheme was developed. Reliability analysis is easy to approach to analysis frame structure, however it has limitation when solving plane stress strain problems a kind of agricultural structures. The BEM (Boundary Element Method) is able to analysis plane strain problems by boundary conditions. Thus, this study applied boundary element method to analysis plane strain problem, load and material properties as a probabilistic value to calculate the analytical model using Monte Carlo simulations were developed.

• Composites Research
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• v.16 no.6
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• pp.1-9
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• 2003

In this paper, probabilistic failure analysis based on Weibull distribution function is proposed to predict the fiber strength of composite pressure vessel. And, experimental tests were performed using fiber strand specimens, unidirectional laminate specimens and composite pressure vessels to confirm the volumetric size effect on the fiber strength. As an analytical method, the Weibull weakest link model and the sequential multi-step failure model are considered and mutually compared. The volumetric size effect shows the clearly observed tendency towards fiber strength degradation with increasing stressed volume. Good agreement of fiber strength distribution was shown between test data and predicted results for unidirectional laminate and hoop ply in pressure vessel. The site effect on fiber strength depends on material and processing factors, the reduction of fiber strength due to the stressed volume shows different values according to the variation of material and processing conditions.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.5
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• pp.412-417
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• 2013

Analytical modeling of photovoltaic power systems has been receiving significant attentions in recent years in that it is easy to apply for prediction of its dynamics and fault detection and diagnosis in advanced engineering technologies. This paper presents a novel probabilistic modeling approach for such power systems with a big data sequence. Firstly, we express input/output function of photovoltaic power systems in which solar irradiation and ambient temperature are regarded as input variable and electric power is output variable respectively. Based on this functional relationship, conditional probability for these three random variables(such as irradiation, temperature, and electric power) is mathematically defined and its estimation is accomplished from ratio of numbers of all sample data to numbers of cases related to two input variables, which is efficient in particular for a big data sequence of photovoltaic powers systems. Lastly, we predict the output values from a probabilistic model of photovoltaic power systems by using the expectation theory. Two case studies are carried out for testing reliability of the proposed modeling methodology in this paper.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.36 no.2
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• pp.73-79
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• 1987

This paper describes a new algorithm to evaluate the production cost for a generation system including energy-limited hydroelectric plants. The algorithm is based upon the analytical production costing model developed under the assumption of Gaussian probabilistic distribution of random load fluctuations and plant outages. Hydro operation and pumped storage operation have been dealt with in the previous papers using the concept of peak-shaving operation. In this paper, the hydro problem is solved by using a new version of the gradient projection method that treats the upper / lower bounds of variables saparately and uses a specified initial active constraint set. Accuracy and validity of the algorithm are demonstrated by comparing the result with that of the peak-shaving model.

• International journal of steel structures
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• v.18 no.4
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• pp.1325-1335
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• 2018

This study dealt with investigating the seismic performance of the smart and shape memory alloy (SMA) and magnets plus rubber-spring (MRS) dampers and their effects on the seismic resistance of multiple-span simply supported bridges. The rubber springs in the MRS dampers were pre-compressed. For this aim, a set of experimental works was performed together with developing nonlinear analytical models to investigate dynamic responses of the bridges subjected to earthquakes. Fragility analysis and probabilistic assessment were conducted to assess the seismic performance for the overall bridge system. Fragility curves were then generated for each model and were compared with those of as-built. Results showed dampers could increase the seismic capacity of bridges. Furthermore, from system fragility curves, use of damper models reduced the seismic vulnerability in comparison to the as-built bridge model. Although the SMA damper showed the best seismic performance, the MRS damper was the most appropriate one for the bridge in that the combination of magnetic friction and pre-compressed rubber springs was cheaper than the shape memory alloy, and had the similar capability of the damper.

• Management Science and Financial Engineering
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• v.15 no.1
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• pp.1-31
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• 2009

This paper considers the value of warehousing contract under probabilistic demands. We consider a supply chain consisting of a supplier, a retailer and its third-party warehousing partner who provides the warehousing service to the retailer through an outsourcing contract. A typical contract is specified by initial space commitment and modification schedule. The retailer decides the order quantity for the supplier and space commitment for the outsourcing contract. Since there is close relationship between order quantity and space commitment to minimize the total cost including ordering cost, inventory carrying cost, shortage cost, and warehousing cost, we develop an analytical model under probabilistic demands, where the retailer can determine the optimal order size and space commitment level jointly. We found the closed-form optimum for a single-period case and the optimal conditions for a two-period case. To evaluate the value of contract flexibility for the two-period case, we compared the total cost under two policies; one with modification, under which the base commitment can be changed at the start of each period and the other without modification. From results of our numerical analysis, we showed that the modification policy is more cost-effective as the variability of demand increases.

• Journal of Electrical Engineering and Technology
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• v.8 no.4
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• pp.719-728
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• 2013

Probabilistic assessment of voltage stability margin (VSM) with existence of correlated wind speeds is investigated. Nataf transformation is adopted to establish wind speed correlation (WSC) model. Based on the saddle-node bifurcation transversality condition equations and Monte Carlo simulation technique, probability distribution of VSM is determined. With correlation coefficients range low to high value, the effect of WSC on VSM is studied. In addition, two risk indexes are proposed and the possible threat caused by WSC is evaluated from the viewpoint of risk analysis. Experimental results show that the presence of correlated wind speeds is harmful to safe and stable operation of a power system as far as voltage stability is concerned. The achievement of this paper gives a detailed elaboration about the influence of WSC on voltage stability and provides a potentially effective analytical tool for modern power system with large-scale wind power sources integration.

• Architectural research
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• v.8 no.2
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• pp.27-36
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• 2006

Structural uncertainties are generally modeled using probabilistic approaches in order to quantify uncertainties in behaviors of structures. This uncertainty results from the uncertainties of structural parameters. Monte Carlo methods have been usually carried out for analyses of uncertainty problems where no analytical expression is available for the forward relationship between data and model parameters. In such cases any direct mathematical treatment is impossible, however the forward relation materializes itself as an algorithm allowing data to be calculated for any given model. This study addresses a new method which is utilized as a basis for the uncertainty estimates of structural responses. It applies double uniform random numbers (i.e. DURN technique) to conventional Monte Carlo algorithm. In DURN method, the scenarios of uncertainties are sequentially selected and executed in its simulation. Numerical examples demonstrate the beneficial effect that the technique can increase uncertainty degree of structural properties with maintaining structural stability and safety up to the limit point of a breakdown of structural systems.

• Journal of Communications and Networks
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• v.15 no.2
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• pp.222-227
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• 2013

This paper presents an analytical framework for dynamic spectrum allocation in cognitive radio networks. We propose a distributed queuing based Markovian model each for single channel and multiple channels access for a contending user. Knowledge about spectrum mobility is one of the most challenging problems in both these setups. To solve this, we consider probabilistic channel availability in case of licensed channel detection for single channel allocation, while variable data rates are considered using channel aggregation technique in the multiple channel access model. These models are designed for a centralized architecture to enable dynamic spectrum allocation and are compared on the basis of access latency and service duration.

• Nuclear Engineering and Technology
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• v.49 no.2
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• pp.411-425
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• 2017

Using a probabilistic safety assessment, a risk evaluation framework for an aircraft crash into an interim spent fuel storage facility is presented. Damage evaluation of a detailed generic cask model in a simplified building structure under an aircraft impact is discussed through a numerical structural analysis and an analytical fragility assessment. Sequences of the impact scenario are shown in a developed event tree, with uncertainties considered in the impact analysis and failure probabilities calculated. To evaluate the influence of parameters relevant to design safety, risks are estimated for three specification levels of cask and storage facility structures. The proposed assessment procedure includes the determination of the loading parameters, reference impact scenario, structural response analyses of facility walls, cask containment, and fuel assemblies, and a radiological consequence analysis with dose-risk estimation. The risk results for the proposed scenario in this study are expected to be small relative to those of design basis accidents for best-estimated conservative values. The importance of this framework is seen in its flexibility to evaluate the capability of the facility to withstand an aircraft impact and in its ability to anticipate potential realistic risks; the framework also provides insight into epistemic uncertainty in the available data and into the sensitivity of the design parameters for future research.