• Structural Engineering and Mechanics
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• v.13 no.2
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• pp.231-239
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• 2002

The problem of dynamic analysis of truss structures based on probability is studied in this paper. Considering the randomness of both physical parameters (elastic module and mass density) of structural materials and geometric dimension of bars respectively or simultaneously, the stiffness and mass matrixes of the elements and structure have been built. The structure dynamic characteristic based on probability is analyzed, and the expressions of numeral characteristics of inherence frequency random variable are derived from the Rayleigh's quotient. The method of structural dynamic analysis based on probability is developed. Finally, two examples are given.

• Korean Journal of Construction Engineering and Management
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• v.17 no.5
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• pp.13-21
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• 2016

Insolvency of construction companies that play the role of main contractors can lead to clients' losses due to non-fulfillment of construction contracts, and it can have negative effects on the financial soundness of construction companies and suppliers. The construction industry has the cash flow financial characteristic of receiving a project and getting payment based on the progress of the construction. As such, insolvency during project progress can lead to financial losses, which is why the prediction of construction companies is so important. The prediction of insolvency of Korean construction companies are often made through the KMV model from the KMV (Kealhofer McQuown and Vasicek) Company developed in the U.S. during the early 90s, but this model is insufficient in predicting construction companies because it was developed based on credit risk assessment of general companies and banks. In addition, the predictive performance of KMV value's insolvency probability is continuously being questioned due to lack of number of analyzed companies and data. Therefore, in order to resolve such issues, the Bayesian Probabilistic Approach is to be combined with the existing insolvency predictive probability model. This is because if the Prior Probability of Bayesian statistics can be appropriately predicted, reliable Posterior Probability can be predicted through ensured conditionality on the evidence despite the lack of data. Thus, this study is to measure the Expected Default Frequency (EDF) by utilizing the Bayesian Probabilistic Approach with the existing insolvency predictive probability model and predict the accuracy by comparing the result with the EDF of the existing model.

• Journal of Electrical Engineering and Technology
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• v.10 no.6
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• pp.2211-2220
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• 2015

This paper analyzes multiple active management (AM) techniques of active distribution network (ADN), and proposes an optimal coordination model of intermittent distributed generation (IDG) accommodation considering the timing characteristic of load and IDG. The objective of the model is to maximize the daily amount of IDG accommodation under the uncertainties of IDG and load. Various active management techniques such as IDG curtailment, on-load tap changer (OLTC) tap adjusting, voltage regulator (VR) tap adjusting, shunt capacitors compensation and so on are fully considered. Genetic algorithm and Primal-Dual Interior Point Method (PDIPM) is used for the model solving. Point estimate method is used to simulate the uncertainties. Different scenarios are selected for the IDG accommodation capability investigation under different active management schemes. Finally a modified IEEE 123 case is used to testify the proposed accommodation model, the results show that the active management can largely increase the IDG accommodation and penetration.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.6
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• pp.77-87
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• 2012

Recently, Load and Resistance Factor Design (LRFD) based on reliability analysis has become a global trend for economical and rational design. In order to implement the LRFD, quantification of uncertainty for load and resistance should be done. The reliability of result relies on input variable, and therefore, it is important to obtain exact uncertainty properties of load and resistance. Since soil stress is the main reason causing the settlement or deformation of ground and load on the underground structure, it is essential to clarify the uncertainty of soil stress distribution for accurately predict the uncertainty of load in LRFD. In this study, laboratory model test on silty sand bed under probabilistic load is performed to observe propagation of upper load uncertainty. The results show that the coefficient of variation (COV) of soil stress are varied depending on location due to non-linear relationship between upper load increment and soil pressure increment. In addition, when the load uncertainty is transmitted through ground, COV is decreased by damping effect.

• Convergence Security Journal
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• v.10 no.3
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• pp.29-41
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• 2010

Survelliance and Reconnaissance Sensor Network(SRSN) which can collect various tactical information within battlefield in real time plays an important role in NCW environment, of sensor to shooter architecture. However, due to the resource-limited characteristics of sensor nodes and the intrinsic attributes of sensor network such as wireless communication, the SRSN may be vulnerable to various attacks compared to traditional networks. Therefore, in this paper, we propose a new group key management scheme to guarantee confidentiality, integrity, availability, and authentication during the operation of the SRSN. Proposed scheme generates and distributes the group key based on the topological characteristic of the SRSN and the probabilistic key sharing. The communication cost for distributing the group key is O(logn).

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.11
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• pp.1125-1135
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• 2010

A fundamental characteristic of PMHT (Probabilistic Multi-Hypothesis Tracker) is that the number of targets and initial states of targets in the surveillance area must be a priori known. This requirement is impossible to fulfil in almost every realistic scenario. In the paper, we present two track initiation methods to solve the problem. The proposed track initiation methods are 2-point track initiation and Hough transform track initiation, and they are used to evaluate track initial states and weights for FTD (False Track Discrimination) of the PMHT algorithm. Also suggested as automatic target detection for tracking systems that combines track initiation for target detection with the PMHT algorithm for target tracking in a cluttered environment. A series of Monte-Carlo simulation runs is employed to evaluate the overall system performance with the two track initiation methods and the results are compared and analyzed.

• Earthquakes and Structures
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• v.15 no.4
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• pp.443-452
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• 2018

In this paper the new intensity measures (IMs) for probabilistic seismic analysis of RC high-rise buildings with core wall structural system are proposed. The existing IMs are analysed and the new optimal ones are presented. The newly proposed IMs are based on the existing ones which: 1) comprise a wider range of frequency velocity spectrum content and 2) are defined as the integral along the velocity spectrum. In analysis characteristics of optimal IMs such as: efficiency, practicality, proficiency and sufficiency are considered. As prototype buildings, RC high-rise buildings with core wall structural system and with characteristic heights: 20-storey, 30-storey and 40-storey, are selected. The non-linear 3D models of the prototype buildings are constructed. 720 non-linear time-history analyses are conducted for 60 ground motion records with a wide range of magnitudes, distances to source and various soil types. Statistical processing of results and detailed regression analysis are performed and appropriate demand models which relate IMs to demand measures (DMs), are obtained. The conducted analysis has shown that the newly proposed IMs can efficiently predict the DMs with minimum dispersion and satisfactory practicality as compared to the other commonly used IMs (e.g., PGA and $S_a(T_1)$). The newly proposed IMs overcome difficulties in calculating of integral along the velocity spectrum and present adequate replacement for IMs which comprise a wider range of frequency velocity spectrum content.

• Computational Structural Engineering
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• v.10 no.4
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• pp.337-347
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• 1997

The dynamic responses of highway bridges are varying depending on the features of either traveling vehicles or bridges. In this study, the probabilistic characteristics of dynamic amplification factors of highway bridges due to traveling heavy vehicles have been examined through analytical simulation processes. The truck with tandem axle and tractor with semitrailer are selected as the representative heavy vehicles, which are modeled with three dimensional 7-DOF and 12-DOF models, respectively. The analytical results have been compared with the experimental results of dynamic loading tests and the validity of the analytical models has been examined. Parametric studies on the means and extreme values of amplification factors have been performed with various traffic conditions such as vehicle types, vehicle weights, surface profiles, number of loading vehicles, loading positions, etc.

• Journal of KIISE:Software and Applications
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• v.33 no.10
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• pp.836-850
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• 2006

Nowadays, due to the rapidly increasing number of package software products, quality test has been emphasized for package software products. When testing software products, one of the most important factors is to select metrics which form the bases for tests. In this paper, the types of package software are represented as characteristic vectors having probabilistic relationships with metrics. The characteristic vectors could be regarded as indicators of software type. To assign the metrics for each software type, the past test metrics are collected and analyzed. Using Bayesian belief network, the dependency relationship network of the characteristic vectors and metrics is constructed. The dependency relationship network is then used to find the proper metrics for the test of new package software products.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.11
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• pp.2421-2428
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• 2002

In this study, the failure probability of the degraded LP turbine blade steel was performed using the Monte Carlo simulation to apply variation of applied stress and strength. For this purpose, applied stress under the service condition of steady state was obtained by theoretical stress analysis and the maximum Von-Mises stress was 219MPa. The fatigue strength under rotating-bending load was evaluated by the staircase method. Furthermore, 3-parameter Weibull distribution was found to be most appropriate among assumed distributions when the probabilistic distributions of tensile and fatigue strength were determined by the proposed analysis. The failure probability with various loading conditions was derived from the strength-stress interference model and the characteristic factor of safety was also estimated.