• Earthquakes and Structures
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• v.11 no.1
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• pp.109-127
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• 2016

This paper examines the contribution of three sources of uncertainties to probabilistic seismic behaviour of wood frame buildings, including ground motions, intensity and seismic mass. This sensitivity analysis is performed using three methods, including the traditional method based on the conditional distributions of ground motions at given intensity measures, a method using the summation of conditional distributions at given ground motion records, and the Monte Carlo simulation. FEMA P-695 ground motions and its scaling methods are used in the analysis. Two archetype buildings are used in the sensitivity analysis, including a two-storey building and a four-storey building. The results of these analyses indicate that using data-fitting techniques to obtain probability distributions may cause some errors. Linear interpolation combined with data-fitting technique may be employed to improve the accuracy of the calculated exceeding probability. The procedures can be used to quantify the risk of wood frame buildings in seismic events and to calibrate seismic design provisions towards design code improvement.

• Computational Structural Engineering
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• v.4 no.4
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• pp.125-133
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• 1991

For the purpose of efficiently calculating the design sensitivity and the reliability for the complicated structures in which the structural responses or limit state functions are given by implicit form, the probabilistic finite element method is introduced to formulate the deterministic design sensitivity analysis method and incorporated with the second moment reliability methods such as MVFOSM, AFOSM and SORM. Also, the probabilistic design sensitivity analysis method needed in the reliability-based design is proposed. As numerical examples, two thin plates are analyzed for the cases of plane stress and plate bending. The initial yielding is defined as failure criterion, and applied loads, yield stress, plate thickness, Young's modulus and Poisson's ratio are treated as random variables. It is found that the response variances and the failure probabilities calculated by the proposed PFEM-based reliability method show good agreement with those by Monte Carlo simulation. The probabilistic design sensitivity evaluates explicitly the contribution of each random variable to probability of failure. Further, the design change can be evaluated without any difficulty, and their effect on reliability can be estimated quickly with high accuracy.

• Journal of the Korean Society of Marine Environment & Safety
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• v.20 no.6
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• pp.685-691
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• 2014

The result of probabilistic maritime risk evaluation is represented by the probability(P=0.0~1.0) These results are shown by an index using Risk Acceptance Criteria(RAC) to base the evaluation generally to know the risk level easily. Current RAC is divided into 3 steps, 5 steps, 7 steps, etc. Despite need to evaluate whether the number of RAC for risk evaluation is reasonable, there is not a related research yet. In this study, It was proposed the evaluation method to determine the optimum index number of RAC using the Sensitivity distribution characteristics and the Sensitivity by the index number of RAC. As application result from the proposed method for probabilistic risk evaluation data obtained from the prior studies, It could be determined the optimum index number of RAC by Sensitivity below 10 times and confirmed that the proposed method is reasonable by this study.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.6 s.177
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• pp.1529-1539
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• 2000

A newly developed optimization method which uses the genetic algorithm combined with the sensitivity analysis is presented in this paper. The genetic algorithm is a probabilistic method, searching the optimum at several points simultaneously, requiring only the values of the object and constraint functions. It has therefore more chances to find global solution and can be applied various problems. Nevertheless, it has such shortcomings that even it approaches the optimum rapidly in the early stage, it slows down afterward and it can't consider the constraints explicitly. It is only because it can't search the local area near the current points. The traditional method, on the other hand, using sensitivity analysis is of great advantage in searching the near optimum. Thus the combination of the two techniques makes use of the individual advantages, that is, the superiority both in global searching by the genetic algorithm and in local searching by the sensitivity analysis. Application of the method to the several test functions verifies that the method suggested is very efficient and powerful to find the global solutions, and that the constraints can be considered properly.

• Smart Structures and Systems
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• v.10 no.2
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• pp.89-110
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• 2012

This study was intended to efficiently perform the probabilistic optimal safety assessment of steel cable-stayed bridges (SCS bridges) using stochastic finite element analysis (SFEA) and expected life-cycle cost (LCC) concept. To that end, advanced probabilistic finite element algorithm (APFEA) which enables to execute the static and dynamic SFEA considering aleatory uncertainties contained in random variable was developed. APFEA is the useful analytical means enabling to conduct the reliability assessment (RA) in a systematic way by considering the result of SFEA based on linearity and nonlinearity of before or after introducing initial tensile force. The appropriateness of APFEA was verified in such a way of comparing the result of SFEA and that of Monte Carlo Simulation (MCS). The probabilistic method was set taking into account of analytical parameters. The dynamic response characteristic by probabilistic method was evaluated using ASFEA, and RA was carried out using analysis results, thereby quantitatively calculating the probabilistic safety. The optimal design was determined based on the expected LCC according to the results of SFEA and RA of alternative designs. Moreover, given the potential epistemic uncertainty contained in safety index, failure probability and minimum LCC, the sensitivity analysis was conducted and as a result, a critical distribution phase was illustrated using a cumulative-percentile.

• Journal of Mechanical Science and Technology
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• v.19 no.spc1
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• pp.350-356
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• 2005

A method of dynamic analysis of mechanical systems considering probabilistic properties is proposed in this paper. Probabilistic properties that result from manufacturing tolerances can be represented by means and standard deviations (or variances). The probabilistic characteristics of dynamic responses of constrained multi-body systems are obtained by two ways : the proposed analytical approach and the Monte Carlo simulation. The formerpaper, necessitates sensitivity information to calculate the standard deviations. In this a direct differentiation method is employed to find the sensitivities of constrained multi-body systems. To verify the accuracy of the proposed method, numerical examples are solved and the results obtained by using the proposed method are compared to those obtained by Monte Carlo simulation.

• Structural Engineering and Mechanics
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• v.11 no.4
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• pp.373-392
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• 2001

The main idea behind the paper is to present two alternative methods of homogenization of the heat conduction problem in composite materials, where the heat conductivity coefficients are assumed to be random variables. These two methods are the Monte-Carlo simulation (MCS) technique and the second order perturbation second probabilistic moment method, with its computational implementation known as the Stochastic Finite Element Method (SFEM). From the mathematical point of view, the deterministic homogenization method, being extended to probabilistic spaces, is based on the effective modules approach. Numerical results obtained in the paper allow to compare MCS against the SFEM and, on the other hand, to verify the sensitivity of effective heat conductivity probabilistic moments to the reinforcement ratio. These computational studies are provided in the range of up to fourth order probabilistic moments of effective conductivity coefficient and compared with probabilistic characteristics of the Voigt-Reuss bounds.

• Journal of the Korea institute for structural maintenance and inspection
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• v.11 no.1
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• pp.141-152
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• 2007

Considering uncertainties of random input data, it is more reasonable to use probabilistic method than the conventional deterministic method for the design of structures or for the assessment of the responses of structures, which are designed as safe even under extreme loads. Therefore, to assess the quantitative effects of the constructed cable stayed bridge by the input random variables, a sensitivity analysis is studied. Using perturbation method, an analysis program is developed for the iterative probabilistic finite element analyses and sensitivity analyses of the cable stayed bridge, except the initial shape analysis. Monte-Carlo Simulations were used for the verification of the developed program. The results of sensitivity analysis shows the governing effects of external loads. Because the results also provide the sensitive effects of the stiffness of members and the magnitudes of prestressing force of cables, the developed

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.3
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• pp.334-342
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• 2012

Data association is important technology which designate final destination in the target tracking. The joint probabilistic data association(JPDA) algorithm provides excellent ability to maintain track on multiple targets. Currently, it is not easily implemented in real time because of track coalescence & switch. The aim of this paper is to develop probabilistic filters that increase JPDA's sensitivity and decrease track coalescence & switch in a cluttered environments.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.8 s.239
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• pp.1102-1108
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• 2005

The integrity of nuclear piping systems has to be maintained sufficiently all the times during operation. In order to maintain the integrity, reliable assessment procedures including fracture mechanics analysis, etc, are required. Up to now, the integrity assessment has been performed using conventional deterministic approach even though there are lots of uncertainties to hinder a rational evaluation. In this respect, probabilistic approach is considered as an appropriate method for piping system evaluation. The objectives of this paper are to develop a probabilistic assessment program using reliability index and simulation technique and to estimate the damage probability of wall-thinned pipes in secondary systems. The probabilistic assessment program consists of three evaluation modules which are first order reliability method, second order reliability method and Monte Carlo simulation method. The developed program has been applied to evaluate damage probabilities of wall-thinned pipes subjected to internal pressure, global bending moment and combined loading. The sensitivity analysis results as well as prototypal evaluation results showed a promising applicability of the probabilistic integrity assessment program.