• Structural Engineering and Mechanics
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• 제37권5호
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• pp.543-560
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• 2011

In structural engineering there are randomness inherently exist on determination of the loads, strength, geometry, and so on, and the manufacturing of the structural members, workmanship etc. Thus, objective and constraint functions of the optimization problem are functions that depend on those randomly natured components. The constraints being the function of the random variables are evaluated by using reliability index or performance measure approaches in the optimization process. In this study, the minimum weight of a space truss is obtained under the uncertainties on the load, material and cross-section areas with harmony search using reliability index and performance measure approaches. Consequently, optimization algorithm produces the same result when both the approaches converge. Performance measure approach, however, is more efficient compare to reliability index approach in terms of the convergence rate and iterations needed.

• 대한기계학회논문집A
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• 제30권8호
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• pp.889-896
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• 2006

The concept of reliability has been applied to the topology optimization based on a reliability index approach or a performance measure approach. Since these approaches, called double-loop single vector approach, require the nested optimization problem to obtain the most probable point in the probabilistic design domain, the time for the entire process makes the practical use infeasible. In this work, new reliability-based topology optimization method is proposed by utilizing single-loop single-vector approach, which approximates searching the most probable point analytically, to reduce the time cost. The results of design examples show that the proposed method provides efficiency curtailing the time for the optimization process and accuracy satisfying the specified reliability.

• 한국생산제조학회지
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• 제19권4호
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• pp.469-475
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• 2010

The objective of this study is to integrate reliability analysis into shape optimization problem using the evolutionary structural optimization (ESO) in the application example. Reliability-based shape optimization is formulated as volume minimization problem with probabilistic stress constraint under minimization max. von Mises stress and allow stress. Young's modulus, external load and thickness are considered as uncertain variables. In order to compute reliability index, four methods, i.e., reliability index approach (RIA), performance measure approach (PMA), single-loop singlevector (SLSV) and adaptive-loop (ADL), are used. Reliability-based shape optimization design process is conducted to obtain optimal shape satisfying max. von Mises stress and reliability index constraints with the above four methods, and then each result is compared with respect to numerical stability and computing time.

• Journal of Electrical Engineering and Technology
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• 제9권4호
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• pp.1248-1257
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• 2014

Overhead transmission lines are crucial components in power transmission systems. Well-designed maintenance strategy for overhead lines is required for power utilities to minimize operating costs, while improving the reliability of the power system. This paper presents a maintenance priority index (MPI) of overhead lines for a reliability centered approach. Proposed maintenance strategy is composed of a state index and importance indices, taking into account a transmission condition and importance in system reliability, respectively. The state index is used to determine the condition of overhead lines. On the other hand, the proposed importance indices indicate their criticality analysis in transmission system, by using a load effect index (LEI) and failure effect index (FEI). The proposed maintenance method using the MPI has been tested on an IEEE 9-bus system, and a numerical result demonstrates that our strategy is more cost effective than traditional maintenance strategies.

• 한국생산제조학회지
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• 제19권4호
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• pp.529-538
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• 2010

This paper presents a reliability-based topology optimization (RBTO) based on bidirectional evolutionary structural optimization (BESO). In design of a structure, uncertain conditions such as material property, operational load and dimensional variation should be considered. Deterministic topology optimization (DTO) is performed without considering the uncertainties related to the design variables. However, the RBTO can consider the uncertainty variables because it can deal with the probabilistic constraints. The reliability index approach (RIA) and the performance measure approach (PMA) are adopted to evaluate the probabilistic constraints in this study. In order to apply the BESO to the RBTO, sensitivity number for each element is defined as the change in the reliability index of the structure due to removal of each element. Smoothing scheme is also used to eliminate checkerboard patterns in topology optimization. The limit state indicates the margin of safety between the resistance (constraints) and the load of structures. The limit State function expresses to evaluate reliability index from finite element analysis. Numerical examples are presented to compare each optimal topology obtained from RBTO and DTO each other. It is verified that the RBTO based on BESO can be effectively performed from the results.

• 한국공작기계학회논문집
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• 제17권6호
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• pp.77-82
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• 2008

This paper presents a Reliability-Based Topology Optimization(RBTO) using the Evolutionary Structural Optimization(ESO). An actual design involves some uncertain conditions such as material property, operational load and dimensional variation. The Deterministic Topology Optimization(DTO) is obtained without considering the uncertainties related to the uncertainty parameters. However, the RBTO can consider the uncertainty variables because it has the probabilistic constraints. In order to determine whether the probabilistic constraints are satisfied or not, simulation techniques and approximation methods are developed. In this paper, the reliability index approach(RIA) is adopted to evaluate the probabilistic constraints. In order to apply the ESO method to the RBTO, sensitivity number is defined as the change in the reliability index due to the removal of the ith element. Numerical examples are presented to compare the DTO with the RBTO.

• Geomechanics and Engineering
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• 제12권2호
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• pp.313-326
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• 2017

Based on the reliability theory and limit analysis method, the roof stability of a shallow tunnel is investigated under the condition of surface settlement. Nonlinear Hoek-Brown failure criterion is adopted in the present analysis. With the consideration of surface settlement, the internal energy and external work are calculated. Equating the rate of energy dissipation to the external rate of work, the expression of support pressure is derived. With the help of variational approach, a performance function is proposed to reliability analysis. Improved response surface method is used to calculate the Hasofer-Lind reliability index and the failure probability. In order to assess the validity of the present results, Monte-Carlo simulation is performed to examine the correctness. Sensitivity analysis is used to estimate the influence of different variables on reliability index. Among random variables, the unit weight significantly affects the reliability index. It is found that the greater coefficient of variation of variables lead to the higher failure probability. On the basis of the discussions, the reliability-based design is achieved to calculate the required tunnel support pressure under different situations when the target reliability index is obtained.

• Structural Engineering and Mechanics
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• 제62권3호
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• pp.365-372
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• 2017

Reliability analysis is a probabilistic approach to determine a safety level of a system. Reliability is defined as a probability of a system (or a structure, in structural engineering) to functionally perform under given conditions. In the 1960s, Basler defined the reliability index as a measure to elucidate the safety level of the system, which until today is a commonly used parameter. However, the reliability index has been formulated based on the pivotal assumption which assumed that the considered limit state function is normally distributed. Nevertheless, it is not guaranteed that the limit state function of systems follow as normal distributions; therefore, there is a need to define a new reliability index for no-normal distributions. The main contribution of this paper is to define a sophisticated reliability index for limit state functions which their distributions are non-normal. To do so, the new definition of reliability index is introduced for non-normal limit state functions according to the probability functions which are calculated based on the convolution theory. Eventually, as the state of the art, this paper introduces a simplified method to calculate the reliability index for non-normal distributions. The simplified method is developed to generate non-normal limit state in terms of normal distributions using series of Gaussian functions.

• Journal of Mechanical Science and Technology
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• 제17권4호
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• pp.492-500
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• 2003

By means of the transformation from the problem of fuzzy reliability to the problem of general reliability, a model for analyzing fuzzy reliability is introduced in this paper Because of the complexity of the Problem of the fuzzy reliability, generally speaking, the analytical equations for calculating fuzzy reliability indexes of machine part cannot be obtained in most cases. Therefore, in this paper, an approach is given wherein progressions are employed to calculate them, or a simulation approach is used to estimate them by expressing general reliability indexes as progressions. By utilizing the approach put forwards in the paper, the calculating quantity for analyzing the fuzzy reliability will be reduced : even substantially reduced sometimes. Some examples are taken to explain the feasibility of the model and a simulation approach.

• Journal of Magnetics
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• 제17권1호
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• pp.46-50
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• 2012

A reliability-based optimization method for electromagnetic design is presented to take uncertainties of design parameters into account. The method can provide an optimal design satisfying a specified confidence level in the presence of uncertain parameters. To achieve the goal, the reliability index approach based on the firstorder reliability method is adopted to deal with probabilistic constraint functions and a double-loop optimization algorithm is implemented to obtain an optimum. The proposed method is applied to the TEAM Workshop Problem 22 and its accuracy and efficiency is verified with reference of Monte Carlo simulation results.