• Steel and Composite Structures
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• 제42권1호
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• pp.59-74
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• 2022

This study introduces a general reliability-based, performance-based design framework to design frames regarding their uncertainties and user-defined design goals. The Iterative-R method extracted from the main framework can designate a proper R (i.e., response modification factor) satisfying the design goal regarding target reliability index and pre-defined probability of collapse. The proposed methodology is based on FEMA P-695 and can be used for all systems that FEMA P-695 applies. To exemplify the method, multiple three-dimensional, four-story steel special moment-resisting frames are considered. Closed-form relationships are fitted between frames' responses and the modeling parameters. Those fits are used to construct limit state functions to apply reliability analysis methods for design safety assessment and the selection of proper R. The frameworks' unique feature is to consider arbitrarily defined probability density functions of frames' modeling parameters with an insignificant analysis burden. This characteristic enables the alteration in those parameters' distributions to meet the design goal. Furthermore, with sensitivity analysis, the most impactful parameters are identifiable for possible improvements to meet the design goal. In the studied examples, it is revealed that a proper R for frames with different levels of uncertainties could be significantly different from suggested values in design codes, alarming the importance of considering the stochastic behavior of elements' nonlinear behavior.

• Structural Engineering and Mechanics
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• 제62권2호
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• pp.125-138
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• 2017

Reliability-based design optimization (RBDO) is a powerful tool for design optimization when considering probabilistic characteristics of design variables. However, it is often computationally intensive because of the coupling of reliability analysis and cost minimization. In this study, the concept of reliability mapping function is defined based on the relationship between the reliability index obtained by using the mean value first order reliability method and the failure probability obtained by using an improved response surface method. Double-loop involved in the classical RBDO can be converted into single-loop by using the reliability mapping function. Since the computational effort of the mean value first order reliability method is minimal, RBDO by using reliability mapping functions should be highly efficient. Engineering examples are given to demonstrate the efficiency and accuracy of the proposed method. Numerical results indicated that the proposed method has the similar accuracy as Monte Carlo simulation, and it can obviously reduce the computational effort.

• Advances in aircraft and spacecraft science
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• 제4권4호
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• pp.467-486
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• 2017

A method for decoupling reliability based design optimization problem into a set of deterministic optimization and performing a reliability analysis is described. The inner reliability analysis and the outer optimization are performed separately in a sequential manner. Since the outer optimizer must perform a large number of iterations to find the optimized shape and size of structure, the computational cost is very high. Therefore, during the course of this research, new multilevel reliability optimization methods are developed that divide the design domain into two sub-spaces to be employed in an iterative procedure: one of the shape design variables, and the other of the size design variables. In each iteration, the probability constraints are converted into equivalent deterministic constraints using reliability analysis and then implemented in the deterministic optimization problem. The framework is first tested on a short column with cross-sectional properties as design variables, the applied loads and the yield stress as random variables. In addition, two cases of curvilinearly stiffened panels subjected to uniform shear and compression in-plane loads, and two cases of curvilinearly stiffened panels subjected to shear and compression loads that vary in linear and quadratic manner are presented.

• Geomechanics and Engineering
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• 제34권6호
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• pp.597-609
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• 2023

One of the applicable methods for the stabilization of soil walls is the nailing system which consists of tensile struts. The stability and safety of soil nail wall systems are influenced by the geometrical parameters of the nailing system. Generally, the determination of nailing parameters in order to achieve optimal performance of the nailing system for the safety of soil walls is defined in the framework of optimization problems. Also, according to the various uncertainty in the mechanical parameters of soil structures, it is necessary to evaluate the reliability of the system as a probabilistic problem. In this paper, the optimal design of the nailing system is carried out in deterministic and probabilistic cases using meta-heuristic and reliability-based design optimization methods. The colliding body optimization algorithm and first-order reliability method are used for optimization and reliability analysis problems, respectively. The objective function is defined based on the total cost of nails and safety factors and reliability index are selected as constraints. The mechanical properties of the nailing system are selected as design variables and the mechanical properties of the soil are selected as random variables. The results show that the reliability of the optimally designed soil nail system is very sensitive to uncertainty in soil mechanical parameters. Also, the design results are affected by uncertainties in soil mechanical parameters due to the values of safety factors. Reliability-based design optimization results show that a nailing system can be designed for the expected level of reliability and failure probability.

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2005년도 춘계 학술대회논문집
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• pp.187-190
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• 2005

In this study, the reliablility based design optimization is peformed for an aircraft wing. The flexiblility of the wing was assumed by considering the interaction modeled by static aeroelasticity between aerodynamic forces and the structure. For a multidisciplinary design optimization the results of aerodynamic analysis and structural analysis were included in the optimization formulation. The First Order Reliability Method(FORM) was employed to consider the uncertainty of the designed points.

• Geomechanics and Engineering
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• 제15권3호
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• pp.879-888
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• 2018

Probability-based design codes have been developed to sufficiently confirm the safety level of structures. One of the most acceptable probability-based approaches is Load Resistance Factor Design (LRFD), which measures the safety level of the structures in terms of the reliability index. The main contribution of this paper is to calibrate the load and resistance factors of the design code for tunnels. The load and resistance factors are calculated using the available statistical models and probability-based procedures. The major steps include selection of representative structures, consideration of the limit state functions, calculation of reliability for the selected structures, selection of the target reliability index and calculation of load factors and resistance factors. The load and resistance models are reviewed. Statistical models of resistance (load carrying capacity) are summarized for strength limit state in bending, shear and compression. The reliability indices are calculated for several segments of a selected circular tunnel designed according to the tunnel manual report (Tunnel Manual). The novelty of this paper is the selection of the target reliability. In doing so, the uniform spectrum of reliability indices is proposed based on the probability paper. The final recommendation is proposed based on the closeness to the target reliability index.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2005년도 학술발표회(1)
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• pp.295-296
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• 2005

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 1990년도 가을 학술발표회 논문집
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• pp.35-40
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• 1990

Because of the inherent random nature of most manmade and environmental loadings and materials as well as the emperfect structural analysis, the reliability-based structural design has been recognized as a rational approach and the probability-based design criteria has been successfully developed for many standards. In order to do this it is necessary to establish target reliability levels, for which the reliability levels inherent in present design practice will be used as a rational guide. In this study the reliability levels implied in current practices, therefore, are investigated using the load and resistance models developed for domestic uses.

• 대한토목학회논문집
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• 제39권1호
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• pp.13-24
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• 2019

이 연구에서는 국내 도로교 한계상태설계법에서 콘크리트부재의 설계를 위하여 적용하고 있는 재료계수의 문제점을 제기하고, 잘 정립된 최적화 과정에 의한 재료계수를 제안하였다. 신뢰도분석을 통하여 현 설계기준의 하중계수와 제안 재료계수가 목표신뢰도지수 보다 높은 신뢰도수준을 확보하고 있음을 보이고, 역신뢰도해석을 통하여 목표신뢰도지수를 잘 근사할 수 있는 하중계수를 제시하였다. 유로코드에서 제시하고 있는 기본 개념에 근거하여 신뢰도기반 하중-재료계수 결정법을 정식화하였다. 제안된 접근법이 신뢰도개념에 의하여 유도되었지만, 이 접근법에 의하여 계산된 하중-재료 계수가 목표신뢰도지수를 정확히 만족시키지 못하는 요인으로서 재료와 부재간에 존재하는 불확실성의 차이를 지적하고, 이러한 차이를 고려하지 않는 유로코드의 개념적 문제점을 제기하였다.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1991년도 가을 학술발표회 논문집
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• pp.57-62
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• 1991

For the purpose of developing the method for efficiently calculating the design sensitivity and the reliability for the complicated structure such as ship structure, 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 needed in the reliability-based design is performed. The reliability analysis is carried out for the initial yielding failure, in which the derivative derived in the deterministic desin sensitivity is used. The present PFEM-based reliability method shows good agreement with Monte Carlo method in terms with the variance of response and the associated probability of failure even at the first or first few iteration steps. The probabilistic design sensitivity analysis evaluates explicitly the contribution of each random variable to probability of failure. Further, the reliability index variation can be easily predicted by the variation of the mean and the variance of the random variables.