Sensitivity and Reliability Analysis of Engineering Structures: Sampling Based Methods

2014 ◽  
pp. 85-112
Author(s):  
M. Oberguggenberger
Keyword(s):  
Reliability Analysis ◽  
Engineering Structures

Recent advances in reliability analysis of aeroengine rotor system: a review

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Xue-Qin Li ◽  
Lu-Kai Song ◽  
Guang-Chen Bai
Keyword(s):  
Reliability Analysis ◽  
Surrogate Model ◽  
Engineering Application ◽  
Rotor System ◽  
Engineering Structures ◽  
Content Type ◽  
Reliability Design ◽  
Rotor Systems ◽  
Practical Engineering ◽  
Complex Engineering

PurposeTo provide valuable information for scholars to grasp the current situations, hotspots and future development trends of reliability analysis area.Design/methodology/approachIn this paper, recent researches on efficient reliability analysis and applications in complex engineering structures like aeroengine rotor systems are reviewd.FindingsThe recent reliability analysis advances of engineering application in aeroengine rotor system are highlighted, it is worth pointing out that the surrogate model methods hold great efficiency and accuracy advantages in the complex reliability analysis of aeroengine rotor system, since its strong computing power can effectively reduce the analysis time consumption and accelerate the development procedures of aeroengine. Moreover, considering the multi-objective, multi-disciplinary, high-dimensionality and time-varying problems are the common problems in various complex engineering fields, the surrogate model methods and its developed methods also have broad application prospects in the future.Originality/valueFor the strong demand for efficient reliability design technique, this review paper may help to highlights the benefits of reliability analysis methods not only in academia but also in practical engineering application like aeroengine rotor system.

An efficient particle swarm optimization-joint probability distribution optimization method for structural reliability analysis

2020 ◽  
pp. 095440622094155
Author(s):  
Hossein Mansourinejad ◽  
Kamran Daneshjou
Keyword(s):  
Particle Swarm Optimization ◽  
Reliability Analysis ◽  
Structural Reliability ◽  
Particle Swarm ◽  
Joint Probability ◽  
Joint Probability Distribution ◽  
Engineering Structures ◽  
Swarm Optimization ◽  
Highly Nonlinear ◽  
Conventional Methods

The performance function of many engineering structures and mechanisms is usually complex, highly nonlinear, and described in the implicit form. The reliability analysis of these structures using common methods requires high cost and time. In this paper, a new approach for reliability analysis of engineering structures and mechanisms by using the particle swarm optimization algorithm is presented. The advantages of this method in comparison with the conventional methods are its simplicity and accuracy. In addition, the limitations of the common previously presented methods are eliminated by the proposed method. This approach is based on a new redefinition of most probable point in the reliability analysis. To evaluate the performance and validity of the proposed method, some examples in the reliability analysis of various functions are employed. Finally, the superiority of the proposed method in performance and accuracy is demonstrated and compared to the conventional methods and it can be used for reliability analysis of complicated engineering structures.

A Novel Time-Variant Reliability Analysis Method Based on Failure Processes Decomposition for Dynamic Uncertain Structures

2018 ◽  
Vol 140 (5) ◽  
Author(s):  
Shui Yu ◽  
Zhonglai Wang
Keyword(s):  
Reliability Analysis ◽  
System Reliability ◽  
Dynamic Properties ◽  
Limit State ◽  
Quadratic Function ◽  
State Function ◽  
Analysis Method ◽  
Engineering Structures ◽  
Reliability Problem ◽  
Time Invariant

Abstract Due to the uncertainties and the dynamic parameters from design, manufacturing, and working conditions, many engineering structures usually show uncertain and dynamic properties. This paper proposes a novel time-variant reliability analysis method using failure processes decomposition to transform the time-variant reliability problems to the time-invariant problems for dynamic structures under uncertainties. The transformation is achieved via a two-stage failure processes decomposition. First, the limit state function with high dimensional input variables and high order temporal parameters is transformed to a quadratic function of time based on the optimized time point in the first-stage failure processes decomposition. Second, based on the characteristics of the quadratic function and reliability criterion, the time-variant reliability problem is then transformed to a time-invariant system reliability problem in the second-stage failure processes decomposition. Then, the kernel density estimation (KDE) method is finally employed for the system reliability evaluation. Several examples are used to verify the effectiveness of the proposed method to demonstrate its efficiency and accuracy.

Asymptotic distribution method for structural reliability analysis in high dimensions

2005 ◽  
Vol 461 (2062) ◽  
pp. 3141-3158 ◽  
Author(s):  
Sondipon Adhikari
Keyword(s):  
Reliability Analysis ◽  
Asymptotic Distribution ◽  
Structural Reliability ◽  
Random Variables ◽  
Computational Time ◽  
High Dimensions ◽  
Engineering Structures ◽  
Distribution Method ◽  
Complex Engineering ◽  
Asymptotic Formulation

In the reliability analysis of safety critical complex engineering structures, a very large number of the system parameters can be considered as random variables. The difficulty in computing the failure probability using the classical first- and second-order reliability methods (FORM and SORM) increases rapidly with the number of variables or ‘dimension’. There are mainly two reasons behind this. The first is the increase in computational time with the increase in the number of random variables. In principle, this problem can be handled with superior computational tools. The second reason, which is perhaps more fundamental, is that there are some conceptual difficulties typically associated with high dimensions. This means that even when one manages to carry out the necessary computations, the application of existing FORM and SORM may still lead to incorrect results in high dimensions. This paper is aimed at addressing this issue. Based on the asymptotic distribution of quadratic form in Gaussian random variables, two formulations for the case when the number of random variables n →∞ is provided. The first is called ‘strict asymptotic formulation’ and the second is called ‘weak asymptotic formulation’. Both approximations result in simple closed-form expressions for the probability of failure of an engineering structure. The proposed asymptotic approximations are compared with existing approximations and Monte Carlo simulations using numerical examples.

scholarly journals Reliability Analysis of High Rise Building Considering Wind Load Uncertainty

2018 ◽  
Vol 4 (3) ◽  
pp. 469
Author(s):  
Yi Zhang ◽  
Keqin Yan ◽  
Tao Cheng
Keyword(s):  
Reliability Analysis ◽  
Wind Load ◽  
Engineering Structures ◽  
Safety Measures ◽  
High Rise ◽  
High Rise Building ◽  
Different Types ◽  
Reliability Methods ◽  
Wind Load Uncertainty ◽  
Distribution Type

In engineering structures, the safety problems are always depending on the respond of structures to different types of load. The safety assessment of a high rise building is highly depending on the analysis of environmental load. Many codes and practices have proposed many requirements for engineers in the design works. These include safety factors, limitations on damage, maximum deflections and so on. When violations in these requirements occur, the structure is believed to be dangerous. But once the problem becomes complicated such as multiple unknown loads in one building, it requires reliability analysis in the design. It must take care of all the assumptions and uncertainties in the structural design. In probabilistic assessment, any input variable is considered as an uncertainty. However, the traditional way to deal with these problems may have problems when uncertainties are large. Many probabilistic safety measures need to be reconsidered in engineering work. This paper, we will provide reliability analysis on a high rise building with consideration of wind load. All the most commonly applied reliability methods are been utilized in this analysis and compared base on the performance. The statistical influences including correlation and distribution type are also discussed in the same reliability problem.

Artificial Bee Colony Algorithm for Reliability Analysis of Engineering Structures

2010 ◽  
Vol 163-167 ◽  
pp. 3103-3109 ◽  
Author(s):  
Hao Jin Li ◽  
Jun Jie Li ◽  
Fei Kang
Keyword(s):  
Reliability Analysis ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Limit State ◽  
Optimization Method ◽  
Iteration Scheme ◽  
State Function ◽  
Engineering Structures ◽  
Bee Colony ◽  
Structure Reliability

Artificial bee colony algorithm is a noval optimization method which is inspired by bee colony foraging behavior. Its use in the structure reliability field presents not only the advantage of its facility of implementation, but also the capability to obtain the design point and the failure probability with good accuracy. And by this method, the reliability index of nonlinear and complex limit state function which iteration scheme may fail to converge could be obtained with efficiency. It is demonstrated by four examples that the present method is reliable and accurate in reliability analysis of engineering structures.

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