Element Reliability Analysis Research Articles

АНАЛИЗ НАДЕЖНОСТИ ЭЛЕМЕНТОВ СООРУЖЕНИЙ НА ОСНОВЕ P-БЛОКОВ

The article describes a method for reliability (probability of non-failure) analysis of structural elements based on p-boxes. An algorithm for constructing two p-blocks is shown. First p-box is used in the absence of information about the probability distribution shape of a random variable. Second p-box is used for a certain probability distribution function but with inaccurate (interval) function parameters. The algorithm for reliability analysis is presented on a numerical example of the reliability analysis for a flexural wooden beam by wood strength criterion. The result of the reliability analysis is an interval of the non-failure probability boundaries. Recommendations are given for narrowing the reliability boundaries which can reduce epistemic uncertainty. On the basis of the proposed approach, particular methods for reliability analysis for any structural elements can be developed. Design equations are given for a comprehensive assessment of the structural element reliability as a system taking into account all the criteria of limit states.

Characterizations of Distributions Through Aging Intensity

In this paper, we characterize univariate positive absolutely continuous random variable through the aging intensity function. Using this function, we propose the characterizations of Weibull- and inverse-Weibull-related distributions. They are alternatives to the basic two-parameter Weibull distribution to be used in reliability analysis of elements and systems. We find that for presented distributions, it is easier to characterize them through their aging intensity function than through their failure rate function. Further on, some other than Weibull family life distributions are presented. However, in their case, characterization through the failure rate seems to be easier. Moreover, aging intensity orders are studied for the considered Weibull distributions. They allow us to decide that one random variable has the better aging property than another one. To show the practical usefulness of the aging intensity, the analysis of this function through some data is performed.

Characterizations of Discrete Weibull related distributions

In this paper discrete aging intensity and discrete alternative aging intensity functions are introduced. Further, using these functions we characterize some Discrete Weibull related distributions. Although, these discrete distributions have their continuous equivalents, quite often they seem to be more convenient in reliability analysis of elements and systems.Finally, for the considered class of Modified Discrete Weibull distributions a discrete aging intensity order is studied. This order allows us to decide that one random variable has the better aging property than the other one.

Reliability Optimization Design of Composite Transmission Shaft

In order to solve reliability-based optimization design of composite transmission shaft, the parametric finite element model of composite transmission shaft was built by secondary development of ABAQUS. The reliability analysis of composite transmission shaft was carried out with the first order reliability method (FORM). Using python language, the finite element program and reliability analysis program are combined. The reliability-based optimization model of composite transmission shaft was obtained. The feasibility and effectiveness of the optimization model was verified by the results of an example application.

Reliability analysis of plate elements under uniaxial compression using an adaptive response surface approach

This paper presents a reliability analysis of plate elements under uniaxial compression using an adaptive response surface approach. The limit state considered is the buckling collapse failure of the plate elements computed through nonlinear finite element analysis. A response surface model based on second-order polynomials is combined with the first-order reliability method in order to compute reliability estimates at moderate computational time. An adaptive interpolation scheme combined with a Latin hypercube sampling technique is used to define the response surface model iteratively in the region of the basic random variables space that most contributes to the failure probability. Plate elements typical of the deck structure of double hull tankers with random thickness, material properties and amplitude of weld-induced initial distortions are used as case study. The uniaxial compressive load is defined considering extreme values in a reference time period of one year of operation of the ship. The effect of considering constrained or restrained boundary conditions along the longitudinal plate edges as well as corroded plate elements on the reliability analysis results is determined. Sensitivity analyses are performed to identify the relative contribution and importance of each basic random variable to the estimated reliability indices.

TASK ALLOCATION MODEL FOR RELIABILITY AND COST OPTIMIZATION IN DISTRIBUTED COMPUTING SYSTEM

A Distributed Computing System (DCS) is defined as a set of processing elements interconnected by communication links. Reliability analysis of these processing elements and communication links is one of the important parameters to achieve the system efficiency. The system efficiency can be improved by making the task allocation properly in DCS. In this paper, we have presented a mathematical model, considering DCS with heterogeneous processors in order to achieve optimal cost and optimal reliability by allocating the tasks to the processors, in such a way that the allocated load on each processor is balanced. The task allocation in DCS is known as NP-hard problem even in the best conditions, and based on the present model, an efficient algorithm have been proposed to obtain optimal solutions. To design the mathematical model, execution time of the tasks on each processor as well as communication time between the tasks has been taken in the form of matrices.

A study on safety assessment of cable-stayed bridges based on stochastic finite element analysis and reliability analysis

It is more reasonable to evaluate the effect of uncertainty included in actual structures using the reliability assessment method. However, using the reliability assessment method to evaluate complicated structures, such as cable-stayed bridges whose limit state function is given as a nonlinear function, was very difficult. Therefore, in this study the structural response characteristics are investigated quantitatively using Stochastic Finite Element Analysis (SFEA) according to the external uncertainty of random variables included in cable-stayed bridges, and Reliability Analysis (RA) considering external uncertainty is performed more efficiently using the result of SFEA. For this approach, after performing the initial shape analysis of the cable-stayed bridge, improved Stochastic Finite Element Method Program (SFEMP) is developed for executing nonlinear SFEA by considering correlation of random variables. The feasibility of the developed program was investigated by comparing the analysis results of beam-cable structures with those of the verified program using Direct Monte Carlo Simulation (DMCS). The effect of each random variable on the structural response was examined by performing sensitivity analysis. The safety index and failure probability according to the correlation was investigated by applying RA that considered the correlation of the major random variables. The critical percentile distribution of the RA result is re-evaluated quantitatively considering the effect of the internal uncertainty.

Determination of point of maximum likelihood in failure domain using genetic algorithms

The point of maximum likelihood in a failure domain yields the highest value of the probability density function in the failure domain. The maximum-likelihood point thus represents the worst combination of random variables that contribute in the failure event. In this work Genetic Algorithms (GAs) with an adaptive penalty scheme have been proposed as a tool for the determination of the maximum likelihood point. The utilization of only numerical values in the GAs operation makes the algorithms applicable to cases of non-linear and implicit single and multiple limit state function(s). The algorithmic simplicity readily extends its application to higher dimensional problems. When combined with Monte Carlo Simulation, the proposed methodology will reduce the computational complexity and at the same time will enhance the possibility in rare-event analysis under limited computational resources. Since, there is no approximation done in the procedure, the solution obtained is considered accurate. Consequently, GAs can be used as a tool for increasing the computational efficiency in the element and system reliability analyses.