scholarly journals Simple novel algorithm for a special diophantine system appeared in the system reliability problem

2015 ◽  
Author(s):  
Majid Forghani-elahabad ◽  
Luiz Henrique Bonani
Keyword(s):  
System Reliability ◽  
Reliability Problem ◽  
Diophantine System ◽  
Novel Algorithm

Fatigue Reliability and Inspection of TLP Tendon System

1991 ◽  
Vol 28 (02) ◽  
pp. 99-110
Author(s):  
Maria Celia C. Ximenes
Keyword(s):  
Order Statistics ◽  
System Reliability ◽  
Fatigue Reliability ◽  
Tension Leg Platform ◽  
Reliability Problem ◽  
Failure Path ◽  
Solution Methods

The collapse of a tension leg platform (TLP) tendon system due to progressive fatigue of several joints is investigated. Two solution methods for the system reliability problem are proposed. The first method is based on the failure path approach and the second on the order statistics approach. The effects of redundancy and uncertainties involved in the problem are analyzed. Inspection of selected joints is also included in order to evaluate its impact on system reliability.

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.

A Time-Variant Reliability Analysis Method Based on Stochastic Process Discretization

2014 ◽  
Vol 136 (9) ◽  
Author(s):  
C. Jiang ◽  
X. P. Huang ◽  
X. Han ◽  
D. Q. Zhang
Keyword(s):  
Stochastic Process ◽  
Reliability Analysis ◽  
System Reliability ◽  
Limit State ◽  
Complex Structure ◽  
Random Variable ◽  
State Function ◽  
Analysis Method ◽  
Reliability Problem ◽  
Reliability Method

Time-variant reliability problems caused by deterioration in material properties, dynamic load uncertainty, and other causes are widespread among practical engineering applications. This study proposes a novel time-variant reliability analysis method based on stochastic process discretization (TRPD), which provides an effective analytical tool for assessing design reliability over the whole lifecycle of a complex structure. Using time discretization, a stochastic process can be converted into random variables, thereby transforming a time-variant reliability problem into a conventional time-invariant system reliability problem. By linearizing the limit-state function with the first-order reliability method (FORM) and furthermore, introducing a new random variable, the converted system reliability problem can be efficiently solved. The TRPD avoids the calculation of outcrossing rates, which simplifies the process of solving time-variant reliability problems and produces high computational efficiency. Finally, three numerical examples are used to verify the effectiveness of this approach.

The negative log-gamma prior distribution for Bayesian assessment of system reliability

2017 ◽  
Vol 232 (3) ◽  
pp. 308-319 ◽  
Author(s):  
Roger Zoh ◽  
Alyson Wilson ◽  
Scott Vander Wiel ◽  
Earl Lawrence
Keyword(s):  
Data Collection ◽  
Gamma Distribution ◽  
System Reliability ◽  
Prior Distribution ◽  
Scale Parameter ◽  
Time Varying ◽  
Prior Distributions ◽  
Reliability Problem ◽  
Series Systems

This paper presents the negative log-gamma distribution as a prior distribution useful for Bayesian assessment of system reliability. When the scale parameter is held fixed, the negative log-gamma distribution is closed under products, making it convenient for specifying priors for series systems. In particular, for series systems, negative log-gamma component priors can be specified to give an exact desired system prior and vice versa. We consider pass/fail data at the system and component levels for both static and time-varying data collection schemes and propose two new prior distributions for analyzing time-varying reliability. Finally, we consider an application of the negative log-gamma to a missile reliability problem and illustrate diagnostics useful for developing the priors.

scholarly journals Overview of mathematical methods for power system reliability evaluation

2020 ◽  
Vol 2 (SI2) ◽  
pp. First
Author(s):  
Đạt Tiến Huỳnh ◽  
Diễm Ngọc Phúc Nguyễn ◽  
Bình Quang Lê
Keyword(s):  
Power System ◽  
System Reliability ◽  
Objective Assessment ◽  
Research Process ◽  
Assessment Tools ◽  
Power System Reliability ◽  
Mathematical Methods ◽  
Reliability Problem ◽  
Peace Of Mind ◽  
Reliability Issue

Nowadays, with the strong development of the world's economy, the power system reliability issue is increasingly concerned. A high reliable power system brings peace of mind in production investment, stability in national security, citizen's satisfaction… Therefore, serious researches of the power system reliability problem is very necessary. Based on that researches, we can accurately evaluate the situation, propose operational scenarios, troubleshoot reasonably, plan properly for the future. From there, we can implement the ultimate goal of the power system reliability problem is to maximize the reliability, meeting the nation's development need. However, at present, power system reliability problems in many countries have not yet applied updated and objective assessment tools, only exploiting the surface of the problem. Through the research process, the authors publish this paper to outline the basic concepts, the classification and the parameters of the power system reliability problem. Besides, the paper summarizes in detail the methods of calculating and evaluating power system reliability based on the current mathematical models (Analytical Graph method, State Space method, Failure Tree method, Monte - Carlo method) with examples of each method. Thereby, these methods are compared and indicated the applications in specific situations.

scholarly journals Solution to the Reliability Problem of Radial Electric Distribution Systems Through Artificial Intelligence

2006 ◽  
Vol 1 (2) ◽  
pp. 61 ◽  
Author(s):  
E. López ◽  
J. Campos ◽  
C. Tardon ◽  
F. Salgado ◽  
J. Tardon ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
System Reliability ◽  
Distribution Systems ◽  
Reliability Prediction ◽  
Reliability Problem ◽  
Electric System ◽  
Medium Voltage ◽  
Electric Distribution ◽  
Prediction Strategy

In this paper the distribution electric system reliability is recognized like an artificial intelligence problem. How this idea is applied in evaluation of reliability is detailed. Concepts as Intelligence Matrix and Inter-feeder Route are defined. From the last one a reliability prediction strategy for medium voltage networks is proposed and tested.

scholarly journals Efficient System Reliability-Based Design Optimization Study for Replaced Hip Prosthesis Using New Optimized Anisotropic Bone Formulations

Materials ◽  
2020 ◽  
Vol 13 (2) ◽  
pp. 362 ◽  
Author(s):  
Ghais Kharmanda ◽  
Samer Gowid ◽  
Elsadig Mahdi ◽  
Abdallah Shokry
Keyword(s):  
Design Optimization ◽  
Yield Stress ◽  
Material Properties ◽  
System Reliability ◽  
Elasticity Modulus ◽  
Hip Prosthesis ◽  
Reliability Based Design Optimization ◽  
Efficient System ◽  
Reliability Problem ◽  
Reliability Based Design

An efficient reliability algorithm is developed to transfer the system reliability problem to a single-component reliability problem, considering the uncertainty of loading cases and the material properties. The main difficulty is that femoral bone densities change after hip arthroplasty and, thus, the mechanical properties of the distinctive bone tissues and, therefore, the corresponding elasticity modulus and yield stress values change. Therefore, taking these changes into account during the hip prosthesis design process is strongly needed. As the bone possesses anisotropic behaviors, as the material properties in both radial and tangential directions in long bone (femur, tibia) are almost similar, the bone anisotropy is represented in this study by transversal isotropy. Two optimized formulations for yield stress against the elasticity modulus relationship are first developed and then integrated into an efficient reliability algorithm. Thus, a coupling between reliability and optimization, so-called reliability-based design optimization (RBDO), is introduced in order to control the reliability level. The proposed RBDO algorithm using optimum safety factors (OSF) takes into account the material uncertainties and leads to new stem dimensions. An in-depth numerical analysis on a cementless hip prosthesis is implemented to demonstrate the appropriateness of the proposed algorithm with the consideration of many different loading cases. The results show that the studied model can be effectively used when compared to previous works, which concerns the changes in both geometry and material properties.

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