Reliability Evaluation for Turbo Pump Component in Two-phase Development with No Failure Data

Author(s):  
Ping Jiang ◽  
Yunyan Xing ◽  
Bo Wang ◽  
Wenfeng Wang
2020 ◽  
Vol 34 (4) ◽  
pp. 1503-1513 ◽  
Author(s):  
Bo Sun ◽  
Narayanaswamy Balakrishnan ◽  
Fei Chen ◽  
Binbin Xu ◽  
Zhaojun Yang ◽  
...  

2016 ◽  
Vol 46 (1) ◽  
pp. 176-188 ◽  
Author(s):  
Wei-an Yan ◽  
Bao-wei Song ◽  
Gui-lin Duan ◽  
Yi-min Shi

2014 ◽  
Vol 556-562 ◽  
pp. 2515-2518
Author(s):  
Bin Quan Li

The material selection and manufacturing processes of numerical control device were related with the reliability of system. Therefore, the reliability evaluation of it was significant. Numerical control system was, obviously, high-reliability product and the application of Bayesian theory has become an important means of its reliability assessment. The failure data of numerical control device obeys Weibull distribution which has complex forms. The posterior distribution becomes extremely complicated and the numerical integration which Bayesian computing depends on is not available. Markov chain Monte Carlo (MCMC) method ensures the implementation of the assessment. The result of Bayesian estimation proves that it increases the robustness, accuracy and effectiveness of the calculation and it's suitable for numerical control device reliability evaluation.


Author(s):  
Wael Fairouz Saleh ◽  
Robert C. Bowden ◽  
Ibrahim Galal Hassan ◽  
Lyes Kadem

The discharge of two-phase flow from a stratified region through single or multiple branches is an important process in many industrial applications including the pumping of fluid from storage tanks, shell-and-tube heat exchangers, and the fluid flow through header to the cooling channels, feeder’s tube, of nuclear reactors during loss-of-coolant accidents (LOCA). Knowledge of the flow phenomena involved along with the quality and mass flow rate of the discharging stream(s) is necessary to adequately predict the different phenomena associated with the process. Stereoscopic Particle Image Velocimetry (3D-PIV) was used to provide detailed measurements of the flow patterns involving distributions of mean velocity, vorticity field, and flow structure. The experimental investigation was carried out to simulate two phase discharge from a stratified region through branches located on a quarter-circular wall configuration exposed to a stratified gas-liquid environment. The quarter-circular test section is in close dimensional resemblance with that of a CANDU header-feeder system, with branches mounted at orientation angles of zero, 45° and 90° degrees from the horizontal. The experimental data for the phase development (mean velocity, flow structure, etc..) was done during dual discharge through the horizontal branch and the 45° or 90° branch from an air/water stratified region over a two selected Froude numbers in the horizontal branch while maintaining the Froude number in the other branch constant. These measurements were used to describe the effect of outlet flow conditions on phase redistribution in headers and understand the entrainment phenomena.


2020 ◽  
Vol 10 (21) ◽  
pp. 7591
Author(s):  
Bo Sun ◽  
Zhaojun Yang ◽  
Narayanaswamy Balakrishnan ◽  
Chuanhai Chen ◽  
Hailong Tian ◽  
...  

In the early stage of product development, reliability evaluation is an indispensable step before launching a product onto the market. It is not realistic to evaluate the reliability of a new product by a host of reliability tests due to the limiting factors of time and test costs. Evaluating the reliability of products in a short time is a challenging problem. In this paper, an approach is proposed that combines a group of experts’ judgments and limited failure data. Novel features of this approach are that it can reflect various kinds of information without considering the individual weight and reduces aggregation error in the uncertainty quantification of multiple inconsistent pieces of information. First, an expert system is established by the Bayesian best–worst method and fuzzy logic inference, which collects and aggregates a group of expert opinions to estimate the reliability improvement factor. Then, an adaptive Bayesian melding method is investigated to generate a posterior by inaccurate prior knowledge and limited test data; this method is made more computationally efficient by implementing an improved sampling importance resampling algorithm. Finally, an application for the reliability evaluation of a subsystem of a CNC lathe is discussed to illustrate the framework, which is shown to validate the reasonability and robustness of our proposal.


2013 ◽  
Vol 634-638 ◽  
pp. 3998-4003
Author(s):  
Qiu Ying Li ◽  
Hui Qi Zhang

The software reliability failure data is the foundation of the software reliability’s quantitative evaluation based on the failure data, and it has an important influence on the accuracy of reliability evaluation. But there are always noises in the original software reliability failure data and make the reliability evaluation accuracy affected. This paper put forward the collecting method of reliability failure data and data preprocessing method including data cleaning and data analysis method, which based on the analysis of the importance and the source of failure data in the software reliability testing and the classification of software failure data. Finally through an example, it displayed the reduction of data noises and the promotion of data quality which produced by the preprocessing methods.


Sign in / Sign up

Export Citation Format

Share Document