Availability and failure frequency of a Gnedenko system

1990 ◽  
Vol 24 (1) ◽  
pp. 53-68 ◽  
Author(s):  
Jinhua Cao
Keyword(s):  
Failure Frequency ◽  
Gnedenko System

Assessment of Failure Frequency Methodology Applied to Dense Phase Carbon Dioxide Pipelines

2019 ◽  
Author(s):  
Christopher Lyons ◽  
Julia Race ◽  
Ben Wetenhall ◽  
Enrong Chang ◽  
Harry Hopkins ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Dense Phase ◽  
Failure Frequency

A Methodology for the Prediction of Pipeline Failure Frequency Due to External Interference

2008 ◽  
Author(s):  
C. Lyons ◽  
J. V. Haswell ◽  
P. Hopkins ◽  
R. Ellis ◽  
N. Jackson
Keyword(s):  
Damage Mechanism ◽  
External Interference ◽  
Gas Industry ◽  
Failure Frequency ◽  
Failure Data ◽  
Mechanics Model ◽  
The United Kingdom ◽  
Pipeline Failure ◽  
The Uk ◽  
Operational Failure

The United Kingdom Onshore Pipeline Operators Association (UKOPA) is developing supplements to the UK pipeline codes BSI PD 8010 and IGE/TD/1. These supplements will provide a standardized approach for the application of quantified risk assessment to pipelines. UKOPA has evaluated and recommended a methodology: this paper covers the background to, and justification of, this methodology. The most relevant damage mechanism which results in pipeline failure is external interference. Interference produces a gouge, dent or a dent-gouge. This paper describes the fracture mechanics model used to predict the probability failure of pipelines containing dent and gouge damage and contains predictions of failure frequency obtained using the gas industry failure frequency prediction methodologies FFREQ and operational failure data from the UKOPA fault database. The failure model and prediction methodology are explained and typical results are presented and discussed.

Well-Posedness of the Gnedenko System with Multiple Vacations

2012 ◽  
Vol 522 ◽  
pp. 902-909
Author(s):  
Bilikiz Yunus ◽  
Abdukerim Haji
Keyword(s):  
Semigroup Theory ◽  
Linear Operators ◽  
Well Posedness ◽  
Multiple Vacations ◽  
Dynamic Solution ◽  
Multiple Vacation ◽  
Gnedenko System

We investigate the solution of the Gnedenko system with multiple vacation of a repairman. By using-semigroup theory of linear operators, we prove well-posedness and the existence of the unique positive dynamic solution of the system.

scholarly journals MARSplines method as a tool for failure frequency modelling

2018 ◽  
Vol 44 ◽  
pp. 00086
Author(s):  
Małgorzata Kutyłowska
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Failure Rate ◽  
Basis Function ◽  
Adaptive Algorithm ◽  
Point Of View ◽  
Water Utility ◽  
Failure Frequency ◽  
Rate Prediction ◽  
Operational Data

The paper presents the results of failure rate prediction using adaptive algorithm MARSplines. This method could be defined as segmental and multiple linear regression. The range of segments defines the range of applicability of that methodology. On the basis of operational data received from Water Utility two separate models were created for distribution pipes and house connections. The calculations were carried out in the programme Statistica 13.1. Maximal number of basis function was equalled to 30; so-called pruning was used. Interaction level equalled to 1, the penalty for adding basis function amounted to 2, and the threshold – 0.0005. GCV error equalled to 0.0018 and 0.0253 as well as 0.0738 and 0.1058 for distribution pipes and house connections in learning and prognosis process, respectively. The prediction results in validation step were not satisfactory in relation to distribution pipes, because constant value of failure rate was observed. Concerning house connections, the forecasting was slightly better, but still the overestimation seems to be unacceptable from engineering point of view.

Analysis of Frequently Failing Tasks and Rescheduling Strategy in the Cloud System

2018 ◽  
Vol 9 (1) ◽  
pp. 16-38
Author(s):  
Hongyan Tang ◽  
Ying Li ◽  
Tong Jia ◽  
Xiaoyong Yuan ◽  
Zhonghai Wu
Keyword(s):  
Cloud Computing ◽  
Early Stage ◽  
Cloud System ◽  
Usage Pattern ◽  
Resource Saving ◽  
Computing Systems ◽  
Cloud Systems ◽  
Failure Frequency ◽  
Task Recognition

To better understand task failures in cloud computing systems, the authors analyze failure frequency of tasks based on Google cluster dataset, and find some frequently failing tasks that suffer from long-term failures and repeated rescheduling, which are called killer tasks as they can be a big concern of cloud systems. Hence there is a need to analyze killer tasks thoroughly and recognize them precisely. In this article, the authors first investigate resource usage pattern of killer tasks and analyze rescheduling strategies of killer tasks in Google cluster to find that repeated rescheduling causes large amount of resource wasting. Based on the above observations, they then propose an online killer task recognition service to recognize killer tasks at the very early stage of their occurrence so as to avoid unnecessary resource wasting. The experiment results show that the proposed service performs a 93.6% accuracy in recognizing killer tasks with an 87% timing advance and 86.6% resource saving for the cloud system averagely.

A new method for dynamically estimating long-term seepage failure frequency for high concrete faced rockfill dams

2020 ◽  
Vol 79 (10) ◽  
Author(s):  
Gang Deng ◽  
Kui Cao ◽  
Rui Chen ◽  
Yanfeng Wen ◽  
Yinqi Zhang ◽  
...  
Keyword(s):  
New Method ◽  
Seepage Failure ◽  
Failure Frequency

scholarly journals Development of Failure Cause–Impact–Duration (CID) Plots for Water Supply and Distribution System Management

Water ◽  
2019 ◽  
Vol 11 (8) ◽  
pp. 1719 ◽  
Author(s):  
Seungyub Lee ◽  
Sueyeun Oak ◽  
Donghwi Jung ◽  
Hwandon Jun
Keyword(s):  
Water Supply ◽  
Distribution System ◽  
System Management ◽  
Failure Frequency ◽  
Supply And Distribution ◽  
Failure Classification ◽  
Component Failures ◽  
The Impact ◽  
The Relationship ◽  
Impact Duration

Understanding the impact and duration (consequences) of different component failures (cause) in a water supply and distribution system (WSDS) is a critical task for water utilities to develop effective preparation and response plans. During the last three decades, few efforts have been devoted to developing a visualization tool to display the relationship between the failure cause and its consequences. This study proposes two visualization methods to effectively show the relationship between the two failure entities: A failure cause–impact–duration (CID) plot, and a bubble plot. The former is drawn for an effective snapshot on the range (extent) of failure duration and the impact of different failures, whereas the latter provides failure frequency information. A simple and practical failure classification system is also introduced for producing the two proposed plots effectively. To verify the visualization schemes, we collected records of 331 WSDS component failures that occurred in South Korea between 1980 and 2018. Results showed that (1) the proposed CID plot can serve as a useful tool for identifying most minor and major WSDS failures, and (2) the proposed bubble plot is useful for determining significant component failures with respect to their failure consequences and occurrence likelihoods.

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