Application of the Two-parameter Weibull Distribution Method to Assess the Reliability of Gas Turbine Compressors

Ozonuwe, Sunday N.; Onyekachi, Dennar; Oside, Collins U.

doi:10.9734/jerr/2020/v18i417213

Cited by 3 publications

(2 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Keywords: petroleum engineer, Monte Carlo method, nuclear fission, gas industry, probability distribution, environmental regulation, Bayesian network, Weibull distribution, electricity distribution network, hydroelectric power, etc. This cluster mentions reliability analysis, risk management, and strategic planning in the oil and gas industry (petroleum engineer) and Hydroelectric power plant by applying Monte Carlo simulation, Bayesian network, or Weibull distribution [37]. Moreover, Monte Carlo simulation and Bayesian network methods are also employed regularly in environmental risk assessment and CM of a nuclear power plant.…”

Section: New Methods Of Clustering Keyword Co-occurrence Networkmentioning

confidence: 99%

The New Method for Analyzing Technology Trends of Smart Energy Asset Performance Management

Viet

Kravets

2022

Energies

View full text Add to dashboard Cite

The development of emerging technologies not only has recently affected current industrial production but also has generated promising manufacturing opportunities that impact significantly on social and economic factors. Exploring upcoming renovation tendencies of technologies prematurely is essential for governments, research and development institutes, and industrial companies in managing strategies to achieve dominant advantages in business competitiveness. Additionally, the prospective changes, the scientific research directions, and the focus of technologies are crucial factors in predicting promising technologies. On the other hand, Industry 4.0 revolutionizes standards and models by accompanying significant technology developments in numerous sectors, including the sector of Smart energy. Moreover, asset performance management is always a prominent topic that has attained prevalence over the last decade because numerous challenges force all industrial companies to optimize their asset usability. However, to the best of our knowledge, no study reported an analysis of technology trends of asset performance management in the Smart energy sector by using proper data mining methods. Hence, this paper aims to fill in this gap and provide an analysis of technology trends of asset performance management in the Smart energy sector by structuring and exploring research subjects, considering problems, and solving methods with numerous experiments on scientific papers and patent data.

show abstract

Section: New Methods Of Clustering Keyword Co-occurrence Networkmentioning

confidence: 99%

The New Method for Analyzing Technology Trends of Smart Energy Asset Performance Management

Viet

Kravets

2022

Energies

View full text Add to dashboard Cite

show abstract

“…Al‐Fawzan 21 presented both graphical and analytical methods for estimation of Weibull parameters to compute reliability and concluded that the result which gives the best estimates is the method of moments. Further Ozonuwe, Onyekachi, and Oside, 22 in their research article, looked into the application of the two‐parameter Weibull distribution to assess the reliability of gas turbine compressors. The study involved the analysis of the failure times of the compressors using the median rank regression estimation method.…”

Section: Introductionmentioning

confidence: 99%

Efficiency, safety, and reliability analysis of turbocharging in a large container vessel

Anantharaman

Islam

Garaniya

et al. 2022

Process Safety Progress

View full text Add to dashboard Cite

Commercial shipping is currently dominated by mega container vessels. The shipping industry has seen a 10‐fold increase in the size of containers over the last four decades. These vessels are propelled by large marine diesel engines, hereafter referred to as the main engine. The performance of the main engine is determined by its subsystems. An important part of the main engine is the turbocharging system, which contributes to its safety, efficiency, and reliability. In this study, the effectiveness and reliability of the turbocharging system are evaluated. The Australian Maritime College has a Kongsberg Engine Simulator that can produce a variety of malfunctions on a running engine's turbocharging system. Analyzing the results obtained from the simulator determines the efficiency of the turbochargers. The study will provide recommendations for improving the safety of the turbocharging system for better performance to be achieved by the turbochargers, leading to an improvement in the main engine's performance. Last, the reliability of the turbocharging system is evaluated quantitatively using a fault tree analysis and reliability block diagrams. This will enable an optimum maintenance strategy to be established to ensure the safe operation of the vessel.

show abstract

Aerothermal Performance Robustness and Reliability Analysis of Turbine Blade Squealer Tip With Film Cooling

Huang,

Zhang,

et al. 2024

Journal of Turbomachinery

View full text Add to dashboard Cite

This paper first proposes an efficient uncertainty quantification method based on an original parallel framework combining Polynomial Chaos Expansions (PCE) with two forms (stochastic response surface-based and Galerkin projection-based) and the Universal Kriging method. Based on the findings of uncertainty quantification, the injection of cooling air drastically enhances the unstable tendency of the flow and thermal fields, resulting in the actual aerothermal performance of the squealer tip being much lower than that predicted by deterministic calculations. The setting of the film cooling, although effective in reducing the heat flux around the cooling holes, also induces more chaotic flow and thermal fields, leading to sharp heat flux fluctuations around the cooling holes. Finally, our novel reliability analysis algorithm, rooted in the quantification of uncertainty, corroborates the assertion that the introduction of coolant gas, while extending the operational longevity of turbine blades, confers only marginal improvements in the mitigation of lifespan variability. The comprehensive lifespan assessment elucidates that the mean operational longevity of the conventional squealer tip design stands at an estimated 16,169.44 hours, accompanied by a standard deviation of 2,750.31 hours. The mean operational longevity of the squealer tip integrated with film cooling measures a significantly enhanced 17,035.17 hours, exhibiting a standard deviation of 2,492.73 hours. Consequently, the operational lifespan of the conventional squealer tip experiences a decrement of 10.17% in comparison to the anticipated mean lifespan, whereas the reduction for the film-cooled squealer tip registers at 5.36%.

show abstract

Application of the Two-parameter Weibull Distribution Method to Assess the Reliability of Gas Turbine Compressors

Cited by 3 publications

References 18 publications

The New Method for Analyzing Technology Trends of Smart Energy Asset Performance Management

The New Method for Analyzing Technology Trends of Smart Energy Asset Performance Management

Efficiency, safety, and reliability analysis of turbocharging in a large container vessel

Aerothermal Performance Robustness and Reliability Analysis of Turbine Blade Squealer Tip With Film Cooling

Contact Info

Product

Resources

About