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  • 标题:A Probabilistic Design Methodology for a Turboshaft Engine Overall Performance Analysis
  • 本地全文:下载
  • 作者:Min Chen ; Kun Zhang ; Hai-Long Tang
  • 期刊名称:Advances in Mechanical Engineering
  • 印刷版ISSN:1687-8140
  • 电子版ISSN:1687-8140
  • 出版年度:2014
  • 卷号:2014
  • DOI:10.1155/2014/976853
  • 出版社:Sage Publications Ltd.
  • 摘要:In reality, the cumulative effect of the many uncertainties in engine component performance may stack up to affect the engine overall performance. This paper aims to quantify the impact of uncertainty in engine component performance on the overall performance of a turboshaft engine based on Monte-Carlo probabilistic design method. A novel probabilistic model of turboshaft engine, consisting of a Monte-Carlo simulation generator, a traditional nonlinear turboshaft engine model, and a probability statistical model, was implemented to predict this impact. One of the fundamental results shown herein is that uncertainty in component performance has a significant impact on the engine overall performance prediction. This paper also shows that, taking into consideration the uncertainties in component performance, the turbine entry temperature and overall pressure ratio based on the probabilistic design method should increase by 0.76% and 8.33%, respectively, compared with the ones of deterministic design method. The comparison shows that the probabilistic approach provides a more credible and reliable way to assign the design space for a target engine overall performance.
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