涡轮叶片模态分析中简化结构模型的考虑

Natalie S. Korpics, Reid A. Berdanier
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引用次数: 1

摘要

喷气发动机硬件模态分析是工程师了解和预测系统振动风险的必要分析工具。由于叶片和圆盘的失效模式和影响,需要对其进行严格的分析,涡轮叶片也需要根据其设计模态标准进行评估,以尽量减少对发动机的潜在风险。虽然整个系统的全环模型是最准确的,但建模和解决方案处理所需的时间通常是令人望而却步的。通过循环对称和商业接触技术的使用,可以创建一个解析模型,该模型可以用一小部分计算时间提供整个系统的行为。然而,模型简化的方法,包括仅叶片模型,还没有得到解决,简化模型准确预测系统模式的潜力是特别感兴趣的。因此,本文研究了采用多接触法和循环对称法对涡轮叶片进行模态分析的有限元建模方法。重点放在评估仅叶片建模技术和一个简化的涡轮机匣模型。另外与传统装配模型的比较评估了有限元模型求解的精度和效率。最后,为涡轮叶片的结构建模提供了正式的建议,包括精度评估、频率预测能力降低和计算效率增益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Consideration of Simplified Structural Models for Turbine Vane Modal Analysis
Modal analysis of jet engine hardware is a necessary analytical tool utilized by engineers to understand and predict the vibrational risks to the system. Whereas blades and disks are critically analyzed due to their failure modes and effects, turbine vanes also need to be evaluated with respect to their design modal criteria to minimize potential risks to the engine. Although full hoop models of the entire system are most accurate, the time required for modeling and solution processing is typically prohibitive. Through cyclic symmetry and the use of commercial contact techniques, an analytical model may be created that provides the behavior of the entire system with a fraction of the computing time. However, methods for model simplification, including vane-only models, have not been addressed, and the potential for simplified models to accurately predict system modes is of particular interest. Accordingly, this paper studies the finite element modeling procedures for turbine vane modal analysis using multiple contact methods and cyclic symmetry applied to a turbine vane. An emphasis is placed on evaluating vane-only modeling techniques and an abbreviated turbine casing model. Additional comparisons with a traditional assembly model assess finite element model solution accuracy and efficiency. Ultimately, formal recommendations are offered for structural modeling of turbine vanes, including assessments of accuracy, reduction of frequency prediction capability, and computational efficiency gain.
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