Efficient metamodeling and uncertainty propagation for rotor systems by sparse polynomial chaos expansion

IF 3 3区 工程技术 Q2 ENGINEERING, MECHANICAL
Ben-Sheng Xu , Xiao-Min Yang , Ai-Cheng Zou , Chao-Ping Zang
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引用次数: 0

Abstract

The modeling of rotor systems involves various parameters prone to uncertainties. These variations typically arise from the mathematical complexities of representing rotor system peculiarities and the limited understanding of material properties in specific applications. Analyzing uncertainties affecting rotor system performance is essential for effective design. A metamodeling approach for rotor systems under uncertain parameters is developed, employing sparse polynomial chaos expansion (sPCE) for uncertainty propagation. The sPCE method integrates basis functions adaptively using the Bayesian compressive sensing (BCS) method, enhancing convergence speed for accurate prediction of statistical moments. Probabilistic outcomes are compared with traditional Monte Carlo simulation (MCS) and Latin Hyper Sampling (LHS) methods. The comparative analysis shows that the proposed method achieves higher computational accuracy than the LHS method and exhibits a 40% improvement in computational efficiency compared to the traditional MCS method, thus providing valuable insights for the design and maintenance of rotor systems.
基于稀疏多项式混沌展开的转子系统有效元建模与不确定性传播
转子系统的建模涉及各种容易产生不确定性的参数。这些变化通常是由表示转子系统特性的数学复杂性和对特定应用中材料特性的有限理解引起的。分析影响转子系统性能的不确定性是有效设计转子系统的必要条件。提出了一种转子系统参数不确定的元建模方法,采用稀疏多项式混沌展开(sPCE)进行不确定传播。sPCE方法采用贝叶斯压缩感知(BCS)方法自适应集成基函数,提高了收敛速度,实现了统计矩的准确预测。将概率结果与传统的蒙特卡罗模拟(MCS)和拉丁超采样(LHS)方法进行了比较。对比分析表明,该方法的计算精度高于LHS方法,计算效率比传统的MCS方法提高了40%,为转子系统的设计和维护提供了有价值的见解。
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来源期刊
Probabilistic Engineering Mechanics
Probabilistic Engineering Mechanics 工程技术-工程:机械
CiteScore
3.80
自引率
15.40%
发文量
98
审稿时长
13.5 months
期刊介绍: This journal provides a forum for scholarly work dealing primarily with probabilistic and statistical approaches to contemporary solid/structural and fluid mechanics problems encountered in diverse technical disciplines such as aerospace, civil, marine, mechanical, and nuclear engineering. The journal aims to maintain a healthy balance between general solution techniques and problem-specific results, encouraging a fruitful exchange of ideas among disparate engineering specialities.
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