Uncertainty Modeling of Fouling Thickness and Morphology on Compressor Blade
Abstract
1. Introduction
2. Fouling Uncertainty Modeling Method
2.1. Description of Fouling Morphology
2.2. Uncertainty Modeling Method of Dense Fouling Layer Thickness
2.3. Uncertainty Modeling Method of Loose Fouling Layer
2.4. Specific Steps for Modeling the Uncertainty of Fouling
2.5. Methods for Modeling Fouling Blades
2.6. Verification of Uncertainty Model of Fouling Rough Structures
2.6.1. The Control Parameters in the FLH Model
2.6.2. Validation of the FLH Model
2.7. Sparse Grid Non-Intrusive Polynomial Chaos (SGNIPC)
3. Research Object and Research Scheme
3.1. Research Object
3.2. Numerical Simulation Methods
3.3. The Scheme of Fouling Modeling
4. Case Validation and Analysis
4.1. Thickness Uncertainty Modeling of Blade Fouling
4.2. Rough Structure Uncertainty Modeling of Blade Fouling
4.3. Numerical Method of Fouling Cascade
4.4. Aerodynamic Uncertainty Response of Blade Fouling
5. Conclusions
- Considering the uncertainty of operating conditions and particle size distribution, the mathematical description method of compressor blade fouling is proposed, which is divided into the thickness of the dense layer and the rough structures of the loose layer. Based on the sparse grid numerical integration and KL expansion method to construct the uncertainty model of the thickness of the dense fouling layer for the compressor blade, and the FLH model is proposed to describe the size of the loose fouling layer roughness and the uncertainty of the rough structures. Using a two-dimensional cascade as the test case, a geometric uncertainty model for a fouling compressor cascade was developed based on the aforementioned modeling approach, demonstrating the feasibility of the methodology. The FLH model has been validated using actual fouling morphology and found to describe fouling with different rough characteristics. Due to the exponential growth in the number of geometric uncertainty models for fouling blades with increasing dimensionality, a 3D compressor blade fouling geometric uncertainty model has not yet been established. Future work will extend this methodology to three-dimensional fouled blades.
- Considering the uncertainty characteristics of the fouling rough structures, the influence law of the control parameters of the FLH model on the roughness of the loose fouling layer is given. When the wavelength control parameters of the rough structure follow a Gaussian distribution, it is guaranteed that the larger an is, the greater the roughness is, and the larger c is, the rougher the model is and the smaller the wavelength between the two wave peaks is when other parameters are kept constant. In addition, the parameter is adjusted to achieve the skew feature and randomness with the same roughness of the rough structures for the loose fouling layer. In addition, the variation of affects the roughness within ±1 μm when other control parameters are conserved constants.
- A method based on the sparse grid chaotic polynomial expansion of the uncertainty fouling model and aerodynamic performance uncertainty response of compressor blade fouling was developed. Assuming both fouling thickness and the wavelength control parameters of fouling roughness structures follow Gaussian distributions, the quantification of the aerodynamic performance uncertainty of compressor blade fouling in dense fouling layer and loose fouling layer was carried out. The results showed that there is a 75.8% probability of aerodynamic performance degradation due to the dense fouling layer, and the probability of aerodynamic performance degradation caused by the morphology uncertainty of the loose fouling layer is 97.2% when the roughness is 50 μm. It is further illustrated that rough structures have a large impact on aerodynamic performance degradation, and therefore it is not sufficient to describe blade fouling in terms of roughness alone; the effect of rough structures on aerodynamic performance must also be considered. With advancements in measurement technology, future research will yield more fouling morphology data from service-exposed blades. The statistical distribution characteristics of this data and its impact on aerodynamic performance degradation can be effectively analyzed using the methodology developed in this study.
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Gao, L.; Tu, P.; Yang, G.; Yang, S. Uncertainty Modeling of Fouling Thickness and Morphology on Compressor Blade. Aerospace 2025, 12, 547. https://doi.org/10.3390/aerospace12060547
Gao L, Tu P, Yang G, Yang S. Uncertainty Modeling of Fouling Thickness and Morphology on Compressor Blade. Aerospace. 2025; 12(6):547. https://doi.org/10.3390/aerospace12060547
Chicago/Turabian StyleGao, Limin, Panpan Tu, Guang Yang, and Song Yang. 2025. "Uncertainty Modeling of Fouling Thickness and Morphology on Compressor Blade" Aerospace 12, no. 6: 547. https://doi.org/10.3390/aerospace12060547
APA StyleGao, L., Tu, P., Yang, G., & Yang, S. (2025). Uncertainty Modeling of Fouling Thickness and Morphology on Compressor Blade. Aerospace, 12(6), 547. https://doi.org/10.3390/aerospace12060547