ANFIS-based Prediction of Strouhal Number for bluff Body Wake

Kharola, Ashwani; Dobriyal, Ritvik; Rahul, *; Pokhriyal, Varun

doi:10.1109/ccet56606.2022.10080553

2022 IEEE International Conference on Current Development in Engineering and Technology (CCET) 2022

DOI: 10.1109/ccet56606.2022.10080553

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ANFIS-based Prediction of Strouhal Number for bluff Body Wake

Ashwani Kharola

Ritvik Dobriyal

* Rahul

et al.

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2023

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Hydrodynamic Flow Characteristics Prediction for Bluff Body Wake via Novel Adaptive Neuro-Fuzzy Controller Avoiding Fuzzy Rule Explosion

Kharola,

Dobriyal,

Sharma

et al. 2023

SAE Technical Paper Series

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<div class="section abstract"><div class="htmlview paragraph">This study analyses the effect of Reynolds number (<i>Re</i>) and bluff body shape (quantified by shape factor <i>SF</i>) variation on various hydrodynamic characteristics of unsteady bluff body flow, such as Strouhal number, maximum lift coefficient, and mean drag coefficient. The study initially examines a relationship among these characteristics and further utilizes artificial neural networks (ANNs) and adaptive neuro-fuzzy inference system (ANFIS) controllers for their precise prediction. The results from real-time computational fluid dynamics (CFD) experimentations were gathered and considered to train ANN controllers. A novel ANFIS controller has been designed using only three membership functions thus solving the problem of fuzzy rule explosion. The results indicate that both the ANN and ANFIS controllers can precisely predict these hydrodynamic flow characteristics as validated through minimal values of root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE). It is observed that ANFIS controller provides better results compared to the proposed feed-forward ANN controller. The RMSE, MAE, and MAPE obtained for ANFIS model for different shape factors for maximum lift coefficient were 0.0024, 0.002, and 0.85%, respectively.</div></div>

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Hydrodynamic Flow Characteristics Prediction for Bluff Body Wake via Novel Adaptive Neuro-Fuzzy Controller Avoiding Fuzzy Rule Explosion

Kharola,

Dobriyal,

Sharma

et al. 2023

SAE Technical Paper Series

View full text Add to dashboard Cite

show abstract

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ANFIS-based Prediction of Strouhal Number for bluff Body Wake

Cited by 1 publication

References 19 publications

Hydrodynamic Flow Characteristics Prediction for Bluff Body Wake via Novel Adaptive Neuro-Fuzzy Controller Avoiding Fuzzy Rule Explosion

Hydrodynamic Flow Characteristics Prediction for Bluff Body Wake via Novel Adaptive Neuro-Fuzzy Controller Avoiding Fuzzy Rule Explosion

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