CALIBRATION OF THE K-ω SST TURBULENCE MODEL FOR BACKWARD FACING STEP PROBLEM USING MULTI-OBJECTIVE OPTIMIZATION

Alperen Yildizeli*, Sertac Cadirci

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Özet

Flow over a Backward Facing Step (BFS) is a classic fluid dynamics problem that has received considerable attention in the research community. In this study, the k-ω SST turbulence model is calibrated using ANSYS Fluent flow solver based on the comparison with Direct Numerical Simulation (DNS) data of a flow over a BFS which is available in the literature. On at a time (OAT) sensitivity analysis is conducted to determine six most dominant turbulence closure coefficients. Skin friction coefficient distribution is examined as quantity of interest. After determining the six most effective parameters, a deep neural network is trained with 500 CFD simulations; and multi-objective genetic algorithm is applied to reduce both RMSE and maximum absolute error of the skin friction coefficient distribution. The results of the study demonstrate that the model coefficients were successfully calibrated using multi-objective optimization. Improvements of the velocity profiles and skin friction coefficient are addressed to the optimization of closure coefficients which are related to the diffusion and production terms of turbulence model of interest. Optimum values of α, β, βi,1, βi,2, a1, and σω,2 were found 13.5% higher, 25% lower, 6.5 % lower, 6.5% higher, 14.5% higher and 3% higher than their original values, respectively.

Orijinal dilİngilizce
Ana bilgisayar yayını başlığıFluids Engineering
YayınlayanAmerican Society of Mechanical Engineers (ASME)
ISBN (Elektronik)9780791887660
DOI'lar
Yayın durumuYayınlandı - 2023
EtkinlikASME 2023 International Mechanical Engineering Congress and Exposition, IMECE 2023 - New Orleans, United States
Süre: 29 Eki 20232 Kas 2023

Yayın serisi

AdıASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE)
Hacim9

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???event.eventtypes.event.conference???ASME 2023 International Mechanical Engineering Congress and Exposition, IMECE 2023
Ülke/BölgeUnited States
ŞehirNew Orleans
Periyot29/10/232/11/23

Bibliyografik not

Publisher Copyright:
Copyright © 2023 by ASME.

Finansman

This work was supported by Research Fund of the Istanbul Technical University. Project Number: MDK-2023-44431

FinansörlerFinansör numarası
Istanbul Teknik ÜniversitesiMDK-2023-44431

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