Convolution neural network for fluid flow simulations in cascade with oscillating blades

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F25%3A43975744" target="_blank" >RIV/49777513:23520/25:43975744 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.1016/j.cam.2024.116478" target="_blank" >https://doi.org/10.1016/j.cam.2024.116478</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.cam.2024.116478" target="_blank" >10.1016/j.cam.2024.116478</a>

Result language

angličtina

Original language name

Convolution neural network for fluid flow simulations in cascade with oscillating blades

Original language description

This paper aims to design a computational model for simulating the unsteady flow field in a cascade of oscillating blades. The core of the new model is a convolutional neural network, which is trained on a simplified cascade consisting of three blades. The primary advantage lies in significantly reducing the computational cost, as the new model is several orders of magnitude faster than traditional CFD methods for evaluations, though training the model remains computationally intensive. The convolutional neural network can accurately predict the unsteady flow field, as demonstrated in validation examples. In the next step, a composition algorithm is proposed to combine several simplified cases, enabling the solution of a cascade with any number of blades.

Czech name

—

Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

20302 - Applied mechanics

Project

<a href="/en/project/GA24-12144S" target="_blank" >GA24-12144S: Investigation of 3D flow structures and their effects on aeroelastic stability of turbine-blade cascades using experiment and deep learning approach</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2025

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS

ISSN

0377-0427

e-ISSN

1879-1778

Volume of the periodical

462

Issue of the periodical within the volume

JUL 2025

Country of publishing house

NL - THE KINGDOM OF THE NETHERLANDS

Number of pages

11

Pages from-to

116478

UT code for WoS article

001399265700001

EID of the result in the Scopus database

2-s2.0-85214314064