公开(公告)号：US20250156610A1

公开(公告)日：2025-05-15

申请号：US18942901

申请日：2024-11-11

Applicant: POSTECH RESEARCH AND BUSINESS DEVELOPMENT FOUNDATION

Inventor： Donghyun YOU ,  Innyoung KIM

IPC: G06F30/28 ,  G06F30/27

Abstract: Disclosed is a computational fluid dynamics (CFD) flow analysis method for blades includes: generating an analysis automation model that predicts CFD flow analysis results according to input analysis conditions, the generating an analysis automation model comprising inputting a blade shape and flow conditions, determining analysis settings for flow analysis over blades, performing CFD simulation based on the determined analysis setting parameters to conduct flow analysis over blades, evaluating results of the performed flow analysis over blades, and training through reinforcement learning using artificial neural networks to satisfy predetermined evaluation criteria, inputting arbitrary blade shape conditions and flow conditions, and determining analysis setting parameters by applying the analysis automation model to the input blade shape and flow conditions, predicting CFD simulation, and outputting the predicted CFD simulation as flow analysis results.

公开(公告)号：US20220205425A1

公开(公告)日：2022-06-30

申请号：US17230235

申请日：2021-04-14

Applicant: POSTECH Research and Business Development Foundation

Inventor： Donghyun YOU ,  Taewan KIM ,  Sejin KIM ,  Jeonghwan SONG

IPC: F03D7/04 ,  F03D17/00

Abstract: According to the disclosure, an artificial intelligence (AI) model receives a power production amount, a power production efficiency, a control variable and the like states as input information through information exchange between a wind turbine and the AI model, and therefore it is possible to provide a control method using the AI model with regard to even the wind turbine given no power coefficient.