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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM33152

SIMULATION AND OPTIMIZATION MATERIAL OF WIND TURBINE BLADE PROFILES USING CATIA AND ANSYS

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM33152

Volume:

8 |

5 |

May 2024

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
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10.55041/IJSREM33152

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

NSSP

N S SURYA PRAKESH

GRK

G. RATNA KAMAL

GJKP

G. JYOTHI KRISHNA PRADEEP

CD

CH. DEEPTHANUSH

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Abstract

I Wind energy is a fast-growing way to make power from wind, and it’s good for the environment. Wind turbines have big blades that catch the wind to make electricity. This project is all about making those blades work better and cost less money. First, we use special computer programs called CATIA and ANSYS to design and test the blades. CATIA helps us design the shape and size of the blades, while ANSYS helps us see how strong they are and how well they catch the wind. We start by making different blade shapes in CATIA, changing things like length, width, and twist. Then we use ANSYS to test them. We look at things like how much stress they can handle, how much they bend, and how well they catch the wind. After testing, we try to make the blades even better. We use special tools in ANSYS and CATIA to find the best combination of blade features. We want blades that are super-efficient at catching wind, strong enough to last a long time, and don’t cost too much to make. By varying material to blade profile checking strength and mode shapes for Aluminium, Carbon fibre and E glass epoxy

KEYWORDS

wind energy Turbines Wind blades CATIA ANSYS

Cite This Article

N S SURYA PRAKESH, G. RATNA KAMAL, G. JYOTHI KRISHNA PRADEEP, CH. DEEPTHANUSH, "SIMULATION AND OPTIMIZATION MATERIAL OF WIND TURBINE BLADE PROFILES USING CATIA AND ANSYS," International Journal of Scientific Research in Engineering and Management, vol. 8, no. 5, May 2024. https://doi.org/10.55041/IJSREM33152

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12/31/45416

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Double-Blind Peer Review

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