Machine learning assisted development of high strength iron-based alloy

High strength alloys are materials with alloying additions designed to produce a specific combination of mechanical qualities such as strength, toughness, weldability, formability as well as atmospheric corrosion resistance. One such example is the Iron-Aluminium (Fe-Al) based alloy that is highly f...

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Main Author: Lim, Chin Siang
Other Authors: Sunil Chandrakant Joshi
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2023
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Online Access:https://hdl.handle.net/10356/167090
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Institution: Nanyang Technological University
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spelling sg-ntu-dr.10356-1670902023-11-29T08:13:06Z Machine learning assisted development of high strength iron-based alloy Lim, Chin Siang Sunil Chandrakant Joshi School of Mechanical and Aerospace Engineering A*STAR Institute of Material Research and Engineering MSCJoshi@ntu.edu.sg Engineering::Aeronautical engineering High strength alloys are materials with alloying additions designed to produce a specific combination of mechanical qualities such as strength, toughness, weldability, formability as well as atmospheric corrosion resistance. One such example is the Iron-Aluminium (Fe-Al) based alloy that is highly favorable due to their properties of high specific yield strength, low cost as well as high corrosion resistance. However, initial methods of traditional alloy development have proved to be an extensive, time-consuming process. Studies of superalloy took nearly 40 years to understand the mechanical behavior even before development. The resources and manhours invested in development of alloys has therefore proved to be inefficient. With the use of Machine Learning, the development of alloys can be accelerated through assisted screenings and high throughout experimentation, thus reducing the overall duration as well as improving the experiment's efficiency. In this study, we attempt to demonstrate an alternative approach that utilizes Machine Learning (ML) algorithm that is trained on a given set of composition with given mechanical properties to predict novel alloy composition with high specific yield strength. Predicted novel compositions of Fe-Al will be validated with the developed alloy through a series of experimental test to determine the model’s accuracy. Bachelor of Engineering (Aerospace Engineering) 2023-05-21T13:03:12Z 2023-05-21T13:03:12Z 2023 Final Year Project (FYP) Lim, C. S. (2023). Machine learning assisted development of high strength iron-based alloy. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/167090 https://hdl.handle.net/10356/167090 en C162 application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Aeronautical engineering
spellingShingle Engineering::Aeronautical engineering
Lim, Chin Siang
Machine learning assisted development of high strength iron-based alloy
description High strength alloys are materials with alloying additions designed to produce a specific combination of mechanical qualities such as strength, toughness, weldability, formability as well as atmospheric corrosion resistance. One such example is the Iron-Aluminium (Fe-Al) based alloy that is highly favorable due to their properties of high specific yield strength, low cost as well as high corrosion resistance. However, initial methods of traditional alloy development have proved to be an extensive, time-consuming process. Studies of superalloy took nearly 40 years to understand the mechanical behavior even before development. The resources and manhours invested in development of alloys has therefore proved to be inefficient. With the use of Machine Learning, the development of alloys can be accelerated through assisted screenings and high throughout experimentation, thus reducing the overall duration as well as improving the experiment's efficiency. In this study, we attempt to demonstrate an alternative approach that utilizes Machine Learning (ML) algorithm that is trained on a given set of composition with given mechanical properties to predict novel alloy composition with high specific yield strength. Predicted novel compositions of Fe-Al will be validated with the developed alloy through a series of experimental test to determine the model’s accuracy.
author2 Sunil Chandrakant Joshi
author_facet Sunil Chandrakant Joshi
Lim, Chin Siang
format Final Year Project
author Lim, Chin Siang
author_sort Lim, Chin Siang
title Machine learning assisted development of high strength iron-based alloy
title_short Machine learning assisted development of high strength iron-based alloy
title_full Machine learning assisted development of high strength iron-based alloy
title_fullStr Machine learning assisted development of high strength iron-based alloy
title_full_unstemmed Machine learning assisted development of high strength iron-based alloy
title_sort machine learning assisted development of high strength iron-based alloy
publisher Nanyang Technological University
publishDate 2023
url https://hdl.handle.net/10356/167090
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