Predicting material fatigue from material properties

The primary purpose of this report is to study how the surface properties of an aluminium alloy changes, at the initial stage of test fatigue test. The surface properties of the aluminium sample include Young’s Modulus and surface roughness. Moreover the changes took place in the indentation on t...

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Main Author: Loh, Teck Yang.
Other Authors: Tan Cher Ming
Format: Final Year Project
Language:English
Published: 2013
Subjects:
Online Access:http://hdl.handle.net/10356/53111
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-531112023-07-07T15:50:59Z Predicting material fatigue from material properties Loh, Teck Yang. Tan Cher Ming School of Electrical and Electronic Engineering DRNTU::Engineering The primary purpose of this report is to study how the surface properties of an aluminium alloy changes, at the initial stage of test fatigue test. The surface properties of the aluminium sample include Young’s Modulus and surface roughness. Moreover the changes took place in the indentation on the test sample will be studied. In order to obtain the data for the changes of surface properties, an aluminium alloy has been sent for fatigue test. In total, the aluminium alloy has gone through an accumulation of 300,000 cycles of fatigue test. The results obtained from the fatigue test indicate that the Young’s modulus increases when the numbers of cycles of fatigue test increases. As for the surface roughness, it increases till 23000 fatigue cycle and start to decrease after that. This may due to the initiation of micro-crack on the aluminium alloy. Moreover, the indentation depth decreases when the fatigue cycle increases. Analyzing work has been done to explain those changes. Lastly, the changes took place in the indentation were observed by both microscope and scanning electron microscopy (SEM).The surface properties data for the aluminium alloy are collected using surface profilometer, optical microscopy, ultrasonic flaw detector, scanning electron microscopy and hardness tester. Bachelor of Engineering 2013-05-30T02:53:00Z 2013-05-30T02:53:00Z 2013 2013 Final Year Project (FYP) http://hdl.handle.net/10356/53111 en Nanyang Technological University 88 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering
spellingShingle DRNTU::Engineering
Loh, Teck Yang.
Predicting material fatigue from material properties
description The primary purpose of this report is to study how the surface properties of an aluminium alloy changes, at the initial stage of test fatigue test. The surface properties of the aluminium sample include Young’s Modulus and surface roughness. Moreover the changes took place in the indentation on the test sample will be studied. In order to obtain the data for the changes of surface properties, an aluminium alloy has been sent for fatigue test. In total, the aluminium alloy has gone through an accumulation of 300,000 cycles of fatigue test. The results obtained from the fatigue test indicate that the Young’s modulus increases when the numbers of cycles of fatigue test increases. As for the surface roughness, it increases till 23000 fatigue cycle and start to decrease after that. This may due to the initiation of micro-crack on the aluminium alloy. Moreover, the indentation depth decreases when the fatigue cycle increases. Analyzing work has been done to explain those changes. Lastly, the changes took place in the indentation were observed by both microscope and scanning electron microscopy (SEM).The surface properties data for the aluminium alloy are collected using surface profilometer, optical microscopy, ultrasonic flaw detector, scanning electron microscopy and hardness tester.
author2 Tan Cher Ming
author_facet Tan Cher Ming
Loh, Teck Yang.
format Final Year Project
author Loh, Teck Yang.
author_sort Loh, Teck Yang.
title Predicting material fatigue from material properties
title_short Predicting material fatigue from material properties
title_full Predicting material fatigue from material properties
title_fullStr Predicting material fatigue from material properties
title_full_unstemmed Predicting material fatigue from material properties
title_sort predicting material fatigue from material properties
publishDate 2013
url http://hdl.handle.net/10356/53111
_version_ 1772825813254668288