Fatigue life prediction for composite materials based on the S-N-φ model

The strength degradation law of composite materials is very important to fatigue life prediction. However, establishing existing residual strength models requires various experimental data to confirm the parameters involved in the models. Sometimes, experimental data on the residual strength of comp...

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Main Authors: Hai An, Weitao Zhao
Format: Article
Language:English
Published: AIP Publishing LLC 2023-08-01
Series:AIP Advances
Online Access:http://dx.doi.org/10.1063/5.0164864
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author Hai An
Weitao Zhao
author_facet Hai An
Weitao Zhao
author_sort Hai An
collection DOAJ
description The strength degradation law of composite materials is very important to fatigue life prediction. However, establishing existing residual strength models requires various experimental data to confirm the parameters involved in the models. Sometimes, experimental data on the residual strength of composite materials are not available because of limitations on experimental cost and project progress. To solve these issues, a new fatigue life prediction model named the S-N-φ model is proposed. The S-N-φ model does not require the experimental data of residual strength, and the residual strength is only reflected in the theoretical deduction process. The S-N-φ model can clearly explain the probability characteristic of fatigue life because both initial strength and cyclic stress are considered. The S-N-φ model is verified by a set of experimental data of composite laminates. The results show that the S-N-φ model is more accurate than the widely used classical S-N curve model, and the probability characteristic of fatigue life predicted by using the S-N-φ model agrees well with the experimental data.
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spelling doaj.art-c21f7d15c18142fcac84f52da7fb7d572023-09-08T16:03:31ZengAIP Publishing LLCAIP Advances2158-32262023-08-01138085328085328-810.1063/5.0164864Fatigue life prediction for composite materials based on the S-N-φ modelHai An0Weitao Zhao1College of Aerospace and Civil Engineering, Harbin Engineering University, Harbin 15001, ChinaCollege of Aerospace Engineering, Shenyang Aerospace University, Shenyang 110136, ChinaThe strength degradation law of composite materials is very important to fatigue life prediction. However, establishing existing residual strength models requires various experimental data to confirm the parameters involved in the models. Sometimes, experimental data on the residual strength of composite materials are not available because of limitations on experimental cost and project progress. To solve these issues, a new fatigue life prediction model named the S-N-φ model is proposed. The S-N-φ model does not require the experimental data of residual strength, and the residual strength is only reflected in the theoretical deduction process. The S-N-φ model can clearly explain the probability characteristic of fatigue life because both initial strength and cyclic stress are considered. The S-N-φ model is verified by a set of experimental data of composite laminates. The results show that the S-N-φ model is more accurate than the widely used classical S-N curve model, and the probability characteristic of fatigue life predicted by using the S-N-φ model agrees well with the experimental data.http://dx.doi.org/10.1063/5.0164864
spellingShingle Hai An
Weitao Zhao
Fatigue life prediction for composite materials based on the S-N-φ model
AIP Advances
title Fatigue life prediction for composite materials based on the S-N-φ model
title_full Fatigue life prediction for composite materials based on the S-N-φ model
title_fullStr Fatigue life prediction for composite materials based on the S-N-φ model
title_full_unstemmed Fatigue life prediction for composite materials based on the S-N-φ model
title_short Fatigue life prediction for composite materials based on the S-N-φ model
title_sort fatigue life prediction for composite materials based on the s n φ model
url http://dx.doi.org/10.1063/5.0164864
work_keys_str_mv AT haian fatiguelifepredictionforcompositematerialsbasedonthesnphmodel
AT weitaozhao fatiguelifepredictionforcompositematerialsbasedonthesnphmodel