Crack growth in high strength mooring line steel under variable amplitude loading

系泊 结构工程 巴黎法 海底管道 振幅 航程(航空) 振动疲劳 工程类 海洋工程 断裂力学 裂缝闭合 岩土工程 有限元法 物理 航空航天工程 量子力学
作者
Mads Aursand,Gunnstein T. Frøseth,P.J. Haagensen,Bjørn Skallerud
出处
期刊:Marine Structures [Elsevier BV]
卷期号:93: 103534-103534 被引量:9
标识
DOI:10.1016/j.marstruc.2023.103534
摘要

Mooring lines are of key importance for the safe and reliable operation of numerous floating offshore structures. Due to the constantly changing wind and wave conditions acting on such structures, any fatigue crack growth in a mooring line will occur under cyclic loading of distinctly variable amplitude. This paper considers a long-term load history for mooring lines on a North Sea offshore platform. For fatigue testing purposes, a characteristic load sequence representing the actual load history in a condensed and simplified form is developed and presented. Fatigue crack growth rate test results for a grade R4 high strength mooring chain steel subjected to this variable amplitude load sequence is furthermore presented, including tests performed in air as well as under free corrosion conditions in artificial seawater. Based on comparison testing performed under variable- and constant amplitude conditions, the validity of a linear damage rule hypothesis for stable crack growth under the characteristic load sequence is investigated. This damage rule converts the load spectrum to an equivalent constant load range, making it a potentially useful tool for estimating fatigue crack growth in mooring chains when test data for a representative characteristic load sequence are unavailable. Results from the comparison testing are used to show that under stable fatigue crack growth conditions, while subjected to the characteristic load sequence developed for this offshore platform, the linear damage rule can be a reasonable assumption.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
zyz完成签到 ,获得积分10
1秒前
Leo000007完成签到,获得积分10
1秒前
我是老大应助彩虹大侠采纳,获得10
1秒前
Manso完成签到,获得积分10
2秒前
2秒前
jam发布了新的文献求助10
2秒前
长情的香魔完成签到 ,获得积分10
2秒前
3秒前
嘉心糖应助科研通管家采纳,获得100
3秒前
Lucas应助额外采纳,获得10
4秒前
桐桐应助科研通管家采纳,获得30
4秒前
共享精神应助科研通管家采纳,获得30
4秒前
传奇3应助科研通管家采纳,获得10
4秒前
SWEETYXY应助科研通管家采纳,获得10
4秒前
4秒前
RenHP发布了新的文献求助10
4秒前
4秒前
5秒前
研友_VZG7GZ应助科研通管家采纳,获得10
5秒前
5秒前
5秒前
情怀应助科研通管家采纳,获得10
5秒前
6秒前
进步完成签到,获得积分10
6秒前
研友_VZG7GZ应助科研通管家采纳,获得10
6秒前
6秒前
AllenLau1031完成签到,获得积分10
6秒前
行走的荷尔蒙应助唔昂wang采纳,获得30
6秒前
美好斓发布了新的文献求助10
7秒前
求助吃草小河马完成签到,获得积分10
7秒前
8秒前
曹健应助michael采纳,获得10
8秒前
8秒前
云扶摇完成签到,获得积分10
8秒前
9秒前
11秒前
渴望者发布了新的文献求助10
11秒前
超级大电影完成签到,获得积分10
11秒前
404nf发布了新的文献求助10
13秒前
方方发布了新的文献求助10
15秒前
高分求助中
Markov Chain Monte Carlo 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Common Foundations of American and East Asian Modernisation: From Alexander Hamilton to Junichero Koizumi 5000
How to Use Machine Learning in Chemistry: An Introduction 1000
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Discerning Saints: Moralization of Intrinsic Motivation and Selective Prosociality at Work 500
Handbuch Trainingswissenschaft – Trainingslehre 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7581442
求助须知:如何正确求助?哪些是违规求助? 9160633
关于积分的说明 19599852
捐赠科研通 7163713
什么是DOI,文献DOI怎么找? 3266005
关于科研通互助平台的介绍 2430925
邀请新用户注册赠送积分活动 2257067