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An improved fatigue life prediction model based on loading sequence
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Qiwen Xue, Xiuyun Du
Railway Sciences | 2022, 1(1) : 90 - 97
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Railway Sciences | 2022, 1(1): 90-97
Research paper
An improved fatigue life prediction model based on loading sequence
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Qiwen Xue, Xiuyun Du
Affiliations
  • Dalian Jiaotong University, Dalian, China
Published: 2022-05-10 doi: 10.1108/RS-04-2022-0015
Outline
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Purpose

In view of the difficulty in determining the key parameters d in the Corten-Dolan model, based on the introduction of small loads, damage degrees and stress states to the Corten-Dolan model and the existing improved model, the sequential effects of the adjacent two-stage load were further considered.

Design/methodology/approach

Two improved Corten-Dolan models were established on the basis of modifying the parameter d by two different methods, namely, increasing stress ratio coefficient as well as considering the effects of loading sequence and damage degree as independent influencing factors respectively. According to the test data of the welded joints of common materials (standard 45 steel), alloy materials (standard 16Mn steel) and Q235B steel, the validity and feasibility of the above two improved models for fatigue life prediction were verified.

Findings

Results show that, compared with the traditional Miner model and the existing Corten-Dolan improved model, the two improved models have higher prediction accuracy in the fatigue life prediction of welding materials whether under two-stage load or multi-stage load.

Originality/value

Because the mathematical expressions of the models are relatively simple and need no multi-layer iterative calculation, it is convenient to predict the fatigue life of welded structure in practical engineering.

Loading sequence  /  Corten-Dolan model  /  Fatigue life  /  Accumulated damage  /  Parameter correction  /  Welding material
Qiwen Xue, Xiuyun Du. An improved fatigue life prediction model based on loading sequence[J]. Railway Sciences, 2022 , 1 (1) : 90 -97 . DOI: 10.1108/RS-04-2022-0015
  • the National Natural Science Foundation of China(10802015)
  • the Joint Fund of Natural Science Foundation of Liaoning Province(2015020119)
  • the Liaoning Province Graduate Education and Teaching Reform Research Project(2017)
  • the Liaoning Province Transformation and the Innovation and Entrepreneurship Education Project(2017)
Year 2022 volume 1 Issue 1
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Article Info
doi: 10.1108/RS-04-2022-0015
  • Receive Date:2022-01-02
  • Online Date:2026-06-11
  • Published:2022-05-10
Article Data
Affiliations
History
  • Received:2022-01-02
  • Revised:2022-01-25
  • Accepted:2022-04-14
Funding
the National Natural Science Foundation of China(10802015)
the Joint Fund of Natural Science Foundation of Liaoning Province(2015020119)
the Liaoning Province Graduate Education and Teaching Reform Research Project(2017)
the Liaoning Province Transformation and the Innovation and Entrepreneurship Education Project(2017)
Affiliations
    Dalian Jiaotong University, Dalian, China

Corresponding:

Qiwen Xue can be contacted at:
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Citations
表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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