Fatigue life prediction of cold expansion hole using physics-enhanced data-driven method
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OpenAlex topics: Fatigue and fracture mechanics · Metallurgy and Material Forming · High Temperature Alloys and Creep
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References (62)
Show source-provided references
1. Dynamic investigation of aeroengine high pressure rotor system considering assembly characteristics of bolted joints10.1016/j.engfailanal.2020.104510 ↗
2. Experimental and analytical investigation for fatigue crack growth characteristics of an aero-engine fan disc10.1016/j.ijfatigue.2021.106252 ↗
3. Experimental investigation of grain size effect on fatigue crack growth rate in turbine disc superalloy GH4169 under different temperatures10.1016/j.msea.2016.05.063 ↗
4. The effects of shot peening, laser shock peening and ultrasonic nanocrystal surface modification on the fatigue strength of Inconel 71810.1016/j.msea.2021.141029 ↗
5. Characteristics and formation mechanisms of defects in surface layer of TC17 subjected to high energy shot peening10.1016/j.apsusc.2019.144711 ↗
6. Design of a novel cold expansion tool for deep small holes based on FEM simulations and experimental study10.1007/s00170-024-12953-w ↗
7. Turning/shot peening of nickel-based powder metallurgy superalloy: effect on surface integrity and high-temperature low-cycle fatigue properties10.1016/j.ijfatigue.2022.107291 ↗
8. Investigation on fatigue performance of cold expansion holes of 6061–T6 aluminum alloy10.1016/j.ijfatigue.2016.10.030 ↗
9. Cold expansion technology of connection holes in aircraft structures: a review and prospect10.1016/j.cja.2015.05.006 ↗
10. Effect of cold expansion on high-temperature low-cycle fatigue performance of the nickel-based superalloy hole structure10.1016/j.ijfatigue.2021.106377 ↗
11. Residual stress redistribution in shot peened samples subject to mechanical loading10.1016/j.msea.2014.06.118 ↗
12. Evolution of cold-expanded microstructure with aging temperature and its influence on fatigue performance of hole structure at elevated temperature10.1016/j.jallcom.2023.172562 ↗
13. Goodman · 1919
14. Factor of safety and working stress
15. A study of the effects of cyclic thermal stresses on a ductile metal
16. Fatigue design handbook
17. A stress-strain function for the fatigue of metals
18. Walker K. The effect of stress ratio during crack propagation and fatigue for 2024-T3 and 7075-T6 aluminum. Effects of environment and complex load history on fatigue life 1970;1:1–14.10.1520/STP32032S ↗
19. High-and low-cycle fatigue crack initiation using polycrystal plasticity10.1098/rspa.2003.1258 ↗
20. Fatigue design of structures under thermomechanical loadings10.1046/j.1460-2695.2002.00612.x ↗
21. Experimental and crystal plasticity modelling study on the crack initiation in micro-texture regions of Ti-6Al-4V during high cycle fatigue tests10.1016/j.ijfatigue.2021.106203 ↗
22. Machine learning-based predictions of fatigue life for multi-principal element alloys10.1016/j.scriptamat.2022.115214 ↗
23. A novel machine learning method for multiaxial fatigue life prediction: Improved adaptive neuro-fuzzy inference system10.1016/j.ijfatigue.2023.108007 ↗
24. High-temperature high-cycle fatigue performance and machine learning-based fatigue life prediction of additively manufactured Hastelloy X10.1016/j.ijfatigue.2023.108012 ↗
25. Random-forest (RF) and support vector machine (SVM) implementation for analysis of gene expression data in chronic kidney disease (CKD)
26. Predictability of different machine learning approaches on the fatigue life of additive-manufactured porous titanium structure10.3390/met14030320 ↗
27. Greedy function approximation: a gradient boosting machine10.1214/aos/1013203451 ↗
28. Xgboost: a scalable tree boosting system
29. On the generalization capability of artificial neural networks used to estimate fretting fatigue life10.1016/j.triboint.2023.109222 ↗
30. Fatigue behavior prediction and analysis of shot peened mild carbon steels10.1016/j.ijfatigue.2018.06.004 ↗
31. New neural network-based algorithm for predicting fatigue life of aluminum alloys in terms of machining parameters
32. Physics-informed machine learning10.1038/s42254-021-00314-5 ↗
33. Uncertainty-aware fatigue-life prediction of additively manufactured Hastelloy X superalloy using a physics-informed probabilistic neural network10.1016/j.ress.2023.109852 ↗
34. A physics-informed generative adversarial network framework for multiaxial fatigue life prediction10.1111/ffe.14123 ↗
35. Process-structure multi-objective inverse optimisation for additive manufacturing of lattice structures using a physics-enhanced data-driven method10.1080/17452759.2023.2266641 ↗
36. A physics-informed neural network for creep-fatigue life prediction of components at elevated temperatures10.1016/j.engfracmech.2021.108130 ↗
37. A physics-informed machine learning model for porosity analysis in laser powder bed fusion additive manufacturing10.1007/s00170-021-06640-3 ↗
38. A Paris-law-informed neural fatigue cohesive model and its application to open-hole composite laminates10.1016/j.ijsolstr.2023.112158 ↗
39. A review on superalloys and IN718 nickel-based INCONEL superalloy
40. Interdiffusion of the platinum-group metals in nickel at elevated temperatures10.1016/S1359-6454(03)00105-8 ↗
41. Effect of cooling recrystallization annealing treatment on properties of an initial aged deformed GH4169 superalloy10.1016/j.msea.2021.142232 ↗
42. Effects of surface roughness and notch on fatigue properties for Ti–5Al–2.5 Sn ELI alloy at cryogenic temperatures10.1016/S1468-6996(03)00058-5 ↗
43. Residual stress measurement of new and in-service X70 pipelines by X-ray diffraction method10.1016/j.ndteint.2011.03.003 ↗
44. Microstructural characterization of low temperature plasma-nitrided 316L stainless steel surface with prior severe shot peening10.1016/j.matdes.2016.07.005 ↗
45. Measurement of plastic strain of polycrystalline material by electron backscatter diffraction10.1016/j.nucengdes.2004.11.006 ↗
46. Microstructure, texture and mechanical properties of cyclic expansion–extrusion deformed pure copper10.1016/j.msea.2015.01.003 ↗
47. Zhang · 2012
48. Physics and phenomenology of strain hardening: the FCC case10.1016/S0079-6425(02)00003-8 ↗
49. Dislocations, vacancies and solute diffusion in physical based plasticity model for AISI 316L10.1016/j.mechmat.2008.05.005 ↗
50. Physics based modeling of machining Inconel 718 to predict surface integrity modification10.1016/j.procir.2019.04.150 ↗
51. A physically-based constitutive model for a typical nickel-based superalloy10.1016/j.commatsci.2013.11.003 ↗
52. Flow stress model for IN718 accounting for evolution of strengthening precipitates during thermal treatment10.1016/j.commatsci.2013.10.007 ↗
53. Dislocation theory based constitutive modelling: foundations and applications10.1016/S0924-0136(98)00208-8 ↗
54. The plastic deformation of metals – a dislocation model and its applicability
55. Frost · 1982
56. Moteff J. Correlation of substructure with mechanical properties of plastically deformed reactor structural materials. Progress report, January 1, 1976--June 30, 1977. Cincinnati (OH): Cincinnati Univ., OH (USA). Dept. of Materials Science and Metallurgical; 1977 Mar 15. Report No.: COO-2107-11. Sponsored by the Department of Energy. https://doi.org/10.2172/7317263.10.2172/7317263 ↗
57. A unified physically based constitutive model for describing strain hardening effect and dynamic recovery behavior of a Ni-based superalloy10.1557/jmr.2015.368 ↗
58. Relaxation of residual stresses in a nickel-base superalloy due to dislocation creep
59. Random forests10.1023/A:1010933404324 ↗
60. A tutorial on support vector regression10.1023/B:STCO.0000035301.49549.88 ↗
61. Ridge regression10.1002/wics.14 ↗
62. Yegnanarayana · 2009