A strain-interfaced digital twin solution for corner fatigue crack growth using Bayesian inference
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OpenAlex topics: Fatigue and fracture mechanics · Structural Health Monitoring Techniques · Gear and Bearing Dynamics Analysis
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References (51)
Show source-provided references
1. Industrial Internet of Things and its applications in industry 4.0: state of the art10.1016/j.comcom.2020.11.016 ↗
2. Fatigue weld crack detection using distributed fiber optic strain sensing10.1016/j.ijfatigue.2023.107851 ↗
3. Digital twin-driven framework for fatigue life prediction of welded structures considering residual stress10.1016/j.ijfatigue.2024.108144 ↗
4. Airframe digital twin technology adaptability assessment and technology demonstration10.1016/j.engfracmech.2019.106793 ↗
5. Probabilistic methods for risk assessment of airframe digital twin structures10.1016/j.engfracmech.2019.106674 ↗
6. An overview of fatigue in aircraft structures10.1111/ffe.12631 ↗
7. Fatigue and crack-growth analyses of riveted lap-joints in a retired aircraft10.1016/j.ijfatigue.2015.04.010 ↗
8. Fatigue crack growth modeling of attachment lugs10.1016/j.ijfatigue.2013.03.016 ↗
9. Analysis of fatigue crack growth in an attachment lug based on the weight function technique and the UniGrow fatigue crack growth model10.1016/j.ijfatigue.2011.07.006 ↗
10. Digitized measurements of the shape of corner cracks at fastener holes10.1016/0013-7944(83)90023-1 ↗
11. Fatigue crack growth of a corner crack at the edge of a hole10.1016/j.ijfatigue.2020.105699 ↗
12. Optimization-improved thermal–mechanical simulation of welding residual stresses in welded connections10.1111/mice.13136 ↗
13. A local digital twin approach for identifying, locating and sizing cracks in CHS X-joints subjected to brace axial loading10.1016/j.engstruct.2023.117085 ↗
14. Enhanced real-time crack monitoring and updating in welded structural components with limited measurement data10.1016/j.ymssp.2023.110403 ↗
15. An adaptive learning approach to determine and update crack sizes from strain relaxation data for welded plate joints10.1016/j.engfracmech.2021.108165 ↗
16. A non-contact approach to measure JR curve for side-grooved specimens using digital image correlation10.1016/j.tafmec.2022.103549 ↗
17. Digital Twin-driven framework for fatigue life prediction of steel bridges using a probabilistic multiscale model: Application to segmental orthotropic steel deck specimen10.1016/j.engstruct.2021.112461 ↗
18. A digital twin approach toward unlocking elasto-plastic fatigue crack growth rates under negative load ratios
19. Digital twin-driven remaining useful life prediction for gear performance degradation: A review10.1115/1.4049537 ↗
20. Mechanics and micromechanics of fatigue crack propagation
21. A path independent integral and the approximate analysis of strain concentration by notches and cracks10.1115/1.3601206 ↗
22. The J-integral applied to cyclic loading10.1016/0013-7944(75)90025-9 ↗
23. ASTM E1820–23b Standard Test Method for Measurement of Fracture Toughness
24. “Some further results of J-integral analysis and estimates”, in progress in flaw growth and fracture toughness testing
25. Fracture resistance curve for single edge notched tension specimens under low cycle actions10.1016/j.engfracmech.2019.02.001 ↗
26. Resistance and strain during tearing for tubular joints under reversed axial actions10.1016/j.jcsr.2023.108328 ↗
27. Dynamic bayesian network for aircraft wing health monitoring digital twin10.2514/1.J055201 ↗
28. Three-dimensional fatigue crack growth based method for fatigue reliability of metallic materials10.1016/j.ijfatigue.2023.107697 ↗
29. Bayesian model updating and prognosis of fatigue crack growth10.1016/j.engstruct.2012.06.012 ↗
30. Multi-fidelity optimization of metal sheets concerning manufacturability in deep-drawing processes10.1007/s00158-023-03631-8 ↗
31. A hierarchical kriging approach for multi-fidelity optimization of automotive crashworthiness problems10.1007/s00158-022-03211-2 ↗
32. Bayesian-based probabilistic fatigue crack growth evaluation combined with machine-learning-assisted GPR10.1016/j.engfracmech.2020.106933 ↗
33. Bayesian prediction and probabilistic model of fatigue cracks in steel structures10.1016/j.engfailanal.2019.04.061 ↗
34. Dassault Systèmes Simulia Corp, Abaqus/CAE User’s Manual, Version 2019. 2019.
35. Low cycle fatigue test and enhanced lifetime estimation of high-strength steel S550 under different strain ratios10.1016/j.marstruc.2018.06.011 ↗
36. Ramberg · 1943
37. LCF behavior of 2024AA under uni-and biaxial loading taking into account creep pre-deformation10.1016/j.engfracmech.2024.109867 ↗
38. ASTM E647–23a standard test method for measurement of fatigue crack growth rates
39. Williams · 2006 · vol. 2
40. Cross-validatory choice and assessment of statistical predictions10.1111/j.2517-6161.1974.tb00994.x ↗
41. Energy release rate along a three-dimensional crack front in a thermally stressed body10.1007/BF00034019 ↗
42. The virtual crack extension method for nonlinear material behavior10.1016/0045-7825(77)90023-8 ↗
43. MathWorks, MATLAB R2020b Documentation. 2020.
44. Hierarchical kriging model for variable-fidelity surrogate modeling10.2514/1.J051354 ↗
45. Kriging hyperparameter tuning strategies10.2514/1.34822 ↗
46. An efficient constraint handling method for genetic algorithms10.1016/S0045-7825(99)00389-8 ↗
47. Neural networks and physical systems with emergent collective computational abilities10.1073/pnas.79.8.2554 ↗
48. A comparison of three methods for selecting values of input variables in the analysis of output from a computer code10.1080/00401706.2000.10485979 ↗
49. A uniform volume-based fatigue indicator for high-and low-cycle assessment of notched components10.1016/j.ijfatigue.2020.106048 ↗
50. Overload effect on the fatigue crack propagation in large-scale tubular joints10.1111/ffe.12013 ↗
51. BSI Group, “BS 7910:2019 Guide to methods for assessing the acceptability of flaws in metallic structures.” BSI Group, 2019.