Probabilistic fatigue life prediction model of natural rubber components based on the expanded sample data
Bibliographic record
Abstract
No abstract is available for this record. The assistant can identify its topic from the title, but cannot infer the study’s results.
Source: Not provided · Quality: missing
Research context
OpenAlex topics: Fatigue and fracture mechanics · Infrastructure Maintenance and Monitoring · Structural Health Monitoring Techniques
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (39)
Show source-provided references
1. Experiment and modeling of uniaxial tension fatigue performances for NRs [J]10.1016/j.matdes.2014.01.035 ↗
2. Dynamic analysis and design calculation methods for powertrain methods for powertrain mounting systems [J]
3. Recent advances on fatigue of rubber after the literature survey by Mars and Fatemi in 2002 and 2004[J]
4. Fatigue crack growth of filled rubber under constant and variable amplitude loading conditions [J]10.1111/j.1460-2695.2007.01143.x ↗
5. A method for modelling of fatigue life for rubbers and rubber isolators [J]10.1111/ffe.12145 ↗
6. A multiaxial fatigue life prediction method for metallic material under combined random vibration loading and mean stress loading in the frequency domain [J]10.1016/j.ijfatigue.2021.106235 ↗
7. A literature survey on fatigue analysis approaches for rubber [J]10.1016/S0142-1123(02)00008-7 ↗
8. Fatigue crack growth analysis of different adhesive systems: Effects of mode munity and load level [J]10.1111/ffe.13145 ↗
9. Prediction of the fatigue life of natural rubber composites by artificial neural network approaches [J]10.1016/j.matdes.2013.12.044 ↗
10. Fatigue life prediction of a rubber mount based on test of material properties and finite element analysis [J]10.1016/j.engfailanal.2009.03.008 ↗
11. Displacement-controlled fatigue testing of rubber is not strain-controlled [J]10.1016/j.ijfatigue.2020.106083 ↗
12. Fatigue damage investigation of ultra-large tire components [J]10.1016/j.ijfatigue.2018.07.009 ↗
13. Study on the Effect of Different Damage Parameters on the Predicting Fatigue Life of Rubber Isolators [J]10.3901/JME.2016.02.116 ↗
14. Prediction of fatigue properties of natural rubber based on the descriptions of the cracks population and of the dissipated energy10.1016/j.polymertesting.2017.01.015 ↗
15. Rubber fatigue life prediction using a random forest method and nonlinear cumulative fatigue damage model [J]10.1002/app.48519 ↗
16. Multiaxial fatigue of rubber: Part II: experimental observations and life predictions [J]10.1111/j.1460-2695.2005.00895.x ↗
17. Probabilistic modeling of uncertainties in fatigue reliability analysis of turbine bladed disks [J]
18. An engineering method for reliability analyses of mechanical structures for long fatigue lives [J]10.1016/S0951-8320(97)00012-4 ↗
19. A probabilistic-based airframe integrity management model [J]10.1016/j.ress.2008.10.010 ↗
20. Determination of fatigue life for low probability of failure for different stress levels using 3-parameter Weibull distribution [J]10.1016/j.ijfatigue.2020.106080 ↗
21. Fatigue Life Reliability Evaluation in a High-Speed Train Bogie Frame Using Accelerated Life and Numerical Test [J]10.1016/j.ress.2019.03.033 ↗
22. Fatigue life prediction of ZE41A magnesium alloy using Weibull distribution [J]10.1016/j.matdes.2008.01.001 ↗
23. Reliability assessment for very few failure data and weibull distribution [J]
24. Uncertainty quantification of fatigue S-N curves with sparse data using hierarchical Bayesian data augmentation [J]10.1016/j.ijfatigue.2020.105511 ↗
25. Advanced Bayesian Estimation of Weibull Early Life Failure Distributions [J]10.1002/qre.1577 ↗
26. Liu G S, Wei P T, Chen K R, et al. Polymer gear contact fatigue reliability evaluation with small data set based on machine learning [J]. Journal of Computational Design and Engineering, 2022, 9(2): 583-597.10.1093/jcde/qwac020 ↗
27. Daiso Z H, Li Z J, Jiao Y J, et al. Reliability assessment based on BP neural network for relay protection system with a few failure data samples [J]. Electric Power Automation Equipment, 2014, 34(11): 129-134.
28. SVM Based Parameter Estimation of Relay Protection Reliability with Small Samples [J]
29. Thermo-mechanical behavior of elastomers with dynamic covalent bonds [J]
30. Flexural fatigue life prediction of a tooth V-belt made of fiber reinforced rubber [J]10.1016/j.ijfatigue.2018.02.025 ↗
31. A method to develop a unified fatigue life prediction model for NRs under uniaxial loads [J]10.1111/ffe.12081 ↗
32. Fatigue life analysis and predictions for NR and SBR under variable amplitude and multiaxial loading conditions [J]10.1016/j.ijfatigue.2007.08.015 ↗
33. A framework for fatigue life prediction of materials under the multi-level cyclic loading [J]10.1016/j.engfailanal.2021.105496 ↗
34. Fatigue Reliability and Hazard Assessment of Road Load Strain Data for Determining the Fatigue Life Characteristics [J]10.1016/j.engfailanal.2021.105314 ↗
35. Machine-learning-based reliability evaluation framework for power distribution networks [J]10.1049/iet-gtd.2019.1520 ↗
36. Support vector machine techniques for nonlinear equalization [J]10.1109/78.875477 ↗
37. Comparing support vector machines with Gaussian kernels to radial basis function classifiers [J]10.1109/78.650102 ↗
38. An Easy-to-Implement Hysteresis Model Identification Method Based on Support Vector Regression [J]10.1109/TMAG.2017.2736164 ↗
39. Fatigue of carbon cord-rubber composites: Effect of frequency, R ratio and lifetime prediction using constant life models [J]