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Low-cycle fatigue reliability analysis of engine pistons based on PC-Kriging model
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Wei LI1, 2, Liansheng LI1, 2, Zunfeng DU3, Tao FAN3
Journal of Mechanical Strength | 2025, 47(5) : 131 - 139
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Journal of Mechanical Strength | 2025, 47(5): 131-139
• Experimental Research·Testing Technology •
Low-cycle fatigue reliability analysis of engine pistons based on PC-Kriging model
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Wei LI1, 2, Liansheng LI1, 2, Zunfeng DU3, Tao FAN3
Affiliations
  • 1.Weichai Power Company Limited, Weifang 261061, China
  • 2.State Key Laboratory of Engine Reliability, Weifang 261061, China
  • 3.School of Civil Engineering, Tianjin University, Tianjin 300354, China
Published: 2025-05-15 doi: 10.16579/j.issn.1001.9669.2025.05.015
Outline
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Low-cycle fatigue is a typical failure mode of engine pistons. In order to study the influence of multi-source uncertainty factors on the reliability of low-circumference fatigue of pistons and improve the efficiency of the reliability analysis, a new reliability calculation method is constructed based on the polynomial-chaos-based Kriging (PC-Kriging) model and the Monte Carlo simulation (MCS), and the accuracy and efficiency of this method are proved by numerical examples.Taking the piston group structure of a certain diesel engine as the research object, a finite element model of the piston is established based on the thermal-mechanical coupling analysis, and the reliability analysis of the piston for low-cycle fatigue is carried out by using this method, taking into account the critical dimensions, the material properties, and the uncertainty of the load. The results of the reliability analysis show that, compared with the same type of method, this method is more efficient in calculation, requiring only 20+93 finite element calculations, and the probability of fatigue failure is 1.053% when the expected design life of the piston is 1.4×104. The sensitivity analysis shows that, the height of the piston, the piston diameter,the elasticity modulus of the material, and the parameters of the fatigue calculation model have a greater influence on the reliability. The analysis results can provide a guidance for the reliability design of the piston.

Fatigue reliability  /  Piston  /  PC-Kriging model  /  Learning function  /  Sensitivity analysis
Wei LI, Liansheng LI, Zunfeng DU, Tao FAN. Low-cycle fatigue reliability analysis of engine pistons based on PC-Kriging model[J]. Journal of Mechanical Strength, 2025 , 47 (5) : 131 -139 . DOI: 10.16579/j.issn.1001.9669.2025.05.015
Funding
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  • National Natural Science Foundation of China(51109158)
  • Open Foundation of State Key Laboratory of Engine Reliability(skler-202112)
Appendix
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Year 2025 volume 47 Issue 5
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Article Info
doi: 10.16579/j.issn.1001.9669.2025.05.015
  • Receive Date：2023-09-22
  • Online Date：2026-03-19
  • Published：2025-05-15
Article Data
Affiliations
History
  • Received：2023-09-22
  • Revised：2023-11-17
Funding
National Natural Science Foundation of China(51109158)
Open Foundation of State Key Laboratory of Engine Reliability(skler-202112)
Affiliations
    1.Weichai Power Company Limited, Weifang 261061, China
    2.State Key Laboratory of Engine Reliability, Weifang 261061, China
    3.School of Civil Engineering, Tianjin University, Tianjin 300354, China

Corresponding:

DU Zunfeng, E-mail：
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表12种不同金属材料的力学参数
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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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