A Nonlinear Fatigue Damage Model Based on Equivalent Transformation of Stress

It is rather difficult for engineers to apply many of the fatigue damage models for requiring a knee point, material-dependent coefficient, or extensive testing, and some of them are only validated by a fatigue test of two-stage loading rather than higher-stage loading. In this paper, we propose a new model of fatigue cumulative damage in variable amplitude loading, which just requires the information of the S-N curve determined from the fatigue experiment. Specifically, the proposed model defines a stress equivalent transformation way to translate the damage of one stress to another stress through simple calculation. Experimental data of fatigue including two-, three-, and four-block loading verify the superiority of the proposed model by comparing it with the Miner model and Manson model. The results show that the proposed model can be generalized to any type of loading and presents a better prediction. Therefore, the advantage of the proposed model can be easily used by an engineer.

Creep–Fatigue Experiment and Life Prediction Study of Piston 2A80 Aluminum Alloy

In order to improve the reliability and service life of vehicle and diesel engine, the fatigue life prediction of the piston in a heavy diesel engine was studied by finite element analysis of piston, experiment data of aluminum alloy, fatigue life model based on energy dissipation criteria, and machine learning algorithm. First, the finite element method was used to calculate and analyze the temperature field, thermal stress field, and thermal–mechanical coupling stress field of the piston, and determine the area of heavy thermal and mechanical load that will affect the fatigue life of the piston. Second, based on the results of finite element calculation, the creep–fatigue experiment of 2A80 aluminum alloy was carried out, and the cyclic response characteristics of the material under different loading conditions were obtained. Third, the fatigue life prediction models based on energy dissipation criterion and twin support vector regression are proposed. Then, the accuracy of the two models was verified using experiment data. The results show that the model based on the twin support vector regression is more accurate for predicting the material properties of aluminum alloy. Based on the established life prediction model, the fatigue life of pistons under actual service conditions is predicted. The calculation results show that the minimum fatigue life of the piston under plain condition is 2113.60 h, and the fatigue life under 5000 m altitude condition is 1425.70 h.

Pseudo-transient 3D Conjugate Heat Transfer Simulation and Lifetime Prediction of a Rocket Combustion Chamber

Rocket engine nozzle structures typically fail after a few engine cycles due to the extreme thermomechanical loading near the nozzle throat. In order to obtain an accurate lifetime prediction and to increase the lifetime, a detailed understanding of the thermomechanical behavior and the acting loads is indispensable. The first part is devoted to a thermally coupled simulation (conjugate heat transfer) of a fatigue experiment. The simulation contains a thermal FEM model of the fatigue specimen structure, RANS simulations of nine cooling channel flows and a Flamelet-based RANS simulation of the hot gas flow. A pseudo-transient, implicit Dirichlet–Neumann scheme is utilized for the partitioned coupling. A comparison with the experiment shows a good agreement between the nodal temperatures and their corresponding thermocouple measurements. The second part consists of the lifetime prediction of the fatigue experiment utilizing a sequentially coupled thermomechanical analysis scheme. First, a transient thermal analysis is carried out to obtain the temperature field within the fatigue specimen. Afterwards, the computed temperature serves as input for a series of quasi-static mechanical analyses, in which a viscoplastic damage model is utilized. The evolution and progression of the damage variable within the regions of interest are thoroughly discussed. A comparison between simulation and experiment shows that the results are in good agreement. The crucial failure mode (doghouse effect) is captured very well.