1. Basis for constructing fatigue life prediction model
The fatigue life prediction model of die-cast aluminum accessories is based on an in-depth understanding of its material properties, structural stress distribution and loading conditions. First, the basic mechanical properties parameters of die-cast aluminum alloys, such as elastic modulus, yield strength, tensile strength, etc., are obtained through material mechanics testing. These parameters are important bases for subsequent stress analysis and fatigue calculation. Then, the stress distribution of die-cast aluminum accessories under actual working loads is simulated using the finite element analysis method. Considering the internal defects (such as pores, shrinkage, etc.) that may be caused by the die-casting process, defect parameters are introduced into the model to more accurately reflect the actual stress state of the accessories. For example, for die-cast aluminum accessories of automobile engines that are subjected to alternating loads, by simulating the stress changes under different working conditions such as engine start, operation, and stop, a stress-time history curve is constructed to provide a data basis for fatigue life prediction.
2. Types and algorithms of fatigue life prediction models
Common fatigue life prediction models for die-cast aluminum accessories include models based on stress-life (S-N) curves and models based on strain-life (ε-N) curves. The S-N curve model is suitable for low stress and high cycle fatigue. It fits the fatigue life relationship of materials under different stress levels through a large amount of fatigue test data. In the calculation, the fatigue damage is calculated using the Miner linear cumulative damage theory based on the maximum stress value obtained by finite element analysis and the S-N curve. The ε-N curve model is more suitable for dealing with high stress and low cycle fatigue problems. It takes into account the strain characteristics of the material in the plastic deformation stage. In terms of algorithm, it is necessary to calculate the plastic strain amplitude of the accessories during cyclic loading, and then determine the fatigue life based on the ε-N curve. For example, die-cast aluminum accessories in the aerospace field are often subjected to complex and variable high stress loads. The model based on the strain-life curve can more accurately predict their fatigue life.
3. Implementation steps of reliability verification method
The reliability verification method must first determine the number of samples to be verified and the sampling method. For die-cast aluminum accessories, the appropriate sample size can be determined based on factors such as batch size and production process stability. Then, the extracted samples are subjected to fatigue tests simulating actual working conditions. During the test, high-precision sensors are used to monitor the stress, strain, and initiation and expansion of fatigue cracks in the accessories. For example, when conducting reliability verification of die-cast aluminum accessories for automobile wheels, the wheel hub is installed on a dedicated fatigue test bench to simulate various stress conditions during vehicle driving, such as radial force, lateral force, etc. At the same time, non-destructive testing technologies (such as ultrasonic testing, magnetic particle testing, etc.) are used to regularly test the accessories in the test and record the development process of fatigue damage. According to the test results, the actual fatigue life of the accessories is calculated and compared with the results of the prediction model.
4. Optimization and application of models and verification methods
With the development of materials science and testing technology, the fatigue life prediction model and reliability verification method of die-cast aluminum accessories need to be continuously optimized. On the one hand, the accuracy of the prediction model can be improved by introducing more advanced material constitutive models and multi-scale analysis methods. For example, considering the influence of microstructure on fatigue performance, a prediction model combining micro-macro is established. On the other hand, more sophisticated test equipment and more comprehensive monitoring methods are used in reliability verification, such as in-situ observation technology, to observe the microscopic behavior of fatigue cracks in real time. In practical applications, accurate fatigue life prediction models and reliable verification methods help die-cast aluminum accessories optimize structure and select materials reasonably in the design stage, control quality and improve yield rate in the production stage, formulate scientific maintenance strategies and ensure safe operation of equipment in the use stage, thereby promoting the wider application of die-cast aluminum accessories in many fields such as automobiles, aerospace, and machinery manufacturing.
