Abstract

To quantify the influence of temperature uncertainty on thermal fatigue life prediction of a shot sleeve in an injection mechanism, an uncertainty analysis method based on a Kriging surrogate model and Monte Carlo simulation (MCS) was proposed. The training samples of the surrogate model were obtained by a finite element simulation, and the response relationships between input variables, such as pouring and preheating temperature, and target variables, such as strain and stress, were constructed by the Kriging surrogate model. The input variables were sampled by the MCS, and the predicted stress and strain parameters were combined with the modified universal slope equation to predict the thermal fatigue life of the shot sleeve. The statistical characteristics of the predicted life were obtained. The comparative analysis results indicate that the predicted life considering temperature uncertainty is more accurate than the deterministically predicted value.

Highlights

  • Squeeze casting is a technology with high efficiency, high yield, and precise forming that is widely used in machinery, automobiles, household appliances, and aerospace industries [1,2]

  • Little research has been conducted to predict the life of the shot sleeve; the shot sleeve and the die-casting die experience similar thermal cyclic loading processes, and both of them are made of H13 steel, so the thermal fatigue life of both can be predicted [6,7]

  • The strain range of the dangerous position of the shot sleeve was obtained by finite element (FE) simulation, and the predicted results were close to the actual production

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Summary

Introduction

Squeeze casting is a technology with high efficiency, high yield, and precise forming that is widely used in machinery, automobiles, household appliances, and aerospace industries [1,2]. For die-casting dies, Lu et al [9] established a thermal fatigue life prediction model of H13 steel reflected by temperature differences based on the modified universal slope equation. Gao et al [23] utilized an MCS to generate random samples and a Kriging surrogate model to approximate a high-order flow field calculation model and successfully analyzed the influence of a blade machining error on compressor performance. After developing a Kriging model and MCS-based method to obtain a large number of sample points’ data, the modified universal slope equation was employed to predict the thermal fatigue life of a shot sleeve. Metals 2021, 11, 1126 the deterministic fatigue life prediction values, the statistical values should achieve h3igohf e13r reliability of shot sleeve

MMeetthhooddoollooggyy The process of uncertainty analysis was as follows:
KKrriiggiinngg SSuurrrrogate Model
Monte Carlo Simulation
Prediction Method of Thermal Fatigue Life
Statistical Characteristic Analysis
Experiment of Injection Mechanism
FE Simulation of Injection Mechanism

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