تجزیه و تحلیل حساسیت از معیار شکست های کمی بر اساس نتایج حاصل از آزمون SICO

Results of numerical simulation of the SICO test, including the resistance heating of samples and metal flow during the test, are described in this paper. The main goal of the work is the determination of the sensitivity of fracture criteria with respect to the test parameters: temperature, die velocity and material parameters—strain rate sensitivity, hardening coefficient, hardening exponent and temperature sensitivity coefficient. It was shown in earlier research that sensitivity analysis allowed the determination of the extent that the value of the fracture criterion changes with change of the SICO test parameters. Beyond this, the sensitivity analysis reveals which parameters interact with each other. This information is crucial for the inverse analysis if larger numbers of parameters are optimized. The present work is an extension of the authors’ earlier research and the variance-based method with correlation ratios is used in the analysis. The results of this analysis contribute to development of more efficient optimization algorithms in the inverse method.

Formulation of a quantitative fracture criterion [1] for materials subjected to plastic deformation is essential for modeling of forming processes for materials characterized by low plasticity. In order to avoid the fracture during forming, it is necessary to determine precisely the material crack resistance and to use this knowledge to design process technological parameters, which prevent the fracture. Criteria based on computing stress and strain history, which are commonly used [1] and [2], give relatively good qualitative results but quantitative accuracy is often insufficient. It is generally due to difficulties with the determination of material parameters in fracture criteria. The problem of formulating a complex criterion, which gives qualitatively good results, is still open. This work is a continuation of earlier research on the design of the new fracture criterion in plastic processes, in which the SICO test was used as material testing method [3]. The SICO test [4], [5] and [6] is commonly used to determine the tendency of materials to fracture during hot forming. The test is a hot workability technique with good reproducibility and the possibility of employment of large strains. Due to inhomogeneities of temperature, stress and strain fields in the test, quantitative interpretation produces certain problems [5]. A suggestion is made that application of the inverse analysis with a finite element solver for simulation of the SICO test is able to obtain values of the material parameters independently of the inhomogeneity of strains, stresses and temperatures. This suggestion is further explored in the present work. The particular objective of the work is determination of the sensitivity of the fracture criterion function with respect to the test parameters and properties of deformed material and investigation of correlation between them. The results of performed analysis is giving the grounds to design the critical value of fracture criterion as a function of appropriate test and material parameters. The critical value of the fracture criterion is responsible for the start of the fracture process.

Correlation analysis shows whether and how strongly pairs of parameters are related. Sensitivity is the measure of the variation of the fracture criteria function value when parameters are disturbed. The general conclusion from the work is that, in the inverse analysis of the SICO test, more accurate quantitative prediction of fracture initiation will be obtained when the critical value C is introduced into the finite element code as a function of process parameters. Thus, the suggestion is made that the critical value of the criterion should be a function of the temperature, hardening coefficient, temperature sensitivity coefficient and strain rate sensitivity. The effect of the die velocity and the hardening exponent is negligible. Strain exponent can be eventually added to the list of the independent variables. Analysis of the correlation results shows that all criteria are correlated with the temperature sensitivity coefficient. Latham and Cockroft and Oyane criteria are correlated with the temperature. Remaining combinations of the fracture criteria and selected independent variables are less correlated.