Abstract
Under conditions where a product is subjected to extreme mechanical loading over a very short time period, the strain rate has considerable influence on the behaviour of the product’s material. To simulate the behaviour of the material accurately under these loading conditions, the appropriate strain-rate parameters for the selected material model should be used. The aim of this paper is to present a quick method for easily determining the appropriate strain-rate-dependent parameter values of the selected material model. The optimisation procedure described in the article combines the design-of-experiment (DoE) technique, finite-element simulations, modelling a response surface and an evolutionary algorithm. First, a non-standard dynamic experiment was designed to study the behaviour of thin, flat, metal sheets during an impact. The experimental data from this dynamic and the conventional tensile experiments for mild steel were the basis for the determination of the Johnson-Cook material model parameters. The paper provides a comparison of two optimisation processes with different DoE techniques and with three different optimisation algorithms (one traditional and two metaheuristic). The performances of the presented method are compared, and the engineering applicability of the results is discussed. The identified parameter values, which were estimated with the presented procedure, are very similar to those from the literature. The paper shows how the application of a properly designed plan of simulations can significantly reduce the simulation time, with only a minor influence on the estimated parameters. Furthermore, it can be concluded that in some cases the traditional optimisation method is as good as the two metaheuristic methods. Finally, it was proven that experiments with different strain rates must be carried out when estimating the corresponding material parameters.
Highlights
The implementation of complex numerical simulations together with design-of-experiment (DoE)methods can have many positive effects on the R&D process
To be able to include in the optimisation process the results from the calculations with error termination, we set their values to the maximum
The Taguchi experimental design was combined with the finite-element code LS-DYNA, the modelled response surface and three optimisation algorithms to estimate the material parameters based on the results of a standard static tensile test and a non-standard impact test between a ball and a thin sheet
Summary
The implementation of complex numerical simulations together with design-of-experiment (DoE). Methods can have many positive effects on the R&D process. It can reduce costs, partially optimise the design of the product or its effectiveness and reliability even before the prototype is built and tested. Finite-element simulations play an important role in these situations, as they can be used to reproduce the behaviour of the product under various operating conditions. Nowadays, they are mostly used to analyse the load-bearing capacity or the resistance of a structure under extreme loading conditions in the early stages of the R&D process. It uses a statistical methodology to analyse the data under all possible conditions within the selected limits and can generate the required information with the minimum number of experiments [1,2,3]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
