An Optimization Method To Identify Parameters Of Aluminum Alloy Under The Condition Of Hypervelocity Impact
- Paper number
IAC-07-A6.I.14
- Author
Dr. Zhendong Hu, Beijing University of Aeronautics and Astronautics, China
- Coauthor
Hai Huang, Beijing University of Aeronautics and Astronautics, China
- Year
2007
- Abstract
There mainly are two problems with respect to modeling spacecraft structure under the condition of hypervelocity impact, including the algorithm of numerical simulation and the definition of material parameters. Currently SPH (Smooth Particle Hydrodynamic) is the most acceptable algorithm, which has been realized in some commercial softwares, such as Autodyn and Ls-Dyna. In these softwares the Johnson-Cook model or Steinberg model is normally used to describe the material characteristics under high pressure and high strain rate. However it is so difficult to simulate such extreme environment in the lab. In order to obtain material parameters, the traditional method is testing a metal material under common temperature, low pressure and strain rate. Therefore the validity and the reliability of material parameters cannot be ensured. In Johnson-Cook model the yield stress can be expressed as a function , in which five parameters have to be defined, i.e. A, B, n, C, m. In this article, a SRSM (Successive response surface method) optimization method combined the physical experiments with SPH numerical simulation is adopted to acquire these five parameters for aluminum LF6. The process of optimization can be divided into five steps. (1) based on 18 experiments of hypervelocity impact, 5 representative cases with different projectile diameters and impact velocity are selected to build up the numerical simulation model; (2) the initial value of parameters is derived from existing literatures; simultaneously the range of variation is defined; (3) the relative errors between experiments and calculation results are defined as the objective of optimization; (4) the calculation and control programs of optimization are integrated. Parameters and the objective are taken into account in the process of optimization; (5) in order to produce the optimum parameters minimize the objective function by SRSM optimization method. Compared with experiments, the average error of numerical simulation by using previous parameters is 17.8
- Abstract document
- Manuscript document
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