Abstract
Lithium is an ideal plasma facing material for fusion plasmas due to its low atomic mass, ability to breed tritium fuel and its gettering characteristics. Liners made of lithium are used as magnetic flux conservers, which can be compressed for Magnetized Target Fusion (MTF) applications. Lithium has been extensively examined in the literature aiming at its mechanical properties for its various applications, and yet the knowledge about its mechanical properties is insufficient for the MTF application in two aspects. First, most of the available studies focus on the quasi-static loading cases. Second, the tests in those studies were commonly performed via uniaxial tensile test where the stress state was not representative for the compression loading scenario.
In this paper, we present an approach to estimate parameters that govern lithium’s behavior at high strain rates up to 500 s−1. In our approach, a series of drop-piston experiments were combined with ANSYS LS-DYNA simulation to determine the material parameters. The bi-linear strain hardening model and Johnson-Cook material model were considered in our studies where the former one accounts for the plastic stress-strain relationship and the latter one describes the plastic stress-strain relationship with the strain-rate effects. In our drop-piston experiments, we use high-speed camera imaging and a feature tracking algorithm to record the velocity and extract the piston impact time. A bi-linear strain hardening model was initially used to estimate plastic behavior of lithium. The strain-rate dependent material parameters were then determined using a reverse engineering approach with the help of numerical simulations that reproduce the tests. A series of numerical simulations with different combinations of material parameters were computed to establish the combination of material parameters that best fit the test results.
The proposed material model will be used in the lithium compression experiments for MTF applications, which accounts for the hardening behavior at different strain rates.
Yu Miao, Michael Sexsmith, Soegi Hartono, Claire Preston, Benjamin Tsai, Jean-Sebastien Dick, Nick Sirmas. Accepted submission to the ASME 2024 Pressure Vessels & Piping Conference.
