Semi-implicit hybrid finite volume/finite element method for the GPR model of continuum mechanics
<|reference_start|>Semi-implicit hybrid finite volume/finite element method for the GPR model of continuum mechanics: We present a new hybrid semi-implicit finite volume / finite element numerical scheme for the solution of incompressible and weakly compressible media. From the continuum mechanics model proposed by Godunov, Peshkov and Romenski (GPR), we derive the incompressible GPR formulation as well as a weakly compressible GPR system. As for the original GPR model, the new formulations are able to describe different media, from elastoplastic solids to viscous fluids, depending on the values set for the model's relaxation parameters. Then, we propose a new numerical method for the solution of both models based on the splitting of the original systems into three subsystems: one containing the convective part and non-conservative products, a second subsystem for the source terms of the distortion tensor and heat flux equations and, finally, a pressure subsystem. In the first stage of the algorithm, the transport subsystem is solved by employing an explicit finite volume method, while the source terms are solved implicitly. Next, the pressure subsystem is implicitly discretised using finite elements. Within this methodology, unstructured grids are employed, with the pressure defined in the primal grid and the rest of the variables computed in the dual grid. To evaluate the performance of the proposed scheme, a numerical convergence analysis is carried out, which confirms the second order of accuracy in space. A wide range of benchmarks is reproduced for the incompressible and weakly compressible cases, considering both solid and fluid media. These results demonstrate the good behaviour and robustness of the proposed scheme in a variety of scenarios and conditions.<|reference_end|>
@article{busto2024semi-implicit,
    title={Semi-implicit hybrid finite volume/finite element method for the GPR
  model of continuum mechanics},
    author={Saray Busto, Laura R'io-Mart'in},
    journal={arXiv preprint arXiv:2407.00823},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.00823},
    primaryClass={math.NA cs.NA}
}