Memory-distributed level set-based inverse homogenisation of three-dimensional piezoelectric materials
<|reference_start|>Memory-distributed level set-based inverse homogenisation of three-dimensional piezoelectric materials: In this paper we use level set-based topology optimisation to design three-dimensional periodic piezoelectric materials with enhanced properties. Our methodology is fully memory-distributed and written in Julia using the package GridapTopOpt. We compare and assess several existing iterative solvers with respect to their weak scalability and find that an approximate Schur complement preconditioned GMRES method demonstrates the best performance and scalability for solving the piezoelectric homogenisation equations. We use the developed techniques to computationally design high-resolution piezoelectric metamaterials with enhanced stiffness and piezoelectric properties that yield new insights into material design for sensor, hydrophone, and actuator applications. We suggest two robust structures with simple geometric features that exhibit enhanced piezoelectric properties several times larger than those of the base material. We find that level set-based topology optimisation is well suited to problems involving piezoelectricity and has the advantage of avoiding large regions of intermediate density material.<|reference_end|>
@article{wegert2024memory-distributed,
    title={Memory-distributed level set-based inverse homogenisation of
  three-dimensional piezoelectric materials},
    author={Zachary J. Wegert, Anthony P. Roberts, Vivien J. Challis},
    journal={arXiv preprint arXiv:2410.03148},
    year={2024},
    archivePrefix={arXiv},
    eprint={2410.03148},
    primaryClass={cs.CE cs.DC}
}