Abstract：The most shining advantage of the data-driven computational mechanics is directly embedding the material data into mechanical simulations. Its basic idea is to assign to each integration point the optimal stress-strain data from the database. However, the original data searching process during the data-driven computing is time-consuming in cases with high-dimensional and high-density databases. This work aims to propose a new hierarchical data searching scheme to improve the data-driven computing efficiency. To this end, the original database is pre-processed to be a multi-layer tree data structure firstly, in which the amount of data decreases layer by layer. Then the tree search algorithm is adopted to narrow down the data search and to reduce the time cost for data searching. Within this data searching scheme, a benchmark test is considered to discuss the influences of the number of database layers and different data allocation settings on the computing efficiency. It is found that the computation time decreases significantly with the increase of database layers and allocating data uniformly for each sub-database allows to further improve the computing efficiency.
2021, Vol. 42 
