Efficient algorithm for computing large scale systems of differential algebraic equations
For researchers and engineers dealing with large-scale DAEs, this work offers a potentially efficient approach, but the lack of quantitative results makes its significance unclear.
The paper presents an efficient algorithm for solving large-scale, sparse, high-index differential algebraic equations (DAEs) by combining shortest augmenting path for maximum value transversal, block triangular forms, and an extended signature matrix method with block fixed point iteration. The algorithm is demonstrated on nontrivial problems, but no concrete numerical results or comparisons are provided.
In many mathematical models of physical phenomenons and engineering fields, such as electrical circuits or mechanical multibody systems, which generate the differential algebraic equations (DAEs) systems naturally. In general, the feature of DAEs is a sparse large scale system of fully nonlinear and high index. To make use of its sparsity, this paper provides a simple and efficient algorithm for computing the large scale DAEs system. We exploit the shortest augmenting path algorithm for finding maximum value transversal (MVT) as well as block triangular forms (BTF). We also present the extended signature matrix method with the block fixed point iteration and its complexity results. Furthermore, a range of nontrivial problems are demonstrated by our algorithm.