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    An Efficient Block Circulant Preconditioner For Simulating Fracture Using Large Fuse Networks

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    {\it Critical slowing down} associated with the iterative solvers close to the critical point often hinders large-scale numerical simulation of fracture using discrete lattice networks. This paper presents a block circlant preconditioner for iterative solvers for the simulation of progressive fracture in disordered, quasi-brittle materials using large discrete lattice networks. The average computational cost of the present alorithm per iteration is O(rslogs)+delopsO(rs log s) + delops, where the stiffness matrix A{\bf A} is partioned into rr-by-rr blocks such that each block is an ss-by-ss matrix, and delopsdelops represents the operational count associated with solving a block-diagonal matrix with rr-by-rr dense matrix blocks. This algorithm using the block circulant preconditioner is faster than the Fourier accelerated preconditioned conjugate gradient (PCG) algorithm, and alleviates the {\it critical slowing down} that is especially severe close to the critical point. Numerical results using random resistor networks substantiate the efficiency of the present algorithm.Comment: 16 pages including 2 figure
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