An efficient algorithm for modelling progressive damage accumulation in disordered materials

This paper presents an efficient algorithm for the simulation of progressive fracture in disordered quasi-brittle materials using discrete lattice networks. The main computational bottleneck involved in modelling the fracture simulations using large discrete lattice networks stems from the fact that a new large set of linear equations needs to be solved every time a lattice bond is broken. Using the present algorithm, the computational complexity of solving the new set of linear equations after breaking a bond reduces to a simple triangular solves (forward elimination and backward substitution) using the already Cholesky factored matrix. This algorithm using the direct sparse solver is faster than the Fourier accelerated iterative solvers such as the preconditioned conjugate gradient (PCG) solvers, and eliminates the critical slowing down associated with the iterative solvers that is especially severe close to the percolation critical points. Numerical results using random resistor networks for modelling the fracture and damage evolution in disordered materials substantiate the efficiency of the present algorithm. In particular, the proposed algorithm is especially advantageous for fracture simulations wherein ensemble averaging of numerical results is necessary to obtain a realistic lattice system response.