For the simulation of complex equilibrium-stage operations, the overal
l computing time is often dominated by the solution of large, sparse s
ystems of linear equations. If the modeling equations for such separat
ion systems are grouped by equilibrium stage, the linear systems take
on an almost banded form with relatively few off-band elements. We pre
sent here a simple multifrontal approach for solving such linear syste
ms on supercomputers. Like the frontal approach, these solvers exploit
supercomputing technology by treating parts of the sparse matrix as f
ull, thereby allowing arithmetic operations to be performed with highl
y vectorized and optimized BLAS dense matrix kernels. In addition, the
se solvers exploit the almost banded structure of the distillation mat
rices by using a modified threshold pivot search strategy that attempt
s to maintain the desirable structure of the matrix during the solutio
n process. Results indicate that this multifrontal approach provides s
ubstantial savings in solution time compared to other techniques often
used.