Computational experiments in equation-based chemical process flowsheeting

Abstract

The central computational problem in equation-based flowsheeting is the simultaneous solution of a large sparse system of nonlinear algebraic equations. SEQUEL-II, our implementation of the equation-based approach, provides a means for comparing nonlinear equation-solving techniques, in particular the techniques used for computing correction steps, for ge nerating initial guesses, and for evaluating sparse Jacobian matrices. Comparisons are made on the basis of both efficiency and reliability. On a set of fourteen process flowsheeting problems, Powell's dogleg correction step is not only very efficient, but also somewhat more reliable than the Newton step when good initial guesses are not available. Schubert's sparse Jacobian update performs very well, but Bogle and Perkins' new least-relative-change update gives improved performance, when used in connection with either the dogleg or Newton correction step. The use of a hybrid update provides a better approximation of the Jacobian than a sparse update alone, one, and so significantly improves, in terms of number of iterations, the efficiency of the dogleg correction step.