M. A. Stadtherr

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In recent years, it has been shown that strategies based on an interval-Newton approach can be used to reliably solve a variety of nonlinear equation solving and optimization problems in chemical process engineering, including problems in parameter estimation and in the computation of phase behavior. These strategies provide a mathematical and computational(More)
A new approach is described for the rigorous global optimization of dynamic systems subject to inequality path constraints (IPCs). This method employs the sequential (control parameterization) approach and is based on techniques developed for the verified solution of parametric systems of ordinary differential equations. These techniques provide rigorous(More)
For the simulation and optimization of large-scale chemical processes, the overall computing time is often dominated by the time needed to solve a large sparse system of linear equations. We describe here a parallel frontal solver which can significantly reduce the wallclock time required to solve these linear equation systems using parallel/vector(More)
For the simulation of complex equilibrium-stage operations, the overall computing time is often dominated by the solution of large, sparse systems of linear equations. If the modeling equations for such separation systems are grouped by equilibrium stage, the linear systems take on an almost banded form with relatively few o -band elements. We present here(More)
For the simulation and optimization of large-scale chemical processes, the overall computing time is often dominated by the time needed to solve a large sparse system of linear equations. We present here a new parallel frontal solver which can signi cantly reduce the wallclock time required to solve these linear equation systems using parallel/vector(More)
High performance computing (HPC) technology, including parallel and/or vector processing, provides opportunities to solve process optimization and simulation problems faster and more reliably than ever before, thus enabling the solution of increasingly large scale problems, even in a real time environment. This presentation will focus on recent advances in(More)
For the simulation and optimization of large scale chemical processes, the overall computing time is often dominated by the time needed to solve a large sparse system of linear equations. A parallel frontal solver can be used to signi cantly reduce the wallclock time required to solve these linear equation systems using parallel/vector supercomputers. This(More)
In this article we consider strategies for exploiting supercomputer technology in solving the sparse matrix problems arising in process simulation and optimization. A new multifrontal solver for use in simulating equilibrium-stage processes and a new parallel frontal solver for large-grained parallel solution of process simulation and optimization problems(More)
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