Abstract
Dynamical process simulation plays an increasingly important role in the design and control of chemical plants. Mathematically speaking, the simulation of such processes requires the numerical solution of systems of partial differential equations (PDEs) of reaction-diffusion type with possibly mild convection. In contrast to some other fields of application, time dependence of the process is of real interest. Moreover, due to additional constraints, differential-algebraic equations will naturally arise. As for the spatial geometry, radial or simply plane symmetry will result in 1-D problems, whereas more complex situations will lead to 2-D or even 3-D models, often only given in the form of some CAD input. Even though such problems have been around for quite a while, they still represent a class of hard problems. For this reason, the development of robust and fast algorithms has been a topic of continuing investigation during the last years. In particular, significant progress has been made by the development of adaptive algorithms, which aim at the control of time and space grids in such a way that on one hand the solution is as accurate as required by the user and on the other hand the necessary work to obtain such a solution is minimized. The present paper surveys some of the essential features of such adaptive methods, which have been developed recently by the authors.
Invited talk, ECMI meeting 1994, Kaiserslautern
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© 1996 John Wiley & Sons Ltd and B. G. Teubner
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Deuflhard, P., Lang, J., Nowak, U. (1996). Adaptive Algorithms in Dynamical Process Simulation. In: Neunzert, H. (eds) Progress in Industrial Mathematics at ECMI 94. Vieweg+Teubner Verlag. https://doi.org/10.1007/978-3-322-82967-2_16
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DOI: https://doi.org/10.1007/978-3-322-82967-2_16
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