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Software supporting optimal experimental design: A case study of binary diffusion using EFCOSS
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DOI：10.1016/j.compchemeng.2008.12.008.png)
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Abstract
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Methods for optimal experimental design aim at minimizing uncertainty in parameter estimation problems. Despite their long tradition in applied mathematics and importance in practical applications, they are currently not widely used in computational science and engineering. To make the techniques of optimal experimental design more accessible to a broader community, we introduce a novel software environment called EFCOSS and demonstrate its ease of use and versatility in two case studies of binary diffusion experiments. Through the use of a component-based software architecture, integration of automatic differentiation technology and facilitated interfacing to optimization algorithms. EFCOSS minimizes the computational overhead for the user who can thus focus on model development and analysis itself. The presented case studies focus on diffusion experiments in liquids since these experiments are typically very demanding. The use of optimal experimental design techniques allows to reduce experimental time and effort significantly. (C) 2009 Elsevier Ltd. All rights reserved.
Keywords:
Optimal experimental design
Parameter estimation
EFCOSS
Diffusion experiment
Distributed computing
Automatic differentiation
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