Integrating effort- and gradient-based approaches in optimal design of experimental campaigns

Model-based design of optimal experimental campaigns comprising multiple parallel runs can prove computationally challenging. Effort-based methods can help in overcoming some of these challenges through discretising the experimental design space. However, the quality of the resulting approximate sol...

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Bibliographic Details
Published inComputer Aided Chemical Engineering Vol. 53; pp. 313 - 318
Main Authors Sandrin, Marco, Chachuat, Benoît, Pantelides, Constantinos C.
Format Book Chapter
LanguageEnglish
Published 2024
Subjects
model-based design of experiments
optimal experiment design
parameter precision
optimal experiment design
model-based design of experiments
parameter precision
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Summary:Model-based design of optimal experimental campaigns comprising multiple parallel runs can prove computationally challenging. Effort-based methods can help in overcoming some of these challenges through discretising the experimental design space. However, the quality of the resulting approximate solutions depends heavily on this a priori discretisation. This paper presents a methodology for integrating the appealing features of effort-based methods with those of conventional gradient-based approaches, with a view to computing maximally-informative campaigns of experiments for improving parameter precision. The effectiveness of the methodology is demonstrated on a case study involving a microbial culture dynamic model.
ISBN:9780443288241
0443288240
ISSN:1570-7946
DOI:10.1016/B978-0-443-28824-1.50053-3