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@ARTICLE{Walz:865633,
author = {Walz, Olga and Djelassi, Hatim and Mitsos, Alexander},
title = {{O}ptimal experimental design for optimal process design:
{A} trilevel optimization formulation},
journal = {AIChE journal},
volume = {66},
number = {1},
issn = {0001-1541},
address = {Hoboken, NJ},
publisher = {Wiley},
reportid = {FZJ-2019-04984},
pages = {e16788},
year = {2020},
abstract = {Typical optimal experimental design (OED) methods aim at
minimizing the covariance matrix of the estimated parameters
regardless of the intended application of the model that is
being estimated. This can unnecessarily increase the
experimental costs. Herein, we propose a new OED method,
which tailors the designed experiments to the model
application. The method is demonstrated for model‐based
process design and aims at mitigating a worst‐case
realization of the process design. The proposed formulation
results in a min–max–min problem and is based on
bounded‐error OED. The method is illustrated via an ad hoc
solution method using two examples, a simple illustrative
example and the van de Vusse reaction, that show the
differences between typical and the new tailored OED method:
experimental designs can be considered good using the latter
method, while the same design would be considered bad with
the former methods.},
cin = {IEK-10},
ddc = {660},
cid = {I:(DE-Juel1)IEK-10-20170217},
pnm = {899 - ohne Topic (POF3-899)},
pid = {G:(DE-HGF)POF3-899},
typ = {PUB:(DE-HGF)16},
UT = {WOS:000488268000001},
doi = {10.1002/aic.16788},
url = {https://juser.fz-juelich.de/record/865633},
}