Measure this, not that: Optimizing the cost and model-based information content of measurements

Wang, Jialu; Peng, Zedong; Hughes, Ryan; Bhattacharyya, Debangsu; Bernal Neira, David E.; Dowling, Alexander W.

doi:10.1016/j.compchemeng.2024.108786

Measure this, not that: Optimizing the cost and model-based information content of measurements

Journal Article · Thu Jul 04 00:00:00 EDT 2024 · Computers and Chemical Engineering

DOI:https://doi.org/10.1016/j.compchemeng.2024.108786· OSTI ID:2447595

^[1]; Peng, Zedong ^[2]; Hughes, Ryan ^[3]; Bhattacharyya, Debangsu ^[4]; Bernal Neira, David E. ^[2]; ^[1]

University of Notre Dame, IN (United States)
Purdue Univ., West Lafayette, IN (United States)
National Energy Technology Laboratory (NETL), Pittsburgh, PA (United States); NETL Support Contractor, Pittsburgh, PA (United States)
West Virginia Univ., Morgantown, WV (United States)

Model-based design of experiments (MBDoE) is a powerful framework for selecting and calibrating science-based mathematical models from data. Here, this work extends popular MBDoE workflows by proposing a convex mixed integer (non)linear programming (MINLP) to optimize the selection of measurements. The solver MindtPy is modified to support calculating the D-optimality objective and its gradient via an external package, scipy, using the grey-box module in Pyomo. The new approach is demonstrated in two case studies: estimating highly correlated kinetics from a batch reactor and estimating transport parameters in a large-scale rotary packed bed for CO₂ capture. Both case studies show how examining the Pareto optimal trade-offs between information content measured by A- and D-optimality versus measurement budget offers practical guidance for selecting measurements for scientific experiments.

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This content will become publicly available on Fri Jul 04 00:00:00 EDT 2025

Research Organization:: National Energy Technology Laboratory (NETL), Pittsburgh, PA, Morgantown, WV, and Albany, OR (United States)

Sponsoring Organization:: USDOE Office of Fossil Energy and Carbon Management (FECM); USDOE

OSTI ID:: 2447595

Alternate ID(s):: OSTI ID: 2403599

Journal Information:: Computers and Chemical Engineering, Vol. 189; ISSN 0098-1354

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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