Explainable discrepancy checker and diagnosis for digital Twin-based supervisory control system

Lin, Linyu; Cavaluzzi, Jack M.; Mikkelson, Daniel Mark; Cittadino, Nicholas

doi:10.1016/j.anucene.2025.112018

Explainable discrepancy checker and diagnosis for digital Twin-based supervisory control system

Journal Article · Tue Dec 02 00:00:00 EST 2025 · Annals of Nuclear Energy

DOI:https://doi.org/10.1016/j.anucene.2025.112018· OSTI ID:3013195

^[1]; ^[1]; ^[1]; Cittadino, Nicholas ^[2]

Idaho National Laboratory (INL), Idaho Falls, ID (United States)
North Carolina State University, Raleigh, NC (United States)

By virtually representing a physical object and process, a digital twin (DT) enables optimal autonomous operations by combining classical and novel frameworks in sensors, state predictions, and multi-input/multi-output systems. A DT’s values depend on how well models estimate quantities of interest and on how uncertainty is handled. Moreover, DTs often combine physics-based and data-driven models with mixed fidelities, where classical uncertainty quantification (UQ) struggles with many sources of uncertainty and real-time constraints. Here, this work presents a UQ-based discrepancy checking and diagnosis tool for a DT-based supervisory control system. The tool is developed using metadata from an automated DT development process to learn correlations between sources of uncertainties and outcomes. During operation, it compares predictions with measurements, attributes discrepancies to dominant sources, and recommends parameter and configuration updates. We verify the workflow on a synthetic temperature-control problem and deploy it on a virtual Thermal Energy Delivery System, reducing mismatch and improving control robustness.

View Accepted Manuscript (DOE)

Research Organization:: Idaho National Laboratory (INL), Idaho Falls, ID (United States)

Sponsoring Organization:: USDOE Laboratory Directed Research and Development (LDRD) Program; USDOE Office of Nuclear Energy (NE)

Grant/Contract Number:: AC07-05ID14517

OSTI ID:: 3013195

Report Number(s):: INL/JOU--25-87630

Journal Information:: Annals of Nuclear Energy, Journal Name: Annals of Nuclear Energy Vol. 228; ISSN 0306-4549

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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