LAPSE:2026.0218
Published Article
LAPSE:2026.0218
OpenAD-lib: Open-Source Framework for Uncertainty-Aware Anaerobic Digestion Digital Twins
June 12, 2026
Abstract
This paper presents OpenAD-lib, an open-source Python framework for anaerobic digestion (AD) digital twins, unifying mechanistic models, machine learning (ML) surrogates, and model predictive control (MPC) within a modular ecosystem. OpenAD-lib addresses the critical fragmentation in AD digitalisation by bridging mechanistic and data-driven paradigms under explicit uncertainty. By integrating uncertainty-aware feedstock characterisation with robust process control, the platform enables the transition from isolated research tools to fully integrated digital twins, delivering economic and environmental value in AD systems.
This paper presents OpenAD-lib, an open-source Python framework for anaerobic digestion (AD) digital twins, unifying mechanistic models, machine learning (ML) surrogates, and model predictive control (MPC) within a modular ecosystem. OpenAD-lib addresses the critical fragmentation in AD digitalisation by bridging mechanistic and data-driven paradigms under explicit uncertainty. By integrating uncertainty-aware feedstock characterisation with robust process control, the platform enables the transition from isolated research tools to fully integrated digital twins, delivering economic and environmental value in AD systems.
Record ID
Keywords
Anaerobic digestion, Bioenegry, Digital twins, Digitalisation, Machine learning, Model Predictive Control, Open-source framework, Uncertainty quantification
Subject
Suggested Citation
Dekhici B, Murali R, Short M. OpenAD-lib: Open-Source Framework for Uncertainty-Aware Anaerobic Digestion Digital Twins. Systems and Control Transactions 5:131-142 (2026) https://doi.org/10.69997/sct.190606
Author Affiliations
Dekhici B: School of Chemistry and Chemical Engineering, University of Surrey, Guildford, GU2 7XH, Surrey, United Kingdom. Supergen Bioenergy Impact Hub, Energy and Bioproducts Research Institute, UK [ORCID]
Murali R: School of Chemistry and Chemical Engineering, University of Surrey, Guildford, GU2 7XH, Surrey, United Kingdom [ORCID]
Short M: School of Chemistry and Chemical Engineering, University of Surrey, Guildford, GU2 7XH, Surrey, United Kingdom. Supergen Bioenergy Impact Hub, Energy and Bioproducts Research Institute, UK [ORCID]
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Murali R: School of Chemistry and Chemical Engineering, University of Surrey, Guildford, GU2 7XH, Surrey, United Kingdom [ORCID]
Short M: School of Chemistry and Chemical Engineering, University of Surrey, Guildford, GU2 7XH, Surrey, United Kingdom. Supergen Bioenergy Impact Hub, Energy and Bioproducts Research Institute, UK [ORCID]
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Journal Name
Systems and Control Transactions
Volume
5
First Page
131
Last Page
142
Year
2026
Publication Date
2026-06-12
Version Comments
Original Submission
Other Meta
PII: 0131-0142-389-SCT-5-2026, Publication Type: Journal Article
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Published Article
LAPSE:2026.0218
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https://doi.org/10.69997/sct.190606
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[v1] (Original Submission)
Jun 12, 2026
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Jun 12, 2026
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Links to Related Works
References Cited
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