Explainable Wastewater Digital Twins: Adaptive Context-Conditioned Structured Simulators with Self-Falsifying Decision Support
The article discusses the development of an explainable digital twin for wastewater treatment plants. This simulator aims to improve safety and efficiency in aeration and dosing processes. It features a decision-support pipeline that has been validated through extensive testing on real-world plants.
- ▪Operators of wastewater treatment plants face a safety-efficiency trade-off in aeration processes.
- ▪The CCSS-IX simulator uses a context-aware gating network to adaptively mix interpretable state-space experts.
- ▪The decision-support pipeline has been validated on full-scale plants and shows significant improvements in safety and efficiency.
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Computer Science > Artificial Intelligence arXiv:2605.19826 (cs) [Submitted on 19 May 2026] Title:Explainable Wastewater Digital Twins: Adaptive Context-Conditioned Structured Simulators with Self-Falsifying Decision Support Authors:Gary Simethy, Daniel Ortiz Arroyo, Petar Durdevic View a PDF of the paper titled Explainable Wastewater Digital Twins: Adaptive Context-Conditioned Structured Simulators with Self-Falsifying Decision Support, by Gary Simethy and 2 other authors View PDF HTML (experimental) Abstract:Operators of safety-critical industrial processes increasingly rely on digital twins to screen control interventions, but such simulators rarely carry certified safety guarantees.
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