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Efficient Multi-level Mine Dewatering Using UPPAAL Stratego

Authors:

Muhammad Naeem, Cristina Seceleanu, Alf J. Isaksson , Tiberiu Seceleanu

Research group:

Formal Modelling and Analysis of Embedded Systems

Publication Type:

Conference/Workshop Paper

Venue:

The 27th International Symposium on Formal Methods

Publisher:

LNCS

Abstract

Effective water management in underground mining requires maintaining safe reservoir levels while minimizing the high energy costs of continuous pumping. Although flexible electricity pricing enables cost-aware operation, traditional threshold-based controllers cannot exploit this flexibility efficiently. This paper presents an industrial case study on efficient mine dewatering using reinforcement-learning-based control synthesized with the UPPAAL Stratego framework. A baseline threshold controller is first implemented, followed by a reinforcement-learning controller trained on forecast inflows and day-ahead electricity prices to minimize pumping costs while limiting pump switching. To ensure safety during learning without distorting the optimization objective, we introduce a pre-shield that blocks unsafe transitions. We formally show that this pre-shield is maximally permissive with respect to a monotonicity safety objective. Simulation results demonstrate that the learning-based strategy reduces total energy consumption by up to 40% compared to threshold-based control, while maintaining safe operation in all scenarios.

Bibtex

@inproceedings{Naeem7391,
author = {Muhammad Naeem and Cristina Seceleanu and Alf J. Isaksson and Tiberiu Seceleanu},
title = {Efficient Multi-level Mine Dewatering Using UPPAAL Stratego},
pages = {711--729},
month = {May},
year = {2026},
booktitle = {The 27th International Symposium on Formal Methods},
publisher = {LNCS},
url = {http://www.es.mdu.se/publications/7391-}
}