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Cybersecurity and dynamic operation in practice: Equipment impacts and safety guarantees
Institution:1. School of Emergency Management and Safety Engineering, China University of Mining and Technology (Beijing), Beijing, 100083, China;2. State Key Laboratory of Coal Resources and Safety Mining, China University of Mining and Technology, Beijing, 100083, China;1. Physikalisch-Technische Bundesanstalt (PTB), Braunschweig, Germany;2. thuba AG, Basel, Switzerland;3. Otto-von-Guericke-Universität Magdeburg, Magdeburg, Germany;1. College of Safety Science and Engineering, Nanjing Tech University, Nanjing, 211816, China;2. Department of Process Engineering & Applied Science, Dalhousie University, Halifax, B3H 4R2, Canada;3. Fire & Explosion Protection Laboratory, Northeastern University, Shenyang, 110819, China;1. Department of Chemical Engineering, Indian Institute of Technology Roorkee, Roorkee, 247667, Uttarakhand, India;2. Assam Energy Institute, Centre of Rajiv Gandhi Institute of Petroleum Technology, Sivasagar, 785697, Assam, India;3. Department of Chemical Engineering, Indian Institute of Technology (Indian School of Mines), Dhanbad, Dhanbad, 826004, Jharkhand, India
Abstract:Though dynamic operation of chemical processes has been extensively explored theoretically in contexts such as economic model predictive control or even considering the potential for cyberattacks on control systems creating non-standard operating policies, important practical questions remain regarding dynamic operation. In this work, we look at two of these with particular relevance to process safety: (1) evaluating dynamic operating policies with respect to process equipment fidelity and (2) evaluating procedures for determining the parameters of an advanced control law that can promote both dynamic operation as well as safety if appropriately designed. Regarding the first topic, we utilize computational fluid dynamics and finite element analysis simulations to analyze how cyberattacks on control systems could impact a metric for stress in equipment (maximum Von Mises stress) over time. Subsequently, we develop reduced-order models showing how both a process variable and maximum Von Mises stress vary over time in response to temperature variations at the boundary of the equipment, to use in evaluating how advanced control frameworks might impact and consider the stress. We close by investigating options for obtaining parameters of an economic model predictive control design that would need to meet a variety of theoretical requirements for safety guarantees to hold. This provides insights on practical safety aspects of control theory, and also indicates relationships between control and design from a safety perspective that highlight further relationships between design and control under dynamic operation to deepen perspectives from the computational fluid dynamics and finite element analysis discussions.
Keywords:Equipment  Cybersecurity  Economic model predictive control  Lyapunov-based economic model predictive control  Process safety
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