Digital twin of regenerative processes in life support systems


Аuthors

Kulikovskikh I. M.

Samara State Medical University, Samara, Russian Federation

e-mail: i.m.kulikovskikh@samsmu.ru

Abstract

The paper presents a major challenge for digital twins in adapting models of different fidelity to a vast range of spatial and temporal scales.  The limitations of integrating this technology into autonomous systems include: executing workflows on edge or embedded devices, ensuring a continuous data stream at the required frequency, and meeting regulatory requirements for the security and safety of transmitted data. Additionally, implicit factors influencing the feasibility of digital twins were uncovered, such as the accumulation of errors, inefficient resource use, and increased risks in critical decision-making. An analysis of root causes was conducted to establish a balance between the compact implementation of the digital solution and the accuracy of reproducing its physical counterpart. The proposed prototype of the digital twin for regenerative processes in life support systems optimizes resource use by automatically reconfiguring in real time.  The mechanisms for reconfiguration are built on key principles of organising complex systems – abstraction, modularity, decomposition, and iteration – which enable the simulation of continuous dynamics observed in regenerative processes. Switching between these mechanisms depends on the current requirements of the prototype: computational efficiency, flexibility and scalability, root cause analysis or troubleshooting, and tracking changes in dynamics. The results of computational experiments confirmed the efficiency of the prototype in managing physicochemical processes of oxygen generation and carbon dioxide scrubbing under variable conditions, load factors, and component degradation.  The presented results allow us to conclude that the capability for automatic reconfiguration of the prototype optimises system resources by maintaining high efficiency and resilience under critical conditions. 

Keywords:

digital twin, systems approach, life support systems, physicochemical regeneration processes

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