Digital models of damaged rod systems for intelligent support throughout the life cycle

The article explores an approach to intelligent support for the life cycle of damaged rod systems, focusing on information support for decision-making in poorly structured operational scenarios. Such situations are marked by the need to justify technical solutions within limited timeframes and in the absence of reliable data on the stress state and residual load-bearing capacity of the damaged structure. The proposed information support involves obtaining a priori data on the structural condition under hypothetical failures of individual elements. This is achieved by constructing digital models that represent the stress state of the damaged system. For a typical poorly structured situation, the specific content of the decision-making tasks is identified, with each task linked to a set of key questions that must be answered. These questions in turn define the requirements for the digital models of damaged rod systems. Uncertainty in such weakly structured scenarios is addressed through a stepwise process: “situation assessment → analysis of decision-making content → formulation of key questions and definition of requirements for digital models → multivariate computational modeling and creation of digital models for decision support.” The development of digital models is carried out in advance of system operation and involves computational simulation of the failure of individual structural elements, followed by analysis of their impact on the system's overall stress state. The novelty of the approach lies in establishing a clear correspondence between the tasks of assessing the safe operability of damaged rod structures and the technologies used to simulate the failure of their components.