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  Optimizing Maintenance Strategies in Power Generation: Embracing Predictive and Preventive Approaches
  In the high-stakes world of power generation, ensuring continuous operation and reducing downtime are central priorities. With the increasing complexity of power generation systems, maintenance practices are evolving to meet these demands more efficiently. Understanding the roles of Predictive Maintenance (PdM), Preventive Maintenance (PM), and Reactive Maintenance (Run-to-Failure) is crucial for maintenance professionals in the energy sector to make informed decisions about equipment management and long-term operational strategy.
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A quasi-steady system analysis of the sodium-water reaction (SWR) phenomena in a liquid-metal reactor (LMR) was performed using the Sodium-water reaction Event Later Phase System Transient Analyzer (SELPSTA) computer simulation code. The code has been formulated by implementing various physical assumptions to simplify the complex SWR phenomena, and it adopts the long-term mass and energy transfer (LMET) model developed in the present study. The LMET model is based on the hypothesis that the system transient can be described by the pressure and temperature transient of the cover gas space, and it can be applied only to the reaction period characterized by bulk motion. To evaluate the feasibility of the physical model and its assumptions, a scale-down mock-up test was carried out, and it was demonstrated that the numerical simulation using the LMET model adequately replicates the overall phenomena of the experiment with reasonable understanding. Based on the findings, as a numerical example, the long-term system transient responses during the SWR event of the Korea Advanced LIquid MEtal Reactor (KALIMER) were investigated, and it was found that the long-term dynamic responses are strongly dependent on the design parameters and operational strategies. As a result, the numerical simulation method developed in the present study is practicable; furthermore, the SELPSTA code is useful to resolve the risk for the SWR event.