Abstract

Rotating machinery has extensive usage in industrial applications, either as leading equipment (power plants) or as auxiliary equipment (oil and gas exploitation). These highly complex systems demand expensive maintenance programs due to the high costs of eventual shutdown. Consequently, critical fault diagnosis and prognosis are essential during the operation of those systems. Fault identification and classification demand robust verification of codes and calculations and a discerning validation of numerical models used for rotating machinery. Hence, verification and validation (V&V) are an essential initial service for a digital twin (DT), offering some advantages in this application. In this context, the following research question is proposed: Does V&V using DT improve data access and reduce the effort of data exchange? The following objectives are created to address the research question: perform a code verification, conduct the calculation verification, validate the models using two different validation approaches, and demonstrate easy access to asset data. For this study, two identical hydrodynamic bearings and a noncentral disk were considered, representing a laboratory experimental setup. The validation metric requirement is promisingly satisfied for the disk and bearings according to validation Approaches 1 and 2. Furthermore, validation Approach 2 generates even more successful results than approach 1. Accurate estimation and reliable interpretation of the numerical model outcomes encourage the application of DT for future fault diagnosis and prognosis.

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