Query-and-Response Digital Twin Framework Using a Multidomain, Multifunction Image Folio

Digital twin (DT) capabilities have been limited to a single function, but the reality of physical assets requires DTs with multidomain, multifunction representations. DTs can and should be designed with multidomain and multifunctional capabilities to enable adaptability to a diverse set of system domains and perform various representation tasks. This approach allows the DT to be as specialized as the physical asset it serves. This study introduces a framework enabling the development of multidomain, multifunctional DTs, adaptable for use in various representation tasks. The proposed framework utilizes a collection of digital images for an accurate depiction of different facets of an asset, ensuring a detailed yet unified DT. The framework is designed to analyze the human-in-the-loop text-based query and select the most suitable digital image for execution. The proposed multidomain, multifunction DT framework reduces the computational effort by 5.15% when compared to a single, unified DT running all studies concurrently. Details on the development of the framework are provided, and experimental results validate the effectiveness of the proposed framework.