Enabling Data Proxies Utilizing Multilayer Networks and Statistical Physics
Abstract
During the early stages of ship and ship systems design, not every component or system can or will be modeled at the level of fidelity required for correct integration into standardized data models or frameworks. While alternative ontology developments and the establishment of new standards can resolve individual cases, these approaches will not work universally. While proper data integrationitself poses an immense challenge, designers must also coordinate their efforts across several design disciplines to produce a converged design in the presence of exogenous factors such as shifting requirements, technology development, and changing information landscapes. The changing information landscape requires the representation of ship and ship systems design data to evolve, as well as allowing large portions of the design knowledge space to be revised. This necessitates the ability to incorporate abstractions of ship and ship systems artifacts into a naval knowledge structure. This has spurred an interest in the notion of a #proxy# coined by Mr. Robert Ames at NSWC Carderock. To date, the approaches have primarily focused the development activities on the product representation side of the problem rather than integrating the incomplete knowledge generated to create and analyze the product. As such, little has been done to understand the conceptual robustness of the data contained within LEAPS when thin abstractions of design artifacts are incorporated. The focus of this research is to investigate the challenges of integrating a diverse set of knowledge structureconcepts into LEAPS through the investigation of a novel network framework and its associated metrics, as well as the use of statistical physics to model and analyze the integration of the temporal logical #proxy# power and ship system architectures to the currently modeled physical architecture in LEAPS. This will enable engineers to effectively manage the various knowledge representation associated with complex ship and ship systems development. The investigation of these methods will help ensure that non-standard engineering data is properly integrated and understood. Approved for Public Release.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- May 15, 2023
- Source ID
- N000142312517
Entities
People
- David Singer
Organizations
- Board of Regents of the University of Michigan
- Office of Naval Research
- United States Navy