CyberSEES: Enabling Sustainable Civil Infrastructure Using Interactive Formal Analytics for Structural Health Diagnosis

This project seeks a holistic approach to real-time asset management of critical infrastructure through an as-yet unexplored intersection amongst structural health monitoring (SHM), and computational formal methods, while considering human interaction in the process. A multidisciplinary team brings computer scientists together with civil engineers experienced in structural health monitoring of real-world highway bridges. The research departs from the conventional approach to infrastructure health monitoring by direct solution of a structural model through application of a Satisfiability Modulo Theories (SMT) solver to mechanics-based constraints. The main objective of the project is to validate the efficacy of this formal approach to structural health diagnostics. This activity involves development of a framework to construct generalized and structure-specific constraints and encode them logically using SMT to formally bound the solution space of a measurement-based structural model satisfying the inverse Eigen problem that is central to vibration-based monitoring. Interpretation of the diagnostics result based on SMT will also be investigated, in a preliminary study of the role of interactive visual analytics utilizing tangible interaction to enhance the ability of practitioners to perceive, understand, and contribute to the diagnosis of the structural health monitoring system.

Maintaining the safety of bridges and other aging civil infrastructure is a challenging societal problem. Structural health monitoring offers a sustainable pathway by maximizing the service life and informing optimized schedule-based maintenance of our costly critical infrastructure without jeopardizing public safety or the functionality of commercial and strategic highway routes. If successful, this project will create solid foundations for a comprehensive diagnosis and prognostication framework. This model for smart infrastructure is directly translatable to a broad spectrum of other cyber-physical systems. To facilitate data sharing and dissemination, the laboratory bridge model is to be distributed as an open-source resource to the broader scientific and engineering communities with experimental details, analytical models, and datasets published and maintained through the NSF NEEShub Project Warehouse. Activities to integrate the project research with education include development of course modules, projects, and case studies.