Digital Twin-Inspired Models of Socio-Technical systems
Simulating how people and systems work together under both nominal and denied conditions requires new approaches that build on and expand “digital twin” constructs. Simulations must, for instance, train operators in detecting, countering and fighting through the adverse effects of communications disruptions. This paper explores a modeling approach and computational tool designed to capture and reflect socio-technical processes needed to train today's forces to be proficient in denied or contested environments.
A digital twin is a virtual model that mirrors physical world persons, devices, systems or processes. We expand this view to model not only individual entity behaviors but also the processes and data that capture their interactions and inter-dependencies. For instance, training scenarios should model how denial effects can disrupt not only a discrete digital twin, but also simulate and predict the adverse effects of coordination lapses on the systemic effectiveness of operators and their intelligent systems.
We implement this enhanced digital twin approach using an agent-based modeling framework, developed by the US Government, called Brahms. Brahms is based on socio-cognitive theories of perception, inference, communication, and collaboration, and employs an activity-based approach that represents how functions are carried out in practice. Brahms emphasizes the interactive behavior among people, systems, and the environment to understand and simulate emergent outcomes.
While the underlying process models and data structures in Brahms are well-suited to our enhanced notion of a digital twin, the Brahms computational environment's realtime performance is limited by a resource-heavy architecture, which was well-suited for the purposes it was originally designed to fulfill, but is inadequate for developing digital twin, socio-technical models of complex, realistic tactical scenarios. Legacy Brahms also supports visualization of a single “run”, generating inspectable log files from one scenario, executed from a specific set of initial conditions. A robust exploration of the space of training scenarios, however, requires visibility into the aggregated findings from collections of runs that the legacy Brahms software does not support.
To address these limitations, we developed Brahms-Lite, a modeling and simulation environment that: (1) supports collecting and visualizing aggregated data from multiple runs; and (2) encapsulates the Brahms model in a modern, supported, efficient and interoperable computational framework. Brahms-Lite preserves the activity-based theoretical construct and basic data structures and process models that power the legacy Brahms environment.
We developed the aggregation and visualization tool to demonstrate Brahms applied to simulating denial attacks in air-to-ground attack scenarios. This work, reported at I/ITSEC in 2018, was the foundation of subsequent implementation of Brahms-Lite, demonstrated more recently in air-to-air combat scenarios to illustrate a broader interpretation of digital twin to model socio-technical systems. This newer work demonstrates the Brahms-Lite toolkit and associated realtime visualization dashboards.We review the Brahms approach and how our extension of digital twin models is applied to socio-technical systems. We discuss Brahms-Lite and present an application to air combat simulation. We conclude with a discussion of how this technique can be applied more broadly to extend digital twin approaches in simulations of complex environments under nominal and denied conditions.