This two-day workshop will identify crosscutting research needs for digital twins. A digital twin is a set of virtual information constructs that mimics the structure, context and behavior of a physical system, is dynamically updated with data from its physical twin, and informs decisions that realize value. This workshop will focus on the interdisciplinary research needs that underpin the development and use of digital twins in domains such as engineering, materials, manufacturing, energy, smart cities, medicine, health, life sciences, climate, natural hazards, and environmental sciences.
Presentations and discussions will focus on foundational gaps that are unique to advancing digital twins. Of particular note is the bi-directional interaction between the virtual and the physical, which is central to distinguishing a digital twin from a conventional simulation. This bi-directional interaction brings many new challenges to modeling, data curation, and decision-making. Topics to be discussed include integration of physics-based and data-driven models, digital twin modeling across disparate temporal and spatial scales, multiphysics/multidisciplinary coupling and emergent behavior, surrogate modeling, real-time assimilation of multi-modal heterogenous data, decision-making under uncertainty, sensor steering and optimal experimental design, and end-to-end digital twin verification, validation and uncertainty quantification.
This event is supported by the National Science Foundation under Grant Number 2335883. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
ZOOM LINK (for observation-only)