The smart grid is a large-scale, societal-level hybrid cyber-physical system with tight coupling between cyber and physical components.  Ensuring availability and reliability of power requires maintaining stability of the power grid even as increasing demand and uncertain renewable power sources push the power system close to its operation limit.  In addition, the cyber-enabled grid has multiple entry points, leaving it highly susceptible to cyber attacks by malicious adversaries.

The VISualization of Terrestrial and Aquatic Systems (VISTAS) team, an NSF/BIO/ABI-funded collaboration among environmental-, computer-, and social-scientists, has integrated new technologies and CS research into terrain visualization software for environmental scientists. The system allows scientists to overlay 2D data onto 3D elevation maps to emphasize landscape topography and to better understand how topography affects the ecology of the land. VISTAS also provides animations over time, fly-throughs, and some analytics.

The goal of this project is to enable small businesses and others to manufacture small batches of complex devices at low cost. Our approach is to develop an agile manufacturing exchange (ME) in which suppliers of raw materials, assemblers, transportation companies, banks, etc., participate through standardized protocols to fulfill manufacturing orders.

The goal of this research project is to develop a scalable cyber-physical system (CPS) framework for seamless integration of physical and computational systems for bridge lifecycle monitoring. Bridge monitoring includes many different components, such as computer-aided design (CAD) system, bridge management system (BMS), structural health monitoring (SHM) system, and various analysis tools. In current practice, these components are isolated from each other and sharing of information across systems is very limited. Information sharing and system integration

Computational simulation is one of the most im- portant ways of reproducing the dynamic responses of a Cyber Physical System using a model of the system. The simulation discovers areas of differential system performance and allows linking such performance back to system characteristics. In the medical domain, patient simulators are used to train physicians in patient management. One critical question is how to verify these systems under realistic human (physician) input.

Modern cyber-physical systems are monitored and controlled by multi-core platforms, and thermal management of multi-core chips is critical as overheated cores thereon will suffer from exponentially decaying lifetime and unacceptable performance degradation. To meet the timing and system lifetime reliability requirements under dynamic workloads and operating environment, we need a real-time thermal management (RTM) scheme that predicts run-time temperature and actuates effective thermal control without compromising task deadlines.

Recent progress in battery technology has made it possible to use batteries to power various physical platforms, such as ground/air/water vehicles. These platforms require hundreds/thousands of battery cells to meet their power and energy needs. Of these, automobiles, locomotives, and unmanned air vehicles (UAVs) face the most stringent environmental challenges. In particular, and of special importance to the automotive industry, is the transition from conventional powertrains to (plug-in) hybrid and electric vehicles, all of which are subject to environmental and operational variations.