Growing demands on our civil infrastructure have heightened the need for smart structural components and systems whose behavior and performance can be controlled under a variety of loading scenarios such as high winds and earthquakes. However, due to the sheer size, scale and cost of most civil engineering structures, design and testing of such smart structures needs to be conducted using a hybrid cyber-physical approach where the infrastructure system in question, for example a bridge, is studied by coupling a small number of physical components with a numerical model of the rest of the structure. Undoubtedly, the success of such a hybrid approach, especially for dynamic real-time applications, hinges on effective integration of the cyber and physical components of the system. This project provides the essential building blocks and a computational integration platform to enable real-time hybrid testing of civil engineering structures. Design and development of physical components, multi-level numerical models, and real-time control algorithms will be conducted at Purdue University. Washington University will provide an adaptive, configurable concurrency platform and communication mechanisms that meet the strict scheduling constraints of real-time cyber-physical systems. The two institutions will collaboratively design a prototype system and conduct extensive testing to validate the integration of the various components and evaluate system performance. Specifications, software, benchmarks, and data developed during the course of this project will be made freely available to the cyber-physical research community. In addition to directly advancing the state-of-the-art in real-time hybrid testing, this research will also impact the areas of avionics, automotive design, smart grids for distributed power transmission and similar applications in other domains.

The electric grid in the United States has evolved over the past century from a series of small independent community-based systems to one of the largest and most complex cyber-physical systems today. However, the established conditions that made the electric grid an engineering marvel are being challenged by major changes, the most important being a worldwide effort to mitigate climate change by reducing carbon emissions. This research investigates key aspects of a computation and information foundation for future cyber-physical energy systems?the smart grids. The overall project objective is to support high penetrations of renewable energy sources, community based micro-grids, and the widespread use of electric cars and smart appliances. The research has three interconnected components that, collectively, address issues of computation architecture, information hierarchy, and experimental modeling and validation. On computation architecture, the framework based on cloud computing is investigated for the scalable, consistent, and secure operations of smart grids. The research aims to quantify fundamental design tradeoffs among scalability, data consistency, security, and trustworthiness for emerging applications of smart grids. On information hierarchy, temporal and spatial characteristics of information hierarchy are investigated with the goal of gaining a foundational understanding on how information should be partitioned, collected, distributed, compressed, and aggregated. The research also develops an open and scalable experimental platform (SmartGridLab) for empirical investigations and testing of algorithms and concepts developed in this project. SmartGridLab integrates the hardware testbed with a software simulator so that software virtual nodes can interact with physical nodes in the testbed. This research also includes a significant education component aimed at integrating frontier research with undergraduate and graduate curricula.

In many important situations, analytically predicting the behavior of physical systems is not possible. For example, the three dimensional nature of physical systems makes it provably impossible to express closed-form analytical solutions for even the simplest systems. This has made experimentation the primary modality for designing new cyber-physical systems (CPS). Since physical prototyping and experiments are typically costly and hard to conduct, "virtual experiments" in the form of modeling and simulation can dramatically accelerate innovation in CPS. Unfortunately, major technical challenges often impede the effectiveness of modeling and simulation. This project develops foundations and tools for overcoming these challenges. The project focuses on robotics as an important, archetypical class of CPS, and consists of four key tasks: 1) Compiling and analyzing a benchmark suite for modeling and simulating robots, 2) Developing a meta-theory for relating cyber-physical models, as well as tools and a test bed for robot modeling and simulation, 3) Validating the research results of the project using two state-of-the-art robot platforms that incorporate novel control technologies and will require novel programming techniques to fully realize their potential 4) Developing course materials incorporating the project's research results and test bed. With the aim of accelerating innovation in a wide range of domains including stroke rehabilitation and prosthetic limbs, the project is developing new control concepts and modeling and simulation technologies for robotics. In addition to new mathematical foundations, models, and validation methods, the project will also develop software tools and systematic methods for using them. The project trains four doctoral students; develops a new course on modeling and simulation for cyber-physical systems that balances both control and programming concepts; and includes an outreach component to the public and to minority-serving K-12 programs.

The objective of this research is the development of methods for the control of energy flow in buildings, as enabled by cyber infrastructure. The approach is inherently interdisciplinary, bringing together electrical and mechanical engineers alongside computer scientists to advance the state of the art in simulation, design, specification and control of buildings with multiple forms of energy systems, including generation and storage. A significant novelty of this project lies in a fundamental view of a building as a set of overlapping, interacting networks. These networks include the thermal network of the physical building, the energy distribution network, the sensing and control network, as well as the human network, which in the past have been considered only separately. This work thus seeks to develop methods for simulating, optimizing, modeling, and control of complex, heterogeneous networks, with specific application to energy efficient buildings. The advent of maturing distributed and renewable energy sources for on-site cooling, heating, and power production and the concomitant developments in the areas of cyberphysical and microgrid systems present an enormous opportunity to substantially increase energy efficiency and reduce energy-related emissions in the commercial building energy sector. In addition, there is a direct impact of the proposed work in training students with backgrounds in the unique blend of engineering and computer science that is needed for the study of cyber-enabled energy efficient management of structures, as well as planned interactions at the undergraduate and K-12 level.

The objective of this research is to check correct functioning of cyber-physical systems during their operation. The approach is to continuously monitor the system and raise an alarm when the system seems to exhibit an erroneous behavior. Correct functioning of cyber-physical systems is of critical importance. This is more so in safety critical systems like medical, automotive and other applications. The approach employs hybrid automata for specifying the property to be monitored and for modeling the system behavior. The system behavior is probabilistic in nature due to noise and other factors. Monitoring such systems is challenging since the monitor can only observe system outputs, but not it's state. Fundamental research, on defining and detecting whether a system is monitorable, is the focus of the work. The project proposes accuracy measures and cost based metrics for optimal monitoring. The project is developing efficient and effective monitoring techniques, based on product automata and Partially Observable Markov Decision Processes. The results of the project are expected to be transformative in ensuring correct operation of systems. The results will have impact in many areas of societal importance and utility for daily life, such as health care, nursing/rehabilitation, automotive systems, home appliances, and more. The benefits in nursing/rehabilitation emanate from the deployment of advanced technologies to assist caregivers. This can lead to improved health and quality of life of older patients at reduced costs. The project includes education and outreach in the form of K-12 outreach and involvement of undergraduate and graduate students in research. The project is committed to involving women and minorities in education and research.

The objective of this research is to develop methods and tools for a multimodal and multi-sensor assessment and rehabilitation game system called CPLAY for children with Cerebral Palsy (CP). CPLAY collects and processes multiple types of stimulation and performance data while a child is playing. Its core has a touch-screen programmable game that has various metrics to measure delay of response, score, stamina/duration, accuracy of motor/hand motion. Optional devices attached to extend CPLAY versions provide additional parallel measurements of level of concentration/participation/engagement that quantify rehabilitation activity. The approach is to model the process as a cyber-physical system (CPS) feedback loop whereby data collected from various physical 3D devices (including fNIR brain imaging) are processed into hierarchical events of low-to-high semantic meaning that impact/ adjust treatment decisions. Intellectual Merit: The project will produce groundbreaking algorithms for event identification with a multi-level data to knowledge feedback loop approach. New machine learning, computer vision, data mining, multimodal data fusion, device integration and event-driven algorithms will lead towards a new type of cyber- physical rehabilitation science for neurological disorders. It will deliver fundamental advancements to engineering by showing how to integrate physical devices with a computationally quantitative platform for motor and cognitive skills assessment. Broader Impacts: The project delivers a modular & expandable game system that has huge implications on the future of US healthcare and rehabilitation of chronic neurological disabilities. It brings hope to children with Cerebral Palsy via lower cost and remote rehabilitation alternatives. It brings new directions to human centered computing for intelligent decision-making that supplements evidence-based practices and addresses social and psychological isolation problems.

Abstract The objective of this research is to develop advanced distributed monitoring and control systems for civil infrastructure. The approach uses a cyber-physical co-design of wireless sensor-actuator networks and structural monitoring and control algorithms. The unified cyber-physical system architecture and abstractions employ reusable middleware services to develop hierarchical structural monitoring and control systems. The intellectual merit of this multi-disciplinary research includes (1) a unified middleware architecture and abstractions for hierarchical sensing and control; (2) a reusable middleware service library for hierarchical structural monitoring and control; (3) customizable time synchronization and synchronized sensing routines; (4) a holistic energy management scheme that maps structural monitoring and control onto a distributed wireless sensor-actuator architecture; (5) dynamic sensor and actuator activation strategies to optimize for the requirements of monitoring, computing, and control; and (6) deployment and empirical validation of structural health monitoring and control systems on representative lab structures and in-service multi-span bridges. While the system constitutes a case study, it will enable the development of general principles that would be applicable to a broad range of engineering cyber-physical systems. This research will result in a reduction in the lifecycle costs and risks related to our civil infrastructure. The multi-disciplinary team will disseminate results throughout the international research community through open-source software and sensor board hardware. Education and outreach activities will be held in conjunction with the Asia-Pacific Summer School in Smart Structures Technology jointly hosted by the US, Japan, China, and Korea.

This project has two closely related objectives. The first is to design and evaluate new Cyber Transportation Systems (CTS) applications for improved traffic safety and traffic operations. The second is to design and develop an integrated traffic-driving-networking simulator. The project takes a multi-disciplinary approach that combines cyber technologies, transportation engineering and human factors. While transportation serves indispensible functions to society, it does have its own negative impacts in terms of accidents, congestion, pollution, and energy consumption. To improve traffic safety, the project will develop and evaluate novel algorithms and protocols for prioritization, delivery and fusion of various warning messages so as to reduce drivers? response time and workload, prevent conflicting warnings, and minimize false alarms. To improve traffic operations, the project will focus on the design of next generation traffic management and control algorithms for both normal and emergency operations (e.g. during inclement weather and evacuation scenarios). Both human performance modeling methods and human subjects? experimental methods will be used to address the human element in this research. As the design and evaluation of CTS applications requires an effective development and testing platform linking the human, transportation and cyber elements, the project will also design and develop a simulator that combines the main features of a traffic simulator, a networking simulator and a driving simulator. The integrated simulator will allow a human driver to control a subject vehicle in a virtual environment with realistic background traffic, which is capable of communicating with the driver and other vehicles with CTS messages. Background traffic will be controlled by a realistic driver model based on our human factors research that accounts for CTS messages? impact on driver behavior. Intellectual Merits: The project explicitly considers human factors in the design and evaluation of CTS safety and operations applications, a topic which has not received adequate attention. Moreover, the proposed integrated simulator represents a first-of-a-kind simulator with unique features that can reduce the design and evaluation costs of new CTS applications. Broader Impacts: The proposed research can improve the safety, efficiency and environmental-friendless of transportation systems, which serve as the very foundation of modern societies and directly affects the quality of life. The integrated simulator will be used as a tool for teenage and elderly driver education and training, and to inspire minority, middle and high school students to pursue careers in math, science, and computer-related fields