computational elements of robust civil infrastructure

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Computational Elements of Robust Civil Infrastructure White paper by: G. Cybenko, K. Fuchs, A. Grama, C. Hoffmann, A. Sameh, N. Shroff, M. Sozen, and B.F. Spencer September 17, 2002

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Computational Elements of Robust Civil Infrastructure. White paper by: G. Cybenko, K. Fuchs, A. Grama, C. Hoffmann, A. Sameh, N. Shroff, M. Sozen, and B.F. Spencer September 17, 2002. Motivation for Study. The country has an investment of $20 trillion in civil infrastructure. - PowerPoint PPT Presentation

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Page 1: Computational Elements of Robust Civil Infrastructure

Computational Elements of Robust Civil Infrastructure

White paper by:

G. Cybenko, K. Fuchs, A. Grama, C. Hoffmann, A. Sameh, N. Shroff, M. Sozen, and B.F. Spencer

September 17, 2002

Page 2: Computational Elements of Robust Civil Infrastructure

Motivation for Study

• The country has an investment of $20 trillion in civil infrastructure.

• Much of this civil infrastructure is “mission-critical”, e.g.,– bridges– power plants and power grid towers– telecommunication centers– water purification plants

Page 3: Computational Elements of Robust Civil Infrastructure

Motivation for Study• Monitoring the health of such infrastructure

through sensing technology can:– assure timely service,– detect the onset of catastrophic failure,– mitigate catastrophic failure, or– allow for effective contingency plans (crisis management).

• Actuation based on sensing infrastructure can:– increase the robustness of such structures very significantly,– enable economical construction of critical infrastructure,– in the event of imminent failure, direct the structure to desirable

failure modes.

Page 4: Computational Elements of Robust Civil Infrastructure

Targeted Hazards• Earthquakes• Explosions• Fire• Rust• Wind• Terrorist events

Page 5: Computational Elements of Robust Civil Infrastructure

State-of-the-art in Controlled Structures - Passive Control

Page 6: Computational Elements of Robust Civil Infrastructure

Focus of the study1. Develop the communication, data integration,

and computational, infrastructure that enables:– Effective design and economical construction of highly

robust “smart” structures that sense and react to external stimuli; and

– Transformation of existing structures into active structures that sense, discriminate, and act in defense.

2. Off-line use of data collected to “solve the inverse problem” – determine actual structural characteristics and specific stimuli leading to failure. This can be done through a series of scenario simulations.

Page 7: Computational Elements of Robust Civil Infrastructure

Research and Development Highlights

1. The design and implementation of a low-power/ low-cost smart sensors-actuators complex (SAC) consisting of:1. smart sensor networks2. data receptors3. computational elements4. real-time control

algorithms

Sensing/Computation/Communication elements - designed by part of our research team at Dartmouth. These units cost under $200 and are the size of a deck of cards. Efforts are on to develop the next generation of such devices at Purdue.

Page 8: Computational Elements of Robust Civil Infrastructure

Research and Development Highlights

• Integrate the SAC with a strut system containing controllable dampers (to change the stiffness characteristics of the structure).

– a magnetorheological (MR) device, also referred to as a smart-strut-device (SSD).

Magnetorheostatic dampers can change their load bearing characteristics from fully solid to fully damping in milliseconds when exposed to magnetic fields.

Page 9: Computational Elements of Robust Civil Infrastructure

Research and Development Highlights

• Develop distributed strategies for computing control vector from sensed signals in real time.

• Develop detailed simulation methodologies for validating control strategies and examining a variety of what-if scenarios for a range of stimuli.

Page 10: Computational Elements of Robust Civil Infrastructure

Research and Development Highlights

• Detailed methodologies for design of structures, including placement and capability of sensors and actuators, precise calibration of impact bearing capacity of the structure.

• Real-time visual information infrastructure to support status checks, and rescue and relief efforts.

Page 11: Computational Elements of Robust Civil Infrastructure

Research and Development Tasks

a) Development of self-configuring, self-calibrating wireless sensor networks and low-latency sensor data management techniques.

b) Development of algorithms and software for continuous real-time testing, diagnosis, and maintenance for all communication and computational components of the sensor/actuator networks.

c) Fault-tolerant operation of the SAC-SSD complexes.

Page 12: Computational Elements of Robust Civil Infrastructure

Research and Development Tasks

• Model reduction of the large-scale dynamical system representing the structure (off-line).

• Development of distributed, real-time (on-line) algorithms for determining the structure’s response to dynamic impulses using the reduced low-order model, together with a real-time visualization environment.

• Development of rapid simulation and visualization infrastructure for exploring (off-line) a range of “what-if” scenarios for real-time disaster management and control strategies.

Page 13: Computational Elements of Robust Civil Infrastructure

Research and Development Tasks

• Validation of the entire computational paradigm on well-instrumented model structures, as well as actual instrumented structures in Puerto Rico (wind effects), and Japan (earthquakes).

Page 14: Computational Elements of Robust Civil Infrastructure

Unique Qualifications of Research Team

• Extensive experience building and applying sensor networks (Cybenko, Dartmouth, Shroff, Purdue).

• Pioneered the development and use of smart-strut devices (Sozen, Purdue, Spencer, Illinois).

• Fundamental work in fault tolerance, testing, and system validation (Fuchs, Cornell).

• Experts in geometric modeling, large scale simulation, and visualization infrastructure, more recently, applied to the Pentagon crash simulation (Hoffmann, Purdue),

• Parallel and distributed algorithms for structural modeling, model reduction, and control (Sameh, Grama, Purdue).

Page 15: Computational Elements of Robust Civil Infrastructure

Relation of Project to Other Sensor Network Efforts

• The fundamental goal of this project is to build robust civil infrastructure.

• From this point of view, the aim is one of integrating a range of existing technologies, and where needed, to develop new technologies.

• Its primary aim is not to build a new class of sensors or RF communication devices. It is our belief that these technologies have matured to a point where they can safely be used for solving the critical task of securing civil infrastructure.