Peter C. Chang

Bio: Peter C. Chang is an academic researcher from University of Maryland, College Park. The author has contributed to research in topics: Optimization problem & Boundary value problem. The author has an hindex of 7, co-authored 14 publications receiving 1086 citations.

Review Paper: Health Monitoring of Civil Infrastructure:

Abstract: Increased awareness of the economic and social effects of aging, deterioration and extreme events on civil infrastructure has been accompanied by recognition of the need for advanced structural health monitoring and damage detection tools. Today, these tasks are done by visual inspection and very traditional methods such as the tap test. This labor-intensive task is done at a frequency of less than once every two years for bridges, and on an as-needed basis for other infrastructures such as buildings. Structural health monitoring techniques based on changes in dynamic characteristics have been studied for the last three decades. When the damage is substantial, these methods have some success in determining if damage has occurred. At incipient stages of damage, however, the existing methods are not as successful. A number of new research projects have been funded to improve the damage detection methods including the use of innovative signal processing, new sensors, and control theory. This survey paper hig...

Recent Research in Nondestructive Evaluation of Civil Infrastructures

Abstract: Assessing the condition of a structure is necessary to determine its safety and reliability. Ideally, structural health monitoring should be similar to medical health monitoring of the body. In medical health monitoring, the life signs such as pulse and blood pressure give an overall indication of the overall health of the body. This is analogous to global structural health monitoring, in which damage to the structure can be identified by measuring changes in the global properties of the structure. Once the body signs show an anomaly, we do a battery of tests to determine the cause of the anomaly. Analogously in structural health monitoring, nondestructive evaluation (NDE) can be used to determine the nature of the damage. NDE methods to determine local damage are also becoming more accepted in practice. This paper describes some of the recent and current National Science Foundation projects in this area of research. Promising areas for NDE are identified.

Improvements to sight distance algorithm

Abstract: This paper describes improvements developed for an existing algorithm that calculates sight distance profiles based on horizontal geometry Exact expressions are developed for vector derivatives for plane curves including clothoid spirals Coordinate and derivative vectors are developed for partial spirals that possess nonzero curvature at both ends, frequently used as transitions between circular curves of different radii As with complete spirals, the coordinate vectors are approximate and the derivative vectors are exact Finally, an exact method for measuring distance along an offset curve to a clothoid spiral is developed Taken together with the results in a previous referenced paper, this represents a complete recipe for computing sight distance profiles along arbitrary horizontal alignments A numerical example is included to illustrate the use of the algorithm

Autonomous agents for traffic simulation and control

Abstract: The development of an infrastructure for multiple autonomous agents, with an application to urban traffic signal control, is described. The agent-based infrastructure, Cybele, allows for distributed computing, interagent communication, agent migration, and computational resource allocation. The agents that are used to solve the traffic signal control problem are known collectively as DAARTS (Decentralized Adaptive Agents for contRol of Traffic Signals). DAARTS adopts a hierarchical multiagent-based architecture in which the lowest level (intersection agents) involves individual intersection-traffic dynamics and phase selection based on "local" information, while higher levels take into account the supervisory (network-level) dynamics. The controller design is based on a receding-horizon model predictive control approach. Coordination between inter-sections is achieved in a decentralized manner at the lowest level. The agents are integrated into a simulation test bed with the microsimulator CORSIM, using t...

Prognostics and health management of electronics

Abstract: There has been a growing interest in monitoring the ongoing "health" of products and systems in order to predict failures and provide warning to avoid catastrophic failure. Here, health is defined as the extent of degradation or deviation from an expected normal condition. While the application of health monitoring, also referred to as prognostics, is well established for assessment of mechanical systems, this is not the case for electronic systems. However, electronic systems are integral to the functionality of most systems today, and their reliability is often critical for system reliability. This paper presents the state-of-practice and the current state-of-research in the area of electronics prognostics and health management. Four current approaches include built-in-test (BIT), use of fuses and canary devices, monitoring and reasoning of failure precursors, and modeling accumulated damage based on measured life-cycle loads. Examples are provided for these different approaches, and the implementation challenges are discussed.

Prognostics and Health Management of Electronics

Abstract: Reliability is the ability of a product or system to perform as intended (i.e., without failure and within specified performance limits) for a specified time, in its life-cycle environment. Commonly used electronics reliability prediction methods (e.g., Mil-HDBK-217, 217-PLUS, PRISM, Telcordia, FIDES) based on handbook methods have been shown to be misleading and provide erroneous life predictions. The use of stress and damage models permits a far superior accounting of the reliability and the physics of failure (PoF); however, sufficient knowledge of the actual operating and environmental application conditions of the product is still required. This article presents a PoF-based prognostics and health management approach for effective reliability prediction. PoF is an approach that utilizes knowledge of a product's life-cycle loading and failure mechanisms to perform reliability modeling, design, and assessment. This method permits the assessment of the reliability of a system under its actual application conditions. It integrates sensor data with models that enable in situ assessment of the deviation or degradation of a product from an expected normal operating condition and the prediction of the future state of reliability. This article presents a formal implementation procedure, which includes failure modes, mechanisms, and effects analysis, data reduction and feature extraction from the life-cycle loads, damage accumulation, and assessment of uncertainty. Applications of PoF-based prognostics and health management are also discussed. Keywords: reliability; prognostics; physics of failure; design-for-reliability; reliability prediction

Guided wave based structural health monitoring: A review

Abstract: The paper provides a state of the art review of guided wave based structural health monitoring (SHM). First, the fundamental concepts of guided wave propagation and its implementation for SHM is explained. Following sections present the different modeling schemes adopted, developments in the area of transducers for generation, and sensing of wave, signal processing and imaging technique, statistical and machine learning schemes for feature extraction. Next, a section is presented on the recent advancements in nonlinear guided wave for SHM. This is followed by section on Rayleigh and SH waves. Next is a section on real-life implementation of guided wave for industrial problems. The paper, though briefly talks about the early development for completeness,. is primarily focussed on the recent progress made in the last decade. The paper ends by discussing and highlighting the future directions and open areas of research in guided wave based SHM.