UMD Theses and Dissertations
Permanent URI for this collectionhttp://hdl.handle.net/1903/3
New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a given thesis/dissertation in DRUM.
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Item Advanced methodologies for reliability-based design optimization and structural health prognostics(2010) Wang, Pingfeng; Youn, Byeng Dong; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Failures of engineered systems can lead to significant economic and societal losses. To minimize the losses, reliability must be ensured throughout the system's lifecycle in the presence of manufacturing variability and uncertain operational conditions. Many reliability-based design optimization (RBDO) techniques have been developed to ensure high reliability of engineered system design under manufacturing variability. Schedule-based maintenance, although expensive, has been a popular method to maintain highly reliable engineered systems under uncertain operational conditions. However, so far there is no cost-effective and systematic approach to ensure high reliability of engineered systems throughout their lifecycles while accounting for both the manufacturing variability and uncertain operational conditions. Inspired by an intrinsic ability of systems in ecology, economics, and other fields that is able to proactively adjust their functioning to avoid potential system failures, this dissertation attempts to adaptively manage engineered system reliability during its lifecycle by advancing two essential and co-related research areas: system RBDO and prognostics and health management (PHM). System RBDO ensures high reliability of an engineered system in the early design stage, whereas capitalizing on PHM technology enables the system to proactively avoid failures in its operation stage. Extensive literature reviews in these areas have identified four key research issues: (1) how system failure modes and their interactions can be analyzed in a statistical sense; (2) how limited data for input manufacturing variability can be used for RBDO; (3) how sensor networks can be designed to effectively monitor system health degradation under highly uncertain operational conditions; and (4) how accurate and timely remaining useful lives of systems can be predicted under highly uncertain operational conditions. To properly address these key research issues, this dissertation lays out four research thrusts in the following chapters: Chapter 3 - Complementary Intersection Method for System Reliability Analysis, Chapter 4 - Bayesian Approach to RBDO, Chapter 5 - Sensing Function Design for Structural Health Prognostics, and Chapter 6 - A Generic Framework for Structural Health Prognostics. Multiple engineering case studies are presented to demonstrate the feasibility and effectiveness of the proposed RBDO and PHM techniques for ensuring and improving the reliability of engineered systems within their lifecycles.Item Design considerations in wireless sensor networks(2004-08-02) Borbash, Steven A.; Ephremides, Anthony; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)We consider three problems in the design of wireless sensor networks: cross-layer optimization, neighbor discovery, and scheduling as a method of medium access control (MAC). Cross-layer optimization will be important for sensor networks, which typically have only one or two objectives to meet. We consider a sensor network which performs decentralized detection. We devise a method in which local observations by sensors are condensed into a single bit message and forwarded to a sink node which makes a final decision. The method involves unusual interactions between the application, the routing function, and the physical layer. Neighbor discovery is useful in sensor networks whose nodes are immobile, since routing and scheduling algorithms can make good use of neighbor information. We propose an asynchronous neighbor discovery algorithm. The algorithm is probabilistic: each node obtains a list of its neighbors which is possibly incomplete. Performance is analyzed and optimal parameter settings are obtained. Scheduling deserves consideration as a MAC in sensor networks, because MACs based on contention methods waste energy in retransmissions. We state a natural centralized scheduling problem, in which link demands are to be satisfied under signal-to-interference-and-noise-ratio (SINR) constraints, and transmit powers may be varied. We show that solving this minimum length scheduling problem is at least as hard as another problem we define, MAX-SINR-MATCHING, in the sense that if there is no polynomial-time algorithm to solve the latter then there is no polynomial-time algorithm to solve the former. We give evidence that MAX-SINR-MATCHING is a difficult problem. We add several theorems on the SINR model which exploit algebraic structure. The theorems predict what sets of links could be simultaneously activated in a wireless network and depend only on the SINR requirements of the nodes and the worst propagation loss in a network. These theorems apply to all wireless networks which can be described by SINR requirements, not only to sensor networks.