A. James Clark School of Engineering
Permanent URI for this communityhttp://hdl.handle.net/1903/1654
The collections in this community comprise faculty research works, as well as graduate theses and dissertations.
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Item Systematic Integration of PHM and PRA (SIPPRA) for Risk and Reliability Analysis of Complex Engineering Systems(2021) Moradi, Ramin; Groth, Katrina; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Complex Engineering Systems (CES) such as power plants, process plants, and manufacturing plants have numerous, interrelated, and heterogeneous subsystems with different characteristics and risk and reliability analysis requirements. With the advancements in sensing and computing technology, abundant monitoring data is being collected. This is a rich source of information for more accurate assessment and management of these systems. The current risk and reliability analysis approaches and practices are inadequate in incorporating various sources of information, providing a system-level perspective, and performing a dynamic assessment of the operation condition and operation risk of CES. In this dissertation, this challenge is addressed by integrating techniques and models from two of the major subfields of reliability engineering: Probabilistic Risk Assessment (PRA) and Prognostics and Health Management (PHM). PRA is very effective at modeling complex hardware systems, and approaches have been designed to incorporate the risks introduced by humans, software, organizational, and other contributors into quantitative risk assessments. However, PRA has largely been used as a static technology mainly used for regulation. On the other hand, PHM has developed powerful new algorithms for understanding and predicting mechanical and electrical device health to support maintenance. Yet, PHM lacks the system-level perspective, relies heavily on operation data, and its outcomes are not risk-informed. I propose a novel framework at the intersection of PHM and PRA which provides a forward-looking, model- and data-driven analysis paradigm for assessing and predicting the operation risk and condition of CES. I operationalize this framework by developing two mathematical architectures and applying them to real-world systems. The first architecture is focused on enabling online system-level condition monitoring. The second architecture improves upon the first and realizes the objectives of using various sources of information and monitoring operation condition together with operational risk.Item STOCHASTIC SIMULATION OF WOLF CREEK DAM OPERATIONS FOR USACE(2019) Padmanabhan, Rahul; Baecher, Gregory B; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The Wolf Creek Dam situated on the Cumberland River in the state of Kentucky, United States is a multipurpose dam generating hydroelectricity, providing flood risk reduction, supporting year-round navigation on the lower Cumberland River, and it creating Lake Cumberland for recreation and water supply. The latter is a popular tourist attraction. Because of piping and internal erosion problems in the dam's foundation, it is a USACE top-priority structure. This thesis experiments with and tests the applicability of a stochastic simulation of the dam using historical inflow data based on a model built on GoldSim™. The model uses standard operating rules of the Dam to spot possible failures to the turbines that could affect the performance of the dam. In addition, the model simulates the behavior of the dam 50 years in to the future during which time the components reach their close to their maximum life. Results of the study suggest that simulation models of this type may serve to provide information for reliability-based maintenance strategies, and to help identify adverse patterns of dam performance which may be addressed through asset management.Item A SYSTEMS RELIABILITY APPROACH TO MODELING OPERATIONAL RISKS IN COMPLEX ENGINEERED SYSTEMS(2018) Komey, Adiel Ayi; Baecher, Gregory B; Modarres, Mohammad; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Since the beginning of the industrial revolution in the late 18th century, the cause of many serious accidents in hydrosystems engineering has shifted from natural causes to human and technology related causes as these systems get more complex. While natural disasters still account for a significant amount of human and material losses, man-made disasters are responsible for an increasingly large portion of the toll, especially in the safety critical domain such as Dam and Levee systems. The reliable performance of hydraulic flow-control systems such as dams, reservoirs, levees etc. depends on the time-varying demands placed upon it by hydrology, operating rules, the interactions among subsystem components, the vagaries of operator interventions and natural disturbances. In the past, engineers have concerned themselves with understanding how the component parts of dam systems operate individually and not how the components interact with one another. Contemporary engineering practices do not address many common causes of accidents and failures, which are unforeseen combinations of usual conditions. In recent decades, the most likely causes of failures associated with dams have more often had to do with sensor and control systems, human agency, and inadequate maintenance than with extreme loads such as floods and earthquakes. This thesis presents a new approach, which combines simulation, engineering reliability modeling, and systems engineering. The new approach seeks to explore the possibilities inherent in taking a systems perspective to modeling the reliability of flow-control functions in hydrosystems engineering. Thus, taking into account the interconnections and dependencies between different components of the system, changes over time in their state as well as the influence upon the system of organizational limitations, human errors and external disturbances. The proposed framework attempts to consider all the physical and functional interrelationships between the parts of the dam and reservoir, and to combine the analysis of the parts in their functional and spatial interrelationships in a unified structure. The method attempts to bring together the systems aspects of engineering and operational concerns in a way that emphasizes their interactions. The argument made in this thesis is that systems reliability approach to analyzing operational risks—precisely because it treats systems interactions—cannot be based on the decomposition, linear methods of contemporary practice. These methods cannot logically capture the interactions and feedback of complex systems. The proposed systems approach relies on understanding and accurately characterizing the complex interrelationships among different elements within an engineered system. The modeling framework allows for analysis of how structural changes in one part of a system might affect the behavior of the system as a whole, or how the system responds to emergent geophysical processes. The implementation of the proposed approach is presented in the context of two case studies of US and Canadian water projects: Wolf Creek Dam in Kentucky and the Lower Mattagami River Project in Northern Ontario.Item Risk Analysis and Damage Assessment For Flood Prone Areas in Washington DC(2011) Lessani, Arian; Baecher, Gregory B; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This thesis presents a loss estimation method regarding areas of District of Columbia susceptible to flooding, specifically the Southwest quadrant, the National Mall, and Federal Triangle. This thesis develops data for input to a flood model that considers parameters such as detailed digital elevation data, global warming potential, and storm surge for a category IV hurricane. The main goal of this study is to employ a standard method for estimating flooding damages in Washington by supplying combination of the mentioned parameters to the HAZUS-MH 2.0 program. The results of this research is useful for planning purposes, such as reducing natural hazard losses and preparing emergency response and recovery. It is predicted that in the projected storm surge flood more than 1500 buildings would be damaged and about ten thousand people would seek temporary refuge in public shelters. The estimate of total loss for flooding is approximately $1,300 million dollars.Item INCREASING DURABILITY OF HOT MIX ASPHALT PAVEMENTS DESIGNED WITH THE SUPERPAVE SYSTEM(2009) Karimi, Sahand Sasha; Goulias, Dimitrios G; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)With the implementation of the Superpave mix design method, state highway agencies have experienced significant problems in durability of Hot Mix Asphalt mixtures due to lower binder content. To get a better understanding of the HMA mix production and the current specifications used by MSHA, the following were examined: i) differences in HMA properties that have been observed between samples taken at the plant (QC) vs. behind the paver (QA), ii)possibility of defining a transfer function between QA and QC data and iii) the potential risk to both the agency and the contractors using simulation analysis and based on the current specifications and pay factor equations. For this purpose a simulation tool was developed. The F and t tests showed that the QA and QC are two different populations and cannot be related. The simulation analysis illustrated that the correlation among mixture parameters doesn't affect the long run average pay factor. In addition it was concluded that the newly adopted pay equations are fairly rewarding and penalizing the contractors for mixtures, but the density pay equation needs modification.Item A Methodology for Project Risk Analysis using Bayesian Belief Networks within a Monte Carlo Simulation Environment(2007-04-26) Ordonez Arizaga, Javier F.; Baecher, Gregory B; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Projects are commonly over budget and behind schedule, to some extent because uncertainties are not accounted for in cost and schedule estimates. Research and practice is now addressing this problem, often by using Monte Carlo methods to simulate the effect of variances in work package costs and durations on total cost and date of completion. However, many such project risk approaches ignore the large impact of probabilistic correlation on work package cost and duration predictions. This dissertation presents a risk analysis methodology that integrates schedule and cost uncertainties considering the effect of correlations. Current approaches deal with correlation typically by using a correlation matrix in input parameters. This is conceptually correct, but the number of correlation coefficients to be estimated grows combinatorially with the number of variables. Moreover, if historical data are unavailable, the analyst is forced to elicit values for both the variances and the correlations from expert opinion. Most experts are not trained in probability and have difficulty quantifying correlations. An alternative is the integration of Bayesian belief networks (BBN's) within an integrated cost-schedule Monte Carlo simulation (MCS) model. BBN's can be used to implicitly generate dependency among risk factors and to examine non-additive impacts. The MCS is used to model independent events, which are propagated through BBN's to assess dependent posterior probabilities of cost and time to completion. BBN's can also include qualitative considerations and project characteristics when soft evidence is acquired. The approach builds on emerging methods of systems reliability.