Investigation of the Effects of End Region Deterioration in Precast, Prestressed Concrete Bridge Girders

An important factor in life expectancy of concrete bridges is the effect of corrosion of reinforcing steel on concrete and appurtenant embedded materials. New bridges, though continuously exposed to the elements, are expected to last roughly 75 years. Particularly important for aging infrastructure is determining methods to rehabilitate a structure where complete replacement may not be a feasible option. This research is intended to build on the current body of knowledge surrounding corrosion related deterioration of prestressed concrete girders due to extreme environments. Nine prestressed half-scale AASHTO Type II girders were constructed that replicated girders from a bridge recently taken out of service (from I-244 in Tulsa County), which was representative of a large number of aging bridges in the state of Oklahoma. Two different girder designs, corresponding to the different prestressing strand configurations used in the original bridge were utilized. One end region of each girder was exposed to a corrosion accelerant process, and three different exposures were used to illustrate varying environmental conditions. The end regions of six girders were shear tested, after damage by corrosion, to provide an understanding of the effects of end region deterioration on strand anchorage and shear capacity. Measured shear values were less than the nominal design shear capacity (ACI and AASHTO LFRD 2007 methods) for each girder. All of the girder ends that had been exposed to the corrosive environment had a larger measured shear than the control end, except for one girder (C2). Of the six shear tests on the corroded end of the girders, four resulted in slip of the prestressing strands prior to the initial crack of the beam. For the control end of the girders, all six shear tests illustrated cracking of the girder prior to the initiation of slip. Concurrently with the lab experiments, this research included visiting and inspecting similar bridges as those used in the design for the lab experiment (prestressed concrete bridges with AASHTO Type II girders) to identify varying levels of deterioration due to corrosion. Over the course of 19 site visits, the following deterioration characteristics were identified: corroded bearing plates; corroded anchor bolts and nuts; spalling above the support; exposed rebar and prestressing strands; diagonal cracking of the back corner of the girder; vertical cracking along the girder and diaphragm interface; diagonal cracking from the top flange and web interface; and diaphragm deterioration. Together, the observations from the field inspections and the lab experiments were used to analyze existing retrofit methods and determine recommendations for in-situ rehabilitation for varying levels of deterioration. While the research does not provide a final solution, the results are expected to provide more breadth in our understanding of prestressed concrete, shear design, effects of corrosion and methods to rehabilitate aging infrastructure

Optimal Coordination of Distributed Energy Resources in Isolated Power Systems: A Cross-Time Scale Perspective

This dissertation investigates the problem of optimally coordinating distributed energy resources (DERs) in isolated power systems. It is motivated by the recent efforts worldwide of integrating large amounts of renewable generation into power grids to provide more sustainable electricity services. The increased penetration of renewable generation presents challenges for power systems operations due to increased variability and uncertainty occurring at multiple time scales. The challenge of coordinating resources cost effectively while ensuring adequate technical performance is even more pronounced in isolated power systems that are vulnerable to disturbances because of low inertia and limited generation capacity. Tertiary control approaches have been proposed for managing resources economically and all approaches assume time scale separation exists with lower level secondary and/or primary controls. Some works have mentioned that tertiary controls should be executed faster (i.e., seconds). However, if tertiary controls are executed faster, so as to interact with lower level control actions, this could cause exacerbated technical performance (e.g., frequency performance). The effect of dispatching at shorter time scales, on technical performance, has not yet been investigated. In this work, such cross-coupling among different time scales is considered, and an optimal coordination (OC) strategy for isolated microgrid systems with a mix of DERs is proposed. The goals of the OC strategy are to simultaneously minimize operating costs of diesel generators and maximize the utilization of wind generation, while considering equipment life of DERs, physical limitations on the individual controllable resources and maintain adequate frequency performance. Time scale coupling between the OC strategy and primary controls was investigated along with key parameters affecting tertiary control performance. The effectiveness of the OC strategy is evaluated in terms of frequency, economic and computational performance under realistic scenarios. To capture the impact on frequency performance, simulations were performed on a dynamical model of an isolated microgrid system. Results suggest that the proposed approach is generalizable towards designing multi-time scale optimal coordination strategies for isolated power systems to satisfy both economic and operational objectives. Recommendations are given on extending the approach to other types of isolated power systems with different variability and uncertainty characteristics

Coordinating Dispatch of Distributed Energy Resources with Model Predictive Control and Q-Learning

Distributed energy resources such as renewable generators (wind, solar), energy storage, and demand response can be used to complement fossil-fueled generators. The uncertainty and variability due to high penetration of renewable resources make power system operations and controls challenging. This work addresses the coordinated operation of these distributed resources to meet economic, reliability, and environmental objectives. Recent research proposes Model Predictive Control (MPC) to solve the problem. However, MPC may yield a poor performance if the terminal penalty function is not chosen correctly. In this work, a parameterized Q-learning algorithm is devised to approximate the optimal terminal penalty function. This approximate penalty function is then used in MPC, thus effectively combining the two techniques. It is argued that this combination approach would lead to the best solution in terms of computation, and adaptability to a changing environment. Simulation studies demonstrating the efficacy of the proposed methodology for power system dispatch problems are presented.National Science Foundation / CPS-0931416Department of Energy / DE-OE0000097 and DE-SC0003879Pacific Northwest National LaboratoryOpe

Long-Term Learning Deficits and Neurochemical Changes Result

METH is known to produce neurotoxic effects in the central nervous system, affecting an array of behaviors. This study examined the effects of METH on spatial learning and correlative changes in neurochemistry. Rats were trained in a visuospatial task requiring a correct barpress opposite the stimulus location until they reached a criterion of acquisition (\u3e85% correct, three sessions). Rats received four injections of METH (9.0 mg/kg) or saline at 12-hour interval. Two weeks following treatment, rats were retested on the same task to examine METH effects on retention. METH treatment displayed no significant effect on retention. Rats then began training on a reversal task requiring a correct barpress same as stimulus location to examine METH effects on new learning. METH treatment impaired performance on the reversal task, showing a delayed learning. The fact that learning prior to METH exposure remains intact suggests that learning METH-induced impairment is specific to new learning. Dopamine levels were measured using HPLC and compared between treatment conditions. Results indicated an upregulation of dopamine in the prefrontal cortex and the nucleus accumbens of METHtreated rats, suggesting the escalated levels of dopamine are responsible for learning deficits