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Electrochemical capacitors (ECs) have received a significant level of interest for use in the electric utility industry for a variety of potential applications. For example, ECs integrated with a power conversion system can be used to assist the electric utility by providing voltage support, power factor correction, active filtering, and reactive and active power support. A number of electric utility applications have been proposed but, to date, ECs have not been very well characterized for use in these applications. Consequently, there is a need to gain a better understanding of ECs when used in electric utility applications. ECs are attractive for utility applications because they have higher energy density than conventional capacitors and higher power density than batteries. ECs also have higher cycle life than batteries, which results in longer life spans. To better understand the system dynamics when ECs are used for utility applications requires suitable models that can be incorporated into the variety of software programs currently used to create dynamic simulations for the applications, programs such as PSPICE™, MATLAB Simulink™, and PSCAD™. To obtain a relevant simulation with predictive capability, the behavior of the EC on which the model is based must be well defined; this necessitates a thorough understanding of the electrical characteristics of these devices. This paper and the associated research focus on the use of the electrochemical impedance spectroscopy (EIS) to develop nonlinear equivalent circuit models to better understand and characterize symmetric ECs (SECs) for electric utility applications. It also focuses on the development of analytical solutions to better understand SEC efficiency and energy utilization. Representative static synchronous compensator (StatCom) systems, with and with out SECs, were simulated and discussed. The temperature effects on device ionic resistance and capacitance are covered as is the effect of temperature on maximum power transfer to a resistive load. Experimental data showed that the SEC's double-layer capacitance and ionic resistance are voltage dependent. Therefore a voltage-dependent RC network model was developed and validated and the results showed that this type of model mimicked the experimental SEC better than traditional electrical models. Analytical solutions were developed for the efficiency and energy utilization of an SEC. The analytical solutions are a function of operating voltages, constant current, and ionic resistance. The operating voltage method is an important factor in system design because the power conversion interface is typically limited by a voltage window and thus can determine the performance of SECs during charge and discharge. If the operating voltage window is not properly selected the current rating of the system can be reduced thus limiting the SECs performance. / Ph. D.

Utility Accrual (UA) scheduling is a method of dynamic real-time scheduling that is designed to respond to overload conditions by producing a feasible schedule that heuristically maximizes a pre-defined metric of utility. Whereas utility accrual schedulers have traditionally focused on CPU overload, this dissertation explores memory overload conditions during which the aggregate memory demand exceeds a system's available memory bandwidth. Real-time systems are typically implemented in C or other languages that use explicit dynamic memory management. Taking advantage of modern type-safe languages, such as Java, necessitates the use of garbage collection (GC). The timeliness requirements of real-time systems, however, impose specific demands on the garbage collector. Garbage collection introduces a significant source of unpredictability in the execution timeline of a task because it unexpectedly interjects pauses of arbitrary length, at arbitrary points in time, with an arbitrary frequency. To construct a feasible schedule, a real-time scheduler must have the ability to predict the collector's activities and plan for them accordingly. We have devised CADUS (Collector-Aware Dynamic Utility Scheduler), a utility accrual algorithm that tightly links CPU scheduling with the memory requirements -and the corresponding garbage collection activities - of real-time tasks. By constructing and storing memory time allocation profiles, we address the problem of GC activation strategy. We estimate GC latency by using a real-time collector and modeling its behavior. We project GC frequency by planning, at schedule construction time, the memory bandwidth available to the collector. CADUS can point the collector's activities to any specific task in the system. The runtime system provides this ability by maintaining separate logical heaps for all tasks. We demonstrate the viability of CADUS through extensive simulation studies. We evaluated the behavior of CADUS under a wide range of CPU and memory load conditions and utility distributions. We compared its performance against an existing GC-unaware UA scheduler and found that CADUS consistently outperformed its GC-unaware counterpart. We investigated and identified the reasons for the superior performance of CADUS and quantified our results. Most significantly, we found that in an overloaded dynamic soft real-time system, a scheduler's preemption decisions have a highly significant impact on GC latency. A dynamic real-time scheduler therefore must predict the impact of its preemption decisions on GC latency in order to construct time-feasible schedules. / Ph. D.

Existing literature on the relationship between ridehailing (RH) and transit services is limited to empirical studies that rely on self-reported answers and lack spatial and temporal contexts. To fill this gap, the research takes a novel approach that uses real-time geospatial analyzes. Using this approach, we estimate the extent to which ride-hailing services have contributed to the recent decline in public transit ridership. With source data on ridehailing trips in Chicago, Illinois, we computed the real-time transit-equivalent trip for the 7,949,902 ridehailing trips in June 2019; the sheer size of this sample is incomparable to the samples studied in existing literature. An existing Multinomial Nested Logit Model was used to determine the probability of a ridehailer selecting a transit alternative to serve the specific origin-destination pair, P(Transit|CTA) . The study found that 31% of RH trips are replaceable, 61% are not replaceable, and 8% lie within the buffer zone. We measured the robustness of this probability using a parametric sensitivity analysis, and performed a two-tailed t-test, with a 95% confidence interval. In combination with a Summation of Probabilities, the results indicate that the total travel time for a transit trip has the greatest influence on the probability of using transit, whereas the airport pass price has the least influence. Further, the walk time, number of stops in the origin and destination census tracts, and household income also have significant impacts on the probability of using transit. Lastly, we performed a Time Value Analysis to explore the cost and trip duration difference between RH trips and their transit-equivalent trips on the probability of switching to transit. The findings demonstrated that approximately 90% of RH trips taken had a transit-equivalent trip that was less expensive, but slower. The main contribution of this study is its thorough approach and fine-tuned series of real-time spatial analyzes that investigate the replaceability of RH trips for public transit. The results and discussion intend to provide perspective derived from real trips and encourage public transit agencies to look into possible opportunities to collaborate with ridehailing companies. Moreover, the methodologies introduced can be used by transit agencies to internally evaluate opportunities and redundancies in services. Lastly, we hope that this effort provides proof of the research benefits associated with the recording and release of ridehailing data. / Master of Science / Existing literature on the relationship between ridehailing (RH) and transit services is limited to empirical studies that rely on self-reported answers and lack spatial and temporal contexts. To fill this gap, the research takes a novel approach that uses real-time geospatial analyzes. Using this approach, we estimated the extent to which ride-hailing services have contributed to the recent decline in public transit ridership. With source data on ridehailing trips in Chicago, Illinois, we computed the real-time transit-equivalent trip for the 7,949,902 ridehailing trips in June 2019; the sheer size of this sample is incomparable to the samples studied in existing literature. An existing Multinomial Nested Logit Model was used to determine the probability of a ridehailer selecting a transit alternative to serve the specific origin-destination pair, P(Transit|CTA) . The study found that 31% of RH trips are replaceable, 61% are not replaceable, and 8% lie within the buffer zone. We measured the robustness of this probability using a parametric sensitivity analysis, and performed a two-tailed t-test, with a 95% confidence interval. In combination with a Summation of Probabilities, the results indicate that the total travel time for a transit trip has the greatest influence on the probability of using transit, whereas the airport pass price has the least influence. Further, the walk time, number of stops in the origin and destination census tracts, and household income also have significant impacts on the probability of using transit. Lastly, we performed a Time Value Analysis to explore the cost and trip duration difference between RH trips and their transit-equivalent trips on the probability of switching to transit. The findings demonstrated that approximately 90% of RH trips taken had a transit-equivalent trip that was less expensive, but slower. The main contribution of this study is its thorough approach and fine-tuned series of real-time spatial analyzes that investigate the replaceability of RH trips for public transit. The results and discussion intend to provide perspective derived from real trips and encourage public transit agencies to look into possible opportunities to collaborate with ridehailing companies. Moreover, the methodologies introduced can be used by transit agencies to internally evaluate opportunities and redundancies in services. Lastly, we hope that this effort provides proof of the research benefits associated with the recording and release of ridehailing data.

Under the evolving environment, a utility company is required to improve the operation and maintenance of its physical assets usually in the forms of an asset management program. This paper proposes an organisational learning model for the utility companies with respect to the asset management activities. CommonKADS is utilised as a tool to capture the knowledge associated with managing the assets from the learning processes of the utility company. A case study of Bangpakong power plant in Thailand is presented. The results show that by applying the proposed methodologies, the learning processes within the utility companies can be categorised and explained by five major learning steps of breakdown, corrective, preventive, predictive, and proactive maintenances.

High-quality drinking water and wastewater systems are essential to public health, business, and quality of life in the United States. Even though the current performance of these systems is moderate, the concern is about the future performance. Planning can be done for improvement once the current performance of utilities is evaluated, and areas with a scope of improvement are identified. Benchmarking and performance evaluation are key components in the process of continuous improvement for utility's performance. Benchmarking helps utilities make policies and programmatic decisions that reduce operational expenses and increase productivity by understanding areas of underperformance, understanding customer needs, developing future plans, and setting goals. This study establishes a strong case for implementing benchmarking methodologies among utilities to evaluate and improve performance. There are many initiatives on performance benchmarking of utilities but a few of them focuses on one or few area of performance. There are a few initiatives which use subjective indicators. Additionally, consultants visit the utilities for performance evaluation. This research focuses on creating a web-based benchmarking platform for performance evaluation using holistic and quantitative indicators. Practical and robust methodologies are used and the research presents the current performance comparisons among utilities for areas that impact overall utility's performance. Web based benchmarking consists of two major parts -- data collection and result visualization. A major contribution from this study is the creation of an online performance benchmarking database. With time more data will be collected which will provide utilities an access to a better database for performance evaluation. The future work in this research will be analyzing the data and results for each participant for each set of indicators, and finding possible reasons for under performance, followed by suggesting solutions for improvement using the best practices. / Master of Science

The location of utilities buried beneath the built environment has always been a concern for those conducting work that involves excavation or the placement of items into the ground. Whether physically removing material or driving piles, posts, and more, the potential for accidental utility strikes is increasing with the movement of more traditional utilities from above ground to below. Also, the addition of utilities and new technology in underground spaces that hasn't existed in the past, such as fiber optics and more highspeed telecommunication lines, is occupying more space. Traditional methods of surveying, in combination with surface geophysics and the development and improvement of processes and technologies to track the location of buried assets led to the engineering services category termed Subsurface Utility Engineering (SUE). In order to aid utility engineers and consultants who are responsible for the collection of utility data this research aimed to help identify a way to compare the various technologies and incorporate information about the individual project in order to choose the most appropriate locating method for a project with a defined set of parameters. The result was the development of standard evaluation forms that can be sent to technology vendors and consultants to evaluate the performance and limitations of a technology. This data can then be compiled into a database located within an Excel-based program created to compare the technologies. The program, VT PALMS (Virginia Tech Program for Asset Locating Method Selection), consists of the performance and economic databases, a project information Page sheet, and the results of the comparison of each technology in the database to the information on the project information sheet. The results are presented in three ways; 1) a speedometer chart with a needle that indicates the percentage of the parameters used in the database that are compatible - also referred to as the Reliability Factor, 2) a matrix view that indicates the parameters where a potential conflict may exist, and 3) an economic indicator that shows the comparable cost of using each technology listed in the database. / Master of Science

The Brief Adjustment Scale-6 (BASE-6) was recently developed and initially examined as a brief, reliable, no-cost survey for measuring general psychological functioning within Measurement-Based Care (MBC). This study aims to further evaluate the psychometric properties of the BASE-6 in both clinical and nonclinical populations. More specifically, psychometric properties including reliability and validity, generalizability for different race/ethnic samples, and clinical utility within the context of MBC were examined. Three adult samples participated in this study: online community participants (Sample 1: n = 394), college students (Sample 2: n = 249), and individuals receiving outpatient clinical services (Sample 3: n = 80). Participants within the clinical sample regularly completed the BASE-6 while receiving evidence-based treatment in a community based psychological training clinic, where the practice of MBC is standard. Results showed that the BASE-6 had a high level of internal consistency and good test-retest reliability. It showed high convergent validity through a significant positive correlation with total and subscale scores of the Depression Anxiety Stress Scale-21 (DASS-21). Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) results supported a unidimensional model that strongly fit the data. All results were uniform across samples. When comparing the clinical and nonclinical samples, participants from the clinical sample demonstrated higher scores in total and most of the single items of the BASE-6. Finally, within the clinical sample, the BASE-6 was sensitive enough to capture change over time by demonstrating a large effect size of pre-post treatment changes and significant linear change in multilevel growth modeling. These results support the BASE-6 as a reliable and valid measure that has a one-factor structure, regardless of race/ethnicity and participants’ clinical status. Additionally, it can sensitively detect clinical change in individuals over the course of the treatment. Thus, the BASE-6 appears to accurately monitor overall psychological adjustment. / M.S. / The Brief Adjustment Scale-6 (BASE-6) is a short, no-cost survey that assesses general psychological adjustment. It can be used in a psychotherapy setting to evaluate overall functioning of individuals on a regular basis. This study aims to further investigate the BASE-6 in both clinical and nonclinical populations, more specifically, whether the BASE-6 questionnaire is reliable, consistent, and valid with various race/ethnic populations. Additionally, it was examined if the BASE-6 can sensitively capture the change in psychological adjustment over the course of treatment. Three adult groups participated in this study: online community participants (Sample 1: n = 394), college students (Sample 2: n = 249), and individuals receiving outpatient clinical services (Sample 3: n = 80). Participants within the clinical sample regularly completed the BASE-6 while receiving psychotherapy in a community based psychological training clinic. Results showed that the BASE-6 was a reliable, consistent measure and the items all measured the same construct – general psychological adjustment. The BASE-6 was also highly correlated with depression, anxiety, and stress. Results did not differ across samples or race/ethnicity. When comparing the clinical and nonclinical samples, participants from the clinical sample showed higher scores of the BASE-6. Finally, within the clinical sample, the BASE-6 was sensitive enough to capture change over time by demonstrating large treatment changes from the beginning until the end of the treatment. These results support the BASE-6 as a reliable and valid measure regardless of race/ethnicity and participants’ clinical status. Additionally, it can sensitively detect clinical changes in clients over the course of the treatment. Thus, the BASE-6 appears to accurately monitor overall psychological adjustment.

Aim: To explore the patient-reported utility of learning incidental results (IR) from genomic sequencing (GS) in a cancer population. Methods: A qualitative study was performed using semi-structured interviews with participants who had undergone genomic sequencing and were returned incidental results. Transcripts were thematically analyzed using constant comparison. Results: Twenty-three participants were interviewed (21/23 women) with an average age of 57. At the heart of returning incidental results was the empowerment of participants. Empowerment was experienced in three ways: clinical utility, back pocket information, and satisfying a thirst for knowledge and learning. Clinical utility informed medical management, “back pocket information” provided greater agency in participants’ future health and the process of learning IR created a sense of security toward participant well-being. The degree of empowerment experienced was influenced by participants’ evaluation of relevancy and perceived risk of their incidental results. Conclusions: Learning incidental results empowered patients by informing medical management, increasing agency in future health, and creating a sense of security toward well-being. These findings could inform future policies surrounding the return of incidental genomic results. / 2026-10-31T00:00:00Z

A study was made of the leakage conductance to earth of the neutral of direct-burial concentric-neutral underground primary cable. This study was suggested in conjunction with a paper by Mr. D, L. Stone of the Rural Electrification Administration, "Reduced Concentric Neutral Primary Cable for Underground Rural Distribution." The derivation of an equation for the leakage conductance is presented which takes into account the return of the leakage currents to the neutral of the cable. Calculations were made and are included which show the effects of changes in the leakage conductance of the neutral based on the study. / M.S.