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- Title
- Analysis and Design Optimization of Resonant DC-DC Converters.
- Creator
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Fang, Xiang, Shen, Zheng, Batarseh, Issa, Mikhael, Wasfy, Wu, Xinzhang, Kutkut, Nasser, University of Central Florida
- Abstract / Description
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The development in power conversion technology is in constant demand of high power efficiency and high power density. The DC-DC power conversion is an indispensable stage for numerous power supplies and energy related applications. Particularly, in PV micro-inverters and front-end converter of power supplies, great challenges are imposed on the power performances of the DC-DC converter stage, which not only require high efficiency and density but also the capability to regulate a wide...
Show moreThe development in power conversion technology is in constant demand of high power efficiency and high power density. The DC-DC power conversion is an indispensable stage for numerous power supplies and energy related applications. Particularly, in PV micro-inverters and front-end converter of power supplies, great challenges are imposed on the power performances of the DC-DC converter stage, which not only require high efficiency and density but also the capability to regulate a wide variation range of input voltage and load conditions. The resonant DC-DC converters are good candidates to meet these challenges with the advantages of achieving soft switching and low EMI. Among the resonant converters, the LLC converter is very attractive for its high gain range and providing ZVS from full load to zero load condition. The operation of the LLC converter is complicated due to its multiple resonant stage mechanism. In this dissertation, a literature review of different analysis methods are presented, and it shows that the study on the LLC is still incomplete. Therefore, an operation mode analysis method is proposed, which divides the operation into six major modes based on the occurrence of resonant stages. The resonant currents, voltages and the DC gain characteristics for each mode is investigated. To get a thorough view of the converter behavior, the boundaries of every mode are studied, and the mode distribution is discussed. An experimental prototype is built and tested to demonstrate its accuracy in operation waveforms and gain prediction. Since most of the LLC modes have no closed-form solutions, simplification is necessary in order to utilize this mode model in practical design. As the peak gain is an important design parameters indicating the LLC's operating limit of input voltage and switching frequency, a numerical peak gain approximation method is developed, which provide a direct way to calculate the peak gain and its corresponding load and frequency condition. In addition, as PO mode is the most favorable operation mode of the LLC, its operation region is investigated and an approximation approach is developed to determine its boundary. The design optimization of the LLC has always been a difficult problem as there are many parameters affecting the design and it lacks clear design guidance in selecting the optimal resonant tank parameters. Based on the operation mode model, three optimization methods are proposed according to the design scenarios. These methods focus on minimize the conduction loss of resonant tank while maintaining the required voltage gain level, and the approximations of peak gains and mode boundary can be applied here to facilitate the design. A design example is presented following one of the optimization procedure. As a comparison, the L-C component values are reselected and tested while the design specifications are the same. The experiments show that the optimal design has better efficiency performance. Finally, a generalized approach for resonant converter analysis is developed. It can be implemented by computer programs or numerical analysis tools to derive the operation waveforms and DC characteristics of resonant converters.
Show less - Date Issued
- 2012
- Identifier
- CFE0004229, ucf:49026
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0004229
- Title
- AN OPTIMAL CONTROL APPROACH FOR DETERMINATION OF THE HEAT LOSS COEFFICIENT IN AN ICS SOLAR DOMESTIC WATER HEATING SYSTEM.
- Creator
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Gil, Camilo, Simaan, Marwan, University of Central Florida
- Abstract / Description
-
Water heating in a typical home in the U.S. accounts for a significant portion (between 14% and 25%) of the total homeÂÂÂÂ's annual energy consumption. The objective of considerably reducing the homeÂÂÂÂ's energy consumption from the utilities calls for the use of onsite renewable energy...
Show moreWater heating in a typical home in the U.S. accounts for a significant portion (between 14% and 25%) of the total homeÂÂÂÂ's annual energy consumption. The objective of considerably reducing the homeÂÂÂÂ's energy consumption from the utilities calls for the use of onsite renewable energy systems. Integral Collector Storage (ICS) solar domestic water heating systems are an alternative to help meet the hot water energy demands in a household. In order to evaluate the potential benefits and contributions from the ICS system, it is important that the parameter values included in the model used to estimate the systemÂÂÂÂ's performance are as accurate as possible. The overall heat loss coefficient (Uloss) in the model plays an important role in the performance prediction methodology of the ICS. This work presents a new and improved methodology to determine Uloss as a function of time in an ICS system using a systematic optimal control theoretic approach. This methodology is based on the derivation of a new nonlinear state space model of the system, and the formulation of a quadratic performance function whose minimization yields estimates of Uloss values that can be used in computer simulations to improve the performance prediction of the ICS system, depending on the desired time of the year and hot water draw profile. Simulation results show that predictions of the systemÂÂÂÂ's performance based on these estimates of Uloss are considerably more accurate than the predictions based on current existing methods for estimating Uloss.
Show less - Date Issued
- 2010
- Identifier
- CFE0003266, ucf:48525
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0003266
- Title
- Computational Methods for Analyzing RNA Folding Landscapes and its Applications.
- Creator
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Li, Yuan, Zhang, Shaojie, Hua, Kien, Jha, Sumit, Hu, Haiyan, Li, Xiaoman, University of Central Florida
- Abstract / Description
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Non-protein-coding RNAs play critical regulatory roles in cellular life. Many ncRNAs fold into specific structures in order to perform their biological functions. Some of the RNAs, such as riboswitches, can even fold into alternative structural conformations in order to participate in different biological processes. In addition, these RNAs can transit dynamically between different functional structures along folding pathways on their energy landscapes. These alternative functional structures...
Show moreNon-protein-coding RNAs play critical regulatory roles in cellular life. Many ncRNAs fold into specific structures in order to perform their biological functions. Some of the RNAs, such as riboswitches, can even fold into alternative structural conformations in order to participate in different biological processes. In addition, these RNAs can transit dynamically between different functional structures along folding pathways on their energy landscapes. These alternative functional structures are usually energetically favored and are stable in their local energy landscapes. Moreover, conformational transitions between any pair of alternate structures usually involve high energy barriers, such that RNAs can become kinetically trapped by these stable and local optimal structures.We have proposed a suite of computational approaches for analyzing and discovering regulatory RNAs through studying folding pathways, alternative structures and energy landscapes associated with conformational transitions of regulatory RNAs. First, we developed an approach, RNAEAPath, which can predict low-barrier folding pathways between two conformational structures of a single RNA molecule. Using RNAEAPath, we can analyze folding pathways between two functional RNA structures, and therefore study the mechanism behind RNA functional transitions from a thermodynamic perspective. Second, we introduced an approach, RNASLOpt, for finding all the stable and local optimal structures on the energy landscape of a single RNA molecule. We can use the generated stable and local optimal structures to represent the RNA energy landscape in a compact manner. In addition, we applied RNASLOpt to several known riboswitches and predicted their alternate functional structures accurately. Third, we integrated a comparative approach with RNASLOpt, and developed RNAConSLOpt, which can find all the consensus stable and local optimal structuresthat are conserved among a set of homologous regulatory RNAs. We can use RNAConSLOpt to predict alternate functional structures for regulatory RNA families. Finally, we have proposed a pipeline making use of RNAConSLOpt to computationally discover novel riboswitches in bacterial genomes. An application of the proposed pipeline to a set of bacteria in Bacillus genus results in the re-discovery of many known riboswitches, and the detection of several novel putative riboswitch elements.
Show less - Date Issued
- 2012
- Identifier
- CFE0004400, ucf:49365
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0004400
- Title
- Virtual Motion Camouflage Based Nonlinear Constrained Optimal Trajectory Design Method.
- Creator
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Basset, Gareth, Xu, Yunjun, Kassab, Alain, Lin, Kuo-Chi, Cho, Hyoung, Qu, Zhihua, University of Central Florida
- Abstract / Description
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Nonlinear constrained optimal trajectory control is an important and fundamental area of research that continues to advance in numerous fields. Many attempts have been made to present new methods that can solve for optimal trajectories more efficiently or to improve the overall performance of existing techniques. This research presents a recently developed bio-inspired method called the Virtual Motion Camouflage (VMC) method that offers a means of quickly finding, within a defined but varying...
Show moreNonlinear constrained optimal trajectory control is an important and fundamental area of research that continues to advance in numerous fields. Many attempts have been made to present new methods that can solve for optimal trajectories more efficiently or to improve the overall performance of existing techniques. This research presents a recently developed bio-inspired method called the Virtual Motion Camouflage (VMC) method that offers a means of quickly finding, within a defined but varying search space, the optimal trajectory that is equal or close to the optimal solution.The research starts with the polynomial-based VMC method, which works within a search space that is defined by a selected and fixed polynomial type virtual prey motion. Next will be presented a means of improving the solution's optimality by using a sequential based form of VMC, where the search space is adjusted by adjusting the polynomial prey trajectory after a solution is obtained. After the search space is adjusted, an optimization is performed in the new search space to find a solution closer to the global space optimal solution, and further adjustments are made as desired. Finally, a B-spline augmented VMC method is presented, in which a B-spline curve represents the prey motion and will allow the search space to be optimized together with the solution trajectory.It is shown that (1) the polynomial based VMC method will significantly reduce the overall problem dimension, which in practice will significantly reduce the computational cost associated with solving nonlinear constrained optimal trajectory problems; (2) the sequential VMC method will improve the solution optimality by sequentially refining certain parameters, such as the prey motion; and (3) the B-spline augmented VMC method will improve the solution optimality without sacrificing the CPU time much as compared with the polynomial based approach. Several simulation scenarios, including the Breakwell problem, the phantom track problem, the minimum-time mobile robot obstacle avoidance problem, and the Snell's river problem are simulated to demonstrate the capabilities of the various forms of the VMC algorithm. The capabilities of the B-spline augmented VMC method are also shown in a hardware demonstration using a mobile robot obstacle avoidance testbed.
Show less - Date Issued
- 2012
- Identifier
- CFE0004298, ucf:49493
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0004298
- Title
- The Influence of Components of Positive Psychology on Student Development.
- Creator
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Ha, Yo-Sang, Robinson, Edward, Van Horn, Stacy, Young, Mark, Lee, Ji-Eun, University of Central Florida
- Abstract / Description
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Considering a wide range of student's delinquencies and problems, preventive intervention in school is strongly required for healthy student development. American School counselor Association (ASCA) has focused on three areas, academic development, career development, and personal/social development to provide various skills and learning opportunities for the successful life of students. During the past 50 years, psychologists have concentrated on the disease treatment model. However, unlike...
Show moreConsidering a wide range of student's delinquencies and problems, preventive intervention in school is strongly required for healthy student development. American School counselor Association (ASCA) has focused on three areas, academic development, career development, and personal/social development to provide various skills and learning opportunities for the successful life of students. During the past 50 years, psychologists have concentrated on the disease treatment model. However, unlike this psychological trend, positive psychology has paid attention to prevent school violence and delinquency. Further, Positive psychologists have discovered not only to prevent problems but also to facilitate human strengths and virtues to live successful and happy life. Therefore, the purpose of this study was to investigate the causal relationship between components of positive psychology and student development. More specifically this research examined the influence of hope, optimism, and self-regulation on student's academic achievement, career development, and social development. This quantitative study included 507 6th grade elementary school students and their parents living in Seoul, South Korea. Four conceptual models were developed to investigate the best fit model to examine the causal relationship between hope, optimism, and self-regulation and student's academic achievement, career development, and social development. Structural Equation Modeling (SEM) was employed to analyze the data. Confirmatory Factor Analysis (CFA) was used to explore measurement model and Path Analysis was engaged in to discover structure model. The results of SEM analysis provided major findings. There was a causal relationship between hope and student's academic achievement, career development, and social development. However, it was not confirmed the causal relationship between optimism and student's academic achievement, career development, and social development and between self-regulation and student's academic achievement, career development, and social development. Further, a structural model on the causal relationship between hope, optimism, self-regulation and student's academic achievement, career development, and social development was not statistically significant. Implications and suggestions for future research are discussed.
Show less - Date Issued
- 2012
- Identifier
- CFE0004380, ucf:49381
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0004380
- Title
- OPTIMIZED MARKET INTRODUCTION OF LARGE CAPITAL PRODUCTS WITH LONG DEVELOPMENT AND LEARNING CYCLES.
- Creator
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Lembcke, Antje, Malone, Linda, University of Central Florida
- Abstract / Description
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Any product sold is expected to be reliable and available when the customer wants to operate it. Companies that produce large capital products (LCP), such as rockets, satellites, or large gas turbines to generate electrical energy, tend to shy away from extending their testing and validation method above the requirements by law, mainly due to the very high costs of each additional test and the uncertain return on investment. This research shows that todayÂÂ's state of...
Show moreAny product sold is expected to be reliable and available when the customer wants to operate it. Companies that produce large capital products (LCP), such as rockets, satellites, or large gas turbines to generate electrical energy, tend to shy away from extending their testing and validation method above the requirements by law, mainly due to the very high costs of each additional test and the uncertain return on investment. This research shows that todayÂÂ's state of the art validation methods for LCP, required by law, or suggested in literature, and adapted by these industries, are not capable of capturing all significant failure modes (or even enough failure modes), with the consequence that the subsequently sold commercial products will still experience failures with significant effects on product reliability, and subsequently on the companiesÂÂ' bottom line earnings projections. The research determines the type of data (significant variables) necessary to correlate a companyÂÂ's validation policy to product failures after commercialization, and predicts the financial impact of the current validation policy on the companyÂÂ's profitability. A systems dynamics model to assess a company's testing policy is developed and an optimized product validation plan is suggested, and its impact on a companyÂÂ's profitability is demonstrated through simulation. A generic methodology is derived and its viability is illustrated using a specific product and a dynamic model developed with data available to the researcher. The generic method can be applied by any company to develop its own model for optimizing product reliability prior to market introduction.
Show less - Date Issued
- 2010
- Identifier
- CFE0003413, ucf:48404
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0003413
- Title
- IMPROVING THE ADVERSE IMPACT AND VALIDITY TRADE-OFF IN PARAETO OPTIMAL COMPOSITES: A COMPARISON OF WEIGHTS DEVELOPED ON CONTEXTUAL VS TASK PERFORMANCE.
- Creator
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Tsang, Howin, Wooten, William, University of Central Florida
- Abstract / Description
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Recent research in reducing adverse impact in personnel selection has focused on the use of various weighting schemes to balance levels of adverse impact and the validity of selection processes. De Corte Lievens & Sackett (2007) suggested the use of the normal boundary intersection method to create a number of weights that optimize adverse impact and criterion validity. This study seeks to improve the efficacy of this solution by looking at specific types of performance, namely task and...
Show moreRecent research in reducing adverse impact in personnel selection has focused on the use of various weighting schemes to balance levels of adverse impact and the validity of selection processes. De Corte Lievens & Sackett (2007) suggested the use of the normal boundary intersection method to create a number of weights that optimize adverse impact and criterion validity. This study seeks to improve the efficacy of this solution by looking at specific types of performance, namely task and contextual performance. It will investigate whether a focus on contextual performance will improve the trade-off by requiring smaller losses in validity for greater gains in adverse impact. This study utilized data from 272 applicants for exempt positions at a multinational financial institution. The two sets of Paraeto optimal composite were developed, one based on contextual performance and the other based on task performance. Results were analyzed based on levels of adverse impact and validity of weights generated using each method. Results indicate that reducing adverse impact required a greater validity trade-off for task performance than contextual performance. Application of this method would allow for greater reductions to adverse impact than the original method while retaining a validity coefficient of 95% of the maximum achieved with regression weighting. Though this method would limit practitioners to selecting based on contextual performance, the use of minimal cut-off scores on task predictors or job experience could allow employers to incorporate task measures while further reducing adverse impact.
Show less - Date Issued
- 2010
- Identifier
- CFE0003399, ucf:48386
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0003399
- Title
- NEW HEURISTICS FOR THE 0-1 MULTI-DIMENSIONAL KNAPSACK PROBLEMS.
- Creator
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Akin, Haluk, Sepulveda, Jose, University of Central Florida
- Abstract / Description
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This dissertation introduces new heuristic methods for the 0-1 multi-dimensional knapsack problem (0-1 MKP). 0-1 MKP can be informally stated as the problem of packing items into a knapsack while staying within the limits of different constraints (dimensions). Each item has a profit level assigned to it. They can be, for instance, the maximum weight that can be carried, the maximum available volume, or the maximum amount that can be afforded for the items. One main assumption is that we have...
Show moreThis dissertation introduces new heuristic methods for the 0-1 multi-dimensional knapsack problem (0-1 MKP). 0-1 MKP can be informally stated as the problem of packing items into a knapsack while staying within the limits of different constraints (dimensions). Each item has a profit level assigned to it. They can be, for instance, the maximum weight that can be carried, the maximum available volume, or the maximum amount that can be afforded for the items. One main assumption is that we have only one item of each type, hence the problem is binary (0-1). The single dimensional version of the 0-1 MKP is the uni-dimensional single knapsack problem which can be solved in pseudo-polynomial time. However the 0-1 MKP is a strongly NP-Hard problem. Reduced cost values are rarely used resources in 0-1 MKP heuristics; using reduced cost information we introduce several new heuristics and also some improvements to past heuristics. We introduce two new ordering strategies, decision variable importance (DVI) and reduced cost based ordering (RCBO). We also introduce a new greedy heuristic concept which we call the "sliding concept" and a sub-branch of the "sliding concept" which we call "sliding enumeration". We again use the reduced cost values within the sliding enumeration heuristic. RCBO is a brand new ordering strategy which proved useful in several methods such as improving Pirkul's MKHEUR, a triangular distribution based probabilistic approach, and our own sliding enumeration. We show how Pirkul's shadow price based ordering strategy fails to order the partial variables. We present a possible fix to this problem since there tends to be a high number of partial variables in hard problems. Therefore, this insight will help future researchers solve hard problems with more success. Even though sliding enumeration is a trivial method it found optima in less than a few seconds for most of our problems. We present different levels of sliding enumeration and discuss potential improvements to the method. Finally, we also show that in meta-heuristic approaches such as Drexl's simulated annealing where random numbers are abundantly used, it would be better to use better designed probability distributions instead of random numbers.
Show less - Date Issued
- 2009
- Identifier
- CFE0002633, ucf:48195
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0002633
- Title
- Data-driven Predictive Analytics For Distributed Smart Grid Control: Optimization of Energy Storage, Voltage and Demand Response.
- Creator
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Valizadehhaghi, Hamed, Qu, Zhihua, Behal, Aman, Atia, George, Turgut, Damla, Pensky, Marianna, University of Central Florida
- Abstract / Description
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The smart grid is expected to support an interconnected network of self-contained microgrids. Nonetheless, the distributed integration of renewable generation and demand response adds complexity to the control and optimization of smart grid. Forecasts are essential due to the existence of stochastic variations and uncertainty. Forecasting data are spatio-temporal which means that the data correspond to regular intervals, say every hour, and the analysis has to take account of spatial...
Show moreThe smart grid is expected to support an interconnected network of self-contained microgrids. Nonetheless, the distributed integration of renewable generation and demand response adds complexity to the control and optimization of smart grid. Forecasts are essential due to the existence of stochastic variations and uncertainty. Forecasting data are spatio-temporal which means that the data correspond to regular intervals, say every hour, and the analysis has to take account of spatial dependence among the distributed generators or locations. Hence, smart grid operations must take account of, and in fact benefit from the temporal dependence as well as the spatial dependence. This is particularly important considering the buffering effect of energy storage devices such as batteries, heating/cooling systems and electric vehicles. The data infrastructure of smart grid is the key to address these challenges, however, how to utilize stochastic modeling and forecasting tools for optimal and reliable planning, operation and control of smart grid remains an open issue.Utilities are seeking to become more proactive in decision-making, adjusting their strategies based on realistic predictive views into the future, thus allowing them to side-step problems and capitalize on the smart grid technologies, such as energy storage, that are now being deployed atscale. Predictive analytics, capable of managing intermittent loads, renewables, rapidly changing weather patterns and other grid conditions, represent the ultimate goal for smart grid capabilities.Within this framework, this dissertation develops high-performance analytics, such as predictive analytics, and ways of employing analytics to improve distributed and cooperative optimization software which proves to be the most significant value-add in the smart grid age, as new network management technologies prove reliable and fundamental. Proposed optimization and control approaches for active and reactive power control are robust to variations and offer a certain level of optimality by combining real-time control with hours-ahead network operation schemes. The main objective is managing spatial and temporal availability of the energy resources in different look-ahead time horizons. Stochastic distributed optimization is realized by integrating a distributed sub-gradient method with conditional ensemble predictions of the energy storage capacity and distributed generation. Hence, the obtained solutions can reflect on the system requirements for the upcoming times along with the instantaneous cooperation between distributed resources. As an important issue for smart grid, the conditional ensembles are studied for capturing wind, photovoltaic, and vehicle-to-grid availability variations. The following objectives are pursued:- Spatio-temporal adaptive modeling of data including electricity demand, electric vehicles and renewable energy (wind and solar power)- Predictive data analytics and forecasting- Distributed control- Integration of energy storage systemsFull distributional characterization and spatio-temporal modeling of data ensembles are utilized in order to retain the conditional and temporal interdependence between projection data and available capacity. Then, by imposing measures of the most likely ensembles, the distributed control method is carried out for cooperative optimization of the renewable generation and energy storage within the smart grid.
Show less - Date Issued
- 2016
- Identifier
- CFE0006408, ucf:51481
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006408
- Title
- INVESTIGATING THE MODERATING EFFECTS OF OPTIMISM, HOPE, AND GRATITUDE ON THE RELATIONSHIP AMONG NEGATIVE LIFE EVENTS AND PSYCHOLOGICAL DISTRESS AND LIFE SATISFACTION.
- Creator
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Gungor, Abdi, Young, Mark, Sivo, Stephen, Barden, Sejal, Munyon, Matthew, University of Central Florida
- Abstract / Description
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The literature has documented that negative life events such as divorce, financial issues, or relationship changes lead to various psychological concerns including depression, anxiety, or suicidal behaviors. However, several variables affect how people cope with negative life events. Among those variables, optimism, hope, and gratitude have been emphasized in the literature, and their relationships with several psychological outcomes have been studied. However, little is known about the...
Show moreThe literature has documented that negative life events such as divorce, financial issues, or relationship changes lead to various psychological concerns including depression, anxiety, or suicidal behaviors. However, several variables affect how people cope with negative life events. Among those variables, optimism, hope, and gratitude have been emphasized in the literature, and their relationships with several psychological outcomes have been studied. However, little is known about the effects of these variables on negative life events and their relationship to psychological distress and life satisfaction. The purpose of this study was to investigate the relationship between negative life events and psychological distress and life satisfaction. This study also examined the moderating effects of optimism, hope, and gratitude on negative life events' prediction of psychological distress and life satisfaction. This investigation tested the theoretical model that negative life events predicted psychological distress and life satisfaction in undergraduate students (N = 738). In addition, this investigation tested three theoretical interaction models that optimism, hope and gratitude moderated the relationships between negative life events and psychological distress and life satisfaction. The results revealed that negative life events predicted psychological distress and life satisfaction. Regarding moderating effects, optimism hope, and gratitude moderated negative life events' prediction of psychological distress, but not life satisfaction. These results are consistent with the existing literature on negative life events. The results and limitations are discussed along with suggestions for future research. Implications are presented for college counselors and counselor educators.
Show less - Date Issued
- 2016
- Identifier
- CFE0006313, ucf:51611
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006313
- Title
- A real-time crane service scheduling decision support system (CSS-DSS) for construction tower cranes.
- Creator
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Zavichi Tork, Amir, Madani Larijani, Kaveh, Oloufa, Amr, Tatari, Mehmet, Xanthopoulos, Petros, University of Central Florida
- Abstract / Description
-
The success of construction projects depends on proper use of construction equipment and machinery to a great extent. Thus, appropriate planning and control of the activities that rely on construction equipment could have significant effects on improving the efficiency of project operations. Cranes are the largest and most conspicuous construction equipment, widely used in typical construction sites. They play a major role in relocation of materials in horizontal and vertical directions on...
Show moreThe success of construction projects depends on proper use of construction equipment and machinery to a great extent. Thus, appropriate planning and control of the activities that rely on construction equipment could have significant effects on improving the efficiency of project operations. Cranes are the largest and most conspicuous construction equipment, widely used in typical construction sites. They play a major role in relocation of materials in horizontal and vertical directions on construction sites. Given the nature of activities relying on construction cranes in various stages of a project, cranes normally have control over the critical path of the project with the potential to create schedule bottlenecks and delaying the completion of the project. This dissertation intends to improve crane operations efficiency by developing a new framework for optimizing crane service sequence schedule. The crane service sequence problem is mathematically formulated as an NP-complete optimization problem based on the well-known Travel Salesman Problem (TSP) and is solved using different optimization techniques depending on the problem's size and complexity. The proposed framework sets the basis for developing near-real time decision support tools for on-site optimization of crane operations sequence. To underline the value of the proposed crane sequence optimization methods, these methods are employed to solve several numerical examples. Results show that the proposed method can create a travel time saving of 28% on average in comparison with conventional scheduling methods such as First in First out (FIFO), Shortest Job First (SJF), and Earliest Deadline First (EDF).
Show less - Date Issued
- 2013
- Identifier
- CFE0005078, ucf:50738
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0005078
- Title
- Development and Implementation of a Streamlined Process for the Creation and Mechanization of Negative Poisson's Ratio Meso-Scale Patterns.
- Creator
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Shuler, Matthew, Gordon, Ali, Kauffman, Jeffrey L., Ghosh, Ranajay, University of Central Florida
- Abstract / Description
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This thesis focuses on the development a streamlined process used to create novel meso-scale pattern used to induce negative Poisson's ratio (NPR) behavior at the bulk scale. This process includes, the development, optimization, and implementation of a candidate pattern. Currently, the majority of NPR structures are too porous to be utilized in conventional applications. For others, manufacturing methods have yet to realize the meso-scale pattern. Consequently, new NPR meta-materials must be...
Show moreThis thesis focuses on the development a streamlined process used to create novel meso-scale pattern used to induce negative Poisson's ratio (NPR) behavior at the bulk scale. This process includes, the development, optimization, and implementation of a candidate pattern. Currently, the majority of NPR structures are too porous to be utilized in conventional applications. For others, manufacturing methods have yet to realize the meso-scale pattern. Consequently, new NPR meta-materials must be developed in order to confer transformative thermomechanical responses to structures where transverse expansion is more desirable than contraction. For example, materials at high temperature. Additionally, patterns that take into account manufacturing limitations, while maintaining the properties characteristically attached to negative Poisson's Ratio materials, are ideal in order to utilize the potential of NPR structures. A novel NPR pattern is developed, numerically analyzed, and optimized via design of experiments. The parameters of the meso-structure are varied, and the bulk response is studied using finite element analysis (FEA). The candidate material for the study is Medium-Density Fiberboard (MDF). This material is relevant to a variety of applications where multiaxial stresses, particularly compressive, lead to mechanical fatigue. Samples are fabricated through a laser cutting process, and a comparison is drawn through the use of experimental means, including traditional tensile loading tests and digital image correlation (DIC). Various attributes of the elasto-plasticity responses of the bulk structure are used as objectives to guide the optimization process.
Show less - Date Issued
- 2017
- Identifier
- CFE0006795, ucf:51830
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006795
- Title
- Mission Analysis for Pico-Scale Satellite Based Dust Detection in Low Earth Orbits.
- Creator
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Belli, Jacob, Xu, Yunjun, Lin, Kuo-Chi, Bradley, Eric, University of Central Florida
- Abstract / Description
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A conceptual dust detection mission, KnightSat III, using pico-scale satellites is analyzed. The purpose of the proposed KnightSat III mission is to aid in the determination of the size, mass, distribution, and number of dust particles in low earth orbits through a low cost and flexible satellite or a formation of satellites equipped with a new dust detector. The analysis of a single satellite mission with an on-board dust detector is described; though this analysis can easily be extended to...
Show moreA conceptual dust detection mission, KnightSat III, using pico-scale satellites is analyzed. The purpose of the proposed KnightSat III mission is to aid in the determination of the size, mass, distribution, and number of dust particles in low earth orbits through a low cost and flexible satellite or a formation of satellites equipped with a new dust detector. The analysis of a single satellite mission with an on-board dust detector is described; though this analysis can easily be extended to a formation of pico-scale satellites. Many design aspects of the mission are discussed, including orbit analysis, power management, attitude determination and control, and mass and power budgets. Two of them are emphasized. The first is a new attitude guidance and control method, and the second is the online optimal power scheduling. It is expected that the measurements obtained from this possible future mission will provide insight into the dynamical processes of inner solar system dust, as well as aid in designing proper micro-meteoroid impact mitigation strategies for future man-made spacecraft.
Show less - Date Issued
- 2013
- Identifier
- CFE0004813, ucf:49728
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0004813
- Title
- Bio-inspired, Varying Manifold Based Method with Enhanced Initial Guess Strategies for Single Vehicle's Optimal Trajectory Planning.
- Creator
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Li, Ni, Xu, Yunjun, Lin, Kuo-Chi, Bai, Yuanli, Behal, Aman, University of Central Florida
- Abstract / Description
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Trajectory planning is important in many applications involving unmanned aerial vehicles, underwater vehicles, spacecraft, and industrial manipulators. It is still a challenging task to rapidly find an optimal trajectory while taking into account dynamic and environmental constraints. In this dissertation, a unified, varying manifold based optimal trajectory planning method inspired by several predator-prey relationships is investigated to tackle this challenging problem. Biological species,...
Show moreTrajectory planning is important in many applications involving unmanned aerial vehicles, underwater vehicles, spacecraft, and industrial manipulators. It is still a challenging task to rapidly find an optimal trajectory while taking into account dynamic and environmental constraints. In this dissertation, a unified, varying manifold based optimal trajectory planning method inspired by several predator-prey relationships is investigated to tackle this challenging problem. Biological species, such as hoverflies, ants, and bats, have developed many efficient hunting strategies. It is hypothesized that these types of predators only move along paths in a carefully selected manifold based on the prey's motion in some of their hunting activities. Inspired by these studies, the predator-prey relationships are organized into a unified form and incorporated into the trajectory optimization formulation, which can reduce the computational cost in solving nonlinear constrained optimal trajectory planning problems. Specifically, three motion strategies are studied in this dissertation: motion camouflage, constant absolute target direction, and local pursuit. Necessary conditions based on the speed and obstacle avoidance constraints are derived. Strategies to tune initial guesses are proposed based on these necessary conditions to enhance the convergence rate and reduce the computational cost of the motion camouflage inspired strategy. The following simulations have been conducted to show the advantages of the proposed methods: a supersonic aircraft minimum-time-to-climb problem, a ground robot obstacle avoidance problem, and a micro air vehicle minimum time trajectory problem. The results show that the proposed methods can find the optimal solution with higher success rate and faster convergent speed as compared with some other popular methods. Among these three motion strategies, the method based on the local pursuit strategy has a relatively higher success rate when compared to the other two.In addition, the optimal trajectory planning method is embedded into a receding horizon framework with unknown parameters updated in each planning horizon using an Extended Kalman Filter.
Show less - Date Issued
- 2013
- Identifier
- CFE0005023, ucf:49986
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0005023
- Title
- Bio-Inspired Cooperative Optimal Trajectory Planning for Autonomous Vehicles.
- Creator
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Remeikas, Charles, Xu, Yunjun, Kassab, Alain, Lin, Kuo-Chi, University of Central Florida
- Abstract / Description
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With the recent trend for systems to be more and more autonomous, there is a growing need for cooperative trajectory planning. Applications that can be considered as cooperative systems such as surveying, formation flight, and traffic control need a method that can rapidly produce trajectories while considering all of the constraints on the system. Currently most of the existing methods to handle cooperative control are based around either simple dynamics and/or on the assumption that all...
Show moreWith the recent trend for systems to be more and more autonomous, there is a growing need for cooperative trajectory planning. Applications that can be considered as cooperative systems such as surveying, formation flight, and traffic control need a method that can rapidly produce trajectories while considering all of the constraints on the system. Currently most of the existing methods to handle cooperative control are based around either simple dynamics and/or on the assumption that all vehicles have homogeneous properties. In reality, typical autonomous systems will have heterogeneous, nonlinear dynamics while also being subject to extreme constraints on certain state and control variables. In this thesis, a new approach to the cooperative control problem is presented based on the bio-inspired motion strategy known as local pursuit. In this framework, decision making about the group trajectory and formation are handled at a cooperative level while individual trajectory planning is considered in a local sense. An example is presented for a case of an autonomous farming system (e.g. scouting) utilizing nonlinear vehicles to cooperatively accomplish various farming task with minimal energy consumption or minimum time. The decision making and trajectory generation is handled very quickly while being able to consider changing environments laden with obstacles.
Show less - Date Issued
- 2013
- Identifier
- CFE0005053, ucf:49978
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0005053
- Title
- Degradation of Hydrazine and Monomethylhydrazine for Fuel Waste Streams using Alpha-ketoglutaric Acid.
- Creator
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Franco, Carolina, Yestrebsky, Cherie, Clausen, Christian, Rex, Matthew, Harper, James, Duranceau, Steven, University of Central Florida
- Abstract / Description
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Alpha-ketoglutaric acid (AKGA) is an organic acid important for the metabolism of essential amino acids as well as for the transfer of cellular energy. It is a precursor of glutamic acid which is produced by the human body during the Krebs Cycle. AKGA has a specific industrial interest as it can be taken as a dietary supplement and is also widely used as a building block in chemical synthesis.Collectively termed as hydrazine (HZs), hydrazine (HZ) and monomethylhydrazine (MMH) are hypergolic...
Show moreAlpha-ketoglutaric acid (AKGA) is an organic acid important for the metabolism of essential amino acids as well as for the transfer of cellular energy. It is a precursor of glutamic acid which is produced by the human body during the Krebs Cycle. AKGA has a specific industrial interest as it can be taken as a dietary supplement and is also widely used as a building block in chemical synthesis.Collectively termed as hydrazine (HZs), hydrazine (HZ) and monomethylhydrazine (MMH) are hypergolic fuels that do not need an ignition source to burn. Because of the particular HZs' characteristics the National Aeronautics and Space Administration (NASA) at Kennedy Space Center (KSC) and the US Air Force at Cape Canaveral Air Force Station (CCAFS) consistently use HZ and MMH as hypergolic propellants. These propellants are highly reactive and toxic, and have carcinogenic properties. The handling, transport, and disposal of HZ waste are strictly regulated under the Resource Conservation and Recovery Act (RCRA) to protect human health and the environment. Significant quantities of wastewater containing residuals of HZ and MMH are generated at KSC and CCAFS that are subsequently disposed off-site as hazardous waste. This hazardous waste is shipped for disposal over public highways, which presents a potential threat to the public and the environment in the event of an accidental discharge in transit. NASA became aware of research done using AKGA to neutralize HZ waste. This research indicated that AKGA transformed HZ in an irreversible reaction potentially leading to the disposal of the hypergols via the wastewater treatment facility located at CCAFS eliminating the need to transport most of the HZ waste off-site.New Mexico Highlands University (NMHU) has researched this transformation of HZ by reaction with AKGA to form stabilized pyridazine derivatives. NMHU's research suggests that the treatment of HZ and MMH using AKGA is an irreversible reaction; once the reaction takes place, HZ and/or MMH cannot re-form from the byproducts obtained. However, further knowledge relating to the ultimate end products of the reaction, and their effects on human health and the environment, must still be addressed. The known byproduct of the AKGA/HZ neutralization reaction is 6-oxo-1,4,5,6-tetrahydro-pyridazine-3-carboxylic acid (PCA), and the byproduct of the AKGA/MMH reaction is 1-methyl-6-oxo-4,5-dihydro-pyridazine-3-carboxylic acid (mPCA).This research addressed several primary areas of interest to further the potential use of AKGA for HZ and MMH neutralization: 1) isolation of the end-product of the MMH-AKGA degradation process, 1-methyl-6-oxo-4,5-dihydro-pyridazine-3-carboxylic acid (mPCA), and determination of several physical properties of this substance, 2) evaluation of the kinetics of the reaction of AKGA with HZ or MMH, 3) verification of the chemical mechanism for the reaction of the individual hypergols with AKGA, 4) determination of whether the addition of a silicone-based antifoaming agent (AF), citric acid (CA) and/or isopropyl alcohol (IPA) to the AKGA and HZ or MMH solution interferes with the degradation reaction, 4) application of laboratory bench scale experiments in field samples, and 5) determination of the reaction enthalpy of these reactions.
Show less - Date Issued
- 2014
- Identifier
- CFE0005493, ucf:50334
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0005493
- Title
- Vision-Based Sensing and Optimal Control for Low-Cost and Small Satellite Platforms.
- Creator
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Sease, Bradley, Xu, Yunjun, Lin, Kuo-Chi, Bradley, Eric, University of Central Florida
- Abstract / Description
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Current trends in spacecraft are leading to smaller, more inexpensive options whenever possible. This shift has been primarily pursued for the opportunity to open a new frontier for technologies with a small financial obligation. Limited power, processing, pointing, and communication capabilities are all common issues which must be considered when miniaturizing systems and implementing low-cost components. This thesis addresses some of these concerns by applying two methods, in attitude...
Show moreCurrent trends in spacecraft are leading to smaller, more inexpensive options whenever possible. This shift has been primarily pursued for the opportunity to open a new frontier for technologies with a small financial obligation. Limited power, processing, pointing, and communication capabilities are all common issues which must be considered when miniaturizing systems and implementing low-cost components. This thesis addresses some of these concerns by applying two methods, in attitude estimation and control. Additionally, these methods are not restricted to only small, inexpensive satellites, but offer a benefit to large-scale spacecraft as well.First, star cameras are examined for the tendency to generate streaked star images during maneuvers. This issue also comes into play when pointing capabilities and camera hardware quality are low, as is often the case in small, budget-constrained spacecraft. When pointing capabilities are low, small residual velocities can cause movement of the stars in the focal plane during an exposure, causing them to streak across the image. Additionally, if the camera quality is low, longer exposures may be required to gather sufficient light from a star, further contributing to streaking. Rather than improving the pointing or hardware directly, an algorithm is presented to retrieve and utilize the endpoints of streaked stars to provide feedback where traditional methods do not. This allows precise attitude and angular rate estimates to be derived from an image which, with traditional methods, would return large attitude and rate error. Simulation results are presented which demonstrate endpoint error of approximately half a pixel and rate estimates within 2% of the true angular velocity. Three methods are also considered to remove overlapping star streaks and resident space objects from images to improve performance of both attitude and rate estimates. Results from a large-scale Monte Carlo simulation are presented in order to characterize the performance of the method.Additionally, a rapid optimal attitude guidance method is experimentally validated in a ground-based, pico-scale satellite test bed. Fast slewing performance is demonstrated for an incremental step maneuver with low average power consumption. Though the focus of this thesis is primarily on increasing the capabilities of small, inexpensive spacecraft, the methods discussed have the potential to increase the capabilities of current and future large-scale missions as well.
Show less - Date Issued
- 2013
- Identifier
- CFE0005249, ucf:50603
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0005249
- Title
- AN HEDONOMIC EVALUATION OF PLEASURABLE HUMAN-TECHNOLOGY EXPERIENCE: THE EFFECT OF EXPOSURE AND AESTHETICS ON THE EXPERIENCE OF FLOW.
- Creator
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Murphy, Lauren, Hancock, Peter, University of Central Florida
- Abstract / Description
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A framework was developed called the Extended Hedonomic Hierarchy (EHH) that provides a basis for evaluating pleasurable human-system experience. Results from a number of experiments within this framework that evaluated specific dimensions of the framework are reported. The 'Exposure' component of the EHH framework and hedonics of the system were investigated to see how changes would affect other dimensions, such as the occurrence of flow, the mode of interaction, and the needs of the user....
Show moreA framework was developed called the Extended Hedonomic Hierarchy (EHH) that provides a basis for evaluating pleasurable human-system experience. Results from a number of experiments within this framework that evaluated specific dimensions of the framework are reported. The 'Exposure' component of the EHH framework and hedonics of the system were investigated to see how changes would affect other dimensions, such as the occurrence of flow, the mode of interaction, and the needs of the user. Simulations and video games were used to investigate how repeated exposure affects flow, interaction mode, and the user needs. The Kansei Engineering method was used to measure user needs and investigate the effect of different hedonic properties of the system on user needs and flow. Findings reveal that: (a) pleasurable human-system experience increases linearly with repeated exposure to the technology of interest; (b) an habituation effect of flow mediated by day; (c) motivation to satisfy human need for technology is hierarchically structured and contributes to pleasurable human-system experience; (d) interactivity is hierarchically structured and seamless mode of interaction is a behavioral outcome of pleasurable human-system experience; (e) there are individual differences among users that affect the likelihood of experiencing pleasurable human-system interaction; (f) performance is positively correlated to flow and (g) the method of kansei engineering provides data from which informed decisions about design can be made and empirical research can be conducted. Suggestions for (a) making Hedonomics a reality in industry, the workplace, and in the field of Human Factors, (b) future research directions for Hedonomics, and (c) principles and guidelines for the practice of Hedonomics are discussed.
Show less - Date Issued
- 2005
- Identifier
- CFE0000875, ucf:46650
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0000875
- Title
- Hybrid Multi-Objective Optimization of Left Ventricular Assist Device Outflow Graft Anastomosis Orientation to Minimize Stroke Rate.
- Creator
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Lozinski, Blake, Kassab, Alain, Mansy, Hansen, DeCampli, William, University of Central Florida
- Abstract / Description
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A Left Ventricular Assist Device (LVAD) is a mechanical pump that is utilized as a bridge to transplantation for patients with a Heart Failure (HF) condition. More recently, LVADs have been also used as destination therapy and have provided an increase in the quality of life for patients with HF. However, despite improvements in VAD design and anticoagulation treatment, there remains a significant problem with VAD therapy, namely drive line infection and thromboembolic events leading to...
Show moreA Left Ventricular Assist Device (LVAD) is a mechanical pump that is utilized as a bridge to transplantation for patients with a Heart Failure (HF) condition. More recently, LVADs have been also used as destination therapy and have provided an increase in the quality of life for patients with HF. However, despite improvements in VAD design and anticoagulation treatment, there remains a significant problem with VAD therapy, namely drive line infection and thromboembolic events leading to stroke. This thesis focuses on a surgical maneuver to address the second of these issues, guided by previous steady flow hemodynamic studies that have shown the potential of tailoring the VAD outflow graft (VAD-OG) implantation in providing up to 50% reduction in embolization rates. In the current study, multi-scale pulsatile hemodynamics of the VAD bed is modeled and integrated in a fully automated multi-objective shape optimization scheme in which the VAD-OG anastomosis along the Ascending Aorta (AA) is optimized to minimize the objective function which include thromboembolic events to the cerebral vessels and wall shear stress (WSS). The model is driven by a time dependent pressure and flow boundary conditions located at the boundaries of the 3D domain through a 50 degree of freedom 0D lumped parameter model (LPM). The model includes a time dependent multi-scale Computational Fluid Dynamics (CFD) analysis of a patient specific geometry. Blood rheology is modeled as using the non-Newtonian Carreua-Yasuda model, while the hemodynamics are that of a laminar and constant density fluid. The pulsatile hemodynamics are resolved using the commercial CFD solver StarCCM+ while a Lagrangian particle tracking scheme is used to track constant density particles modeling thromobi released from the cannula to determine embolization rated of thrombi. The results show that cannula anastomosis orientation plays a large role when minimizing the objective function for patient derived aortic bed geometry used in this study. The scheme determined the optimal location of the cannula is located at 5.5 cm from the aortic root, cannula angle at 90 degrees and coronal angle at 8 degrees along the AA with a peak surface average WSS of 55.97 dy/cm2 and stroke percentile of 12.51%. A Pareto front was generated showing the range of 9.7% to 44.08% for stroke and WSS of 55.97 to 81.47 dy/cm2 ranged over 22 implantation configurations for the specific case studied. These results will further assist in the treatment planning for clinicians when implementing a LVAD.
Show less - Date Issued
- 2019
- Identifier
- CFE0007833, ucf:52827
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0007833
- Title
- Data-Driven Modeling and Optimization of Building Energy Consumption.
- Creator
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Grover, Divas, Pourmohammadi Fallah, Yaser, Vosoughi, Azadeh, Zhou, Qun, University of Central Florida
- Abstract / Description
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Sustainability and reducing energy consumption are targets for building operations. The installation of smart sensors and Building Automation Systems (BAS) makes it possible to study facility operations under different circumstances. These technologies generate large amounts of data. That data can be scrapped and used for the analysis. In this thesis, we focus on the process of data-driven modeling and decision making from scraping the data to simulate the building and optimizing the...
Show moreSustainability and reducing energy consumption are targets for building operations. The installation of smart sensors and Building Automation Systems (BAS) makes it possible to study facility operations under different circumstances. These technologies generate large amounts of data. That data can be scrapped and used for the analysis. In this thesis, we focus on the process of data-driven modeling and decision making from scraping the data to simulate the building and optimizing the operation. The City of Orlando has similar goals of sustainability and reduction of energy consumption so, they provided us access to their BAS for the data and study the operation of its facilities. The data scraped from the City's BAS serves can be used to develop statistical/machine learning methods for decision making. We selected a mid-size pilot building to apply these techniques. The process begins with the collection of data from BAS. An Application Programming Interface (API) is developed to login to the servers and scrape data for all data points and store it on the local machine. Then data is cleaned to analyze and model. The dataset contains various data points ranging from indoor and outdoor temperature to fan speed inside the Air Handling Unit (AHU) which are operated by Variable Frequency Drive (VFD). This whole dataset is a time series and is handled accordingly. The cleaned dataset is analyzed to find different patterns and investigate relations between different data points. The analysis helps us in choosing parameters for models that are developed in the next step. Different statistical models are developed to simulate building and equipment behavior. Finally, the models along with the data are used to optimize the building Operation with the equipment constraints to make decisions for building operation which leads to a reduction in energy consumption while maintaining temperature and pressure inside the building.
Show less - Date Issued
- 2019
- Identifier
- CFE0007810, ucf:52335
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0007810
