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Title: A Comprehensive Severity Analysis of Large Vehicle Crashes.
Creator: Laman, Haluk, Abdel-Aty, Mohamed, Tatari, Mehmet, Ahmed, Mohamed, University of Central Florida
Abstract / Description: The goal of this thesis is to determine the contributing factors affecting severe traffic crashes (severe: incapacitating and fatal - non-severe: no injury, possible injury, and non-incapacitating), and in particular those factors influencing crashes involving large vehicles (heavy trucks, truck tractors, RVs, and buses). Florida Department of Highway Safety and Motor Vehicles (DHSMV) crash reports of 2008 have been used. The data included 352 fatalities and 9,838 injuries due to large...
Show moreThe goal of this thesis is to determine the contributing factors affecting severe traffic crashes (severe: incapacitating and fatal - non-severe: no injury, possible injury, and non-incapacitating), and in particular those factors influencing crashes involving large vehicles (heavy trucks, truck tractors, RVs, and buses). Florida Department of Highway Safety and Motor Vehicles (DHSMV) crash reports of 2008 have been used. The data included 352 fatalities and 9,838 injuries due to large vehicle crashes.Using the crashes involving large vehicles, a model comparison between binary logit model and a Chi-squared Automatic Interaction Detection (CHAID) decision tree model is provided. There were 13 significant factors (i.e. crash type with respect to vehicle types, residency of driver, DUI, rural-urban, etc.) found significant in the logistic procedure while 7 factors found (i.e. posted speed limit, intersection, etc.) in the CHAID model. The model comparison results indicate that the logit analysis procedure is better in terms of prediction power.The following analysis is a modeling structure involving three binary logit models. The first model was conducted to estimate the crash severity of crashes that involved only personal vehicles (PV). Second model uses the crashes that involved large vehicles (LV) and passenger vehicles (PV). The final model estimated the severity level of crashes involving only large vehicles (LV). Significant differences with respect to various risk factors including driver, vehicle, environmental, road geometry and traffic characteristics were found to exist between those crash types and models. For example, driving under the influence of Alcohol (DUI) has positive effect on the severity of PV vs. PV and LV vs. PV while it has no effect on LV vs. LV. As a result, 4 of the variables found to be significant were similar in all three models (although often with quite different impact) and there were 11 variables that significantly influenced crash injury severity in PV vs. PV crashes, and 9 variables that significantly influenced crash injury severity in LV vs. PV crashes.Based on the significant variables, maximum posted speed, number of vehicles involved, and intersections are among the factors that have major impact on injury severity. These results could be used to identify potential countermeasures to reduce crash severity in general, and for LVs in particular. For example, restricting the speed limits and enforcing it for large vehicles could be a suggested countermeasure based on this study.
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Date Issued: 2012
Identifier: CFE0004566, ucf:49216
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0004566

Title: Non-Destructive Evaluation of Concrete Structures Using High Resolution Digital Image and Infrared Thermography Technology.
Creator: Watase, Azusa, Catbas, Fikret, Tatari, Mehmet, Nam, Boo Hyun, University of Central Florida
Abstract / Description: As existing bridge structures age, they are susceptible to the effects of deterioration, damage and other deleterious processes. These effects hamper the capacity and efficiency of transportation networks and adversely impact local, regional and national economic growth. As a result, bridge authorities and other professionals have become more sensitive to maintenance issues related to this aging infrastructure. While highway bridge condition have been monitored by visual inspection, non...
Show moreAs existing bridge structures age, they are susceptible to the effects of deterioration, damage and other deleterious processes. These effects hamper the capacity and efficiency of transportation networks and adversely impact local, regional and national economic growth. As a result, bridge authorities and other professionals have become more sensitive to maintenance issues related to this aging infrastructure. While highway bridge condition have been monitored by visual inspection, non-destructive evaluation (NDE) technologies have also been developing and they are expected to be utilized for effective management of highway bridges or other civil infrastructure systems. Efficient use of these technologies saves time spent or bridge inspections, and also helps the bridge authorities for management decision-making. One of the NDE technologies is the image-based technology. In this thesis research, image-based technologies using high resolution digital images (HRDI) and infrared thermography image (IRTI) are introduced, described and implemented.First, a review of the mechanisms of these technologies is presented. Due to the specific engineering utilization and recent technological development, there is a need to validate effectiveness of HRDI and IRTI for their practical use for engineering purpose. For this reason, a pilot project using these technologies was conducted at an in-service bridge and a parking structure with the support of Florida Department of Transportation District 5 and the results are presented in this thesis. Secondly, in order to explore and enhance the usability of infrared thermography technology (IRTI), experiments on campus and on another bridge were conducted to determine the best time to test bridges and the sensitivity of IRTI to delamination volume. Since the accuracy of damage detection using infrared thermography technology is greatly affected by daily temperature variation, it is quite important to estimate an appropriate duration for infrared thermography inspection prior to the inspection. However, in current practice, the way to estimate the duration is to monitor the temperature of the concrete surface. Since the temperature varies depending on the area or region, there is a need to visit the bridge before the actual test and monitor the temperature variation. This requires additional visits to the bridge site and also access to the bridge for measuring concrete temperature. Sometimes, this can be a practical issue. In this research, in order to estimate an appropriate duration without visiting bridges, a practical method is explored by monitoring and analyzing variation of concrete surface temperature at one location and projected to another location by also incorporating other factors that affect the concrete temperature, such as air temperature and humidity. For this analysis, specially-designed concrete plates of a few types of thickness and shapes are used and the regression analysis is employed to establish a relationship between environmental effects and temperature variation between two different sites. The results have been promising for this research study and it is shown that HRDI and IRTI are excellent technologies for assessing concrete structures in a very practical manner.
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Date Issued: 2013
Identifier: CFE0004956, ucf:49581
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0004956

Title: Resilience of Bridges Following Aftershocks.
Creator: Espinosa, Diego, Mackie, Kevin, Chopra, Manoj, Tatari, Mehmet, University of Central Florida
Abstract / Description: The ability to predict the reduction in capacity of a structure after an earthquake is vital in the process of assessing a structure after a main-shock or an after-shock. Main-shocks are normally followed by a few aftershocks in a short period of time. Researchers in the past have focused for the most part on the effects of main-shocks on buildings. Very little research has been performed on the ability to predict the reduction in capacity of bridges in aftershocks. This thesis focuses on...
Show moreThe ability to predict the reduction in capacity of a structure after an earthquake is vital in the process of assessing a structure after a main-shock or an after-shock. Main-shocks are normally followed by a few aftershocks in a short period of time. Researchers in the past have focused for the most part on the effects of main-shocks on buildings. Very little research has been performed on the ability to predict the reduction in capacity of bridges in aftershocks. This thesis focuses on providing a way of assessing the reduction in capacity for main-shocks as compared to aftershocks and the effects and importance of both in a bridge. The reduction in capacity was defined using three different ratios: ultimate force, stiffness, and strain energy ratio. The ratios were computed relative to an undamaged state following both the main-shock scenario and the main-shock combined with aftershock scenario. The force, stiffness, and strain energy quantities were obtained from lateral pushover analyses along the two lateral bridge axes. Probabilistic demand models describing the loss in capacity were formulated by pairing intensity measures, based on real ground motions obtained from previous earthquakes, for the main-shock and aftershock with the capacity ratios, obtained from nonlinear dynamic time history analysis. Additionally, the reduction in capacity was conditioned on residual displacement and intensity measure in an attempt to discover the reduction in capacity ratio due to the contribution of residual displacement and therefore separate contributions from geometrical and material nonlinearities. This thesis demonstrates that the usage of strain energy ratio provides a definition of capacity that ultimately provides the best correlation between capacity and intensity measure.
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Date Issued: 2012
Identifier: CFE0004311, ucf:49494
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0004311

Title: A Framework for Process Data Collection, Analysis, and Visualization in Construction Projects.
Creator: Akhavian, Reza, Behzadan, Amir, Oloufa, Amr, Tatari, Mehmet, University of Central Florida
Abstract / Description: Automated data collection, simulation and visualization can substantially enhance the process of designing, analysis, planning, and control of many engineering processes. In particular, managing processes that are dynamic in nature can significantly benefit from such techniques. Construction projects are good examples of such processes where a variety of equipment and resources constantly interact inside an evolving environment. Management of such settings requires a platform capable of...
Show moreAutomated data collection, simulation and visualization can substantially enhance the process of designing, analysis, planning, and control of many engineering processes. In particular, managing processes that are dynamic in nature can significantly benefit from such techniques. Construction projects are good examples of such processes where a variety of equipment and resources constantly interact inside an evolving environment. Management of such settings requires a platform capable of providing decision-makers with updated information about the status of project entities and assisting site personnel making critical decisions under uncertainty. To this end, the current practice of using historical data or expert judgments as static inputs to create empirical formulations, bar chart schedules, and simulation networks to study project activities, resource operations, and the environment under which a project is taking place does not seem to offer reliable results.The presented research investigates the requirements and applicability of a data-driven modeling framework capable of collecting and analyzing real time field data from construction equipment. In the developed data collection scheme, a stream of real time data is continuously transferred to a data analysis module to calculate the input parameters required to create dynamic 3D visualizations of ongoing engineering activities, and update the contents of a discrete event simulation (DES) model representing the real engineering process. The generated data-driven simulation model is an effective tool for projecting future progress based on existing performance. Ultimately, the developed framework can be used by project decision-makers for short-term project planning and control since the resulting simulation and visualization are completely based on the latest status of project entities.
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Date Issued: 2012
Identifier: CFE0004347, ucf:49419
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0004347

Title: Sustainability Analysis of Intelligent Transportation Systems.
Creator: Ercan, Tolga, Tatari, Mehmet, Al-Deek, Haitham, Oloufa, Amr, University of Central Florida
Abstract / Description: Commuters in urban areas suffer from traffic congestion on a daily basis. The increasing number of vehicles and vehicle miles traveled (VMT) are exacerbating this congested roadway problem for society. Although literature contains numerous studies that strive to propose solutions to this congestion problem, the problem is still prevalent today. Traffic congestion problem affects society's quality of life socially, economically, and environmentally. In order to alleviate the unsustainable...
Show moreCommuters in urban areas suffer from traffic congestion on a daily basis. The increasing number of vehicles and vehicle miles traveled (VMT) are exacerbating this congested roadway problem for society. Although literature contains numerous studies that strive to propose solutions to this congestion problem, the problem is still prevalent today. Traffic congestion problem affects society's quality of life socially, economically, and environmentally. In order to alleviate the unsustainable impacts of the congested roadway problem, Intelligent Transportation Systems (ITS) has been utilized to improve sustainable transportation systems in the world. The purpose of this thesis is to analyze the sustainable impacts and performance of the utilization of ITS in the United States. This thesis advances the body of knowledge of sustainability impacts of ITS related congestion relief through a triple bottom line (TBL) evaluation in the United States. TBL impacts analyze from a holistic perspective, rather than considering only the direct economic benefits. A critical approach to this research was to include both the direct and the indirect environmental and socio-economic impacts associated with the chain of supply paths of traffic congestion relief. To accomplish this aim, net benefits of ITS implementations are analyzed in 101 cities in the United States. In addition to the state level results, seven metropolitan cities in Florida are investigated in detail among these 101 cities. For instance, the results of this study indicated that Florida saved 1.38 E+05 tons of greenhouse gas emissions (tons of carbon dioxide equivalent), $420 million of annual delay reduction costs, and $17.2 million of net fuel-based costs. Furthermore, to quantify the relative impact and sustainability performance of different ITS technologies, several ITS solutions are analyzed in terms of total costs (initial and operation (&) maintenance costs) and benefits (value of time, emissions, and safety). To account for the uncertainty in benefit and cost analyses, a fuzzy-data envelopment analysis (DEA) methodology is utilized instead of the traditional DEA approach for sustainability performance analysis. The results using the fuzzy-DEA approach indicate that some of the ITS investments are not efficient compared to other investments where as all of them are highly effective investments in terms of the cost/benefit ratios approach. The TBL results of this study provide more comprehensive picture of socio-economic benefits which include the negative and indirect indicators and environmental benefits for ITS related congestion relief. In addition, sustainability performance comparisons and TBL analysis of ITS investments contained encouraging results to support decision makers to pursue ITS projects in the future.
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Date Issued: 2013
Identifier: CFE0004994, ucf:49549
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0004994

Title: Development of the Strategy to Select optimum Reflective Cracking Mitigation Methods for the Hot-Mix Asphalt Overlays in Florida.
Creator: Maherinia, Hamid, Nam, Boo Hyun, Behzadan, Amir, Tatari, Mehmet, University of Central Florida
Abstract / Description: Hot Mix Asphalt (HMA) overlay is a major rehabilitation treatment for the existing deteriorated pavements (both flexible and rigid pavements). Reflective cracking (RC) is the most common distress type appearing in the HMA overlays which structurally and functionally degrades the whole pavement structure, especially under high traffic volume. Although many studies have been conducted to identify the best performing RC mitigation technique, the level of success varies from premature failure to...
Show moreHot Mix Asphalt (HMA) overlay is a major rehabilitation treatment for the existing deteriorated pavements (both flexible and rigid pavements). Reflective cracking (RC) is the most common distress type appearing in the HMA overlays which structurally and functionally degrades the whole pavement structure, especially under high traffic volume. Although many studies have been conducted to identify the best performing RC mitigation technique, the level of success varies from premature failure to good performance in the field. In Florida, Asphalt Rubber Membrane Interlayers (ARMIs) have been used as a RC mitigation technique but its field performance has not been successful. In this study, the best performing means to mitigate RC in the overlays considering Florida's special conditions have been investigated. The research methodology includes (1) extensive literature reviews regarding the RC mechanism and introduced mitigation options, (2) nationwide survey for understanding the current practice of RC management in the U.S., and (3) the development of decision trees for the selection of the best performing RC mitigation method. Extensive literature reviews have been conducted to identify current available RC mitigation techniques and the advantages and disadvantages of each technique were compared. Lesson learned from the collected case studies were used as input for the selection of the best performing RC mitigation techniques for Florida's roads. The key input parameters in selecting optimum mitigation techniques are: 1) overlay characterization, 2) existing pavement condition, 3) base and subgrade structural condition, 4) environmental condition and 5) traffic level. In addition, to understand the current practices how reflective cracking is managed in each state, a nationwide survey was conducted by distributing the survey questionnaire (with the emphasis on flexible pavement) to all other highway agencies. Based on the responses, the most successful method of treatment is to increase the thickness of HMA overlay. Crack arresting layer is considered to be in the second place among its users. Lack of cost analysis and low rate of successful practices raise the necessity of conducting more research on this subject.Considering Florida's special conditions (climate, materials, distress type, and geological conditions) and the RC mechanism, two RC mitigation techniques have been proposed: 1) overlay reinforcement (i.e. geosynthetic reinforcement) for the existing flexible pavements and 2) Stress Absorbing Membrane Interlayer (SAMI) for the existing rigid pavements. As the final products of this study, decision trees to select an optimum RC mitigation technique for both flexible and rigid pavements were developed. The decision trees can provide a detailed guideline to pavement engineer how to consider the affecting parameters in the selection of RC mitigation technique.
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Date Issued: 2013
Identifier: CFE0005108, ucf:50753
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005108

Title: Sustainability Assessment of Wind Energy for Buildings.
Creator: Noori, Mehdi, Tatari, Mehmet, Oloufa, Amr, Nam, Boo Hyun, University of Central Florida
Abstract / Description: Due to increasing concerns for global climate change, onshore and offshore wind energy technologies have stimulated a tremendous interest worldwide, and are considered as a viable solution to mitigate the environmental impacts related to electricity generation. Although wind energy technologies have been considered as one of the cleanest energy sources, they have a wide range of direct and indirect environmental impacts when the whole supply chain is considered. This study aims to quantify...
Show moreDue to increasing concerns for global climate change, onshore and offshore wind energy technologies have stimulated a tremendous interest worldwide, and are considered as a viable solution to mitigate the environmental impacts related to electricity generation. Although wind energy technologies have been considered as one of the cleanest energy sources, they have a wide range of direct and indirect environmental impacts when the whole supply chain is considered. This study aims to quantify the direct and indirect environmental impacts of onshore and offshore wind power technologies by tracing all of the economy-wide supply chain requirements. To accomplish this goal, we developed a comprehensive hybrid life cycle assessment (LCA) model in which process-based LCA model is combined with the economic input-output (EIO) analysis. The analysis results show that on average, concrete and steel and their supply chains are responsible for 37% and 24% of carbon footprint, consequently. On average, offshore wind turbines produce 48% less greenhouse gas emissions per kWh produced electricity than onshore wind turbines. For the onshore wind turbines, concrete, aggregates, and crushed stone approximately consume 95% of total water in this construction phase. On the other hand, concrete, lead, copper, and aggregate are responsible for around 90% of total water for the offshore wind turbines. It is also found that the more capacity the wind turbine has, the less environmental impact the wind turbine generates per kWh electricity. Moreover, based on the economic and environmental impacts of studied wind turbines and also three more nonrenewable energy sources, this study develops a decision making framework to understand the best energy source mix for a building in the state of Florida. This framework accounts for the uncertainty in the input material by deploying a Monte Carlo simulation approach. The results of decision making framework show that natural gas is a better option among nonrenewable sources. On the other hand, V90-3.0 MW offshore wind turbine is the best source of energy among renewable energy sources for a building.The findings of this research are critical for policy makers to understand the direct and indirect environmental impacts of different onshore and offshore wind energy systems. Also this study furnishes the decision maker with a range of possible energy mixes based on different economic and environmental weights.
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Date Issued: 2013
Identifier: CFE0005038, ucf:50017
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005038

Title: Characterization of Impact Damage and Fiber Reinforced Polymer Repair Systems for Metallic Utility Poles.
Creator: Johnson, Cara, Mackie, Kevin, Tatari, Mehmet, Chopra, Manoj, University of Central Florida
Abstract / Description: Previous studies have demonstrated that the behavior of ber reinforced polymers(FRPs) bonded to metallic utility poles are governed by the following failure modes; yieldingof the metallic substrate, FRP tensile rupture, FRP compressive buckling, and debonding ofFRP from the substrate. Therefore, an in situ method can be devised for the repair of utilitypoles, light poles, and mast arms that returns the poles to their original service strength.This thesis investigates the eect of damage due to...
Show morePrevious studies have demonstrated that the behavior of ber reinforced polymers(FRPs) bonded to metallic utility poles are governed by the following failure modes; yieldingof the metallic substrate, FRP tensile rupture, FRP compressive buckling, and debonding ofFRP from the substrate. Therefore, an in situ method can be devised for the repair of utilitypoles, light poles, and mast arms that returns the poles to their original service strength.This thesis investigates the eect of damage due to vehicular impact on metallic poles,and the eectiveness of externally-bonded FRP repair systems in restoring their capacity.Damage is simulated experimentally by rapid, localized load application to pole sections,creating dents ranging in depth from 5 to 45% of the outer diameter. Four FRP compositerepair systems were selected for characterization and investigation due to their mechani-cal properties, ability to balance the system failure modes, and installation eectiveness.Bending tests are conducted on dented utility poles, both unrepaired and repaired.Nonlinear nite element models of dented and repaired pole bending behavior aredeveloped in MSC.Marc. These models show good agreement with experimental results,and can be used to predict behavior of full-scale repair system. A relationship between dentdepth and reduced pole capacity is developed, and FRP repair system recommendations arepresented.
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Date Issued: 2013
Identifier: CFE0004697, ucf:49872
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0004697

Title: Context-Aware Mobile Augmented Reality Visualization in Construction Engineering Education.
Creator: Shirazi, Arezoo, Behzadan, Amir, Oloufa, Amr, Tatari, Mehmet, University of Central Florida
Abstract / Description: Recent studies suggest that the number of students pursuing science, technology, engineering, and mathematics (STEM) degrees has been generally decreasing. An extensive body of research cites the lack of motivation and engagement in the learning process as a major underlying reason of this decline. It has been discussed that if properly implemented, instructional technology can enhance student engagement and the quality of learning. Therefore, the main goal of this research is to implement...
Show moreRecent studies suggest that the number of students pursuing science, technology, engineering, and mathematics (STEM) degrees has been generally decreasing. An extensive body of research cites the lack of motivation and engagement in the learning process as a major underlying reason of this decline. It has been discussed that if properly implemented, instructional technology can enhance student engagement and the quality of learning. Therefore, the main goal of this research is to implement and assess effectiveness of augmented reality (AR)-based pedagogical tools on student learning. For this purpose, two sets of experiments were designed and implemented in two different construction and civil engineering undergraduate level courses at the University of Central Florida (UCF). The first experiment was designed to systematically assess the effectiveness of a context-aware mobile AR tool (CAM-ART) in real classroom-scale environment. This tool was used to enhance traditional lecture-based instruction and information delivery by augmenting the contents of an ordinary textbook using computer-generated three-dimensional (3D) objects and other virtual multimedia (e.g. sound, video, graphs). The experiment conducted on two separate control and test groups and pre- and post- performance data as well as student perception of using CAM-ART was collected through several feedback questionnaires. In the second experiment, a building design and assembly task competition was designed and conducted using a mobile AR platform. The pedagogical value of mobile AR-based instruction and information delivery to student learning in a large-scale classroom setting was also assessed and investigated. Similar to the first experiment, students in this experiment were divided into two control and test groups. Students' performance data as well as their feedback, suggestions, and workload were systematically collected and analyzed. Data analysis showed that the mobile AR framework had a measurable and positive impact on students' learning. In particular, it was found that students in the test group (who used the AR tool) performed slightly better with respect to certain measures and spent more time on collaboration, communication, and exchanging ideas in both experiments. Overall, students ranked the effectiveness of the AR tool very high and stated that it has a good potential to reform traditional teaching methods.
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Date Issued: 2014
Identifier: CFE0005257, ucf:50609
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005257

Title: Safety Effectiveness of Conversion of Two-Way-Left-Turn Lanes into Raised Medians.
Creator: Alarifi, Saif, Abdel-Aty, Mohamed, Tatari, Mehmet, Kuo, Pei-Fen, University of Central Florida
Abstract / Description: Two way left turn lanes (TWLTL) and raised medians are common median treatments on roadways. This research focused on evaluating the safety effectiveness of conversion of TWLTLs into raised medians using Before-After and Cross Sectional Studies. In the Before-After Studies, we evaluated the effect of this treatment using the Na(&)#239;ve, Before-After with Comparison Group (CG), and Before-After with Empirical Bayes (EB) Methods. In order to apply these methods, a total of 33 segments of a...
Show moreTwo way left turn lanes (TWLTL) and raised medians are common median treatments on roadways. This research focused on evaluating the safety effectiveness of conversion of TWLTLs into raised medians using Before-After and Cross Sectional Studies. In the Before-After Studies, we evaluated the effect of this treatment using the Na(&)#239;ve, Before-After with Comparison Group (CG), and Before-After with Empirical Bayes (EB) Methods. In order to apply these methods, a total of 33 segments of a treated group and 109 segments of a comparison group have been collected. Also, safety performance functions (SPFs) have been developed using the negative binomial model in order to calibrate crash modification factors (CMF) using the Before-After with Empirical Bayes Method. This research also evaluated the safety effectiveness of this treatment on four and six lane roads using Before-After with CG and Before-After with EB. The type of raised medians was further evaluated using Before-After with CG and EB.In sum, the results from this study show that applying the before-After and Cross Sectional studies have proved that the conversion from a TWLTL to a raised median helped to reduce total, fatal and injury, head on, angle, and left turn crashes. It significantly reduces crashes for head-on and left turn crashes, by restricting turning maneuvers. Also, this study has proved that the treatment is more effective on four rather than six lane roads. Furthermore, two types of raised medians, concrete and lawn curb, were evaluated after the conversion from TWLTLs. It was found that both medians have similar effects due to the conversion, and both median types helped in reducing the number of crashes.
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Date Issued: 2014
Identifier: CFE0005122, ucf:50698
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005122

Title: Spectrally Uniform Frames and Spectrally Optimal Dual Frames.
Creator: Pehlivan, Saliha, Han, Deguang, Mohapatra, Ram, Sun, Qiyu, Tatari, Mehmet, University of Central Florida
Abstract / Description: Frames have been useful in signal transmission due to the built in redundancy. In recent years, theerasure problem in data transmission has been the focus of considerable research in the case theerror estimate is measured by operator (or matrix) norm. Sample results include the characterizationof one-erasure optimal Parseval frames, the connection between two-erasure optimal Parsevalframes and equiangular frames, and some characterization of optimal dual frames.If iterations are allowed in...
Show moreFrames have been useful in signal transmission due to the built in redundancy. In recent years, theerasure problem in data transmission has been the focus of considerable research in the case theerror estimate is measured by operator (or matrix) norm. Sample results include the characterizationof one-erasure optimal Parseval frames, the connection between two-erasure optimal Parsevalframes and equiangular frames, and some characterization of optimal dual frames.If iterations are allowed in the reconstruction process of the signal vector, then spectral radiusmeasurement for the error operators is more appropriate then the operator norm measurement.We obtain a complete characterization of spectrally one-uniform frames (i.e., one-erasure optimalframes with respect to the spectral radius measurement) in terms of the redundancy distributionof the frame. Our characterization relies on the connection between spectrally optimal frames andthe linear connectivity property of the frame. We prove that the linear connectivity property isequivalent to the intersection dependence property, and is also closely related to the well-knownconcept of k-independent set. For spectrally two-uniform frames, it is necessary that the framemust be linearly connected. We conjecture that it is also necessary that a two-uniform frame mustbe n-independent. We confirmed this conjecture for the case when N = n+1, n+2, where N is thenumber of vectors in a frame for an n-dimensional Hilbert space. Additionally we also establishseveral necessary and sufficient conditions for the existence of an alternate dual frame to make the iterated reconstruction to work.
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Date Issued: 2013
Identifier: CFE0005111, ucf:50747
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005111

Title: A real-time crane service scheduling decision support system (CSS-DSS) for construction tower cranes.
Creator: 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).
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Date Issued: 2013
Identifier: CFE0005078, ucf:50738
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005078

Title: Life Cycle Sustainability Assessment Framework for the U.S. Built Environment.
Creator: Kucukvar, Murat, Tatari, Mehmet, Oloufa, Amr, Behzadan, Amir, Al-Deek, Haitham, Pazour, Jennifer, University of Central Florida
Abstract / Description: The overall goals of this dissertation are to investigate the sustainability of the built environment, holistically, by assessing its Triple Bottom Line (TBL): environmental, economic, and social impacts, as well as propose cost-effective, socially acceptable, and environmentally benign policies using several decision support models. This research is anticipated to transform life cycle assessment (LCA) of the built environment by using a TBL framework, integrated with economic input-output...
Show moreThe overall goals of this dissertation are to investigate the sustainability of the built environment, holistically, by assessing its Triple Bottom Line (TBL): environmental, economic, and social impacts, as well as propose cost-effective, socially acceptable, and environmentally benign policies using several decision support models. This research is anticipated to transform life cycle assessment (LCA) of the built environment by using a TBL framework, integrated with economic input-output analysis, simulation, and multi-criteria optimization tools. The major objectives of the outlined research are to (1) build a system-based TBL sustainability assessment framework for the sustainable built environment, by (a) advancing a national TBL-LCA model which is not available for the United States of America; (b) extending the integrated sustainability framework through environmental, economic, and social sustainability indicators; and (2) develop a system-based analysis toolbox for sustainable decisions including Monte Carlo simulation and multi-criteria compromise programming. When analyzing the total sustainability impacts by each U.S. construction sector, (")Residential Permanent Single and Multi-Family Structures" and "Other Non-residential Structures" are found to have the highest environmental, economic, and social impacts compared to other construction sectors. The analysis results also show that indirect suppliers of construction sectors have the largest sustainability impacts compared to on-site activities. For example, for all U.S. construction sectors, on-site construction processes are found to be responsible for less than 5 % of total water consumption, whereas about 95 % of total water use can be attributed to indirect suppliers. In addition, Scope 3 emissions are responsible for the highest carbon emissions compared to Scope 1 and 2. Therefore, using narrowly defined system boundaries by ignoring supply chain-related impacts can result in underestimation of TBL sustainability impacts of the U.S. construction industry.Residential buildings have higher shares in the most of the sustainability impact categories compared to other construction sectors. Analysis results revealed that construction phase, electricity use, and commuting played important role in much of the sustainability impact categories. Natural gas and electricity consumption accounted for 72% and 78% of the total energy consumed in the U.S. residential buildings. Also, the electricity use was the most dominant component of the environmental impacts with more than 50% of greenhouse gases emitted and energy used through all life stages. Furthermore, electricity generation was responsible for 60% of the total water withdrawal of residential buildings, which was even greater than the direct water consumption in residential buildings. In addition, construction phase had the largest share in income category with 60% of the total income generated through residential building's life cycle. Residential construction sector and its supply chain were responsible for 36% of the import, 40% of the gross operating surplus, and 50% of the gross domestic product. The most sensitive parameters were construction activities and its multiplier in most the sustainability impact categories.In addition, several emerging pavement types are analyzed using a hybrid TBL-LCA framework. Warm-mix Asphalts (WMAs) did not perform better in terms of environmental impacts compared to Hot-mix Asphalt (HMA). Asphamin(&)#174; WMA was found to have the highest environmental and socio-economic impacts compared to other pavement types. Material extractions and processing phase had the highest contribution to all environmental impact indicators that shows the importance of cleaner production strategies for pavement materials. Based on stochastic compromise programming results, in a balanced weighting situation, Sasobit(&)#174; WMA had the highest percentage of allocation (61%), while only socio-economic aspects matter, Asphamin(&)#174; WMA had the largest share (57%) among the WMA and HMA mixtures. The optimization results also supported the significance of an increased WMA use in the United States for sustainable pavement construction. Consequently, the outcomes of this dissertation will advance the state of the art in built environment sustainability research by investigating novel efficient methodologies capable of offering optimized policy recommendations by taking the TBL impacts of supply chain into account. It is expected that the results of this research would facilitate better sustainability decisions in the adoption of system-based TBL thinking in the construction field.
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Date Issued: 2013
Identifier: CFE0005018, ucf:50007
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005018

Title: Structural Health Monitoring using Novel Sensing Technologies and Data Analysis Methods.
Creator: Malekzadeh, Seyedmasoud, Catbas, Fikret, Yun, Hae-Bum, Tatari, Mehmet, Moslehy, Faissal, Gul, Mustafa, University of Central Florida
Abstract / Description: The main objective of this research is to explore, investigate and develop the new data analysis techniques along with novel sensing technologies for structural health monitoring applications. The study has three main parts. First, a systematic comparative evaluation of some of the most common and promising methods is carried out along with a combined method proposed in this study for mitigating drawbacks of some of the techniques. Secondly, non-parametric methods are evaluated on a real life...
Show moreThe main objective of this research is to explore, investigate and develop the new data analysis techniques along with novel sensing technologies for structural health monitoring applications. The study has three main parts. First, a systematic comparative evaluation of some of the most common and promising methods is carried out along with a combined method proposed in this study for mitigating drawbacks of some of the techniques. Secondly, non-parametric methods are evaluated on a real life movable bridge. Finally, a hybrid approach for non-parametric and parametric method is proposed and demonstrated for more in depth understanding of the structural performance. In view of that, it is shown in the literature that four efficient non-parametric algorithms including, Cross Correlation Analysis (CCA), Robust Regression Analysis (RRA), Moving Cross Correlation Analysis (MCCA) and Moving Principal Component Analysis (MPCA) have shown promise with respect to the conducted numerical studies. As a result, these methods are selected for further systematic and comparative evaluation using experimental data. A comprehensive experimental test is designed utilizing Fiber Bragg Grating (FBG) sensors simulating some of the most critical and common damage scenarios on a unique experimental structure in the laboratory. Subsequently the SHM data, that is generated and collected under different damage scenarios, are employed for comparative study of the selected techniques based on critical criteria such as detectability, time to detection, effect of noise, computational time and size of the window. The observations indicate that while MPCA has the best detectability, it does not perform very reliable results in terms of time to detection. As a result, a machine-learning based algorithm is explored that not only reduces the associated delay with MPCA but further improves the detectability performance. Accordingly, the MPCA and MCCA are combined to introduce an improved algorithm named MPCA-CCA. The new algorithm is evaluated through both experimental and real-life studies. It is realized that while the methods identified above have failed to detect the simulated damage on a movable bridge, the MPCA-CCA algorithm successfully identified the induced damage. An investigative study for automated data processing method is developed using non-parametric data analysis methods for real-time condition maintenance monitoring of critical mechanical components of a movable bridge. A maintenance condition index is defined for identifying and tracking the critical maintenance issues. The efficiency of the maintenance condition index is then investigated and demonstrated against some of the corresponding maintenance problems that have been visually and independently identified for the bridge.Finally, a hybrid data interpretation framework is designed taking advantage of the benefits of both parametric and non-parametric approaches and mitigating their shortcomings. The proposed approach can then be employed not only to detect the damage but also to assess the identified abnormal behavior. This approach is also employed for optimized sensor number and locations on the structure.
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Date Issued: 2014
Identifier: CFE0005207, ucf:50648
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005207

Life Cycle Assessment (2)	+ -
Aftershocks (1)	+ -
Assessment (1)	+ -
Augmented Reality (1)	+ -
Before-After Studies (1)	+ -

Bridges (1)	+ -
Buildings (1)	+ -
Capacity (1)	+ -
Construction (1)	+ -
Construction Management (1)	+ -
Construction and Civil Engineering (1)	+ -
Crane (1)	+ -
Crash Modification Factor (1)	+ -
Curriculum (1)	+ -
Data Driven (1)	+ -
Data Envelopment Analysis (1)	+ -
Data-Driven (1)	+ -
Decision Support System (1)	+ -
Decision Tree (1)	+ -
Decision-Making (1)	+ -
Economic Input-Output Analysis (1)	+ -
Energy Mix (1)	+ -
Engineering Education (1)	+ -
FRP (1)	+ -
Fiber Optic Sensing (1)	+ -
Frames (1)	+ -
HMA Overlays (1)	+ -
Image-based technology (1)	+ -
Infrared (1)	+ -
Intelligent Transportation Systems (1)	+ -

Tatari, Mehmet (14)	+ -
University of Central Florida (14)	+ -
Oloufa, Amr (6)	+ -
Behzadan, Amir (4)	+ -
Nam, Boo Hyun (3)	+ -

Abdel-Aty, Mohamed (2)	+ -
Al-Deek, Haitham (2)	+ -
Catbas, Fikret (2)	+ -
Chopra, Manoj (2)	+ -
Mackie, Kevin (2)	+ -
Ahmed, Mohamed (1)	+ -
Akhavian, Reza (1)	+ -
Alarifi, Saif (1)	+ -
Ercan, Tolga (1)	+ -
Espinosa, Diego (1)	+ -
Gul, Mustafa (1)	+ -
Han, Deguang (1)	+ -
Johnson, Cara (1)	+ -
Kucukvar, Murat (1)	+ -
Kuo, Pei-Fen (1)	+ -
Laman, Haluk (1)	+ -
Madani Larijani, Kaveh (1)	+ -
Maherinia, Hamid (1)	+ -
Malekzadeh, Seyedmasoud (1)	+ -
Mohapatra, Ram (1)	+ -
Moslehy, Faissal (1)	+ -
Noori, Mehdi (1)	+ -
Pazour, Jennifer (1)	+ -
Pehlivan, Saliha (1)	+ -
Shirazi, Arezoo (1)	+ -

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