Theses and Dissertations - Department of Civil, Construction & Environmental Engineering

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Active construction safety leading indicator data collection and evaluation
(University of Alabama Libraries, 2017) Awolusi, Ibukun Gabriel; Batson, Robert G.; Marks, Eric D.; University of Alabama Tuscaloosa
The construction industry continues to experience an increased rate of workplace injuries and fatalities when compared to other U.S. industrial sectors. Construction workers often face safety and health risks throughout the construction process because of these dangerous working environments. Current safety practices, which are largely passive in nature, have not yielded the desired optimum results. Further improvements are necessary to enhance construction safety through the implementation of proactive safety strategies. This research seeks to evaluate how construction safety performance can be enhanced during the construction phase through the application of active construction safety leading indicators and sensing technologies. A near miss data collection and analysis framework is created and implemented for the management of safety leading indicator information. An objective evaluation of wearable technology systems for personalized construction safety monitoring is presented together with a model for integrating wearable sensors for multi-parameter safety performance monitoring. The characteristics of wearable devices and safety metrics capable of predicting safety performance and management practices are identified and analyzed. Strategies for the evaluation, selection, and implementation of vehicle intrusion sensing technologies for highway work zone safety are provided. The major contributions of this research involve the scientific data for collecting and evaluating safety leading indicators and innovative technologies, as well as an implementation guide for their application in construction. This research also provides best practices for construction management personnel that allows for the implementation of innovative safety technologies, as well as the use of collected data and information in operational procedures, safety training, and education.
Analysis and rehabilitation of the 1882 wrought iron bridge
(University of Alabama Libraries, 2010) Mathis, Brandi Price; Richardson, James A.; University of Alabama Tuscaloosa
The Friends of Historic Northport in conjunction with the City of Northport planned to relocate and preserve an existing span of a bridge that originally crossed the Black Warrior River in 1882. The 1882 Bridge is an old wrought iron arch-shaped truss bridge manufactured by the King Iron and Bridge Company of Ohio. A tensile test and metallographic analysis were performed on samples taken from the bridge, and it was determined that the bridge is composed of at least two grades of wrought iron. The tests also indicated the presence of brittle iron. The wood decking system, the concrete bridge abutments, and the keystone retaining wall for the bridge approaches were designed for material quantities for the relocation project. A structural analysis of the bridge at its new location showed that some of the bridge members were slightly overstressed under certain loading conditions. Parts of the top chord, floor beam, and diagonals were overstressed under the dead and pedestrian loads, and the bottom diagonals were overstressed under the wind load. Four lifting methods were analyzed for the bridge's relocation. The method considered the most efficient was to attach the lifting cables directly to the top chord near the ends of the bridge.
Analysis of the impacts of drinking water infrastructure on water quality in Alabama's Black Belt
(University of Alabama Libraries, 2013) Forehand, Richard Warren; Johnson, Pauline; University of Alabama Tuscaloosa
Research has suggested that residents of Alabama's Black Belt are at elevated risk of waterborne disease due to a problem with failing septic tanks in the area. At the same time, cities and towns across the nation are realizing the dire need for replacing and rehabilitating America's declining water infrastructure to protect public health. An EPA-STAR project is being conducted in three Black Belt counties to further assess the situation and help local water utilities combat the increased risk of contamination. Water loss, low pressure, low chlorine, high residence time, and presence of total coliforms were used as indicators to assess which service areas of one Black Belt system were most likely vulnerable to contamination. Collected data from 195 households within the system and simulated data from an EPANET model of the system were used for the analysis. The results identified the regions with the highest prevalence of these indicators and suggested further system level sampling to evaluate if the problem is more associated with system water mains or households.
Analyzing crash frequency and severity data using novel techniques
(University of Alabama Libraries, 2014) Mehta, Gaurav Satish; Jones, Steven L.; Lou, Yingyan; University of Alabama Tuscaloosa
Providing safe travel from one point to another is the main objective of any public transportation agency. The recent publication of the Highway Safety Manual (HSM) has resulted in an increasing emphasis on the safety performance of specific roadway facilities. The HSM provides tools such as crash prediction models that can be used to make informed decisions. The manual is a good starting point for transportation agencies interested in improving roadway safety in their states. However, the models published in the manual need calibration to account for the local driver behavior and jurisdictional changes. The method provided in the HSM for calibrating crash prediction models is not scientific and has been proved inefficient by several studies. To overcome this limitation this study proposes two alternatives. Firstly, a new method is proposed for calibrating the crash prediction models using negative binomial regression. Secondly, this study investigates new forms of state-specific Safety Performance Function SPFs using negative binomial techniques. The HSM's 1st edition provides a multiplier applied to the univariate crash prediction models to estimate the expected number of crashes for different crash severities. It does not consider the distinct effect unobserved heterogeneity might have on crash severities. To address this limitation, this study developed a multivariate extension of the Conway Maxwell Poisson distribution for predicting crashes. This study gives the statistical properties and the parameter estimation algorithm for the distribution. The last part of this dissertation extends the use of Highway Safety Manual by developing a multivariate crash prediction model for the bridge section of the roads. The study then compares the performance of the newly proposed multivariate Conway Maxwell Poisson (MVCMP) model with the multivariate Poisson Lognormal, univariate Conway Maxwell Poisson (UCMP) and univariate Poisson Lognormal model for different crash severities. This example will help transportation researchers in applying the model correctly.
Assessment of bamboo culm ash for use as as an additive in concrete
(University of Alabama Libraries, 2015) Soleimanzadeh, Sara; Giannini, Eric R.; University of Alabama Tuscaloosa
Each year tens of millions of tons of bamboo are utilized commercially, generating a vast amount of waste. One solution is to calcine this waste and use it as additive in concrete to keep it out of landfills and save money on waste disposal. This research project identifies (1) the optimal calcination condition of bamboo culm ash (BCAsh) and (2) the effect of various cement replacement levels on mortar properties. After considering the amount of energy consumed and the carbon content, burning at 700 °C [1292 °F] for 1.5 h was selected as the optimum condition. Cement replacement levels between 0.5 and 5% were investigated by evaluating the effects on heat of hydration and compressive strength of four mixes of BCAsh mortar. While the BCAsh reduced the strength of the mortar only slightly, it did show a considerable retarding effect on mortar hydration.
Assessment of integrated green infrastructure-based stormwater controls in small to large scale developed urban watersheds
(University of Alabama Libraries, 2014) Talebi, Leila; Pitt, Robert; University of Alabama Tuscaloosa
Green infrastructure (GI) stormwater control approaches and techniques store, infiltrate, evapotranspire, and in some cases reuse stormwater to reduce runoff quantity and to improve overall environmental quality. The literature review indicates substantial benefits provided by GI stormwater controls in small scales including reduced stormwater runoff volumes, enhanced groundwater recharge, reduced pollutant discharges to water bodies, and decreased combined sewer overflow events. The main objective of this dissertation research was to examine the benefits of individual and integrated GI stormwater control practices at small to large scales in urban watersheds. The hypothesis of this research is: "Retrofitting integrated green infrastructure controls in large areas served by separate or combined sewers can result in significant runoff volume reductions." Three case studies which were extensively monitored and evaluated have been selected for this dissertation research; 1) Millburn, NJ with dry wells monitored at a small scale, 2) Kansas City, MO with various GI practices including biofilters, curb extension biofilters, cascade biofilters, porous pavement, rain gardens monitored at small scales (individual GI performance) and monitored at large scales (overall integrated GI performance and their impact on combined sewer overflows (CSOs), and 3) Cincinnati, OH with three study sites including Cincinnati State College, the Cincinnati Zoo, and the Clark Montessori High School, which have several GI stormwater control types with monitoring at large scales. Analyses were conducted at infiltration facilities and at combined and separate sewer flow monitoring locations in the study areas to calculate the benefits of green infrastructure-based stormwater controls. The analyses conducted as part of this dissertation research were aimed at showing that monitoring results for runoff volume reductions from isolated small-scale stormwater controls can be scaled-up for use in typical drainage area benefit predictions, but only if sufficient information is available (such as soil characteristics, land development, actual runoff treated, etc.). The analyses at the small scales at Millburn, NJ and Kansas City, MO, indicated that there were varying levels of infiltration performance in the areas, but most dry wells and biofilters were able to completely drain within a few days. However, several had extended periods of standing water that may have been associated with high water tables, poorly draining soils (or partially clogged soils), or detrimental effects from snowmelt on the clays in the soils. At large scales at the Kansas City and Cincinnati test areas, direct measurements of flows by the in-system flow monitors in the combined or separate sewers on or adjacent to several of the green infrastructure components were used to directly measure whole system performance. The results at the large scales indicated that for most flow monitoring locations, there was a statistically significant difference (p<0.05) between the "after" construction period data and the "before" construction period data, which supports the hypothesis of this dissertation research. The runoff volume reductions for the large-scale studied areas ranged from 20% (for the Clark Montessori High School that has about 25% of its drainage area treated by green infrastructure controls) to about 85% (for Cincinnati State College where most of the area's runoff was treated by the treatment devices). The results showed that the green infrastructure locations and coverage in the watersheds directly affected the runoff reductions in the areas. The watersheds should have most of their flows treated by the green infrastructure stormwater control practices to result in large runoff volume reductions in the watersheds. Some of the flow monitoring results appears to be faulty and since the monitoring period has concluded and the equipment removed, it is not possible to verify the calibrations. Therefore, an important part of this dissertation research was to develop and demonstrate an effective monitoring and evaluation strategy and QA/QC process. This dissertation research also utilized a calibrated version of WinSLAMM for each study area that can be used to determine likely long-term benefits under a large variety of conditions, as well as recommendations for flow monitoring of green infrastructure stormwater controls.
Assessment of project controls for shutdowns/turnarounds/outages
(University of Alabama Libraries, 2017) Premraj, Pratheeksha; Vereen, Stephanie C.; University of Alabama Tuscaloosa
Shutdown/Turnaround/Outages (STOs) are unique construction projects required to meet demands such as maintenance needs, increased market demand, and changes in technology. Shutdown, Turnarounds, and Outages projects (STOs) are maintenance projects subject to compressed schedules, and hence require a time efficient cost control system with robust monitoring, reporting, and mitigating to ensure the success of the project. The purpose of this research was to address the significant lack of literature about project controls for STOs by identifying current project control tools used by industry practitioners. Relevant data was collected using the Delphi methodology. The Delphi process, an approach particularly effective in exploring areas of research where there is little or no information available, was applied to the collected data to allow for anonymity, interactivity, and feedback in the survey process. The data collection process involved three rounds of surveys: (1) Survey Round 1 was conducted using questionnaire, (2) Survey Round 2 through conducting semi-structured interviews, and (3) Survey Round 3 using questionnaire. The questionnaires used in Survey round 1 and Survey round 2 had two parts – Part A and Part B. Part A was designed to collect demographic data and Part B had three main sections. The first section was to prove that STOs vary significantly from traditional construction projects; the second section to obtain information on current practices, and section three to analyze barriers to implementation of optimum project controls. The research contributes to the body of knowledge through addressing the significant lack in literature on STOs and project controls for STOs. Additionally, the paper informs less experienced professionals about information required for effective planning and risk management processes by providing a list of risk factors. The research results will be fundamental to improving project controls processes for STOs and may also benefit traditional projects and provide significant information on the cost and schedule controls for STOs.
Automated assessment of tornado-induced building damage based on terrestrial laser scanning
(University of Alabama Libraries, 2014) Kashani, Alireza G.; Graettinger, Andrew Joseph; University of Alabama Tuscaloosa
Assessing the damage states of the built environment after a tornado is one method to better understand tornado induced loads and failure progress, as well as improve knowledge used for tornado mitigation, response, and recovery. Building damage states and geometry need to be measured and taken into consideration when estimating tornado wind pressures and speeds. This perishable damage data should be appropriately recorded, and investigations should be completed in a timely and unobtrusive manner in order to avoid interfering with clean up and recovery efforts that quickly change damage sites. Laser scanning or Light Detection And Ranging (LiDAR) provides 3D data that virtually captures damaged areas and allows for geometric queries and accurate measurements. Although robust, the 3D LiDAR data requires sophisticated data processing to extract meaningful information. The data processing becomes more challenging and time consuming when a large number of damaged buildings are investigated after a large-scale tornado. This research developed and tested a LiDAR data processing framework to automatically extract quantitative damage information needed for tornado wind speed estimation and structural damage analysis. The framework developed in this research includes methods for: 1) detecting damaged roof and wall surfaces in scans of damaged sites, 2) quantifying the percentages of roof/wall sheathing and covering losses, 3) estimating wind speeds at individual building scales, and 4) evaluating current tornado fragility models with actual damage information obtained by laser scanning. Performance of the developed methods was assessed with simulated data, laboratory scans, and actual data collected after large-scale tornadoes. A series of experiments in controlled conditions were conducted to determine the best algorithm settings and also objectively evaluate the performance of the proposed methods under varying environmental conditions. The proposed methods and their contributions to tornado wind speed estimation and structural fragility assessment were also tested with actual data collected after the Tuscaloosa, AL and Moore, OK tornadoes. The tests and case studies indicated that the detailed information extracted from LiDAR data could provide insight about tornado wind pressures and speeds with a resolution and accuracy not achievable with current visual inspections. This research determined the optimum data collection and processing settings that resulted in less than 10% error in calculating the percentages of roof and wall losses. The proposed method also estimates wind speeds at small-scale (individual buildings) as opposed to large-scale estimates often provided by field reconnaissance teams. Noting the fact that tornado wind speeds and pressures dramatically vary over short distances, the presented method provides engineers with a tool to improve the resolution and understanding of tornado effects, thereby improving building design and construction.
Autonomous engineering: a multi-scale GIS-based approach to green infrastructure design
(University of Alabama Libraries, 2019) Greer, Ashton Danielle; Graettinger, Andrew; University of Alabama Tuscaloosa
This dissertation presents a new method called “Autonomous Engineering” that incorporates geographic information systems (GIS) to automatically design green stormwater infrastructure. The Autonomous Engineering framework aims to increase the efficiency at which green infrastructure is designed, thus promoting increased implementation. Green infrastructure design is a unique challenge in that it is multi-scale; planning and design considerations must be made at both the site-level and the watershed level by analyzing various types of spatial data. This framework presents a methodology for designing green infrastructure based on a combination of remotely sensed watershed-scale data and ultra-high resolution site-level Light Detection and Ranging (LiDAR) data. First, watershed level data is analyzed to generate site recommendations and quantify runoff characteristics. Second, LiDAR data is processed using both deep learning and machine learning frameworks so that site-level spatial features can automatically be recognized and extracted and so that an ultra high resolution digital elevation model (DEM) is generated. Next, linear referencing techniques are used to analyze terrain and identify geometric design recommendations. The results are finalized in the form of custom design drawings and reports. This work has outcomes for improved green infrastructure design workflows as well as the spatial analysis of robust site-level data for other applications. Future work includes the extension of these methodologies to applications beyond green infrastructure.
Bridge weigh-in-motion deployment opportunities in Alabama
(University of Alabama Libraries, 2011) Brown, Alan James; Jones, Steven L.; Richardson, James A.; University of Alabama Tuscaloosa
Overweight vehicle enforcement is a continuous problem for all state Departments of Transportation. Various technologies are in use across the US to aid in the enforcement of vehicle weight limits. However, to date, no technology has been shown to be a definitive solution. The various technologies currently available were researched and the pros and cons of each highlighted. Focus was placed on Bridge Weigh-in-Motion (B-WIM) and an extensive literature review has been conducted following all developments in the field of B-WIM since 1979. The advantages of B-WIM include its ease of installation, portability and potential for high accuracy vehicle weight measurements. Accuracy however is site specific, which makes the selection of a bridge an extremely important element in the success of a B-WIM installation. A bridge selection tool prototype was developed using ArcGIS. The tool was designed to select bridges with the physical characteristics associated with achieving high B-WIM weight measurement accuracies. Daily truck volumes and current Weigh-in-Motion (WIM) sites were also included in the tool to allow for an effective choice of route for installation. As the systems use cellular data signals to transfer data to the weigh crew during the pre-selection process, cell service maps were also included in the tool. The prototype showed that such a tool is feasible and should be beneficial for ALDOT. ALDOT owns two B-WIM systems which it intends to use for overweight vehicle enforcement. An accuracy test of the system was conducted. A bridge in West Alabama was selected for installation. Calibration was conducted and random vehicles were statically weighed to verify the accuracy of the system. A gross vehicle weight accuracy of B (10) was obtained which is more than sufficient for pre-selection of potentially overweight vehicles. Alternative sensor locations and orientations were also investigated and signals were compared. It was found that longitudinal axle detectors located close to the bridge supports provided the cleanest and most distinct signals at the test location. Weighing sensors located at the mid-span provided the best signals for weighing trucks.
Building information modeling: how it can benefit a modern construction project in a university setting
(University of Alabama Libraries, 2013) Duke, William Michael; Johnson, Philip W.; University of Alabama Tuscaloosa
The benefits offered by Building Information Modeling, when implemented during a modern construction project, were analyzed. Common inefficiencies of current construction industry practices were observed through evaluation of historical data, and used to demonstrate the need for an improved project approach. Several surveys were presented to reveal the most popular uses of BIM while also displaying the value participating construction companies placed on each use. A case study of the North Engineering Research Complex located on the University of Alabama campus was presented, and observed benefits were evaluated up through the current progress. Potential benefits were explained for the remaining project phases. The research revealed that a wide variety of benefits can be enjoyed by all project parties when utilizing Building Information Modeling. The most valuable benefit is that of overall increased collaboration during the project. The ability of the entire project team to share the BIM models helped in identifying problems prior to construction, reducing the project cost by avoiding these problems, improving the project schedule and increasing the overall quality of the end product. Viewing the three-dimensional BIM model also helped project members attain a better understanding of the project as a whole. Because Building Information Modeling is a relatively new concept, the owner, architect and general contractor also learned valuable lessons for future projects.
Built environment system resiliency subject to extreme events with fema ihp
(University of Alabama Libraries, 2015) Lester, Henry; Moynihan, Gary P.; University of Alabama Tuscaloosa
Repairing and rebuilding structures following an extreme event requires capital. Due to shifting demographics, high-risk settlements are increasingly placing both populations and the built environment at substantial loss exposure to such extreme events. Instead of retaining extreme event risks associated with these settlements, owners tend to transfer the risk to government. The primary purpose of this research is to develop a post-disaster model to analyze the public structural indemnification influences on building construction resiliency and to develop a quantitative basis for pre-disaster planning to increase this resiliency. The framework consists of designing a model for analyzing the impact of extreme event reconstruction project municipal financing on built environment resiliency and ascertaining the primary stakeholder risk transfer. Specifically, the methodology entails an operational analysis and modeling of current post-disaster Federal Emergency Management Agency (FEMA) Individual and Households Program and determining its impact upon residential built environment resiliency. While resiliency is hazard specific, spatially dependent, and a complex amalgamation of many socioeconomic factors, a regional multistate approach will focus on Presidentially Declared Disasters concentrating on the coastal regions of Western Florida, Alabama, and Eastern Mississippi. The model establishes a quantitative metric for future public policy decision analysis pertaining extreme event indemnification, risk allocation, and resiliency.
Characterization and modeling of long-term behavior of frp-to-concrete interface in aggressive environments
(University of Alabama Libraries, 2015) Amidi, Shahrooz; Wang, Jialai; University of Alabama Tuscaloosa
Fiber reinforced plastics (FRP) composites have emerged as one the foremost structural materials in retrofit/rehabilitation of concrete structural members in last decades. The long-term durability of the FRP-to-concrete interface in aggressive environments places a critical role in the success of this technique. A comprehensive program using both the analytical and experimental approaches has been carried out in this study to examine the integrity and long-term durability of the FRP-to-concrete interface in presence of aggressive environments. Novel analytical solutions based on three-parameter elastic/viscoelastic foundation models have been developed for adhesively bonded joints first in this study to gain better understanding of stress transfer through FRP-to-concrete interface. These models overcome drawbacks in existing models by satisfying all boundary conditions and producing different peel stress distributions along two adhesive-adherend interfaces, making it possible to accurately predict the location of debonding initiation. These models have been verified with finite element analysis and experimental observations. Comprehensive experimental programs have been carried out to evaluate the deterioration of the FRP-to-concrete induced by moisture. In the first part, a novel environment-assisted subcritical debonding method using a wedge driving test has been proposed to examine the synergistic effect of the mechanical loads and environmental conditions on the deterioration of the FRP-to concrete interface. The deterioration of the interface induced by water has also been evaluated through measuring the residual fracture toughness of the FRP-to-concrete interface conditioned in water through two different ways. It has been found that conditioning method can have significant effect on the testing results. A novel wedge-split test has been proposed and carried out to directly measure the traction-separation law of the epoxy-concrete interfaces under mode I loading, which is not available in the literature. The potential of using silane coupling agent to improve the durability of the FRP-to-concrete interface has also been examined in the experimental program. Testing results confirm that the residual fracture toughness of the FRP-to-concrete interface attacked by moisture can be significantly increased by silane treatment.
Characterization of reinforced structural composites with carbon nanotubes grown directly on the fibers/fabrics using the Poptube Approach
(University of Alabama Libraries, 2017) Guin, William Edward; Wang, Jialai; University of Alabama Tuscaloosa
Carbon nanotubes (CNTs) are ideal candidates for the reinforcement of the matrix and interphase zone in polymer matrix composites (PMCs), due to their ability to more effectively bind the reinforcing fibers to the matrix material. This can lead to the enhancement of several critical composite properties – including interfacial shear strength and interlaminar fracture toughness – that are typically associated with a composite material’s resistance to delamination. Direct dispersion of CNTs into the matrix of the composites has been shown to be very difficult. A more effective way to reinforce PMCs using CNTs is to grow CNTs directly on the reinforcing fibers. To this end, a novel technique used to grow CNTs directly on carbon fibers has been developed at The University of Alabama and Auburn University. This method, referred to as the PopTube Approach, uses microwave irradiation to grow CNTs at room temperature in air, without the need for inert gas protection or additional feed stock gases. The simple nature of the PopTube Approach lends itself to large-scale, high-yield manufacturing that can be done in a cost effective manner. However, before this technique is developed beyond the laboratory scale, its effectiveness as a route to produce CNT-reinforced composites must be evaluated in a comprehensive manner. The objective of this work is to do just that – characterize the mechanical properties of CNT-reinforced composites produced via the PopTube Approach. A systematic experimental program is carried out to provide a comprehensive assessment of the effects of the PopTube Approach on a wide range of composite mechanical properties. Results show that the PopTube Approach provides for enhanced resistance to delamination with respect to several different loading events. Fractography studies are used to qualitatively understand the mechanisms responsible for these improvements in delamination resistance on the micro-scale. Results also suggest that improvements in delamination resistance via CNT reinforcement may come at the expense of the tensile properties of PMCs – which gives rise to the conclusion that in practice, the degree and manner of CNT reinforcement in PMCs should be carefully considered on an application-by-application basis. Together, the collection of studies performed herein provides a wide-ranging quantitative and qualitative assessment of the effects of the PopTube Approach CNT reinforcement scheme on the mechanical properties and behavior of polymer matrix composites.
Climatic drivers of Southeast U.S hydrology
(University of Alabama Libraries, 2019) Tabatabaei Sadeghi, Sahar; Tootle, Glenn; University of Alabama Tuscaloosa
The growing demand for water has raised concerns regarding future resource scarcity. For water management, agriculture, fisheries needs and hydro-climatic research, there has been conflict over water in Southeastern United States (SEUS). In this dissertation, I intend to evaluate the temporal (monthly) variability of El Nino on SEUS streamflow and Atlantic Ocean Sea Surface Temperature (AO SST) variability and SEUS streamflow. The development of an El Nino and the association of increased moisture (e.g., precipitation, streamflow) in coastal Mississippi and Alabama is misleading in agricultural practices (Sadeghi et al., 2019b). While annual increases were ~20%, this increase was in the winter and late-spring during the planting season for crops. Thus, moist soil conditions could delay crop planting. During the summer growing season, moisture was decreased and, thus, given the majority of agricultural lands are rain-fed and not irrigated, this could severely impact crop production (drought). A multi-decadal teleconnection was established between north Atlantic Ocean SSTs and SEUS streamflow (Sadeghi et al., 2019a). SEUS streamflow has been in a multi-decadal decline since ~1990 and the warming of north Atlantic Ocean SSTs exhibits a strong, linear relationship with this decline. The use of “raw” SSTs confirms previous efforts establishing an Atlantic Multidecadal Oscillation “like” signal in SEUS streamflow. Future research efforts will utilize the multi-decadal teleconnection of Atlantic Ocean SSTs to forecast SEUS streamflow. Future forecasts of Atlantic Oceans SSTs from multiple Global Climate Models (GCMs) will be used as independent variables in regression models to forecast future multi-decadal variability of SEUS streamflow. These results can be compared to “traditional” methods in which physically based distributed hydrologic models are developed and downscaled future “forcings” are input to determine future flows.
Conceptual cost estimation decision support system in university construction projects
(University of Alabama Libraries, 2018) Chau, Anh Duc; Moynihan, Gary P.; University of Alabama Tuscaloosa
Recently, many construction organizations have shifted from offline to online data storage platforms, such as MS SharePoint. Construction companies are storing more historical data than ever. The question is how these historical data can be structured and analyzed to make actionable decisions and bring competitive advantages. This dissertation discusses a reliable solution for using historical data in construction. In this project, we developed a decision support system which predicts conceptual costs of construction projects and supports decision-making for long-term capital planning in public universities. A prototype system was developed based on historical data for roofing projects at the University of Alabama. We collected this historical data via a web-based data entry form subsystem. The developed system uses ridge regression models to train historical data, which helps reduce multicollinearity. K-fold cross-validation and evolutionary algorithm are used to fit ridge regression models. This system has a user-friendly interface and supports what-if analysis which allows the user to see multiple scenarios of the estimation. Also, the system has an automated process which adjusts inflation based on construction start date. Finally, validation has shown that the system can improve in the accuracy in conceptual estimation of roofing projects at the University of Alabama.
Conditional cell transmission model for two-way arterials in oversaturated conditions
(University of Alabama Libraries, 2010) Wang, Ping; Jones, Steven L.; University of Alabama Tuscaloosa
In 2007, congestion caused urban Americans to travel 4.2 billion hours more and to purchase an extra 2.8 billion gallons of fuel for a congestion cost of $87.2 billion - an increase of more than 50% over the previous decade. Urban arterials operating in oversaturated conditions are now very common and are expected to become even more prevalent. As a result, there is an urgent need to explicitly address oversaturation. Simulation of oversaturation plays an important role in addressing it. However, the previous research, including existing traffic simulation software and theoretical approaches, take full account of traffic flow on two way arterials in oversaturated conditions. Therefore, improvements of existing traffic flow model simulation techniques are necessary to adequate study such fully oversaturated arterials. The objective of this research is to develop a novel feature for traffic flow models, to simulate when traffic queues on two way arterials periodically extend until then block an upstream signal in oversaturated conditions. Such a model should be capable of delineating the dynamic of traffic flow created by the merging and diverging activities on two way arterials. In additional, it should have the capability of describing blockages, spillback and shock wave phenomena along the oversaturated arterials. The Cell Transmission model (CTM) is used in the dissertation, because it can accommodate all traffic conditions from light condition to oversaturated condition. However, it has limitations and has only recently been extended from one way two way arterials. Two way arterials have more diverge and merge activities at intersections, which make the coding of CTM more complex and time-consuming. Second, a noticeable inaccuracy in prior CTM research is the failure to simulate the blockages at intersections. They typically estimate the delay occurring on segments and ignore the delay occurring at intersections. These limitations affect CTM's accuracy and limit its use. To enhance CTM, a conditional cell transmission model (CCTM) is developed with two improvements. First, CTM is expanded for two-way arterials by taking account of all diverge and merge activities at intersections. Second, a conditional cell is added to simulate periodic spillback and blockages at an intersection. The cell exists conditionally, depending on whether or not there is a spillback at an intersection. In other words, if spillback happens, the conditional cell exists and stores the vehicles which spill back into the intersection; if there is no spillback, the conditional cell will not exist. In CCTM, users may input the probability of a conditional cell (drivers breaking the driving rule) and probability of occurrence of useful location of a gap to match the characteristics of local drivers' behavior. This is a unique contribution of CCTM. The CCTM traffic flow simulation was initially developed using evolutions of small model of six cell mode. It included (a segment cell, a diverge cell, a cell in front of an intersection, a cell in a left turn lane, a cell in the minor street and a conditional cell). They were loaded with light duty traffic, moderate duty traffic and heavy duty traffic respectively. To test the overall performance of CCTM, a series of experiments are designed and performed for a multilane, two-way, three-signal sample network. Experiments were conducted to give sensitivity analyses to four user-defined parameters including traffic demand, traffic signal timing, possibility of occurrence of a useful gap and possibility of a conditional cell. The results demonstrate that CCTM can accommodate various traffic demands and CCTM's accurate representation of traffic flow. Finally, to validate CCTM, it is compared with HCS (Highway Capacity Software 2000). Three scenarios of traffic demand are inputted into HCS and the results of travel speeds are compared with those of CCTM. The consistency between HCS 2000 and CCTM shows that CCTM is a reliable methodology of modeling traffic flow in oversaturated condition.
Construction equipment travel path visualization and productivity evaluation
(University of Alabama Libraries, 2017) Song, Siyuan; Moynihan, Gary P.; Marks, Eric D.; University of Alabama Tuscaloosa
The U.S. construction industry represents approximately 4% of the U.S. gross domestic product (BEA 2015) and currently involves over 6 million workers employed by an estimated 750,000 construction firms (BLS 2015). Within this industry, productivity is a key driver for economic growth and strongly affects prosperity for the country (Vogl and Abdel-Wahab 2014). More specifically, higher construction productivity and more reliable installation (quality) translates into higher wages and increased profits (Vogl and Abdel-Wahab 2014). On many construction projects, productivity is defined or greatly impacted by equipment cycle time. Furthermore, the U.S. construction industry continues to be one of the more dangerous work environments for employees (BLS 2015). Construction workers in the U.S. experience a disproportionate number of fatalities when compared other major industrial sectors in the U.S. (BLS 2013). Visibility has proven to be a major cause of accidents on construction sites (Hinze and Teizer 2011). This research seeks to prove the hypothesis that visibility and location-based data can be automatically collected and analyzed for construction equipment operators to assess a construction equipment cycle. As one of the more promising recent implementations in the construction industry, sensing and design technology provide unique opportunities to capture and analyze location-based information on construction sites. These technologies can enable productivity managers to identify, assess, and decrease the overall cycle time of a specific operation. This research implements Building Information Modeling (BIM), Global Positioning System (GPS) location identification, and laser scanning to enable automated data collection and analysis. The overall objective of the research is to automatically capture and analyze elements of a construction equipment cycle. The outcomes of this research addresses the following key components of an equipment cycle time: 1) automated cycle time path planning, 2) location-based data capture and analysis of real-time equipment cycles, and 3) equipment path environment visualization. The research framework was tested with active construction site data, and feedback from the workforce and management was assessed and integrated into the research approach. The research has the potential to improve productivity on construction sites and enhance construction employee safety performance. It will also assist in adding a link between productivity planning and management and existing project BIMs.
Crack identification through computer vision: from non-learning-based to learning-based methodologies, and from patch-level to pixel-level detections
(University of Alabama Libraries, 2020-12) Zhou, Shanglian; Song, Wei; University of Alabama Tuscaloosa
Modern society requires a sustainable, robust, and serviceable infrastructure to promote social welfare and boost economy. To support such infrastructure systems, an efficient health monitoring framework is needed which can promptly detect the presence of defects and perform associated rehabilitation and maintenance. In civil infrastructure, one of the most common types of defects is cracking, which evolves rapidly under the impacts of heavy traffic, aging of materials, and drastic environmental changes. In recent decades, image-based automated crack detection methodologies have been developed and extensively applied by professionals and researchers. Nevertheless, a few issues and challenges existing in this type of methodology are yet to be systematically investigated and properly addressed. In this study, an image-based condition assessment framework for roadway crack detection is developed. It consists of four topics: i) proposing a filter-based methodology that can address image disturbances to promote a robust image-based roadway crack detection; ii) performing a systematic study to investigate the impact from hyperparameter selection on the performance of deep convolutional neural network (DCNN) on roadway crack classification; iii) achieving pixel-level crack detection resolution on image data of real-world complexities through DCNN-based roadway crack segmentation; and iv) investigating the impact from heterogeneous image data on DCNN-based roadway crack detection and proposing heterogeneous image fusion strategies to address data uncertainties. Overall, experimental results and discussions show that the proposed crack detection framework is capable to properly address the issues under investigation and leads to improved and more robust crack detection performance than current image-based methodologies.
A decision analysis tool for building renovations regarding adaptive reuse
(University of Alabama Libraries, 2020-12) Harbin, Kristopher Belton; Moynihan, Gary P.; University of Alabama Tuscaloosa
Renovation projects are an important part of a building’s life cycle and are performed for a variety of reasons, including adaptive reuse which can vary in scope and size. They are also prone to unexpected issues which can lead to costly changes. This can be exacerbated by arbitrarily choosing the renovation space. The renovation project may waste time, money, and effort and lead to a space that does not meet the needs of the user.A better understanding of a project’s scope earlier in the development process helps to identify renovation spaces that meets users’ needs with less need for renovation. This leads to the selection of a renovation space that reduces construction by minimizing the impact to existing systems. This benefits everyone involved in the renovation process. This dissertation presents an improved approach to minimize the impact of adaptive reuse by providing a decision analysis tool to help select the space for renovation. The tool provides information to help reduce the arbitrary nature of selection. The decision analysis tool allows users to select a space that minimizes the impact yet fits the renovation needs. The tool provides an exhaustive search of room combinations with room areas and shape, and impacts to building system and current room usages. The information is provided to users in a format that is easy to filter and sort. The tool addresses some of the deficiencies of earlier methods such as providing misaligned room selections. By providing the fit of the room shape users can choose the space that best fits the needs of the renovation. The tool also minimizes the need for user input, which has been an issue for previous approaches. User inputs do not require an extensive knowledge of the tool or general building information. The tool uses building information and renovation standards from The University of Alabama in the decision analysis. The research incorporates existing buildings on The University of Alabama campus to help ensure adequate historical information is available for validation. In the future, any building could be analyzed by the tool as long as the necessary information is available.

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Browsing Theses and Dissertations - Department of Civil, Construction & Environmental Engineering by Subject "Civil engineering"

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