Department of Civil, Construction & Environmental Engineering

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The 2009-2010 El Niño: Hydrologic Relief to U.S. Regions
(2009-12-15) Tootle, G. A.; Piechota, T. C.; Aziz, O.; Miller, W. P.; Lakshmi, V.; Dracup, J. A.; Jerla, C.; University of Alabama Tuscaloosa
Current forecasts by the U.S. National Oceanic and Atmospheric Administration (NOAA) are that the Pacific Ocean will experience El Niño conditions in late 2009 and into 2010. These forecasts are similar to past El Niño events in 1972–1973, 1982–1983, 1986–1987, and 2002–2003.Evaluating the hydrologic conditions for these past El Niño events reveals that during these times, surface water supply conditions improved in many parts of the United States, including the Southeast, Midwest, and Southwest. At the same time, the Pacific Northwest and other specific regions of the United States experienced below‐average water supply conditions. This is consistent with the long‐established linkages between oceanic‐atmospheric phenomena, El Niño, and streamflow [e.g., Kahya and Dracup, 1993; Tootle et al., 2005].
A Reinforcement Learning Approach for GNSS Spoofing Attack Detection of Autonomous Vehicles
(Transportation Research Record, 2021) Dasgupta, Sagar; Ghosh, Tonmoy; Rahman, Mizanur
A resilient and robust positioning, navigation, and timing (PNT) system is a necessity for the navigation of autonomous vehicles (AVs). Global Navigation Satelite System (GNSS) provides satellite-based PNT services. However, a spoofer can temper an authentic GNSS signal and could transmit wrong position information to an AV. Therefore, a GNSS must have the capability of real-time detection and feedback-correction of spoofing attacks related to PNT receivers, whereby it will help the end-user (autonomous vehicle in this case) to navigate safely if it falls into any compromises. This paper aims to develop a deep reinforcement learning (RL)-based turn-by-turn spoofing attack detection using low-cost in-vehicle sensor data. We have utilized Honda Driving Dataset to create attack and non-attack datasets, develop a deep RL model, and evaluate the performance of the RL-based attack detection model. We find that the accuracy of the RL model ranges from 99.99% to 100%, and the recall value is 100%. However, the precision ranges from 93.44% to 100%, and the f1 score ranges from 96.61% to 100%. Overall, the analyses reveal that the RL model is effective in turn-by-turn spoofing attack detection.
A Web-Based Geotechnical GIS
(Wiley, 2011-10-05) Graettinger, Andrew J.; Ryals, Zachary T.; Smith, Randy K.
A web-based Geotechnical Geographic Information System (GeoGIS) was developed and tested for the Alabama Departmentof Transportation. This web-based system stores geotechnical information about transportation projects, such as subsurface data,construction drawings, and design information. Typically, this information is in a report or plan sheet format, but raw geotechnicaldata can also be accommodated in the GeoGIS. The goal of this system is to provide easy access and storage for all geotechnicaland subsurface structural information from across a state. Access through a secure web interface allows for keyword searches andinteractive map selection. The web-based GeoGIS has four geotechnical layers (project, bridge, foundation, and soil boring) thatcan be displayed on a road map, aerial photos, or USGS 7.5 minute quadrangles. For testing purposes the GeoGIS was populatedwith multiple document types, formats, and sizes. In all cases, the system performed above expectations.
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.
Assessing the social and economic impacts of hydrologic extremes
(University of Alabama Libraries, 2017) Zhu, Lian; Tootle, Glenn A.; University of Alabama Tuscaloosa
Disaster impact assessments are crucial for understanding disasters and effective disaster prevention. Deciding how to respond to disasters cannot be efficient without considering the disaster’s social and economic impacts. Among all types of disasters, drought and flood induce the largest human and economic cost. Interbasin transfer is a commonly used strategy to overcome the mismatch between water availability and water demand, and enhance economic development. The researches present within this dissertation discuss how can we develop an efficient economic impact model or models which can take into consideration sector vulnerability and resiliency strategies in response to extreme climate events, to assist decision makers in devising response strategies. The first and second studies in this dissertation investigate methods to assess the economic consequences of drought induced water restriction and the economic consequences of flood impact in public water supply systems. Drought and flood induce water outage, and cause substantial impacts in public water supply systems. However, researches and tools which assess drought and flood impact in water supply systems are uncommon. We adapt previous work on economic consequence assessment in the event of water services disruption to evaluate the economic impact of water restrictions resulting from extended drought conditions, and water contamination and outage resulting from flood conditions. These two models focus on all commercial and industrial economic sectors across multiple basins using a continuous dynamic social accounting matrix approach.The third study in this dissertation investigates the interbasin transfer impact to the basin(s), with a focus on agriculture production, and discusses the necessity to establish a state-level interbasin transfer regulation in Alabama. A framework for comprehensive impact assessment of interbasin transfer is developed in this dissertation. The interbasin transfer research reviews four representative interbasin transfer projects, concludes the triggers of interbasin transfer projects and impacts in economic, hydrologic, ecological, and social systems. The relation between irrigation and agriculture production is simulated with AquaCrop. Three states’ interbasin transfer regulations and acts are studied. Results indicate the required processes to establish a state-level interbasin transfer regulation and the focuses of future researches.
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.
Behavior of Residential Safe Room Walls Impacted by Windborne Debris
(University of Alabama Libraries, 2021) Pierce, Blair Butler; Song, Wei; University of Alabama Tuscaloosa
Tornadoes and hurricanes are among the most devastating storms on the planet. Much of the damage from these storms occurs when debris is picked up by high winds and strikes structures. Safe rooms are often constructed in commercial and residential buildings to protect occupants from windborne debris. The process for designing safe rooms requires all components to pass the large missile test, in which a 2x4 wood missile is fired at high speeds at safe room assemblies. Prescriptive designs may be utilized for residential safe rooms; however, these designs can be costly and difficult to construct. The purpose of this research is to 1) Test safe room wall assemblies constructed with conventional steel sheets and alternative materials in order to decrease the cost and improve constructability of safe rooms, and 2) Develop an experimental procedure to measure full-field deformation of safe room wall assemblies under impact during large missile test. High speed photographs are taken of each impact and digital image correlation technology is used to obtain the deformation of the wall assemblies. Additionally, the stiffness and effective mass are measured for each specimen to verify the results. While the alternative materials tested as part of this research were not successful in resisting debris impact, the non-contact measurements obtained for the passing specimens produced fair results. These measurements are further used to evaluate the behavior of the passing specimens, providing insights that go beyond the qualitative pass/fail method used in previous research.
Bioinspired Polypeptide Dendrimer-Modified Thin-FilmComposite Membranes for Selective Lithium-MagnesiumSeparation with DFT Insights
(Wiley, 2025-12-26) Yassari, Mehrasa; Seyedpour, Seyedeh Fatemeh; Setegne, Bamlak; Aghaei, Amir; Ahvazi, Behzad; Firouzjaei, Mostafa Dadashi; Elliott, Mark; Sadrzadeh, Mohtada
Selective ion transport in nanofiltration (NF) enables sustainable lithium (Li+) recovery. While many membranes rely on strong positive charge for Li⁺/Mg2⁺ separation, we show that negatively charged membranes can also excel using a biomimetic approach. Inspired by biological ion channels that achieve cation selectivity via specific binding sites despite their negative charge, we designed a nitrogen-rich polypeptide dendrimer (amino acid–based) bearing carboxylate coordination sites with higher affinity for Mg2⁺ than Li⁺, while moderating the membrane's net negative charge. This biomimetic design enhanced Li+ recovery by inhibiting Mg2+ transport through stronger interactions, thereby allowing for preferential Li+ permeation. This process occurred through a combination of electrostatic modulation and ligand-assisted coordination. Density functional theory (DFT) calculations indicated strong oxygen-donor coordination: lysine motifs bind hydrated Mg2+ (E ≈ −170 kcal.mol−1) far more strongly than Li+ (E ≈ −50.2 kcal.mol−1). The optimized membrane achieved Li+/Mg2+ selectivity of 15.6 at neutral pH with 23 LMH flux, and 136 at pH 4, highlighting strong performance in acidic feeds. Long-term tests showed ∼0.4% leaching over 10 days with stable rejection and enrichment of Li⁺ (feed Li⁺/Mg2⁺ increased from 0.05 to 0.20). Antifouling tests showed a twofold lower flux-decline ratio and higher flux-recovery than the unmodified TFC.
Block-level vulnerability assessment reveals disproportionate impacts of natural hazards across the conterminous United States
(Nature Portfolio, 2023) Yarveysi, Farnaz; Alipour, Atieh; Moftakhari, Hamed; Jafarzadegan, Keighobad; Moradkhani, Hamid; University of Alabama Tuscaloosa
The global increase in the frequency, intensity, and adverse impacts of natural hazards on societies and economies necessitates comprehensive vulnerability assessments at regional to national scales. Despite considerable research conducted on this subject, current vulnerability and risk assessments are implemented at relatively coarse resolution, and they are subject to significant uncertainty. Here, we develop a block-level Socio-Economic-Infrastructure Vulnerability (SEIV) index that helps characterize the spatial variation of vulnerability across the conterminous United States. The SEIV index provides vulnerability information at the block level, takes building count and the distance to emergency facilities into consideration in addition to common socioeconomic vulnerability measures and uses a machine-learning algorithm to calculate the relative weight of contributors to improve upon existing vulnerability indices in spatial resolution, comprehensiveness, and subjectivity reduction. Based on such fine resolution data of approximately 11 million blocks, we are able to analyze inequality within smaller political boundaries and find significant differences even between neighboring blocks. Introduces a precise, machine-learning-based Socio-Economic-Infrastructure Vulnerability index for natural hazards that uncovers stark variations in vulnerability at the block level emphasizing crucial information for risk-informed decision making.
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.
CARE IMPACT Study of Drowsy Driving (DrD)
(2020-01-25) Brown, David B.

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