Department of Civil and Environmental Engineering

: Calibration and Evaluation of Link Congestion Functions; This paper explores the use of archived data to calibrate volume delay functions (VDFs) and updates their input parameters (capacity and free-flow speed) for planning applications. The sensitivity analysis of speed to change in congestion level is performed to capture functional characteristics of VDFs in modeling specific facility types. Different sensitivity characteristics shown by the VDFs indicate that each function is suitable to a particular facility type. The results of sensitivity analysis are confirmed by the root mean square percent error (RMSPE) values calculated using the Orlando Urban Area Transportation Study (OUATS) model results and observed data. The modified Davidson's function exhibits remarkable performance in nearly all facility types. The strength of the modified Davidson's function across a broad range of facilities can be attributed to the flexibility of its tuning parameter, μ. Fitted Bureau of Public Road (BPR) and conical delay functions show lower RMSPE for uninterrupted flow facilities (freeways/expressways, managed lanes) and higher values for toll roads (which might have partial interruptions due to toll booths) and signalized arterials. Akcelik function underperforms on freeways/expressways and managed lanes but shows some improvements for toll roads and superior results for the signalized arterials. This was a desired strength of Akcelik function when modeling link travel speed on facilities where stopped delays were encountered., Keywords: travel demand modeling, congestion functions, ITS data applications, Note: This work is licensed under the Creative Commons Attribution International License (CC-BY) with support from the Florida State University Open Access Publishing Fund., Citation: Mtoi, E. and Moses, R. (2014) Calibration and Evaluation of Link Congestion Functions: Applying Intrinsic Sensitivity of Link Speed as a Practical Consideration to Heterogeneous Facility Types within Urban Network. Journal of Transportation Technologies, 4, 141-149. doi: 10.4236/jtts.2014.42014.

: Calibration and Evaluation of Link Congestion Functions; This paper explores the use of archived data to calibrate volume delay functions (VDFs) and updates their input parameters (capacity and free-flow speed) for planning applications. The sensitivity analysis of speed to change in congestion level is performed to capture functional characteristics of VDFs in modeling specific facility types. Different sensitivity characteristics shown by the VDFs indicate that each function is suitable to a particular facility type. The results of sensitivity analysis are confirmed by the root mean square percent error (RMSPE) values calculated using the Orlando Urban Area Transportation Study (OUATS) model results and observed data. The modified Davidson’s function exhibits remarkable performance in nearly all facility types. The strength of the modified Davidson’s function across a broad range of facilities can be attributed to the flexibility of its tuning parameter, μ. Fitted Bureau of Public Road (BPR) and conical delay functions show lower RMSPE for uninterrupted flow facilities (freeways/expressways, managed lanes) and higher values for toll roads (which might have partial interruptions due to toll booths) and signalized arterials. Akcelik function underperforms on freeways/expressways and managed lanes but shows some improvements for toll roads and superior results for the signalized arterials. This was a desired strength of Akcelik function when modeling link travel speed on facilities where stopped delays were encountered., Keywords: Travel demand modeling, Congestion functions, ITS data applications, Publication Note: This is an open access article published in the Journal of Transportation Technologies and can be found at https://www.doi.org/10.4236/jtts.2014.42014.

: Estimation Of Fugitive Landfill Methane Emissions Using Surface Emission Monitoring And Genetic Algorithms Optimization; As municipal solid waste (MSW) landfills can generate significant amounts of methane, there is considerable interest in quantifying fugitive methane emissions at such facilities. A variety of methods exist for the estimation of methane emissions from landfills. These methods are either based on analytical emission models or on measurements. This paper presents a method to estimate methane emissions using ambient air methane measurements obtained on the surface of a landfill. Genetic Algorithms based optimization combined with the standard Gaussian dispersion model is employed to identify locations as well as emission rates of potential emission sources throughout a municipal solid waste landfill. Four case studies are employed in order to evaluate the performance of the proposed methodology. It is shown that the proposed approach enables estimation of landfill methane emissions and localization of major emission hotspots in the studied landfills. The proposed source-locating-scheme could be seen as a cost effective method assisting landfill operators to reasonably estimate and locate major methane emissions. (C) 2016 Elsevier Ltd. All rights reserved., Keywords: oxidation, Methane emission, Genetic Algorithms, Methane measurements, municipal landfill, Solid waste landfill, Publication Note: The publisher's version of record is available at https://doi.org/10.1016/j.wasman.2016.11.024

: Evaluating The Service Life Of Thermoplastic Pavement Markings; The study applied the Markov chain (MC) model that uses a transition matrix to transmit the probability of monitored pavement markings being in one service life state then changing into another service life state over a time interval. The service life prediction by MC models were then compared with those from linear models, testing if there were any clear advantages of using one model over the other in terms of predicting longevity of the marking retroreflectivity. The retroreflectivity data were collected by monitoring the coefficient of dry retroreflective luminance for 2 years using a handheld retroreflectometer. Using the MC model, the study found that the pavement marking retroreflectivity (PMR) degradation follows an exponential curve trend whereby the degradation rates decrease as the time increases. Significant differences were found in the deterioration of the markings based on the colors (white or yellow) and line type (center, lane line, or edge line). White thermoplastic edge lines on two-lane roadways were found to have a better performance (low deterioration rates) compared with the same lines on four-lane highways. Based on the transition probability matrix (TPM), it was observed that retroreflectivity is in an excellent or good state for a short period of time(54% probability) but is in a fair or poor state for a longer time (92% probability), suggesting the trend has a higher degradation rate at the beginning and a lower rate near the failure state. Keeping the minimum failure states at 150 and 100 mcd/m(2)/lx for white and yellow markings, respectively, the service life of white markings was found to be approximately 4 years (49.5 months) and it was found to be about 2.4 years (29 months) for yellow markings. The MC model findings were compared with those obtained through linear regression, which showed that white thermoplastic pavement markings take approximately 3.5 years (42 months) to deteriorate to failure state level, while yellow thermoplastics take about 2.1 years (25 months). The study concluded that there is a clear difference between the prediction using MC models compared with linear models, with MC models being more cost effective in terms of maintenance and replacement scheduling due to a longer life prediction. (C) 2018 American Society of Civil Engineers., Keywords: Markov chain, Monte Carlo, Paint, Pavement marking, Retroreflectivity, Thermoplastic, Publication Note: The publisher’s version of record is available at https://doi.org/10.1061/JPEODX.0000055

: Factors Affecting The Effectiveness Of Bioelectrochemical System Applications; Microbial fuel cells (MFCs) and microbial electrolysis cells (MECs) are promising bioelectrochemical systems (BESs) for simultaneous wastewater treatment and energy/resource recovery. Unlike conventional fuel cells that are based on stable chemical reactions, these BESs are sensitive to environmental and operating conditions, such as temperature, pH, external resistance, etc. Substrate type, electrode material, and reactor configuration are also important factors affecting power generation in MFCs and hydrogen production in MECs. In order to discuss the influence of these above factors on the performance of MFCs and MECs, this study analyzes published data via data synthesis and meta-analysis. The results revealed that domestic wastewater would be more suitable for treatment using MFCs or MECs, due to their lower toxicity for anode biofilms compared to swine wastewater and landfill leachate. The optimal temperature was 25-35 degrees C, optimal pH was 6-7, and optimal external resistance was 100-1000 Omega. Although systems using carbon cloth as the electrodes demonstrated better performance (due to carbon cloth's large surface area for microbial growth), the high prices of this material and other existing carbonaceous materials make it inappropriate for practical applications. To scale up and commercialize MFCs and MECs in the future, enhanced system performance and stability are needed, and could be possibly achieved with improved system designs., Keywords: meta-analysis, hydrogen-production, electricity-generation, microbial fuel-cells, bioelectrochemical system (BES), COD removal, data synthesis, different external resistances, electrolysis cells, graphite fiber brush, hydrogen production rate, maximum power density, microbial electrolysis cell (MEC), microbial fuel cell (MFC), power-generation, single-chamber, treating landfill leachate, waste-water treatment, Publication Note: The publisher’s version of record is available at https://doi.org/10.3390/batteries4030034

: Optimization Model And Solution Algorithms For The Vehicle Routing Problem With A "factory-in-a-box"; The "factory-in-a-box" concept involves assembling production modules (i.e., factories) in containers and transporting the containers to different customer locations. Such a concept could be highly effective during emergencies, when there is an urgent demand for products (e.g., the COVID-19 pandemic). The "factory-in-a-box" planning problem can be divided into two sub-problems. The first sub-problem deals with the assignment of raw materials to suppliers, sub-assembly decomposition, assignment of sub-assembly modules to manufacturers, and assignment of tasks to manufacturers. The second sub-problem focuses on the transport of sub-assembly modules between suppliers and manufacturers by assigning vehicles to locations, deciding the order of visits for suppliers, manufacturers, and customers, and selecting the appropriate routes within the transportation network. This study addresses the second sub-problem, which resembles the vehicle routing problem, by developing an optimization model and solution algorithms in order to optimize the "factory-in-a-box" supply chain. A mixed-integer linear programming model, which aims to minimize the total cost of the "factory-in-a-box" supply chain, is presented in this study. CPLEX is used to solve the model to the global optimality, while four metaheuristic algorithms, including the Evolutionary Algorithm, Variable Neighborhood Search, Tabu Search, and Simulated Annealing, are employed to solve the model for large-scale problem instances. A set of numerical experiments, conducted for a case study of "factory-in-a-box", demonstrate that the Evolutionary Algorithm outperforms the other metaheuristic algorithms developed for the model. Some managerial insights are outlined in the numerical experiments as well., decomposition, delivery, berth-allocation, Companies, container terminals, Containers, evolutionary algorithm, Factory-in-a-box, hybrid metaheuristic algorithm, metaheuristics, pickup, Production facilities, Raw materials, supply chain, supply chains, Supply chains, time windows, urgent demand, variable neighborhood search, Vehicle routing, vehicle routing problem, The publisher's version of record is availible at https://doi.org/10.1109/ACCESS.2020.3010176

: Resilience Of Regional Transportation Networks Subjected To Hazard-induced Bridge Damages; The comprehension of network-level consequences resulting from disruptive events is a main gray area in the evaluation of transportation network resilience at the regional level. Explaining hazard impacts on regional network infrastructures and identifying significantly affected areas are important for communicating the need for building resilient infrastructure. This paper presents a framework for assessing the regional network resilience by leveraging scenario-based traffic modeling and GIS techniques. High-impact-zone location identification metrics were developed and implemented in preliminarily identifying areas affected by bridge closures. Resilience was estimated, and an index developed by utilizing practical functionality metrics based on vehicle distance and hours traveled. These are illustrated for the Tampa Bay, Florida, area. Findings for 10 bridge closure scenarios and recovery schemas indicated significant regional resilience losses. The 1-275 bridge closure indicated the highest functional loss to the regional network: the aggregated resilience index below 0.5 reflects severe network performance deficit and mobility limitations. (C) 2018 American Society of Civil Engineers., Keywords: systems, framework, Resilience, vulnerability, Bridge closures, hurricane-katrina, Network performance, Transportation network, Publication Note: The publisher’s version of record is available at https://doi.org/10.1061/JTEPBS.0000186

: Self-adaptive Evolutionary Algorithm For The Berth Scheduling Problem; Since ancient times, maritime transportation has played a very important role for the global trade and economy of many countries. The volumes of all major types of cargo, which are transported by vessels, has substantially increased in recent years. Considering a rapid growth of waterborne trade, marine container terminal operators should focus on upgrading the existing terminal infrastructure and improving operations planning. This study aims to assist marine container terminal operators with improving the seaside operations and primarily focuses on the berth scheduling problem. The problem is formulated as a mixed integer linear programming model, minimizing the total weighted vessel turnaround time and the total weighted vessel late departures. A self-adaptive Evolutionary Algorithm is proposed to solve the problem, where the crossover and mutation probabilities are encoded in the chromosomes. Numerical experiments are conducted to evaluate performance of the developed solution algorithm against the alternative Evolutionary Algorithms, which rely on the deterministic parameter control, adaptive parameter control, and parameter tuning strategies, respectively. Results indicate that all the considered solution algorithms demonstrate a relatively low variability in terms of the objective function values at termination from one replication to another and can maintain the adequate population diversity. However, application of the self-adaptive parameter control strategy substantially improves the objective function values at termination without a significant impact on the computational time., Keywords: system, model, optimization, marine container terminals, parameter control, allocation problem, computational time, container terminals, evolutionary computation, marine transportation, parameter tuning, solution quality, Publication Note: The publisher’s version of record is available at https://doi.org/10.3390/a11070100

: Strain rate dependency in paratransit bus rollover; This paper examines the effect of structural steel strain rate dependency on the outcome of the FDOT/ECE-R66 bus rollover test. Bending and impact tests were performed on structural tubing in order to evaluate strain rate dependency parameters. Several mesh densities were used to investigate the influence of mesh size on the final outcome of the analysis. Two strain rate dependency formulations, Cowper-Symonds and Johnson-Cook, were calibrated and then implemented in the finite element analysis of a paratransit bus rollover. Unlike strain rate effect on other types of impact such as the frontal crash, the results show that the strain rate has no significant effect on the FDOT/ECE-R66 rollover test. Therefore, the current approach used by researchers investigating bus rollovers, to validate finite element models based on quasi-static experiments, is well-grounded and the strain rate dependent effects may be ignored for the global deformation response in the ECE-R66 bus rollover., Keywords: bus safety, crashworthiness assessment, finite element analysis, rollover, safety, standards, strain rate, UN ECE-R66, Publication Note: The publisher’s version of record is available at http://www.dx.doi.org/10.1504/IJHVS.2016.074624

: Theoretical Lower Bounds For Parallel Pipelined Shift-and-add Constant Multiplications With N-input Arithmetic Operators; New theoretical lower bounds for the number of operators needed in fixed-point constant multiplication blocks are presented. The multipliers are constructed with the shift-and-add approach, where every arithmetic operation is pipelined, and with the generalization that n-input pipelined additions/subtractions are allowed, along with pure pipelining registers. These lower bounds, tighter than the state-of-the-art theoretical limits, are particularly useful in early design stages for a quick assessment in the hardware utilization of low-cost constant multiplication blocks implemented in the newest families of field programmable gate array (FPGA) integrated circuits., Keywords: design, algorithm, digital-filters, fpga, Lower bound, mcm, Multiplication, multipliers, scm, Publication Note: The publisher's version of record is available at https://doi.org/10.1186/s13634-017-0466-z

: Using Crash Modification Factors To Appraise The Safety Effects Of Pedestrian Countdown Signals For Drivers; Although pedestrian countdown signals (PCSs) are meant for pedestrians, they give cues to drivers on the remaining amount of green as the timer counts down. This study focuses on the evaluation of safety effectiveness of PCSs to drivers in the cities of Jacksonville and Gainesville, Florida, using the before-after study with the empirical Bayes method. This analysis explored 110 intersections with PCSs and their respective 93 comparison sites. The findings indicate that PCSs significantly improve driver safety by 8.8% reduction in total crashes, 8.0% in rear-end and 7.1% in property-damage-only crashes, where both of these results were significant at the 95% confidence level. Results for angle crashes as well as fatal and injury crashes were not significant at the 95% confidence level. Also discussed in this study are the crash modification functions developed to show the relationship between the estimated crash modification factors and total entering traffic volume at the intersection. In summary, the results suggest the usefulness of PCSs for drivers. (C) 2018 American Society of Civil Engineers., Keywords: intersections, frequency, Crash reduction factors, Crash modification factors, Empirical Bayes, green, Pedestrian countdown signals, Publication Note: The publisher’s version of record is available at https://doi.org/10.1061/JTEPBS.0000130

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Department of Civil and Environmental Engineering