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|Investigation of Corrosion and Other Deterioration Effects in Highway Bridge Components Using Nondestructive Testing Technology of Acoustic Emission|
|Impact of Education and Awareness Programs on the Usage and Attitude Towards Texting While Driving Among Young Drivers|
|Investigation of Fine Particulate Matter, Nox, and Tropospheric Ozone Transport Around a Major Roadway|
|A Research Framework for Studying Transit Bus Driver Distraction|
|Further Analysis Of NOx And O3 Data, And The Acquisition, Installation And Laboratory Testing Of The PM Equipment|
Principal Investigators: Ates Akyurtlu and Jale Akyurtlu
|Modeling and Predicting Traffic Accidents at Signalized Intersections in the City of Norfolk, VA|
1. Develop an exploratory statistical model that would provide a valid explanation of traffic accidents. A set of geometric, design, control and road signage factors would be used as independent variables for model development.
2. Validate the statistical model developed at step one. Principal Investigators: Dr. Sharad K. Maheshwari & Dr. Kelwyn A. D’Souza
Principal Investigators: Dr. Sharad K. Maheshwari & Dr. Kelwyn A. D'Souza
|Non-Destructive Bridge Testing With Advanced Micro-II Digital AE System|
Principal Investigator: Devendra S Parmar
Summary: This study was an attempt to apply a proactive approach using traffic pattern and signalized intersection characteristics to predict accident rates at signalized The proposed research at the Coast Guard Blvd. in the City of Portsmouth was completed according to the plan of action prepared in consultation with the VDOT and the Virginia Council of Transportation Innovation and Research (VCTIR). The major elements of the work are shown below:
|Investigation of NOx and Tropospheric Ozone Transport around a Major Roadway|
|Principal Investigators: Ates Akyurtlu and Jale Akyurtlu|
|Modeling Traffic Accidents at Signalized Intersections in the City of Norfolk, VA.|
Objective: Develop and Validate Statistical Model for Traffic Accident
Principal Investigator: Dr. Sharad K. Maheshwari & Dr. Kelwyn A. D’Souza
Summary: This study was an attempt to apply a proactive approach using traffic pattern and signalized intersection characteristics to predict accident rates at signalized intersections in a city’s arterial network. An earlier analysis of accident data at selected intersections within the City of Norfolk indicated that in addition to traffic volume, other controllable factors contributed to traffic accidents at specific intersections. These factors included area topography, lane patterns, type of road signs, turning lanes, etc. It is also known that administrative factors such as signal types, signal polices, road closures, etc., and maintenance factors such as road conditions, condition of the signals, condition of road signs, etc. also impact road accidents.
The objective of this study was to relate these variables to accident rate and delineate variables that are statistically more significant for accident rate. Data on several topographical variables was collected in the City of Norfolk. These variables included number of lanes, turn lanes, pedestrian crossing, restricted lanes, etc. A linear regression model was used to establish relationship between these variables and the accident rate. The resulting regression model explained 60% of the variability. It also showed that four topographical variables are more important than other variables. These variables include number of lanes, number of turn lanes, presence of median and presence of permanent hazard like railway crossing. However, validation of model showed higher than expected variation. The model developed, in this study, overestimates the accident rate by 33%, thus, limiting its practical application.
|Non-Destructive Bridge Testing and Monitoring With Acoustic Emission (AE) Sensor Technology|
Principal Investigator: Devendra S. Parmar
Summary: The proposed research at the Coast Guard Blvd. in the City of Portsmouth was according to the plan of action prepared in consultation with the VDOT. The major elements of the work include
|Investigation of Nitrogen Oxides Emissions from a Major Roadway|
Principal Investigators: Ates Akyurtlu and Jale Akyurtlu.
Executive Summary: Despite recent advances in the automobile industry in reducing emissions from individual vehicles, air pollution in some localities still persist at problematic levels because of the regional increases in the traffic volumes. Vehicular emissions are the major contributors to atmospheric NOx, constituting about half of all anthropogenic emissions. The secondary species formed in the atmosphere as the result of the reactions of NOx with other species, are known to cause a wide variety of health and environmental problems.
Measurements done at the air pollution monitoring stations provide regional data with some temporal resolution but their numbers are too few to provide a detailed spatial resolution. Air pollutant concentrations can be significantly higher close to major roadways. This makes the local pollutant concentration measurements and finding ways to predict concentrations with a much higher spatial resolution essential in making decisions about locating buildings that will house sensitive populations, such as hospitals, day care centers, elementary schools, retirement homes and assisted living facilities. Therefore, there is a need for more data on NOx concentrations especially near major roadways, and for models, which can predict NOx concentrations with more accuracy and more spatial resolution.
Two recent developments highlighted the importance of our work. The first one is the proposed revisions to the National Ambient Air Quality Standards (NAAQS) for nitrogen dioxide announced on June 26, 2009. EPA is proposing a new 1-hour standard at a level between 80 and 100 ppb while retaining the current average NO2 standard of 53 ppb. This proposal increases the importance of measuring the peak concentrations over shorter time periods especially near major roads in urban areas. The second development is the January 7, 2010 announcement by EPA proposing to change the standard for ground level ozone to no more than 0.06 to 0.07 ppm from the current value of 0.075 ppm. Since ground level ozone is formed by the reaction of nitrogen oxides with volatile organic compounds, the proposed change emphasizes the importance of the investigation of nitrogen oxide concentrations around major roadways.
In this research project, we
Measurements showed that NOx concentration decreases rapidly with the distance from the roadway and drops from 25.4 ppb to a value around 8.3 ppb, which remains fairly constant for distances greater than about 150 m from the I-64 median. The reason for this decrease is 4 atmospheric dispersion and conversion of NOx to other nitrogen containing compounds. Close to the roadway (less than about 100 m from the I-64 median), the majority of NOx is NO, which converts to NO2 and other nitrogen compounds and falls from17.3 to a value about 3.4 ppb at distances greater than 150 m from the median. The decrease in nitrogen dioxide concentration is not as much and falls from about 12 ppb at 74 m to about 5.5 ppb beyond 150 m. This may be due to the conversion of some NO to NO2 possibly through its reaction with ozone. Close to the roadway, there was significant variation in the measured NO and NOx concentrations due to the effects of emissions coming from individual vehicles passing close to the analyzer intake. This effect became less significant at larger distances from the roadway.
The NO2 concentrations at the receptor locations were predicted using CALINE4, which can provide estimates with a sensitivity of ± 5 ppb. Since the measured NO2 concentrations were between 5 and 15 ppb, CALINE4 was expected to predict 0.010 ppm NO2 at each receptor location. As expected, the predicted NO2 concentrations at receptors beyond 100 m of the I-64 median were 0.01 ppm. CALINE4 also correctly predicted 0.01 ppm NO2 at the first receptor location, which had a measured value of 0.012 ppm. These observations indicate that the current data cannot provide an adequate evaluation of the CALINE4 program. To obtain a reasonable evaluation, data are needed during the rush hour traffic and closer to the roadway, which are expected to give higher NO2 concentrations.
Since the measured NOx levels are lower than the 24-hr EEGL value of 0.04 ppm for NO2, they do not by themselves represent a significant health risk. But since the main health effects of nitrogen oxides are through their role in the formation of ground level ozone (smog) and nitrogen containing particulates, it is imperative that ozone and particulates are also measured.
|Short term Evaluation of Bridge Cables Using Acoustic Emission Sensors|
Objective: Facilitate maintenance and inspection of cable stay bridges across the Commonwealth of Virginia.
Partner: Virginia Transportation Research Council (VTRC).
Principal Investigator: Dr. Devendra Parmar.
Summary:To perform this study, acoustic emission (AE) sensors had been strategically affixed to a single cable and were monitored for two and a half months each during the winter and the summer months of 2008 and 2009. A sample plot of the data representing AE events (hits), their amplitude and the dates and times recorded is shown below. AE in this plot is related to weather. AE technique is capable of detecting even feeble sounds originating from impacts on the bridge cable from factors such as rain drops and snowflakes.
(a): AE Sensor locations on north span of the cable (b): AE Sensor locations on south span of the cable
(c): AE hits as recorded by sensors (d): AE hits and their amplitudes
|Development of Vehicle Usage Policy for ROME, NASA Langley, Hampton, VA, July 2007|
Objective: The purpose of this General Vehicle Usage Policy is to provide use, maintenance, and replacement guidelines for all vehicles owned by the Research Operations, Maintenance, and Engineering (ROME) Group that provides building and other general maintenance service to NASA, Langley. Facilitate maintenance and inspection of cable stay bridges across the Commonwealth of Virginia.
Partner: Research Operations, Maintenance, and Engineering (ROME) Group
Principal Investigator: Dr. Sharad Maheshwari and Dr. Sid Credle
Summary: Drs. Sharad Maheshwari and Sid Credle conducted a comprehensive analysis of existing vehicle data which included vehicle make, model and type, the age of vehicles, the years placed in service, type of use, and assignment of vehicle. The financial data available for the vehicle were purchase price, book value, and the accounting depreciation schedule. The maintenance data on each vehicle comprised of type and annual cost of maintenance. All this information and data were used to prepare a Fleet maintenance policy. The results from the data analysis are highlighted as follows: