4 resultados para Perturb and Observe

em Iowa Publications Online (IPO) - State Library, State of Iowa (Iowa), United States


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The stability of air bubbles in fresh concrete can have a profound influence of the potential durability of the system, because excessive losses during placement and consolidation can compromise the ability of the mixture to resist freezing and thawing. The stability of air void systems developed by some air entraining admixtures (AEAs) could be affected by the presence of some polycarboxylate-based water reducing admixtures (WRAs). The foam drainage test provides a means of measuring the potential stability of air bubbles in a paste. A barrier to acceptance of the test was that there was little investigation of the correlation with field performance. The work reported here was a limited exercise seeking to observe the stability of a range of currently available AEA/WRA combinations in the foam drainage test; then, to take the best and the worst and observe their stabilities on concrete mixtures in the lab. Based on the data collected, the foam drainage test appears to identify stable combinations of AEA and WRA.

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On the October 7 and 8, 2008, a road safety audit was conducted for the intersection of US 61/Harrison Street and West Locust Street in Davenport, Iowa. US 61/Harrison Street is a one-way street and a principal arterial route through Davenport, with three southbound lanes. Locust Street is a four-lane, two-way minor arterial running across the city from west to east. The last major improvement at this intersection was implemented approximately 20 years ago. The Iowa Department of Transportation requested a safety audit of this intersection in response to a high incidence of crashes at the location over the past several years, in view of the fact that no major improvements are anticipated for this intersection in the immediate future. The road safety audit team discussed current conditions at the intersection and reviewed the last seven years of crash data. The team also made daytime and nighttime field visits to the intersection to examine field conditions and observe traffic flow and crossing guard operations with younger pedestrians. After discussing key issues, the road safety audit team drew conclusions and suggested possible enforcement, engineering, public information, and educational strategies for mitigation.

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The primary goal of this project is to demonstrate the accuracy and utility of a freezing drizzle algorithm that can be implemented on roadway environmental sensing systems (ESSs). The types of problems related to the occurrence of freezing precipitation range from simple traffic delays to major accidents that involve fatalities. Freezing drizzle can also lead to economic impacts in communities with lost work hours, vehicular damage, and downed power lines. There are means for transportation agencies to perform preventive and reactive treatments to roadways, but freezing drizzle can be difficult to forecast accurately or even detect as weather radar and surface observation networks poorly observe these conditions. The detection of freezing precipitation is problematic and requires special instrumentation and analysis. The Federal Aviation Administration (FAA) development of aircraft anti-icing and deicing technologies has led to the development of a freezing drizzle algorithm that utilizes air temperature data and a specialized sensor capable of detecting ice accretion. However, at present, roadway ESSs are not capable of reporting freezing drizzle. This study investigates the use of the methods developed for the FAA and the National Weather Service (NWS) within a roadway environment to detect the occurrence of freezing drizzle using a combination of icing detection equipment and available ESS sensors. The work performed in this study incorporated the algorithm developed initially and further modified for work with the FAA for aircraft icing. The freezing drizzle algorithm developed for the FAA was applied using data from standard roadway ESSs. The work performed in this study lays the foundation for addressing the central question of interest to winter maintenance professionals as to whether it is possible to use roadside freezing precipitation detection (e.g., icing detection) sensors to determine the occurrence of pavement icing during freezing precipitation events and the rates at which this occurs.

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Rural intersections account for 30% of crashes in rural areas and 6% of all fatal crashes, representing a significant but poorly understood safety problem. Transportation agencies have traditionally implemented countermeasures to address rural intersection crashes but frequently do not understand the dynamic interaction between the driver and roadway and the driver factors leading to these types of crashes. The Second Strategic Highway Research Program (SHRP 2) conducted a large-scale naturalistic driving study (NDS) using instrumented vehicles. The study has provided a significant amount of on-road driving data for a range of drivers. The present study utilizes the SHRP 2 NDS data as well as SHRP 2 Roadway Information Database (RID) data to observe driver behavior at rural intersections first hand using video, vehicle kinematics, and roadway data to determine how roadway, driver, environmental, and vehicle factors interact to affect driver safety at rural intersections. A model of driver braking behavior was developed using a dataset of vehicle activity traces for several rural stop-controlled intersections. The model was developed using the point at which a driver reacts to the upcoming intersection by initiating braking as its dependent variable, with the driver’s age, type and direction of turning movement, and countermeasure presence as independent variables. Countermeasures such as on-pavement signing and overhead flashing beacons were found to increase the braking point distance, a finding that provides insight into the countermeasures’ effect on safety at rural intersections. The results of this model can lead to better roadway design, more informed selection of traffic control and countermeasures, and targeted information that can inform policy decisions. Additionally, a model of gap acceptance was attempted but was ultimately not developed due to the small size of the dataset. However, a protocol for data reduction for a gap acceptance model was determined. This protocol can be utilized in future studies to develop a gap acceptance model that would provide additional insight into the roadway, vehicle, environmental, and driver factors that play a role in whether a driver accepts or rejects a gap.