24 resultados para Data portal performance


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This document is the second of two deliverables for the project Optimizing Pavement Base, Subbase, and Subgrade Layers for Cost and Performance on Local Roads (TR-640). The first deliverable is the 454-page Final Field Data Report. The field data report describes test results and comparative analysis from 16 different portland cement concrete (PCC) pavement sites on local city and county roads in Iowa. At each site the surface conditions of the pavement (i.e., crack survey) and foundation layer strength, stiffness, and hydraulic conductivity properties were documented. The field test results were used to calculate in situ parameters used in pavement design methodologies for AASHTO (1993) and Iowa’s Statewide Urban Design and Specifications (SUDAS). Overall, the results of the study demonstrate how in situ and lab testing can be used to assess the support conditions and design values for pavement foundation layers and how the measurements compare to the assumed design values. This guide summarizes the study results and outlines general guidelines for applying them to optimize pavement bases, subbases, and subgrade layers of local roads with PCC pavements and thus their performance.

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The work described in this report documents the activities performed for the evaluation, development, and enhancement of the Iowa Department of Transportation (DOT) pavement condition information as part of their pavement management system operation. The study covers all of the Iowa DOT’s interstate and primary National Highway System (NHS) and non-NHS system. A new pavement condition rating system that provides a consistent, unified approach in rating pavements in Iowa is being proposed. The proposed 100-scale system is based on five individual indices derived from specific distress data and pavement properties, and an overall pavement condition index, PCI-2, that combines individual indices using weighting factors. The different indices cover cracking, ride, rutting, faulting, and friction. The Cracking Index is formed by combining cracking data (transverse, longitudinal, wheel-path, and alligator cracking indices). Ride, rutting, and faulting indices utilize the International Roughness Index (IRI), rut depth, and fault height, respectively.

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This Phase II follow-up study of IHRB Project TR-473 focused on the performance evaluation of rubblized pavements in Iowa. The primary objective of this study was to evaluate the structural condition of existing rubblized concrete pavements across Iowa through Falling Weight Deflectometer (FWD) tests, Dynamic Cone Penetrometer (DCP) tests, visual pavement distress surveys, etc. Through backcalculation of FWD deflection data using the Iowa State University's advanced layer moduli backcalculation program, the rubblized layer moduli were determined for various projects and compared with each other for correlating with the long-term pavement performance. The AASHTO structural layer coefficient for rubblized layer was also calculated using the rubblized layer moduli. To validate the mechanistic-empirical (M-E) hot mix asphalt (HMA) overlay thickness design procedure developed during the Phase I study, the actual HMA overlay thicknesses from the rubblization projects were compared with the predicted thicknesses obtained from the design software. The results of this study show that rubblization is a valid option to use in Iowa in the rehabilitation of portland cement concrete pavements provided the foundation is strong enough to support construction operations during the rubblization process. The M-E structural design methodology developed during Phase I can estimate the HMA overlay thickness reasonably well to achieve long-lasting performance of HMA pavements. The rehabilitation strategy is recommended for continued use in Iowa under those conditions conducive for rubblization.

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Among the variety of road users and vehicle types that travel on U.S. public roadways, slow moving vehicles (SMVs) present unique safety and operations issues. SMVs include vehicles that do not maintain a constant speed of 25 mph, such as large farm equipment, construction vehicles, or horse-drawn buggies. Though the number of crashes involving SMVs is relatively small, SMV crashes tend to be severe. Additionally, SMVs can be encountered regularly on non-Interstate/non-expressway public roadways, but motorists may not be accustomed to these vehicles. This project was designed to improve transportation safety for SMVs on Iowa’s public roadway system. This report includes a literature review that shows various SMV statistics and laws across the United States, a crash study based on three years of Iowa SMV crash data, and recommendations from the SMV community.

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To provide insight into subgrade non-uniformity and its effects on pavement performance, this study investigated the influence of non-uniform subgrade support on pavement responses (stress and deflection) that affect pavement performance. Several reconstructed PCC pavement projects in Iowa were studied to document and evaluate the influence of subgrade/subbase non-uniformity on pavement performance. In situ field tests were performed at 12 sites to determine the subgrade/subbase engineering properties and develop a database of engineering parameter values for statistical and numerical analysis. Results of stiffness, moisture and density, strength, and soil classification were used to determine the spatial variability of a given property. Natural subgrade soils, fly ash-stabilized subgrade, reclaimed hydrated fly ash subbase, and granular subbase were studied. The influence of the spatial variability of subgrade/subbase on pavement performance was then evaluated by modeling the elastic properties of the pavement and subgrade using the ISLAB2000 finite element analysis program. A major conclusion from this study is that non-uniform subgrade/subbase stiffness increases localized deflections and causes principal stress concentrations in the pavement, which can lead to fatigue cracking and other types of pavement distresses. Field data show that hydrated fly ash, self-cementing fly ash-stabilized subgrade, and granular subbases exhibit lower variability than natural subgrade soils. Pavement life should be increased through the use of more uniform subgrade support. Subgrade/subbase construction in the future should consider uniformity as a key to long-term pavement performance.

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The goal of this research project was to develop a method to measure the performance of a winter maintenance program with respect to the task of providing safety and mobility to the travelling public. Developing these measures required a number of steps, each of which was accomplished. First, the impact of winter weather on safety (crash rates) and mobility (average vehicle speeds were measured by a combination of literature reviews and analysis of Iowa Department of Transportation traffic and Road Weather Information System data. Second, because not all winter storms are the same in their effects on safety and mobility, a method had to be developed to determine how much the various factors that describe a winter storm actually change safety and mobility. As part of this effort a storm severity index was developed, which ranks each winter storm on a scale between 0 (a very benign storm) and 1 (the worst imaginable storm). Additionally a number of methods of modeling the relationships between weather, winter maintenance actions and road surface conditions were developed and tested. The end result of this study was a performance measure based on average vehicle speed. For a given class of road, a maximum expected average speed reduction has been identified. For a given storm, this maximum expected average speed reduction is modified by the storm severity index to give a target average speed reduction. Thus, if for a given road the maximum expected average speed reduction is 20 mph, and the storm severity for a particular storm is 0.6, then the target average speed reduction for that road in that storm is 0.6 x 20 mph or 12 mph. If the average speed on that road during and after the storm is only 12 mph or less than the average speed on that road in good weather conditions, then the winter maintenance performance goal has been met.

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The effects of farm equipment on the structural behavior of flexible and rigid pavements were investigated in this study. The project quantified the difference in pavement behavior caused by heavy farm equipment as compared to a typical 5-axle, 80 kip semi-truck. This research was conducted on full scale pavement test sections designed and constructed at the Minnesota Road Research facility (MnROAD). The testing was conducted in the spring and fall seasons to capture responses when the pavement is at its weakest state and when agricultural vehicles operate at a higher frequency, respectively. The flexible pavement sections were heavily instrumented with strain gauges and earth pressure cells to measure essential pavement responses under heavy agricultural vehicles, whereas the rigid pavement sections were instrumented with strain gauges and linear variable differential transducers (LVDTs). The full scale testing data collected in this study were used to validate and calibrate analytical models used to predict relative damage to pavements. The developed procedure uses various inputs (including axle weight, tire footprint, pavement structure, material characteristics, and climatic information) to determine the critical pavement responses (strains and deflections). An analysis was performed to determine the damage caused by various types of vehicles to the roadway when there is a need to move large amounts agricultural product.

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The purpose of performance measures in planning operations is to identify and track meaningful, quantifiable measures that reflect progress toward the goals of the plan. The Iowa Department of Transportation (DOT) has already adopted performance measures in a number of operational areas, including highway maintenance, highway safety, public transportation, and aeronautics. This report is an initial effort to utilize performance measures for transportation system planning. The selected measures provide a cross-section of system performance indicators across three selected transportation planning goals (safety, efficiency, and quality of life) and five transportation modes (highways/bridges, public transit, railroads, aviation, and pedestrian/bicycle). These performance measures are exploratory in nature, and constitute a first attempt to apply performance measures in the context of a statewide, multimodal transportation plan from the Iowa DOT. As such, the set of performance measures that the Iowa DOT uses for planning will change over time as more is learned about the application of such measures. The performance measures explained in this document were developed through consultation with Iowa DOT modal staff (aviation, railroads, highways, public transportation, and pedestrian/bicycle) and the Office of Traffic and Safety. In addition, faculty and staff at the Iowa State University Center for Transportation Research and Education were consulted about performance measurement and data within their areas of expertise.

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The Mechanistic-Empirical Pavement Design Guide (MEPDG) was developed under National Cooperative Highway Research Program (NCHRP) Project 1-37A as a novel mechanistic-empirical procedure for the analysis and design of pavements. The MEPDG was subsequently supported by AASHTO’s DARWin-ME and most recently marketed as AASHTOWare Pavement ME Design software as of February 2013. Although the core design process and computational engine have remained the same over the years, some enhancements to the pavement performance prediction models have been implemented along with other documented changes as the MEPDG transitioned to AASHTOWare Pavement ME Design software. Preliminary studies were carried out to determine possible differences between AASHTOWare Pavement ME Design, MEPDG (version 1.1), and DARWin-ME (version 1.1) performance predictions for new jointed plain concrete pavement (JPCP), new hot mix asphalt (HMA), and HMA over JPCP systems. Differences were indeed observed between the pavement performance predictions produced by these different software versions. Further investigation was needed to verify these differences and to evaluate whether identified local calibration factors from the latest MEPDG (version 1.1) were acceptable for use with the latest version (version 2.1.24) of AASHTOWare Pavement ME Design at the time this research was conducted. Therefore, the primary objective of this research was to examine AASHTOWare Pavement ME Design performance predictions using previously identified MEPDG calibration factors (through InTrans Project 11-401) and, if needed, refine the local calibration coefficients of AASHTOWare Pavement ME Design pavement performance predictions for Iowa pavement systems using linear and nonlinear optimization procedures. A total of 130 representative sections across Iowa consisting of JPCP, new HMA, and HMA over JPCP sections were used. The local calibration results of AASHTOWare Pavement ME Design are presented and compared with national and locally calibrated MEPDG models.