11 resultados para CALIBRATION CURVE
em Iowa Publications Online (IPO) - State Library, State of Iowa (Iowa), United States
Resumo:
This report presents the results of a comparative laboratory study between well- and gap-graded aggregates used in asphalt concrete paving mixtures. A total of 424 batches of asphalt concrete mixtures and 3, 960 Marshall and Hveem specimens were examined. The main thrust of the statistical analysis conducted in this experiment was in the calibration study and in Part I of the experiment. In the former study, the compaction procedure between the Iowa State University Lab and the Iowa Highway Commission Lab was calibrated. By an analysis of the errors associated with the measurements we were able to separate the "preparation" and "determination" errors for both laboratories as well as develop the calibration curve which describes the relationship between the compaction procedures at the two labs. In Part I, the use of a fractional factorial design in a split plot experiment in measuring the effect of several factors on asphalt concrete strength and weight was exhibited. Also, the use of half normal plotting techniques for indicating significant factors and interactions and for estimating errors in experiments with only a limited number of observations was outlined,
Resumo:
A validation study has been performed using the Soil and Water Assessment Tool (SWAT) model with data collected for the Upper Maquoketa River Watershed (UMRW), which drains over 16,000 ha in northeast Iowa. This validation assessment builds on a previous study with nested modeling for the UMRW that required both the Agricultural Policy EXtender (APEX) model and SWAT. In the nested modeling approach, edge-offield flows and pollutant load estimates were generated for manure application fields with APEX and were then subsequently routed to the watershed outlet in SWAT, along with flows and pollutant loadings estimated for the rest of the watershed routed to the watershed outlet. In the current study, the entire UMRW cropland area was simulated in SWAT, which required translating the APEX subareas into SWAT hydrologic response units (HRUs). Calibration and validation of the SWAT output was performed by comparing predicted flow and NO3-N loadings with corresponding in-stream measurements at the watershed outlet from 1999 to 2001. Annual stream flows measured at the watershed outlet were greatly under-predicted when precipitation data collected within the watershed during the 1999-2001 period were used to drive SWAT. Selection of alternative climate data resulted in greatly improved average annual stream predictions, and also relatively strong r2 values of 0.73 and 0.72 for the predicted average monthly flows and NO3-N loads, respectively. The impact of alternative precipitation data shows that as average annual precipitation increases 19%, the relative change in average annual streamflow is about 55%. In summary, the results of this study show that SWAT can replicate measured trends for this watershed and that climate inputs are very important for validating SWAT and other water quality models.
Resumo:
This paper describes the application of the Soil and Water Assessment Tool (SWAT) model to the Maquoketa River watershed, located in northeast Iowa. The inputs to the model were obtained from the Environmental Protection Agency’s geographic information/database system called Better Assessment Science Integrating Point and Nonpoint Sources (BASINS). Climatic data from six weather stations located in and around the watershed, and measured streamflow data from a U.S. Geological Survey gage station at the watershed outlet were used in the sensitivity analysis of SWAT model parameters as well as its calibration and validation for watershed hydrology and streamflow. A sensitivity analysis was performed using an influence coefficient method to evaluate surface runoff and base flow variations in response to changes in model input hydrologic parameters. The curve number, evaporation compensation factor, and soil available water capacity were found to be the most sensitive parameters among eight selected parameters when applying SWAT to the Maquoketa River watershed. Model calibration, facilitated by the sensitivity analysis, was performed for the period 1988 through 1993, and validation was performed for 1982 through 1987. The model performance was evaluated by well-established statistical methods and was found to explain at least 86% and 69% of the variability in the measured stream flow data for the calibration and validation periods, respectively. This initial hydrologic modeling analysis will facilitate future applications of SWAT to the Maquoketa River watershed for various watershed analysis, including water quality.
Resumo:
This study aims to improve the accuracy of AASHTO Mechanistic-Empirical Pavement Design Guide (MEPDG) pavement performance predictions for Iowa pavement systems through local calibration of MEPDG prediction models. A total of 130 representative pavement sites across Iowa were selected. The selected pavement sites represent flexible, rigid, and composite pavement systems throughout Iowa. The required MEPDG inputs and the historical performance data for the selected sites were extracted from a variety of sources. The accuracy of the nationally-calibrated MEPDG prediction models for Iowa conditions was evaluated. The local calibration factors of MEPDG performance prediction models were identified to improve the accuracy of model predictions. The identified local calibration coefficients are presented with other significant findings and recommendations for use in MEPDG/DARWin-ME for Iowa pavement systems.
Resumo:
This study aims to improve the accuracy of AASHTO Mechanistic-Empirical Pavement Design Guide (MEPDG) pavement performance predictions for Iowa pavement systems through local calibration of MEPDG prediction models. A total of 130 representative pavement sites across Iowa were selected. The selected pavement sites represent flexible, rigid, and composite pavement systems throughout Iowa. The required MEPDG inputs and the historical performance data for the selected sites were extracted from a variety of sources. The accuracy of the nationally-calibrated MEPDG prediction models for Iowa conditions was evaluated. The local calibration factors of MEPDG performance prediction models were identified to improve the accuracy of model predictions. The identified local calibration coefficients are presented with other significant findings and recommendations for use in MEPDG/DARWin-ME for Iowa pavement systems.
Resumo:
Electronic distance measuring instruments (EDMI) are used by surveyors in routine length measurements. The constant and scale factors of the instrument tend to change due to usage, transportation, and aging of crystals. Calibration baselines are established to enable surveyors to check the instruments and determine any changes in the values of constant and scale factors. The National Geodetic Survey (NGS) has developed guidelines for establishing these baselines. In 1981 an EDMI baseline at ISU was established according to NGS guidelines. In October 1982, the NGS measured the distances between monuments. Computer programs for reducing observed distances were developed. Mathematical model and computer programs for determining constant and scale factors were developed. A method was developed to detect any movements of the monuments. Periodic measurements of the baseline were made. No significant movement of the monuments was detected.
Resumo:
The asphalt concrete (AC) dynamic modulus (|E*|) is a key design parameter in mechanistic-based pavement design methodologies such as the American Association of State Highway and Transportation Officials (AASHTO) MEPDG/Pavement-ME Design. The objective of this feasibility study was to develop frameworks for predicting the AC |E*| master curve from falling weight deflectometer (FWD) deflection-time history data collected by the Iowa Department of Transportation (Iowa DOT). A neural networks (NN) methodology was developed based on a synthetically generated viscoelastic forward solutions database to predict AC relaxation modulus (E(t)) master curve coefficients from FWD deflection-time history data. According to the theory of viscoelasticity, if AC relaxation modulus, E(t), is known, |E*| can be calculated (and vice versa) through numerical inter-conversion procedures. Several case studies focusing on full-depth AC pavements were conducted to isolate potential backcalculation issues that are only related to the modulus master curve of the AC layer. For the proof-of-concept demonstration, a comprehensive full-depth AC analysis was carried out through 10,000 batch simulations using a viscoelastic forward analysis program. Anomalies were detected in the comprehensive raw synthetic database and were eliminated through imposition of certain constraints involving the sigmoid master curve coefficients. The surrogate forward modeling results showed that NNs are able to predict deflection-time histories from E(t) master curve coefficients and other layer properties very well. The NN inverse modeling results demonstrated the potential of NNs to backcalculate the E(t) master curve coefficients from single-drop FWD deflection-time history data, although the current prediction accuracies are not sufficient to recommend these models for practical implementation. Considering the complex nature of the problem investigated with many uncertainties involved, including the possible presence of dynamics during FWD testing (related to the presence and depth of stiff layer, inertial and wave propagation effects, etc.), the limitations of current FWD technology (integration errors, truncation issues, etc.), and the need for a rapid and simplified approach for routine implementation, future research recommendations have been provided making a strong case for an expanded research study.
Resumo:
The Highway Safety Manual is the national safety manual that provides quantitative methods for analyzing highway safety. The HSM presents crash modification factors related to work zone characteristics such as work zone duration and length. These crash modification factors were based on high-impact work zones in California. Therefore there was a need to use work zone and safety data from the Midwest to calibrate these crash modification factors for use in the Midwest. Almost 11,000 Missouri freeway work zones were analyzed to derive a representative and stratified sample of 162 work zones. The 162 work zones was more than four times the number of work zones used in the HSM. This dataset was used for modeling and testing crash modification factors applicable to the Midwest. The dataset contained work zones ranging from 0.76 mile to 9.24 miles and with durations from 16 days to 590 days. A combined fatal/injury/non-injury model produced a R2 fit of 0.9079 and a prediction slope of 0.963. The resulting crash modification factors of 1.01 for duration and 0.58 for length were smaller than the values in the HSM. Two practical application examples illustrate the use of the crash modification factors for comparing alternate work zone setups.
Resumo:
Based on results of an evaluation performed during the winter of 1985-86, six Troxler 3241-B Asphalt Content Gauges were purchased for District use in monitoring project asphalt contents. Use of these gauges will help reduce the need for chemical based extractions. Effective use of the gauges depends on the accurate preparation and transfer of project mix calibrations from the Central Lab to the Districts. The objective of this project was to evaluate the precision and accuracy of a gauge in determining asphalt contents and to develop a mix calibration transfer procedure for implementation during the 1987 construction. The first part of the study was accomplished by preparing mix calibrations in the Central Lab gauge and taking multiple measurements of a sample with known asphalt content. The second part was accomplished by preparing transfer pans, obtaining count data on the pans using each gauge, and transferring calibrations from one gauge to another through the use of calibration transfer equations. The transferred calibrations were tested by measuring samples with a known asphalt content. The study established that the Troxler 3241-B Asphalt Content Gauge yields results of acceptable accuracy and precision as evidenced by a standard deviation of 0.04% asphalt content on multiple measurements of the same sample. The calibration transfer procedure proved feasible and resulted in the calibration transfer portion of Materials I.M. 335 - Method of Test For Determining the Asphalt Content of Bituminous Mixtures by the Nuclear Method.
Resumo:
In the previous study, moisture loss indices were developed based on the field measurements from one CIR-foam and one CIR-emulsion construction sites. To calibrate these moisture loss indices, additional CIR construction sites were monitored using embedded moisture and temperature sensors. In addition, to determine the optimum timing of an HMA overlay on the CIR layer, the potential of using the stiffness of CIR layer measured by geo-gauge instead of the moisture measurement by a nuclear gauge was explored. Based on the monitoring the moisture and stiffness from seven CIR project sites, the following conclusions are derived: 1. In some cases, the in-situ stiffness remained constant and, in other cases, despite some rainfalls, stiffness of the CIR layers steadily increased during the curing time. 2. The stiffness measured by geo-gauge was affected by a significant amount of rainfall. 3. The moisture indices developed for CIR sites can be used for predicting moisture level in a typical CIR project. The initial moisture content and temperature were the most significant factors in predicting the future moisture content in the CIR layer. 4. The stiffness of a CIR layer is an extremely useful tool for contractors to use for timing their HMA overlay. To determine the optimal timing of an HMA overlay, it is recommended that the moisture loss index should be used in conjunction with the stiffness of the CIR layer.
Resumo:
In urban areas, interchange spacing and the adequacy of design for weaving, merge, and diverge areas can significantly influence available capacity. Traffic microsimulation tools allow detailed analyses of these critical areas in complex locations that often yield results that differ from the generalized approach of the Highway Capacity Manual. In order to obtain valid results, various inputs should be calibrated to local conditions. This project investigated basic calibration factors for the simulation of traffic conditions within an urban freeway merge/diverge environment. By collecting and analyzing urban freeway traffic data from multiple sources, specific Iowa-based calibration factors for use in VISSIM were developed. In particular, a repeatable methodology for collecting standstill distance and headway/time gap data on urban freeways was applied to locations throughout the state of Iowa. This collection process relies on the manual processing of video for standstill distances and individual vehicle data from radar detectors to measure the headways/time gaps. By comparing the data collected from different locations, it was found that standstill distances vary by location and lead-follow vehicle types. Headways and time gaps were found to be consistent within the same driver population and across different driver populations when the conditions were similar. Both standstill distance and headway/time gap were found to follow fairly dispersed and skewed distributions. Therefore, it is recommended that microsimulation models be modified to include the option for standstill distance and headway/time gap to follow distributions as well as be set separately for different vehicle classes. In addition, for the driving behavior parameters that cannot be easily collected, a sensitivity analysis was conducted to examine the impact of these parameters on the capacity of the facility. The sensitivity analysis results can be used as a reference to manually adjust parameters to match the simulation results to the observed traffic conditions. A well-calibrated microsimulation model can enable a higher level of fidelity in modeling traffic behavior and serve to improve decision making in balancing need with investment.