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Ronald S. Harichandran - One of the best experts on this subject based on the ideXlab platform.
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impact of systematic Axle Load measurement error on pavement design using mechanistic empirical pavement design guide
Journal of Transportation Engineering-asce, 2012Co-Authors: Syed Waqar Haider, Ronald S. Harichandran, Monther B. DwaikatAbstract:In traffic characterization, Axle Load spectra (ALS) are one of the most critical inputs in the new Mechanistic-Empirical Pavement Design Guide (MEPDG). Axle Load spectra have a significant effect on predicted pavement performance and, thus, the design life. Typically, Axle Load spectra as measured by weigh-in-motion (WIM) systems are assumed to have adequate data quality and accuracy. In fact, the quality of WIM-based data has inherent uncertainties attributable to inaccuracy and systematic bias. Whereas WIM data accuracy depends on the sensor technology, calibration errors and drift over time may introduce a systematic bias. This technical note investigates the effect of Axle Load measurement bias on pavement design for flexible and rigid pavements. The results show that negative bias in Axle Load measurements significantly affects cracking performance for both pavement types. The bias is more critical for rigid pavements with thinner slabs. Therefore, a measurement bias limit of less than ±5% should be...
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Allowable Systematic Axle Load Measurement Error for Pavement Design
2011Co-Authors: Syed Waqar Haider, Ronald S. Harichandran, Monther B. DwaikatAbstract:In traffic characterization, Axle Load spectra (ALS) are one of the most critical inputs in the new Mechanistic-Empirical Pavement Design Guide (M-E PDG). Axle Load spectra have a significant impact on the predicted pavement performance and thus the design lives. At the design stage, it is typically assumed that Axle Load spectra as measured by weigh-in-motion (WIM) systems have adequate data quality and accuracy. In fact, the quality of WIM-based data has inherent uncertainties due to inaccuracy and systematic bias. While WIM data accuracy depends on the sensor technology, calibration errors and drift over time may introduce a systematic bias. The paper investigates the effect of Axle Load measurement bias on pavement design for flexible and rigid pavements. The results of the study show that cracking performance for both pavement types is significantly affected by negative bias in Axle Load measurements. This impact of measurement bias is more critical for rigid pavements with thinner slabs. Therefore, a measurement bias limit of less than 5% in either direction should be enforced in order to ensure that both flexible and rigid pavements have the adequate design reliability against cracking. It is strongly recommended that WIM scales be calibrated periodically to prevent a high negative bias.
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effect of Axle Load measurement errors on pavement performance and design reliability
Transportation Research Record, 2010Co-Authors: Syed Waqar Haider, Ronald S. Harichandran, Monther B. DwaikatAbstract:In traffic characterization, Axle Load spectra (ALS) are one of the most critical inputs in the new Mechanistic-Empirical Pavement Design Guide (MEPDG). ALS have a significant impact on the predicted pavement performance. At the design stage, it is typically assumed that ALS as measured by weigh-in-motion (WIM) systems have adequate data quality and accuracy. In fact, the quality of WIM-based data has inherent uncertainties because of inaccuracy and systematic bias. While WIM data accuracy depends on the sensor technology, calibration errors and drift over time may introduce a systematic bias. Several studies have investigated the impact of traffic data collection technologies, data coverage, accuracy, and calibration errors on pavement Loading and performance prediction. However, these studies were limited to a few distress measures and did not address design reliability aspects as considered in the MEPDG. This study investigated the impact of probable WIM errors on the ALS and quantified the effects of ...
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Effect of Axle Load Spectrum Characteristics on Flexible Pavement Performance
Transportation Research Record, 2009Co-Authors: Syed Waqar Haider, Ronald S. HarichandranAbstract:The Mechanistic-Empirical Pavement Design Guide (MEPDG) uses performance models to predict cracking and rutting in flexible pavements. A unique mechanism controls the initiation and accumulation of each distress, but each mechanism can have several causes. Axle repetitions and Loads are the main causes of all Load-related distress types. MEPDG incorporates Axle Load spectra to characterize Axle Loading for a site and uses them to calculate pavement response and damage accumulation. These Load distributions have a bimodal shape, and a mixture of two continuous distributions can be used to model them. In this paper, closed-form solutions are developed to estimate the characteristics of a mixture of bimodal Axle Load distributions. The observed Axle Load spectra from 14 sites in different states were used to relate Load distribution characteristics to predicted flexible pavement performance. The overall mean and other characteristics of a bimodal Axle Load distribution explained the variations in expected fl...
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Correlation between Properties of Axle Load Distribution and RigidPavement Performance Measures
2008Co-Authors: Syed Waqar Haider, Ronald S. HarichandranAbstract:The new Mechanistic-Empirical Pavement Design Guide (M-E PDG) utilizes Axle Load spectra to characterize the unique traffic Loadings for a site. These Loading characteristics are employed to calculate pavement response and for subsequent damage computations. Generally, these Axle Load distributions exhibit a bimodal shape and a mixture of two continuous distributions can be used to model them. In this paper, closed-form solutions are developed to estimate the characteristics of a mixture bimodal Axle Load distribution. The observed Axle Load spectra from eleven sites in different states were used to relate Load distribution characteristics with predicted rigid pavement performance. Cracking performance was related to the 85th percentile Load, faulting was found to be strongly related to the overall mean, and roughness (IRI) was strongly associated with the root of the 4th moment of the Axle Load spectra, respectively. These findings imply that cracking in rigid pavements is mainly caused by the highest 15 percent of Loads while faulting is mostly caused by the overall average Loads in an Axle Load distribution. The overall Loads, along with higher contributions from the heavier Loads, seem to cause higher roughness in rigid pavements. In addition, the relationships developed for different performance measures can directly indicate the relative pavement damage caused by Axle distributions.
Syed Waqar Haider - One of the best experts on this subject based on the ideXlab platform.
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impact of systematic Axle Load measurement error on pavement design using mechanistic empirical pavement design guide
Journal of Transportation Engineering-asce, 2012Co-Authors: Syed Waqar Haider, Ronald S. Harichandran, Monther B. DwaikatAbstract:In traffic characterization, Axle Load spectra (ALS) are one of the most critical inputs in the new Mechanistic-Empirical Pavement Design Guide (MEPDG). Axle Load spectra have a significant effect on predicted pavement performance and, thus, the design life. Typically, Axle Load spectra as measured by weigh-in-motion (WIM) systems are assumed to have adequate data quality and accuracy. In fact, the quality of WIM-based data has inherent uncertainties attributable to inaccuracy and systematic bias. Whereas WIM data accuracy depends on the sensor technology, calibration errors and drift over time may introduce a systematic bias. This technical note investigates the effect of Axle Load measurement bias on pavement design for flexible and rigid pavements. The results show that negative bias in Axle Load measurements significantly affects cracking performance for both pavement types. The bias is more critical for rigid pavements with thinner slabs. Therefore, a measurement bias limit of less than ±5% should be...
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Allowable Systematic Axle Load Measurement Error for Pavement Design
2011Co-Authors: Syed Waqar Haider, Ronald S. Harichandran, Monther B. DwaikatAbstract:In traffic characterization, Axle Load spectra (ALS) are one of the most critical inputs in the new Mechanistic-Empirical Pavement Design Guide (M-E PDG). Axle Load spectra have a significant impact on the predicted pavement performance and thus the design lives. At the design stage, it is typically assumed that Axle Load spectra as measured by weigh-in-motion (WIM) systems have adequate data quality and accuracy. In fact, the quality of WIM-based data has inherent uncertainties due to inaccuracy and systematic bias. While WIM data accuracy depends on the sensor technology, calibration errors and drift over time may introduce a systematic bias. The paper investigates the effect of Axle Load measurement bias on pavement design for flexible and rigid pavements. The results of the study show that cracking performance for both pavement types is significantly affected by negative bias in Axle Load measurements. This impact of measurement bias is more critical for rigid pavements with thinner slabs. Therefore, a measurement bias limit of less than 5% in either direction should be enforced in order to ensure that both flexible and rigid pavements have the adequate design reliability against cracking. It is strongly recommended that WIM scales be calibrated periodically to prevent a high negative bias.
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effect of Axle Load measurement errors on pavement performance and design reliability
Transportation Research Record, 2010Co-Authors: Syed Waqar Haider, Ronald S. Harichandran, Monther B. DwaikatAbstract:In traffic characterization, Axle Load spectra (ALS) are one of the most critical inputs in the new Mechanistic-Empirical Pavement Design Guide (MEPDG). ALS have a significant impact on the predicted pavement performance. At the design stage, it is typically assumed that ALS as measured by weigh-in-motion (WIM) systems have adequate data quality and accuracy. In fact, the quality of WIM-based data has inherent uncertainties because of inaccuracy and systematic bias. While WIM data accuracy depends on the sensor technology, calibration errors and drift over time may introduce a systematic bias. Several studies have investigated the impact of traffic data collection technologies, data coverage, accuracy, and calibration errors on pavement Loading and performance prediction. However, these studies were limited to a few distress measures and did not address design reliability aspects as considered in the MEPDG. This study investigated the impact of probable WIM errors on the ALS and quantified the effects of ...
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Effect of Axle Load Spectrum Characteristics on Flexible Pavement Performance
Transportation Research Record, 2009Co-Authors: Syed Waqar Haider, Ronald S. HarichandranAbstract:The Mechanistic-Empirical Pavement Design Guide (MEPDG) uses performance models to predict cracking and rutting in flexible pavements. A unique mechanism controls the initiation and accumulation of each distress, but each mechanism can have several causes. Axle repetitions and Loads are the main causes of all Load-related distress types. MEPDG incorporates Axle Load spectra to characterize Axle Loading for a site and uses them to calculate pavement response and damage accumulation. These Load distributions have a bimodal shape, and a mixture of two continuous distributions can be used to model them. In this paper, closed-form solutions are developed to estimate the characteristics of a mixture of bimodal Axle Load distributions. The observed Axle Load spectra from 14 sites in different states were used to relate Load distribution characteristics to predicted flexible pavement performance. The overall mean and other characteristics of a bimodal Axle Load distribution explained the variations in expected fl...
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Correlation between Properties of Axle Load Distribution and RigidPavement Performance Measures
2008Co-Authors: Syed Waqar Haider, Ronald S. HarichandranAbstract:The new Mechanistic-Empirical Pavement Design Guide (M-E PDG) utilizes Axle Load spectra to characterize the unique traffic Loadings for a site. These Loading characteristics are employed to calculate pavement response and for subsequent damage computations. Generally, these Axle Load distributions exhibit a bimodal shape and a mixture of two continuous distributions can be used to model them. In this paper, closed-form solutions are developed to estimate the characteristics of a mixture bimodal Axle Load distribution. The observed Axle Load spectra from eleven sites in different states were used to relate Load distribution characteristics with predicted rigid pavement performance. Cracking performance was related to the 85th percentile Load, faulting was found to be strongly related to the overall mean, and roughness (IRI) was strongly associated with the root of the 4th moment of the Axle Load spectra, respectively. These findings imply that cracking in rigid pavements is mainly caused by the highest 15 percent of Loads while faulting is mostly caused by the overall average Loads in an Axle Load distribution. The overall Loads, along with higher contributions from the heavier Loads, seem to cause higher roughness in rigid pavements. In addition, the relationships developed for different performance measures can directly indicate the relative pavement damage caused by Axle distributions.
Rattan Lal - One of the best experts on this subject based on the ideXlab platform.
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Axle Load impacts on hydraulic properties and corn yield in no till clay and silt loam
Agronomy Journal, 2008Co-Authors: Humberto Blancocanqui, Rattan LalAbstract:Wheel traffic-induced compaction in no-till (NT) farming can alter soil hydraulic properties and reduce crop yields, but specific information on the impacts of different levels of Axle Loads on the relationships between soil hydraulic properties and crop yields under long-term NT systems is limited. Thus, this study set out to measure the differences in soil hydraulic properties including earthworm (Lumbricus terrestris) population and assess their relationships with corn (Zea mays L.) grain and stover yield in NT silt loam and clay loam in Ohio receiving three levels of Axle Loads for 20 yr. Imposition of three Axle Load treatments including control, 10 Mg, and 20 Mg affected water infiltration rates but not bulk density ( p b ), saturated hydraulic conductivity (K sat ), soil water retention (SWR), plant available water (PAW), and pore-size distribution in both soils. Imposition of Axle Loads reduced cumulative water infiltration by 6- to 20-fold in the silt loam and by about sixfold in the clay loam. It decreased sorptivity by 10-fold and steady state infiltration by fivefold. The reduction in water infiltration was related to the reductions in earthworm population. Application of 20 Mg Axle Load reduced earthworm numbers by 50% in the silt loam and by 70% in the clay loam. There were no significant differences in water infiltration parameters and earthworm population between 10 and 20 Mg Axle Loads. Application of Axle Loads reduced grain yield by 13% and stover yield by 23% on the clay loam but not on the silt loam. It reduced both grain and stover yields by 1.2 Mg ha -1 . Cumulative infiltration explained 58% of the variability in grain yield and 53% in stover yield in the clay loam. Overall, Axle Load-induced significant changes in water infiltration and earthworm population but changes in crop yields were soil specific.
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Axle Load and tillage effects on crop yield for two soils in central Ohio
Soil & Tillage Research, 2000Co-Authors: Rattan Lal, M AhmadiAbstract:Abstract A Load of 5–20 Mg on a single Axle cart is a common practice for spreading manure and harvesting grains in the US Corn Belt. Yet, effects of such a Load used for a long time of 5–10 years on crop yield are not known for predominant soils of the region. Further, Axle Load effects on crop yield may depend on tillage methods. Thus, effects of Axle Load and tillage methods on corn ( Zea mays L.) grain yield were studied for Wooster silt loam an Orthic Luvisol (at Wooster) and Crosby silt loam a Gleyic Luvisol (at South Charleston) in Ohio. Experiments were conducted for 11 consecutive growing seasons (1988 through 1998) at Wooster and 6 seasons (1991–1994, 1997–1998) at South Charleston. Three Axle Load treatments at Wooster consisted of: (1) regular machine traffic (RMT), (2) 7.5 Mg Axle Load as guided or controlled traffic (CT), and (3) 7.5 Mg Axle Load covering the entire plot (CEP). There were three tillage methods at Wooster: (1) no till (NT), (2) chisel plowing (CP), and (3) moldboard plowing (MP). Three Axle Load treatments at South Charleston were: (1) control, (2) 10 Mg Axle Load, and (3) 20 Mg Axle Load. Two tillage methods used at South Charleston were NT and MP. There were no significant differences in soil bulk density and penetration resistance of Wooster silt loam soil measured after 11 seasons of harvest traffic. Harvest traffic treatments at Wooster significantly affected corn grain yield only in 1988 and 1998, for 2 out of 11 seasons. In 1988, corn grain yield was reduced by 14% by 7.5 Mg Axle Load treatments. In 1998, the reduction in grain yield was 5% by the CT and 15% by the CEP Axle Load treatments. Mean corn grain yield for 11 years was 6.6 Mg ha −1 for RMT, 6.3 Mg ha −1 for 7.5 Mg Axle Load with CT (reduction of 5%), and 6.0 Mg ha −1 for 7.5 Mg Axle Load with CEP (reduction of 9%). The mean grain yield reduction for the 11-year period for the CEP treatment was 10%. There were no consistent trends in grain yield from year to year with regard to tillage methods. The CP treatment out-yielded the other tillage treatments in 4 out of 11 years. Mean corn grain yield in CP was 7% more than that of NT and 13% more than that of MP. Neither Axle Load nor tillage treatment had any effect on corn grain yield at South Charleston, and mean corn grain yield was 7.5 Mg ha −1 for control, 7.6 Mg ha −1 for 10 Mg Axle Load, and 7.3 Mg ha −1 for 20 Mg Axle Load. The mean corn grain yield was 7.0 Mg ha −1 for NT and 7.8 Mg ha −1 for MP treatment.
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Axle Load and tillage effects on the shrinkage characteristics of a Mollic Ochraqualf in northwest Ohio
Soil & Tillage Research, 1999Co-Authors: M.d Flowers, Rattan LalAbstract:Abstract Cracking due to soil shrinkage is a complex process whose effect on soil properties, crop growth and water quality are not adequately understood. The intensity of cracking depends on soil characteristics and management. The effect of three Axle Loads and three tillage methods on shrinkage characteristics and cracking behavior were studied for a heavy-textured lake bed soil in northwest Ohio. The three Axle Load treatments were 0, 10 and 20 Mg, and the three tillage treatments were no till (NT), chisel plowing (CP) and moldboard plowing (MP). Cracking area increased from 1.75% in July to 12.27% in September, was maximum in the NT treatment, and increased with increase in Axle Load. The no till and 30 Mg Axle Load caused significantly higher cracking than other Axle Load and tillage treatment combinations. Shrinkage of compressed soil cores under laboratory conditions showed that a bulk density of 1.5 Mg/m 3 had the lowest total shrinkage volume. A combination of no till and heavy Axle Load increased the cracking area and accentuated adverse effects on soil structure.
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Axle Load and tillage effects on crop yields on a Mollic Ochraqualf in Northwest Ohio
Soil and Tillage Research, 1996Co-Authors: Rattan LalAbstract:Effects of Axle Load and tillage methods were studied for four crops grown on a clayey soil in the lake-bed region of northwestern Ohio for 7 consecutive years from 1988 to 1994. Three tillage methods were no-till (NT), chisel plough (CP) and mouldboard ploughing (MP). Split-plot Axle Load treatments were control, 10 Mg Axle Load and 20 Mg Axle laod. Axle laod was created using a single Axle grain cart either half full (10 Mg) or full (20 Mg). Maize (Zea mays), soybeans (Glycine max), oats (Avena sativa), and sugarbeet (Beta vulgaris) were grown in 3-year or 2-year rotation sequences. Axle Load treatments had a significant effect on crop yield. Considering average yield for the 3-year rotation over all tillage treatments and 7 seasons, mean maize yield was 7.2 Mg ha−1 for control, 6.0 Mg ha−1 for 10 Mg Axle Load, and 5.4 Mg ha−1 for 20 Mg Axle Load. Mean maize yield in 2-year rotation was 7.1 Mg ha−1 for control, 6.1 Mg ha−1 for 10 Mg Axle Load, and 5.4 Mg ha−1 for 20 Mg Axle Load. Soybean grain yield in the 3-year rotation was 2.4 Mg ha−1 for control, 2.2 Mg ha−1 for 10 Mg Axle Load, and 1.9 Mg ha−1 for 20 Mg Axle Load. Mean soybean grain yield for the 2-year rotation was 2.6 Mg ha−1 for control, 2.0 Mg ha−1 for 10 Mg Axle Load, and 1.6 Mg ha−1 for 20 Mg Axle Load. Mean oat grain yield, based on the average of all tillage treatments over the 7 seasons, was 2.6 Mg ha−1 for control, 2.1 Mg ha−1 for 10 Mg Axle Load, and 1.8 Mg ha−1 for 20 Mg Axle Load. Crop yield was also affected by the tillage treatments. Mean maize grain yield was 5.8 Mg ha−1 for NT, 6.5 Mg ha−1 for CP, and 6.3 Mg ha−1 for MP in the 3-year rotation compared with 6.4 Mg ha−1 for NT, 6.0 Mg ha−1 for CP, and 6.1 Mg ha−1 for MP method in the 2-year rotation. The average soybean yield in 3-year rotation was 2.1 Mg ha−1 for NT, 2.1 Mg ha−1 for CP, and 2.2 Mg ha−1 for MP methods. Mean oat grain yield was 2.3 Mg ha−1 for NT, 2.3 Mg ha−1 for CP, and 2.0 Mg ha−1 for MP method. Tillage methods had no significant effect on sugarbeet yield, which was 10.8 Mg ha−1 for NT, 16.0 Mg ha−1 for CP, and 14.0 Mg ha−1 for MP methods.
Kevin D Hall - One of the best experts on this subject based on the ideXlab platform.
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development and influence of statewide Axle Load spectra on flexible pavement performance
Transportation Research Record, 2007Co-Authors: Nam H Tran, Kevin D HallAbstract:The Mechanistic—Empirical Pavement Design Guide (MEPDG) developed under NCHRP Project 1-37A requires new inputs for traffic characterization. One important traffic input is Axle Load distribution factors, or Axle Load spectra. These spectra represent the percentage of the total Axle applications within each Load interval for single, tandem, tridem, and quad Axles. The Arkansas State Highway and Transportation Department sponsored research to develop statewide Axle Load spectra and evaluate the significance of the developed inputs in the MEPDG. Of 25 weigh-in-motion sites selected for this study, only 10 stations provided good weight data for development of statewide Axle Load spectra. On the basis of the available weight data, statewide Axle Load spectra for single, tandem, and tridem Axles were developed. However, the data contained few quad Axles; therefore, statewide quad-Axle Load spectra were not generated. A sensitivity analysis related to the Axle Load spectra showed a significant difference in pre...
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Evaluation of Weigh-in-Motion Data for Developing Axle Load Distribution Factors for Mechanistic-Empirical Pavement Design Guide
2007Co-Authors: Nam H Tran, Kevin D HallAbstract:Axle Load spectra are essential to structural pavement design using the new Mechanistic-Empirical Pavement Design Guide (MEPDG) developed under National Cooperative Highway Research Program (NCHRP) Project 1-37A. The Axle Load spectra can only be determined from traffic data collected at weigh-in-motion (WIM) stations. Studies have shown that traffic data collected at WIM sites, especially for those using temperature-dependent piezoelectric sensors, often have errors. Thus, quality control checks should be performed on the WIM data which are used for developing the design inputs. This paper presents the results of an extensive quality control evaluation of traffic data collected at 25 WIM sites selected for the development of statewide Axle Load spectra in Arkansas. The data were evaluated using the quality control procedure recommended by the Long Term Pavement Performance (LTPP) program. In addition, the influence of the WIM data accuracy on predicted pavement performance was also evaluated using the MEPDG software. Among the 25 sites, only ten stations provided WIM data suitable for the development of statewide Axle Load spectra in the MEPDG. Pavement performance predictions provided by the MEPDG software were found to be sensitive to underestimated and overestimated WIM data. The effect of misestimated WIM data can be minimized if the data meet the quality requirements specified by the LTPP.
Inge Hakansson - One of the best experts on this subject based on the ideXlab platform.
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subsoil compaction by vehicles with high Axle Load extent persistence and crop response
Soil & Tillage Research, 1994Co-Authors: Inge Hakansson, Randall C ReederAbstract:Abstract Extent and persistence of soil and crop responses to subsoil compaction caused by vehicles with high Axle Loads are reviewed and methods to protect the subsoil from permanent deterioration are discussed. Traffic by vehicles with high Axle Loads on soils with high moisture contents generally causes deep subsoil compaction. At an Axle Load of 10 Mg, compaction typically penetrates to a depth of 50 cm. With still higher Loads, compaction to a depth of 1 m has been reported. Subsoil compaction is very persistent. At depths of more than 40 cm it is virtually permanent even in clay soils in regions with annual freezing. Deep subsoil compaction also causes persistent and possibly permanent reductions of crop yields. Complete amelioration by mechanical loosening is usually impossible and definitely expensive. From a soil productivity point of view, limits for mechanical stresses in the subsoil are needed. These may have the form of Axle Load limits for the vehicles or a combination of limits for the Axle Load and for some other important factors, such as the ground contact pressure of the running gear or the per cent water saturation of the soil at the time of trafficking. Guidelines for such limits should preferably be worked out in an international joint effort.
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swedish experiments on the persistence of subsoil compaction caused by vehicles with high Axle Load
Soil & Tillage Research, 1994Co-Authors: Ararso Etana, Inge HakanssonAbstract:Abstract Final results from nine Swedish field experiments on soil and crop response to traffic by vehicles with an Axle Load of 10 Mg are reported. The traffic significantly compacted the soils to a depth of 50–60 cm. Eleven years later, virtually no alleviation of the compaction effects in the subsoil was observed, and crop yields were still affected in spite of normal annual freezing to a depth of 40–70 cm.