Recently, highway agencies have become in need to enhance their pavement management systems (PMSs... more Recently, highway agencies have become in need to enhance their pavement management systems (PMSs) using sound engineering and economic principles that find more prudent solutions to support wise investment choices and preserve the value of infrastructure assets. As pavement performance prediction models are one of the most important and fundamental components in any PMS, this paper focuses on comparing the master sigmoidal curve-based model as a deterministic technique with the Markov chain-based model as a probabilistic technique for the prediction of the international roughness index (IRI) as a pavement performance indicator. The IRI data obtained from the long-term pavement performance (LTPP) program were used to evaluate and compare both methods. In this paper, 44 flexible pavement sections from the GPS-1 experiment incorporating 432 IRI measurements ranging from 0.32 to 5.12 m/km were selected. Results showed that the predictive ability of the investigated models for the selected LTPP data was good with a reasonable coincidence ratio of about 65 percent between the predicted results of the two modeling techniques.
California bearing ratio (CBR) is an important property used to express the quality and strength ... more California bearing ratio (CBR) is an important property used to express the quality and strength of the unbound granular materials and subgrade soils. It is one of the material inputs for the American Association State Highway Transportation Officials 1993 guide, and the Mechanistic Empirical Pavement Design Guide for the structural design of flexible pavements in case of the resilient modulus is not known. CBR is also conducted on the unbound materials for the quality control/quality assurance during construction. Because of its importance, this paper presents an attempt to develop simple and reliable CBR models based on routine material properties such as gradation, Atterberg limits and compaction properties using regression analysis (RA) and artificial neural networks (ANNs). Database of 207 CBR values was collected from the quality control reports prepared at the Highway and Airport Engineering Laboratory, Mansoura University. The collected CBR values were found to range between 26 and 98%. About 80% of the collected data were used for model development, while the remaining 20% were used for model validation in addition to 11 laboratory tested specimens. The developed model by RA and ANNs correlates CBR values with maximum dry density and diameter at 60% passing (D60). The prediction accuracy in terms of coefficient of determination ($${R}^{2}$$R2) for the developed CBR model by both techniques was excellent, and the validation of the suggested model was satisfactory.
International Journal of Pavement Engineering, 2018
ABSTRACT This paper focused on predicting the performance of asphalt mixes modified with nano-mon... more ABSTRACT This paper focused on predicting the performance of asphalt mixes modified with nano-montmorillonite (NMMT) and nano silicon dioxide (NSD) using the Quality-Related Specifications Software (QRSS), which is a simplification to the Pavement ME Design. The nanomaterials were thoroughly mixed with the binder at a temperature of 145 ± 5°C. The conventional and the rheological properties were determined for the penetration grade 60–70 control binder as well as binders modified by 3, 5 and 7% of NMMT and NSD by the weight of asphalt. The optimum nanomaterial content was found for each modifier and was then used for preparing asphalt mixtures by the conventional Marshall method. Finally, Witczak 1-40D complex shear modulus (G*) based predictive model was used to estimate the dynamic modulus (E*) for the control and nanomodified asphalt mixtures. The field performance in terms of asphalt concrete (AC) layer rutting and fatigue cracking was predicted using the QRSS software for two typical pavement sections and three different climatic locations in Egypt (Alexandria, Cairo and Aswan). The simulation runs revealed that both nanomodified asphalt mixtures exhibited superior pavement performance in terms of AC rutting compared to the control mix without a significant effect on fatigue life.
This paper presents the results and analysis of permanent strain testing from Repeated Load Triax... more This paper presents the results and analysis of permanent strain testing from Repeated Load Triaxial Testing (RLTT) conducted on three base products; two crushed concrete or Recycled Concrete Aggregate (RC A) materials and a local Virgin Aggregate (VA). The objective of testing was to study the impact of change in stresses on permanent deformation of the investigated materials using three different permanent strain testing protocols from Australian and New Zealand road authorities. A series of permanent strain tests were performed under drained conditions on cylindrical specimens, which had been statically compacted at different levels of moisture content. Duplicate specimens were tested at 60, 80 and 90% of Optimum Moisture Content (OMC) and a dry density ratio of 98% of Maximum Dry Density (MDD) from Modified Proctor compaction testing. On-sample measurements were made of sample deformation. Permanent strain was found to be dependent on both moisture content and applied stress. In terms of accumulative permanent strain or the rate of permanent strain, it was found that the two RC A products performed better than the VA for the three permanent strain testing approaches.
Recently, highway agencies have become in need to enhance their pavement management systems (PMSs... more Recently, highway agencies have become in need to enhance their pavement management systems (PMSs) using sound engineering and economic principles that find more prudent solutions to support wise investment choices and preserve the value of infrastructure assets. As pavement performance prediction models are one of the most important and fundamental components in any PMS, this paper focuses on comparing the master sigmoidal curve-based model as a deterministic technique with the Markov chain-based model as a probabilistic technique for the prediction of the international roughness index (IRI) as a pavement performance indicator. The IRI data obtained from the long-term pavement performance (LTPP) program were used to evaluate and compare both methods. In this paper, 44 flexible pavement sections from the GPS-1 experiment incorporating 432 IRI measurements ranging from 0.32 to 5.12 m/km were selected. Results showed that the predictive ability of the investigated models for the selected LTPP data was good with a reasonable coincidence ratio of about 65 percent between the predicted results of the two modeling techniques.
California bearing ratio (CBR) is an important property used to express the quality and strength ... more California bearing ratio (CBR) is an important property used to express the quality and strength of the unbound granular materials and subgrade soils. It is one of the material inputs for the American Association State Highway Transportation Officials 1993 guide, and the Mechanistic Empirical Pavement Design Guide for the structural design of flexible pavements in case of the resilient modulus is not known. CBR is also conducted on the unbound materials for the quality control/quality assurance during construction. Because of its importance, this paper presents an attempt to develop simple and reliable CBR models based on routine material properties such as gradation, Atterberg limits and compaction properties using regression analysis (RA) and artificial neural networks (ANNs). Database of 207 CBR values was collected from the quality control reports prepared at the Highway and Airport Engineering Laboratory, Mansoura University. The collected CBR values were found to range between 26 and 98%. About 80% of the collected data were used for model development, while the remaining 20% were used for model validation in addition to 11 laboratory tested specimens. The developed model by RA and ANNs correlates CBR values with maximum dry density and diameter at 60% passing (D60). The prediction accuracy in terms of coefficient of determination ($${R}^{2}$$R2) for the developed CBR model by both techniques was excellent, and the validation of the suggested model was satisfactory.
International Journal of Pavement Engineering, 2018
ABSTRACT This paper focused on predicting the performance of asphalt mixes modified with nano-mon... more ABSTRACT This paper focused on predicting the performance of asphalt mixes modified with nano-montmorillonite (NMMT) and nano silicon dioxide (NSD) using the Quality-Related Specifications Software (QRSS), which is a simplification to the Pavement ME Design. The nanomaterials were thoroughly mixed with the binder at a temperature of 145 ± 5°C. The conventional and the rheological properties were determined for the penetration grade 60–70 control binder as well as binders modified by 3, 5 and 7% of NMMT and NSD by the weight of asphalt. The optimum nanomaterial content was found for each modifier and was then used for preparing asphalt mixtures by the conventional Marshall method. Finally, Witczak 1-40D complex shear modulus (G*) based predictive model was used to estimate the dynamic modulus (E*) for the control and nanomodified asphalt mixtures. The field performance in terms of asphalt concrete (AC) layer rutting and fatigue cracking was predicted using the QRSS software for two typical pavement sections and three different climatic locations in Egypt (Alexandria, Cairo and Aswan). The simulation runs revealed that both nanomodified asphalt mixtures exhibited superior pavement performance in terms of AC rutting compared to the control mix without a significant effect on fatigue life.
This paper presents the results and analysis of permanent strain testing from Repeated Load Triax... more This paper presents the results and analysis of permanent strain testing from Repeated Load Triaxial Testing (RLTT) conducted on three base products; two crushed concrete or Recycled Concrete Aggregate (RC A) materials and a local Virgin Aggregate (VA). The objective of testing was to study the impact of change in stresses on permanent deformation of the investigated materials using three different permanent strain testing protocols from Australian and New Zealand road authorities. A series of permanent strain tests were performed under drained conditions on cylindrical specimens, which had been statically compacted at different levels of moisture content. Duplicate specimens were tested at 60, 80 and 90% of Optimum Moisture Content (OMC) and a dry density ratio of 98% of Maximum Dry Density (MDD) from Modified Proctor compaction testing. On-sample measurements were made of sample deformation. Permanent strain was found to be dependent on both moisture content and applied stress. In terms of accumulative permanent strain or the rate of permanent strain, it was found that the two RC A products performed better than the VA for the three permanent strain testing approaches.
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