The Experts below are selected from a list of 3348 Experts worldwide ranked by ideXlab platform
Henrique Borges Miranda - One of the best experts on this subject based on the ideXlab platform.
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influence of laboratory aggregate compaction method on the particle packing of stone mastic asphalt
Construction and Building Materials, 2020Co-Authors: Henrique Borges Miranda, Fatima Alexandra Batista, M L Antunes, Jose NevesAbstract:Abstract The type of aggregates and their packing characteristics under compaction are key factors for the design of asphalt mixtures with improved performance, namely, with respect to resistance to permanent deformation. A good example is Stone Mastic Asphalt (SMA), known by its stone–on–stone structure. In the U.S.A., the aggregate particles packing characteristics in a SMA, specially the stone–on–stone effect, are normally assessed using the “manually dry–rodded” method. However, this method may not be representative of field aggregate particle packing conditions, which may compromise the SMA performance. This article presents new findings regarding aggregate laboratory compaction methods to optimise the coarse aggregate structure in a SMA. Particle breakage, bulk density, air voids (compacted & uncompacted skeleton) in the aggregate / coarse aggregate were assessed for existing methods as well as for new methods using existing Compactors, but with different procedures and/or specific devices, e.g. Proctor hammer. The assessed methods were: (1) “non–compaction”; (2) “manually dry–rodded” method; (3) established Proctor compaction; (4) modified Proctor compaction (light and heavy compaction) and (5) steel roller compaction. The 2 latter “new methods” aimed at mechanically simulating the dry-rodded method and the effect of field Compactors, respectively. The results highlight that the new laboratory compaction methods developed with Proctor and steel roller Compactor, provide a particle packing that is more representative of the field conditions, comparatively to other aggregate compaction methods.
Jose Neves - One of the best experts on this subject based on the ideXlab platform.
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influence of laboratory aggregate compaction method on the particle packing of stone mastic asphalt
Construction and Building Materials, 2020Co-Authors: Henrique Borges Miranda, Fatima Alexandra Batista, M L Antunes, Jose NevesAbstract:Abstract The type of aggregates and their packing characteristics under compaction are key factors for the design of asphalt mixtures with improved performance, namely, with respect to resistance to permanent deformation. A good example is Stone Mastic Asphalt (SMA), known by its stone–on–stone structure. In the U.S.A., the aggregate particles packing characteristics in a SMA, specially the stone–on–stone effect, are normally assessed using the “manually dry–rodded” method. However, this method may not be representative of field aggregate particle packing conditions, which may compromise the SMA performance. This article presents new findings regarding aggregate laboratory compaction methods to optimise the coarse aggregate structure in a SMA. Particle breakage, bulk density, air voids (compacted & uncompacted skeleton) in the aggregate / coarse aggregate were assessed for existing methods as well as for new methods using existing Compactors, but with different procedures and/or specific devices, e.g. Proctor hammer. The assessed methods were: (1) “non–compaction”; (2) “manually dry–rodded” method; (3) established Proctor compaction; (4) modified Proctor compaction (light and heavy compaction) and (5) steel roller compaction. The 2 latter “new methods” aimed at mechanically simulating the dry-rodded method and the effect of field Compactors, respectively. The results highlight that the new laboratory compaction methods developed with Proctor and steel roller Compactor, provide a particle packing that is more representative of the field conditions, comparatively to other aggregate compaction methods.
Thomas Harman - One of the best experts on this subject based on the ideXlab platform.
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Target and Tolerance Study for Angle of Gyration Used in Superpave Gyratory Compactor
Transportation Research Record, 2002Co-Authors: Ghazi Ai-khateeb, Chuck Paugh, Kevin D Stuart, Thomas Harman, John D'angeloAbstract:Five companies offer eight models of the Superpave® gyratory Compactor (SGC) in the United States. Each model uses a unique method of setting and inducing the specified angle of gyration. However, all angles are set externally relative to the mold and none of the manufacturer's calibration systems can be universally applied to all models. The specified external angle of gyration (α) is 1.25° FHWA, in partnership with Test Quip, Inc., developed a dynamic angle validation kit that measures the dynamic internal angle (DIA) of gyration during loading. The DIA accounts for equipment compliance issues, such as bending of the platens during compaction, which is not apparent when the angle is measured externally. Differences in specimen density produced by different Compactors have been attributed to differences in compliance. Thus, the SGC test method needs to be revised to obtain uniformity. However, it would be inappropriate to assign the external angle of 1.25° to the DIA because the internal angle is always ...
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quantifying laboratory compaction effects on the internal structure of asphalt concrete
Transportation Research Record, 1999Co-Authors: Eyad Masad, Balasingam Muhunthan, Naga Shashidhar, Thomas HarmanAbstract:The performance of asphalt concrete (AC) mixtures is influenced by its internal structure, which refers to the arrangement of aggregates and their associated air voids. Currently, most of the discussion on the effects of internal structure on AC performance is qualitative. This study proposes computer-automated image analysis procedures to quantify the internal structure of AC. Internal structure is quantified in terms of aggregate orientation, aggregate contacts, and air void distribution. The new procedures are useful tools to describe and compare AC materials produced by different compaction methods and mix designs. The new procedures are used to study the difference in internal structure of AC specimens compacted with the Superpave gyratory Compactor (SGC) and the linear kneading Compactor (LKC). Specimens compacted with the SGC were found to have aggregates with more preferred orientation and fewer contacts than specimens compacted with the LKC. In addition, SGC specimens were found to have more air ...
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evaluation of superpave gyratory Compactor in the field management of asphalt mixes four simulation studies
Transportation Research Record, 1995Co-Authors: Thomas Harman, John Dangelo, John R BukowskiAbstract:The SHRP-SUPERPAVE Design System utilizes the SUPERPAVE Gyratory Compactor (SGC) for asphalt-mixture specimen compaction. As part of the Demonstration Project Program, the Federal Highway Administration Office of Technology Applications (FHWA-OTA) has incorporated the SGC into FHWA-OTA mobile asphalt laboratories. Simulation studies are conducted for states to demonstrate aspects of the SUPERPAVE Design System, along with the application of certain innovative concepts in field management of asphalt mixes. The use of the SGC for field management is investigated. Four production mixes are evaluated. Based on production results, tolerance limits are established for SGC acceptance parameters. FHWA-OTA-recommended SGC volumetric acceptance parameters are asphalt binder content, voids in total mix, and voids in mineral aggregate. During the studies, companion samples were taken using the standard Marshall Compactor. Results indicate that the Marshall Compactor cannot be used as a surrogate for the SGC. The two compaction methods do not produce equivalent specimens.
A A Oloufa - One of the best experts on this subject based on the ideXlab platform.
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quality control of asphalt compaction using gps based system architecture
IEEE Robotics & Automation Magazine, 2002Co-Authors: A A OloufaAbstract:This paper describes research to develop a GPS-based automated quality control system for tracking pavement compaction. The research team has experimented with both vector and raster based algorithms and believe that the raster-based algorithm may be more efficient in this application. Simulated tests on CTS-111 have been extremely encouraging, and the team continues to improve the system for testing. After the tests are completed, the researchers are confident that this technology can be fitted in existing Compactors at a cost of about $10,000 per Compactor, including GPS devices, radios, hardware, and software.
Musharraf Zaman - One of the best experts on this subject based on the ideXlab platform.
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neural network based intelligent compaction analyzer for estimating compaction quality of hot asphalt mixes
Journal of Construction Engineering and Management-asce, 2011Co-Authors: Sesh Commuri, Musharraf ZamanAbstract:Continuous real-time estimating of compaction quality during the construction of a hot mix asphalt (HMA) pavement is addressed in this paper. The densification of asphalt pavements during construction usually is accomplished by using vibratory Compactors. During compaction, the Compactor and the asphalt mat form a coupled system whose dynamics are influenced by the changing stiffness of the mat. The measured vibrations of the Compactor along with process parameters such as lift thickness, mix type, mix temperature, and compaction pressure can be used to predict the asphalt mat density. Contrary to existing techniques in the literature in which a model is developed to fit experimental data and to predict mat density, a neural network-based approach is adopted that is model-free and uses pattern-recognition techniques to estimate density. The neural network is designed to read the entire frequency spectrum of roller vibrations and to classify these vibrations into different levels. The intelligent asphalt c...
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a novel neural network based asphalt compaction analyzer
International Journal of Pavement Engineering, 2008Co-Authors: Sesh Commuri, Musharraf ZamanAbstract:Achieving the desired density during field compaction of asphalt mixes is critical to meeting the design specifications of an asphalt pavement. Existing techniques measure the density of asphalt mixes at a discrete number of points. As such, the process is cumbersome, time consuming, and is not indicative of the overall compaction achieved unless large amounts of data is collected and analyzed. In this paper, the concept of a novel neural network-based asphalt compaction analyzer capable of predicting the density continuously, in real time, during the construction of the pavement is presented. The concept is verified using laboratory data from an asphalt vibratory Compactor (AVC). The compaction analyzer is based on the hypothesis that a vibratory Compactor and the hot mix asphalt (HMA) mat form a coupled system having unique vibration properties. The measured vibrations of the Compactor along with the process parameters such as lift thickness, mix type, mix temperature, and compaction pressure can be use...
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neural network based intelligent compaction analyzer for estimating compaction quality of hot asphalt mixes
IFAC Proceedings Volumes, 2008Co-Authors: Sesh Commuri, Musharraf ZamanAbstract:Abstract The development and validation of a tool that can estimate the level of compaction of a Hot Mix Asphalt (HMA) pavement during its construction is addressed in this paper. Densification of asphalt pavements during their construction is usually accomplished through the use of vibratory Compactors. During compaction, the Compactor and the asphalt mat form a coupled system whose dynamics are influenced by the changing stiffness of the mat. In this paper, it is shown that the measured vibrations of the Compactor along with the process parameters such as lift thickness, mix type, mix temperature, and compaction pressure can be used to predict the density of the asphalt mat. Contrary to existing techniques in the literature where a model is developed to fit the experimental data and to predict the density of the mat, a novel neural network based approach is adopted that is model-free and uses pattern-recognition techniques to estimate the density. During compaction of a HMA mat, the neural network then classifies the observed vibrations as those corresponding to a known level of compaction. The results also show that the analyzer can estimate the density continuously, and in real-time with accuracy levels adequate for quality control in the field. Using this tool, for the first time, the overall quality of construction of a HMA pavement can be verified thereby creating the potential to improve the quality of the roads.