Accelerated Pavement Testing for Rutting Evaluation of Hot-Mix Asphalt Overlay under High Tire Pressure

Ling, Jianming; Wei, Fulu; Chen, Hui; Zhao, Hongduo; Tian, Yu; Han, Bingye

doi:10.1061/jpeodx.0000157

Cited by 15 publications

(6 citation statements)

References 29 publications

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“…Therefore, monitoring the strain in the asphalt pavement structure is helpful to understand the structural condition of the pavement, explain the pavement failure mechanism, and formulate a reasonable maintenance plan [3][4][5]. At present, researchers are monitoring the dynamic mechanical response of pavement structures by embedding strain sensors in the asphalt layer [6][7][8][9]. In these efforts, the readings from the embedded strain sensors are usually considered error-free and no further calibration is required when using these readings.…”

Section: Introductionmentioning

confidence: 99%

Measurement accuracy evaluation and optimization of embedded strain sensor for asphalt mixture: laboratory tests and finite element simulation

Han,

Tang,

Liu

et al. 2024

Smart Mater. Struct.

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Due to the temperature sensitivity of asphalt mixtures, the synergistic deformation between embedded strain sensors and asphalt mixtures may be poor at certain temperatures, resulting in less accurate strain measurements. Therefore, the main purpose of this article is to consider the synergistic deformation between asphalt mixtures and embedded sensors and to provide guidance for the reasonable design of embedded strain sensors for asphalt pavements. Firstly, the finite element analysis and laboratory tests were used as the main approaches to analyze the main factors affecting the synergistic deformation between the embedded strain sensor and the asphalt mixture. Then, critical design requirements and optimization initiatives for embedded strain sensors dedicated to asphalt pavements were proposed. Finally, the optimal embedded strain sensors were further developed and the proposed design requirements were validated. The results show that the output of the sensor can be consistent with the deformation state of the asphalt mixture only if the equivalent modulus of the embedded strain sensor is the same as the modulus of the asphalt mixture. However, asphalt mixture modulus is susceptible to temperature, and it is difficult to keep the asphalt mixture modulus consistent with the sensor equivalent modulus at different ambient temperatures. Therefore, embedded strain sensors with low equivalent modulus and no encapsulated reinforcement are recommended to monitor the strain of asphalt pavement over a wide range of temperatures. The corresponding optimal embedded strain sensor was developed using low modulus polyimide as the elastic strain beam and silicone rubber as the flexible wrapping layer. The optimal embedded strain sensor has a maximum measurement error of only 4.5% over a wide temperature range. Overall, this article provides a reference for the accurate measurement of strain sensors for asphalt pavement.

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Section: Introductionmentioning

confidence: 99%

Measurement accuracy evaluation and optimization of embedded strain sensor for asphalt mixture: laboratory tests and finite element simulation

Han,

Tang,

Liu

et al. 2024

Smart Mater. Struct.

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show abstract

“…Evidently, the myriad of factors proposed for modelling pavement behaviour and performance predictions and for explaining deterioration varies among authors. See, for example, the factors to explain rutting proposed by Xu and Huang (2012), Gao et al (2009), Walker (2009), Huang et al (2009), Ling et al (2020), and Sybilski et al (2013). Such variance exists because it is difficult to determine which pavement layer contributes the most to surface deformations (Walker 2009).…”

Section: Introductionmentioning

confidence: 99%

Design, Construction, and In-Service Causes of Premature Pavement Deterioration: A Fuzzy Delphi Application

Milling

Martin

Mwasha

2023

J. Transp. Eng., Part B: Pavements

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Flexible pavements are prone to premature deterioration, and researchers are unresolved regarding the importance of the underlying causes resulting in inappropriately selected modelling parameters and increased uncertainty in predicting subsequent behaviour and performance. A windshield survey, literature survey, and fuzzy Delphi study are undertaken as complementary approaches to costly conventional investigations to identify reasons for flexible pavement deterioration in the design, construction and lifespan phases. Overall, the results revealed that the lifespan phase consists of the most contributors to pavement deterioration, which is approximately twice as much as the design and construction phases. However, the findings suggest that most causes of deterioration in the lifespan phase can be attributed to deficiencies in the preceding phases. Experts believe that structural and traffic are the most significant contributors to pavement deterioration, more so than construction, environment and maintenance factors. Additionally, the surface and subgrade layers were deemed to be the most problematic. Applying the Fuzzy Delphi method minimises the ambiguities associated with the causes of pavement deterioration identified in the literature and is advantageous for limited data. This study proposes measures for improving the design and construction of more sustainable tropical pavements. Improved knowledge of the causes of deterioration is vital for selecting the appropriate design, construction, and maintenance strategies.

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“…With the aggravating trend of China’s traffic toward the direction of “large flow, large-scale vehicles, heavy load, and overload” [ 1 ] and the frequent occurrence of extreme weather, early diseases of stone mastic asphalt (SMA) mixture pavement, such as rutting, cracks, and water damage, are becoming increasingly serious [ 2 – 4 ]. One reason for such a phenomenon is that the standard of 50 times Marshall double-compaction number is adopted for the mix proportion design of SMA mixture, which is evidently lagging behind the current traffic situation to prevent aggregate breakage due to excessive compaction number [ 5 ].…”

Section: Introductionmentioning

confidence: 99%

Laboratory evaluation of the effect of compaction method and compaction work on the performance of SMA-13 mixture

et al. 2022

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The influence of compaction methods such as the Marshall compaction method (MCM), vibration compaction method (VCM) and gyration compaction method (GCM), on the performance of stone mastic asphalt (SMA-13) mixture has yet to be explored. Therefore, to compare the influences of compaction methods and work on the physical and mechanical properties of SMA-13 mixture, the volume parameters, mechanical properties, and gradation changes of SMA-13 mixture specimens prepared under different vibration compaction times, Marshall double-compaction numbers, and gyration compaction numbers were studied. The compaction method for SMA-13 mixture design was also proposed under the principle of optimum properties. Results demonstrate that the asphalt aggregate ratio and compaction work directly affect the volumetric properties (VV, VFA, and VMA) of asphalt mixture specimens while the raw material and mineral aggregate gradation were fixed. The influence of compaction work on physical properties is greater than that of asphalt aggregate ratio. The mechanical strength of VCM and GCM specimens is higher than that of MCM specimens under the same compaction work and the optimum asphalt aggregate ratio. With the increase in compaction work, the mechanical properties of SMA-13 mixture are improved at the same compaction method and the optimum asphalt aggregate ratio. The aggregate gradation of the SMA-13 mixture before and after compacted using VCM and GCM changes minimally compared with that of the SMA-13 mixture compacted by MCM. Thus, the compaction methods of VCM65 and GCM130 were recommended for SMA-13 mixture design.

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Accelerated Pavement Testing for Rutting Evaluation of Hot-Mix Asphalt Overlay under High Tire Pressure

Cited by 15 publications

References 29 publications

Measurement accuracy evaluation and optimization of embedded strain sensor for asphalt mixture: laboratory tests and finite element simulation

Measurement accuracy evaluation and optimization of embedded strain sensor for asphalt mixture: laboratory tests and finite element simulation

Design, Construction, and In-Service Causes of Premature Pavement Deterioration: A Fuzzy Delphi Application

Laboratory evaluation of the effect of compaction method and compaction work on the performance of SMA-13 mixture

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