Mechanical Response Analysis of Asphalt Pavement Structure with Embedded Sensor

Wang, Pengcheng; Zhong, Guoqiang; Xue, Xin; Xiao, Fei; Liang, Ming; Wang, Chao; Jiao, Yuepeng; Zhu, Yanli; Liu, Shang; Wang, Hao

doi:10.3390/coatings12111728

Cited by 2 publications

(1 citation statement)

References 26 publications

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“…Then, the effects of various combinations of these variables can be easily analyzed to select the optimal sensor through the multi-factor analysis of variance. Wang et al [25] analyzed the influence of the sensing element shape on the stress-strain fields of the surrounding asphalt mixture through FEM. The optimal shape and size of the sensing element are determined by comparative analysis.…”

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.

View full text Add to dashboard Cite

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Application of FBG sensor in health monitoring of engineering building structure: a review

Zhou,

Jia,

Song

et al. 2024

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Purpose The aging and deterioration of engineering building structures present significant risks to both life and property. Fiber Bragg grating (FBG) sensors, acclaimed for their outstanding reusability, compact form factor, lightweight construction, heightened sensitivity, immunity to electromagnetic interference and exceptional precision, are increasingly being adopted for structural health monitoring in engineering buildings. This research paper aims to evaluate the current challenges faced by FBG sensors in the engineering building industry. It also anticipates future advancements and trends in their development within this field. Design/methodology/approach This study centers on five pivotal sectors within the field of structural engineering: bridges, tunnels, pipelines, highways and housing construction. The research delves into the challenges encountered and synthesizes the prospective advancements in each of these areas. Findings The exceptional performance of FBG sensors provides an ideal solution for comprehensive monitoring of potential structural damages, deformations and settlements in engineering buildings. However, FBG sensors are challenged by issues such as limited monitoring accuracy, underdeveloped packaging techniques, intricate and time-intensive embedding processes, low survival rates and an indeterminate lifespan. Originality/value This introduces an entirely novel perspective. Addressing the current limitations of FBG sensors, this paper envisions their future evolution. FBG sensors are anticipated to advance into sophisticated multi-layer fiber optic sensing networks, each layer encompassing numerous channels. Data integration technologies will consolidate the acquired information, while big data analytics will identify intricate correlations within the datasets. Concurrently, the combination of finite element modeling and neural networks will enable a comprehensive simulation of the adaptability and longevity of FBG sensors in their operational environments.

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Mechanical Response Analysis of Asphalt Pavement Structure with Embedded Sensor

Cited by 2 publications

References 26 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

Application of FBG sensor in health monitoring of engineering building structure: a review

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