Effects of Crack Damage on Acceleration Response of Asphalt Pavement via Numerical Analysis

Yan, Guannan; Wang, Linbing; Ye, Zhoujing; Wang, Wentao

doi:10.1061/(asce)mt.1943-5533.0003221

Cited by 10 publications

(9 citation statements)

References 21 publications

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“…Due to the limited budget and labor, highway agencies have been in search of a cost effective way to find an affordable pavement condition survey method such as accelerometers, real-time images, etc. A study by Yan et al indicated that the acceleration signals have a significant effect on the deeper and longer cracks in the pavement condition [11]. A report by Alavi et al expressed that the vertical acceleration data from a smartphone can be used in assessing overall airport pavement condition [12].…”

Section: Literature Reviewmentioning

confidence: 99%

“…To precisely analyze vibration signals and transfer the results in to the pavement distress classifications, a variety of computing algorithms have been used in the determination of pavement distress such as numerical analysis, supervised machine learning, and image processing through MATLAB software [11][12][13][14][15][16][17][18]. For example, Fast Fourier transform (FFT) and Short-term Fourier Transform (STFT) have been used to find the displacement data based on the vertical acceleration for evaluating road performance [5,17].…”

Section: Literature Reviewmentioning

confidence: 99%

“…Their results indicated that higher displacement values, and poor road conditions, visually matched with road conditions. Through numerical analysis of vertical acceleration, Yan et al found that most cracks have positive vertical acceleration in pavement condition assessments [11] and the cracks can be identified by integrating the differential intensity and height changes from the data [19]. Additionally, using polynomial approximation is another way to determine the locations of potholes in the condition assessment [20].…”

Section: Literature Reviewmentioning

confidence: 99%

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Evaluating the impact of factors in vehicle based pavement sensing implementation: sensor placement, pavement temperature, speed, and threshold

Zhang

2023

J Infrastruct Preserv Resil

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The purpose of the paper is to improve the efficiency of vehicle based sensing technology in highway pavement condition assessment by evaluating the effect of four factors (sensor placement, pavement temperature, drive speed, and threshold for pavement distress classification) and providing suggestions to better improve the accuracy of pavement condition detection and minimize the interruption of pavement sensing operation. Two I-10 corridors in the Phoenix region were selected for vibration data collection and data analysis. A series of statistical analyses were performed to determine if each one of the factors has a significant impact on the pavement distress detection. The results of Analysis of Variance (ANOVA) tests and Analysis of Covariance (ANCOVA) tests show that the placement of sensors have a significant effect in the pavement condition assessments. The significant differences occurred in the group of sensors that were placed on the same side of the vehicle, as well as, in either front wheels or rear wheels of the vehicle. The effect of pavement temperature on the vehicle based sensing implementation is significant while the mean drive speed is not seen as a significant factor in the pavement condition survey. The two thresholds were determined to select points of interest (POI; cracks, potholes) for the pavement distress classification and these POIs are in good agreement with international roughness index (IRI) data in an ArcGIS map. The findings of the paper can be used to better improve the computing algorithms of vehicle based sensing techniques.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

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Evaluating the impact of factors in vehicle based pavement sensing implementation: sensor placement, pavement temperature, speed, and threshold

Zhang

2023

J Infrastruct Preserv Resil

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“…Combined with Equation (1) and Equation ( 4), the relationship between ε m and ε t can be expressed in Equation (5).…”

Section: Rationality Of Requirementmentioning

confidence: 99%

“…Understanding the internal stress–strain state of pavement structure can guide pavement structure design and explain pavement failure mechanism 1–3 . Previous studies 4–6 demonstrated that horizontal tensile strain at the bottom of the asphalt layer was the primary contributor of bottom‐up fatigue cracking of pavement structure. Consequently, the tensile strain at bottom of asphalt layer is the crucial observation object in the pavement structure health monitoring.…”

Section: Introductionmentioning

confidence: 99%

Theoretical analysis on the measurement accuracy of embedded strain sensor in asphalt pavement dynamic response monitoring based on FEM

Han

Liu

2022

Structural Contr & Hlth

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Embedded strain sensors are the primary measurement device for strain in the tensile layer of asphalt pavement. The favorable deformation compatibility between embedded strain sensor and asphalt layer is the key to ensure the precise measurement of mechanical response. However, the good deformation coordination may be difficult to maintain under different environments due to the viscoelasticity of asphalt mixture. In this study, 4-point bending beam tests were performed to investigate deformation compatibility between embedded strain sensor and asphalt mixture under different temperature. Then, a quasistatic finite element model (FEM) was employed to simulate static mechanical response of asphalt pavement, and the design requirements for embedded strain sensor were proposed considering deformation coordination. In addition, the rationality of the design requirements of the sensor was further validated in the dynamic response monitoring. The results indicate that the deformation compatibility between embedded strain sensor and pavement material changes at different temperatures. In order to ensure favorable deformation compatibility, the reinforcement of the protective housing should be eliminated and the equivalent modulus (EM) of the sensitive element shall be the same as that of the asphalt mixture. Considering the viscoelasticity of asphalt mixture, the strain sensor with lower EM is recommended in the dynamic response monitoring of pavement structure. This study provides a basis for optimizing the embedded strain sensor of asphalt pavement from the perspective of deformation compatibility.

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Segmentation network of concrete cracks with multi-frequency OctaveRes dual encoder and cross-attention mechanism optimized by average weight

Wang

Chen

Cai

et al. 2023

Automation in Construction

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Effects of Crack Damage on Acceleration Response of Asphalt Pavement via Numerical Analysis

Cited by 10 publications

References 21 publications

Evaluating the impact of factors in vehicle based pavement sensing implementation: sensor placement, pavement temperature, speed, and threshold

Evaluating the impact of factors in vehicle based pavement sensing implementation: sensor placement, pavement temperature, speed, and threshold

Theoretical analysis on the measurement accuracy of embedded strain sensor in asphalt pavement dynamic response monitoring based on FEM

Segmentation network of concrete cracks with multi-frequency OctaveRes dual encoder and cross-attention mechanism optimized by average weight

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