Abstract

In transport sector, improving the quality of road construction plays a crucial role in developing a more sustainable and cost-effective infrastructure network. Intelligent Compaction (IC) has been actively studied as a novel and promising technology for quality monitoring and control in asphalt road construction. However, a successful application of IC in pavement construction is still bothered by its accuracy and stability in quality evaluation. This paper proposed AICV– Acceleration Intelligent Compaction Value, a new evaluation index for harmonic intelligent compaction quality evaluation and with a higher accuracy than the frequently used index CMV– Compaction Measurement Value. In order to optimize the evaluation of the compaction quality uniformity of asphalt pavement, the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$3\sigma $ </tex-math></inline-formula> of Normal Distribution is adopted to estimate the compaction uniformity. The statistical analyses of the field measurement data show that, both CMV and AICV are applicable to evaluate the uniformity of compaction quality. However, the dispersion degree of AICV is far less than that of CMV, indicating that AICV is more stable as an index for compaction quality evaluation. By using spatial statistics, the spatial correlation distance of the compaction quality is further obtained, which gives to an assessment of the influence range of intelligent roller. Overall, the study provides a basis for improving the quality control of asphalt pavement construction by means of more delicate monitoring of the compaction process.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.