Use of Intelligent Compaction in Detecting and Remediating Under-Compacted Spots During Compaction of Asphalt Layers

Author(s):  
Manik Barman ◽  
Syed Asif Imran ◽  
Moeen Nazari ◽  
Sesh Commuri ◽  
Musharraf Zaman
2015 ◽  
Vol 52 (4) ◽  
pp. 459-468 ◽  
Author(s):  
Aaron Neff ◽  
Mallory McAdams ◽  
Judith Wang ◽  
Michael Mooney

This paper describes the interpretation of intelligent compaction (IC) data from two layered soil test beds using center of gravity (CG) roller-measured soil stiffness. Conventional edge-mounted (EM) roller-measured soil stiffness values are interpreted from vertical accelerations measured by discrete, single-position accelerometers. However, these EM accelerometers are located at variable distances from the drum CG; the resulting vertical accelerations are thus affected by the rotation of the roller drum about the drum CG in the direction of roller travel. This leads to undesirable measurement artifacts, specifically multiple possible soil stiffness values for one soil location and an artificial dependence of the soil stiffness values on the direction of roller travel. In this study, left and right EM acceleration data from a vibratory roller are used to compute vertical accelerations at the CG of the roller drum. These vertical accelerations are used to compute CG stiffness values, which are not subject to the measurement artifacts associated with EM stiffness values. The resulting CG stiffness values are used to interpret IC data from two test beds with multiple 15–30 cm thick base–subbase–subgrade lifts. CG soil stiffness increases with the addition of subbase and base lifts, showing a desired sensitivity to changes in soil materials. CG stiffness also increases with the addition of multiple base lifts, showing a desired sensitivity to an increase in the overall thickness of the base material. This study demonstrates the efficacy of this unambiguous measure of soil stiffness for practical usage in IC of layered earthwork systems.


Author(s):  
George K. Chang ◽  
Kiran Mohanraj ◽  
William A. Stone ◽  
Daniel J. Oesch ◽  
Victor (Lee) Gallivan

Intelligent compaction (IC) is an emerging technology with rollers equipped with global navigation satellite system (GNSS), an accelerometer-based measurement system, and an onboard color-coded display for real-time monitoring and compaction control. Paver-mounted thermal profiling (PMTP) is used to monitor asphalt surface temperatures behind a paver with a thermal scanner, and to track paver speeds, stops, and stop durations. Leveraging both IC and PMTP technologies allows for paving and compaction controls in real time, and for executing appropriate adjustments as needed. A case study is used to demonstrate the advantage of using both IC and PMTP over conventional operations. Postconstruction asphalt coring and tests, as well as pavement profile surveys were conducted to provide asphalt density data and pavement smoothness acceptance data for comparison and correlation analysis with IC and PMTP data. The data from 2 days of operations, one without the Material Transfer Vehicle (MTV) and another with the MTV, were analyzed and compared to illustrate the benefits of using IC, PMTP, and MTV for producing quality pavement products. Durability and smoothness are two key construction qualities for agencies and users of hot mix asphalt (HMA) pavements. These two factors also affect the long-term structural and functional pavement performance.


2021 ◽  
Author(s):  
Xiaolai Jiao ◽  
Zhengang Feng ◽  
Shujuan Wang ◽  
Merveille Wilhelm BIBOUSSI ◽  
Xinjun Li

2020 ◽  
Vol 10 (6) ◽  
pp. 2008
Author(s):  
Changwei Yang ◽  
Liang Zhang ◽  
Yixuan Han ◽  
Degou Cai ◽  
Shaowei Wei

Compaction quality of railroad subgrade relates directly to the stability and safety of train operation, and the core problem of the Intelligent Compaction of railroads is the transmission and evolution characteristics of vibration wave. Aiming at the shortages in exploring the transmission and evolution characteristics of the vibration signal, the typical subgrade compaction project of Jingxiong Intercity Railway Gu’an Station was selected to carry out the field prototypes tests, and the dynamic response from the vibratory roller to filling materials was monitored in the whole compaction process, and some efficient field tests data will be obtained. Based on this, the transmission and evolution characteristics of the vibration wave from the vibratory roller to filling materials in the compaction process are studied from the time domain, frequency domain, jointed time–frequency domain and energy domain by using one new signal analysis technology—Hilbert–Huang Transform. Some conclusions are shown as follows: first, the vibration acceleration peak gradually decreases with the increase of buried depth, and when the buried depth reaches 1.8 m, the vibration acceleration peak is closed to zero. At the same time, when the vibration wave propagates from the wheel to the surface of filling, the attenuation rate of acceleration gradually increases with the increase of rolling compaction times, while the attenuation rate of other layers in different buried depths gradually decreases. Second, the vibration wave contains fundamental wave and multiple harmonics, and the dominant frequency of the fundamental wave is nearly 21 Hz. With the increase of buried depth, the amplitude of fundamental, primary, secondary, until fifth harmonics decreases exponentially and the concrete functional relationship among different amplitudes of harmonics can be summarized as y = Ae−BX. Third, the vibration energy focuses on the fundamental wave and primary wave, which can increase with the increase of rolling compaction times, and when the rolling compaction time reaches five, their energy reaches maximum. However, when the filling reaches a dense situation, the energy of the primary wave gradually decreases. Therefore, the maximum rolling compaction time is five in the practical engineering applications, which will be helpful for optimizing the compaction quality control models and providing some support for the development of the Intelligent Compaction theory of railway subgrade.


Author(s):  
Jimmy Z. Si

This paper presents the results of the intelligent compaction data that were collected from various layers including subgrade soil, lime-treated subgrade, cement-treated base and flexible aggregate base layers. Sets of proof-mapping data were collected from each layer upon completion of compaction. The data was then downloaded and analyzed using a computer program. Based on the data analysis and field compaction observation, a new statistical methodology for analyzing intelligent compaction data is proposed. The method is used to assess the uniformity of soil and base compaction quality and this is successfully demonstrated through a case study. A typical normal distribution of an intelligent compaction dataset indicates that a good and uniform compaction is achieved. It is, therefore, possible to assess the compaction quality by evaluating the perfection of normal districtuion of an intelligent compaction (IC) dataset. The compaction uniformity is evaluated by a compaction uniformity index, which is defined as the ratio of the probability within the specified limits in a field compaction data distribution to the probability in a target normal distribution.


2008 ◽  
Vol 22 (4) ◽  
pp. 243-251 ◽  
Author(s):  
R. Edward Minchin ◽  
David C. Swanson ◽  
Alexander F. Gruss ◽  
H. Randolph Thomas

Sign in / Sign up

Export Citation Format

Share Document