Evaluation and Harmonization of Intelligent Compaction Systems

Mazari, Mehran; Beltrán, Jorge; Aldouri, Raed; Chang, George K.; Si, Jimmy; Nazarian, Soheil

doi:10.1061/9780784479926.076

Cited by 4 publications

(6 citation statements)

References 4 publications

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“…However, the average stiffness of the LTS dataset did not improve compared with that for the subgrade. This could be attributed to the additional moisture content when lime slurry was added and the time when the IC data were collected, since the stiffness is highly sensitive to the moisture content ( 11 ). In fact, just as the moisture and the chemical reactions between the lime and soil keep changing with time, the stiffness of the material also continues to change.…”

Section: Resultsmentioning

confidence: 99%

“…Intelligent Compaction (IC) technology is a continuous compaction quality control process whose objective is to achieve uniform and consistent compaction during construction. Extensive research has been carried out and extensive literature has been well documented regarding equipment development, data collection, analyasis and interpretation as well applications ( 2 – 12 ). Currently, the most popular analysis model is plotting a semivarigram graph.…”

Section: Theoretical Methodologymentioning

confidence: 99%

“…It is gaining popularity in the U.S. because of its flexibility and cost-effectiveness. This after-market equipment can be retrofitted onto any dynamic vibratory rollers and works the same way as the Original Equipment Manufacturer (OEM) IC rollers ( 11 ).…”

Section: Theoretical Methodologymentioning

confidence: 99%

“…Certainly, not all field compaction IC data sets follow a normal distribution curve. Based on TxDOT’s database ( 11 ), most original IC datasets have, in fact, a right-skewed distribution with extremely high values on the right side as outliers, as shown in Figure 3.…”

Section: Theoretical Methodologymentioning

confidence: 99%

See 3 more Smart Citations

Intelligent Compaction for Quality Control and Acceptance for Soil and Base Compaction through Statistical Analysis

Jimmy

2018

Transportation Research Record: Journal of the Transportation R

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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.

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Section: Resultsmentioning

confidence: 99%

Section: Theoretical Methodologymentioning

confidence: 99%

Section: Theoretical Methodologymentioning

confidence: 99%

Section: Theoretical Methodologymentioning

confidence: 99%

See 2 more Smart Citations

Intelligent Compaction for Quality Control and Acceptance for Soil and Base Compaction through Statistical Analysis

Jimmy

2018

Transportation Research Record: Journal of the Transportation R

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“…As an example, the skewness of the data and the ratio of the head to the tail in the best-fit distribution may affect the selection of the classification technique. Furthermore, not all IC data fit into a normal distribution, as has been observed in a number of field studies (2,14). The following section discusses the impact of ICMV distribution on the selection of the classification method.…”

Section: Optimization Of Class Break Valuesmentioning

confidence: 93%

Impact of Geospatial Classification Method on Interpretation of Intelligent Compaction Data

Mazari

Tirado

Nazarian³

et al. 2017

Transportation Research Record: Journal of the Transportation R

Self Cite

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Intelligent compaction is an emerging technology in the management of pavement layers, more specifically, of unbound geomaterial layers. Different types of intelligent compaction measurement values (ICMVs) are available on the basis of the configuration of the roller, vibration mechanism, and data collection and reduction algorithms. The spatial distribution of the estimated ICMVs is usually displayed as a color-coded map, with the ICMVs categorized into a number of classes with specific color codes. The number of classes, as well as the values of the breaks between classes, significantly affect the perception of compaction quality during the quality management process. In this study, three sets of ICMV data collected as a part of a field investigation were subjected to geostatistical analyses to evaluate different classification scenarios and their impact on the interpretation of the data. The classification techniques were evaluated on the basis of the information theory concept of minimizing the information loss ratio. The effect of the ICMV distribution on the selection of the classification method was also studied. An optimization technique was developed to find the optimal class breaks that minimize the information loss ratio. The optimization algorithm returned the best results, followed by the natural breaks and quantile methods, which are suited to the skewness of the ICMV distribution. The identification of less-stiff areas by using the methods presented will assist highway agencies to improve process control approaches and further evaluate construction quality criteria. Although the concepts discussed can apply to any compacted geomaterial layer, the conclusions apply to the type of compacted soil in this particular test section.

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The Role of Dynamic Cone Penetrometer Testing in Assessing Pavement Subgrade Strength: A Literature Review

Garcia

2024

GEOMATE

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In-situ tests for predicting geotechnical parameters related to shear strength, such as California Bearing Ratio (CBR), typically require drilling boreholes and manual cone driving, which can be timeconsuming, expensive, and labor-intensive. The Dynamic Cone Penetrometer Test (DCPT) has emerged as a simpler, faster, and less expensive alternative for predicting CBR and other geotechnical parameters. This systematic review uses Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to examine relevant literature on DCP testing for accurately predicting CBR and other geotechnical parameters. After trimming 111 relevant studies to 55, the review discusses various research questions, including the correlation between DCP and CBR, factors such as water content and seasonal variations, and recent advances in DCP testing. The review emphasizes the importance of considering unsaturated soil behavior, such as soil suction, in pavement subgrade design to ensure the longevity and quality of the pavement. The findings provide compelling evidence for the utilization of DCP testing as an essential tool for predicting geotechnical parameters and designing high-performance pavements. By demonstrating the DCPT's remarkable convenience, reliability, and cost-effectiveness in CBR and geotechnical parameter prediction, this study paves the way for significant advancements in pavement design efficiency and economic viability.

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Evaluation and Harmonization of Intelligent Compaction Systems

Cited by 4 publications

References 4 publications

Intelligent Compaction for Quality Control and Acceptance for Soil and Base Compaction through Statistical Analysis

Intelligent Compaction for Quality Control and Acceptance for Soil and Base Compaction through Statistical Analysis

Impact of Geospatial Classification Method on Interpretation of Intelligent Compaction Data

The Role of Dynamic Cone Penetrometer Testing in Assessing Pavement Subgrade Strength: A Literature Review

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