Development and Evaluation of Relative Compaction Specifications Using Roller-Based Measurements

Facas, Norman W.; Rinehart, Robert V.; Mooney, Michael A.

doi:10.1520/gtj102915

Cited by 13 publications

(3 citation statements)

References 12 publications

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“…However, the regression correlations between ICMV and ISMV are complicated because the correlations are not only affected by roller parameters but also by subgrade properties [18][19][20][21]. It primarily includes roller speed and roller vibration amplitude in terms of roller parameters.…”

Section: Introductionmentioning

confidence: 99%

Study of Regression Algorithms and Influent Factors between Intelligent Compaction Measurement Values and In-Situ Measurement Values

et al. 2023

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Intelligent compaction (IC) technology have been used for quality control and quality assurance (QC/QA) in subgrade construction. The effective regression correlations between Intelligent Compaction Measurement Values (ICMV) and In-situ Measurement Values (ISMV, including compaction degree and subgrade modulus ELWD) are the essential prerequisite of using IC technology for QC/QA. This paper presents the results from an experimental research study that was conducted from a practical subgrade project of China to explore the regression relationships between ICMV and ISMV. Three types of ICMV, including CMV, CCV and Evib, were collected along with the corresponding positions of the rollers. Two types of ISMV, containing compaction degree and ELWD, were measured by ring sampler method and light weight deflectometer (LWD) at specified test points, respectively. Based on these data, the influences of roller parameters and subgrade properties on the regression relationships of ICMV and ISMV were investigated. In addition, linear regression and 5 nonlinear regression algorithms were compared. The results suggest that ICMV reflect the stiffness of subgrade more than reflecting the density. In the regression of ICMV and ISMV, subgrade properties are more important than roller parameters while both of them should not be neglected. The influences of underlying stiffness and roller amplitude are linear while that of roller speed and moisture content are nonlinear. Nonlinear algorithms, especially the random forest, have the better performance compared to linear algorithm. Moreover, the combination of random forest and linear algorithm can further improve the accuracy of ISMV prediction.

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Section: Introductionmentioning

confidence: 99%

Study of Regression Algorithms and Influent Factors between Intelligent Compaction Measurement Values and In-Situ Measurement Values

et al. 2023

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“…In exploring the transmission and evolution characteristics of the vibration signal, two approaches have been used: (1) analyses were performed in the time domain, but only vibration time-history responses were obtained [8,[22][23][24]; (2) analyses were performed in the frequency, but only Fourier spectrums and energy spectrums are obtained [25][26][27][28][29]. However, the vibration wave is a complicated nonlinear non-stationary signal and its vibration frequency and amplitude are constantly changing in the compaction progress.…”

Section: Introductionmentioning

confidence: 99%

Study on the Transmission and Evolution Characteristics of Vibration Wave from Vibratory Roller to Filling Materials Based on the Field Test

et al. 2020

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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.

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“…As federal and state transportation agencies move toward the adoption of mechanistic design procedures and performance-based assessment of earthwork construction, the role of stiffness/ modulus-based quality management through nondestructive testing (NDT) has become more important (1)(2)(3)(4). As discrete NDT measurements cannot provide complete coverage of the compacted sections, transportation agencies are now considering adopting intelligent compaction (IC) for pavement earthwork construction (5,6). Proof rolling using IC mapping after the completion of compaction can be used to assess the uniformity of the compacted layer and identify less stiff areas if performed properly (4).…”

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confidence: 99%

Incorporating Calibrated Numerical Models in Estimating Moduli of Compacted Geomaterials from Integrated Intelligent Compaction Measurements and Laboratory Testing

Fathi

Tirado

Rocha

et al. 2020

Transportation Research Record: Journal of the Transportation R

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Proof rolling after completion of compaction of earthwork using intelligent compaction (IC) technology can be used to assess the uniformity of the compacted geomaterials and to identify less stiff compacted areas. To better understand the process of quality management using IC technology, a three-dimensional finite element model was developed to document the theoretical limitations and the sensitivity of IC technology. The model can also be used for setting the target values, and can be part of a methodology to extract the moduli of geomaterials in more rigorous and defensible specifications. Different levels of complexity in relation to linear versus nonlinear behavior of geomaterial and different levels of roller operating conditions (static versus dynamic, moving versus stationary) can be assigned to the model. Such model can only be used with confidence if it is calibrated and validated with experimental field data. Five test sites including single-layer (subgrade only) and two-layer (subgrade and base) geosystems were instrumented using in-ground sensors for calibrating the model. Different vibratory IC rollers from different manufacturers were used to implement IC tests at vibratory stationary as well as moving conditions at the test sites. In all scenarios, a locally calibrated transfer function was necessary to accommodate the differences in the numerical models and vibration data obtained from the IC measurements on test sections with distinct geomaterial conditions. The study also concluded that the predictive power of the numerical models improves if the field measurements and laboratory data are integrated, and more importantly the variability of the materials is incoprorated.

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Development and Evaluation of Relative Compaction Specifications Using Roller-Based Measurements

Cited by 13 publications

References 12 publications

Study of Regression Algorithms and Influent Factors between Intelligent Compaction Measurement Values and In-Situ Measurement Values

Study of Regression Algorithms and Influent Factors between Intelligent Compaction Measurement Values and In-Situ Measurement Values

Study on the Transmission and Evolution Characteristics of Vibration Wave from Vibratory Roller to Filling Materials Based on the Field Test

Incorporating Calibrated Numerical Models in Estimating Moduli of Compacted Geomaterials from Integrated Intelligent Compaction Measurements and Laboratory Testing

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