Monitoring Pavement Response and Performance Using In-Situ Instrumentation

Dh, Chen; Bilyeu, John; Hugo, F

doi:10.1520/stp14217s

Cited by 6 publications

(9 citation statements)

References 1 publication

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“…A trend is observed that the difference between predicted and measured values increases when the loading level increases. This behavior is consistent with the observations reported by Chen and Murphy (1996). The maximum difference of 24% and minimum difference of 1% were obtained for tensile strain at the loading level of 15,000 and 6,000 lbs., respectively.…”

Section: Pavement Instrumentation Response Analysissupporting

confidence: 93%

“…A welldefined relationship between laboratory and backcalculated M r values could not be established. Chen and Murphy (1996) conducted FWD testing on an in-situ instrumented pavement section for a better understanding and characterization of the behavior of pavement materials. FWD tests were conducted on the top of strain gauges or pressure cells, while FWD surface displacement, and strain or pressure were collected simultaneously.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Pavement layer modulus can also be backcalculated by measuring pavement layer response in terms of deflection using a Falling Weight Deflectometer (FWD) test. Several studies (e.g., Daleiden et al, 1994;Chen and Murphy, 1996;Quintus and Killingsworth, 1998;Rahim and George, 2003) have shown that the M r values determined from laboratory testing can differ significantly from that evaluated using the backcalculation of FWD data. The differences between the two moduli can lead to potentially large systematic differences in pavement designs.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Evaluation of Resilient Moduli of Pavement Layers at an Instrumented Section on I-35 in Oklahoma

Solanki¹,

Zaman²,

Muraleetharan³

et al. 2009

Road Materials and Pavement Design

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Resilient Modulus (M r ) is an important material property for pavement design and evaluation. The M r values can be estimated in the laboratory by measuring material's response under simulated field loading conditions. It can also be determined from nondestructive tests such as the falling weight deflectometer. Some previous studies have shown, however, that the M r values determined from laboratory testing can differ significantly from that determined from the backcalculated resilient moduli using FWD data. This paper presents the results of a site-specific comparison of the M r values determined through laboratory testing and backcalculation of FWD data. Both laboratory and FWD data are related to an instrumented pavement section on I-35 in central Oklahoma. Unlike most previous studies that focused on FWD testing on the top of asphalt concrete, in the present study FWD tests are conducted on different layers namely, natural subgrade, stabilized subgrade, aggregate base and asphalt concrete. The study indicated increase in backcalculated M r values due to the construction of overlying layers. For natural subgrade and aggregate base layer, backcalculated M r values were found higher than corresponding laboratory determined M r values. In addition, FWD tests were also performed on top of the asphalt strain gauges and earth pressure cells and strains and pressure data were collected simultaneously. A comparison of the pavement response between the predictions from a multilayer elastic program, KENPAVE, and the in-situ sensors was made.

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Section: Pavement Instrumentation Response Analysissupporting

confidence: 93%

Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Evaluation of Resilient Moduli of Pavement Layers at an Instrumented Section on I-35 in Oklahoma

Solanki¹,

Zaman²,

Muraleetharan³

et al. 2009

Road Materials and Pavement Design

View full text Add to dashboard Cite

show abstract

“…This was not unexpected due to the difference in the nature of the rehab processes. It also ties in with the quantitative analysis done by Hugo et al (1999) in their comparison of the rutting performance of 281 N1 and 28 1 S I. In contrast, the a and p values for F5 in Table IV are drastically different from those in Table I11 , since F5 is in a different location and the material properties and mix characteristics are totally different (Hugo et al 1997).…”

Section: Parameters a P And Esupporting

confidence: 53%

Application of VESYS3AM in Characterization of Permanent Deformation

Chen

Lin

Hugo

2000

International Journal of Pavement Engineering

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Reprints nvailablc dimlly from the publisher Photmopying permiltcd by liccnr only 0 2000 OPA IOverurr Fublirhcr. Asociulion) N. V. Fublirhcd by liccnw under the Cordon and B r c r h Scicncc Publirhcn irnprinl.Rinlcd in Malawi3The mechanistic system rutting model VESYS3AM was used to predict the rutting performance of three full-scale accelerated pavement test pads. Since the VESYS3AM system rutting model is not formulated to calculate layer rutting, a method was devised to extract the information by manipulating the layer input rutting parameters. Two MDDs were installed into each MLS test pad to determine layer deformation under a uniformly applied set of loads. For simplicity, all comparisons were made for a two-layer system; that is, an AC layer and a subsystem. The layer deformations from the MDDs were used to calibrate the VESYS3AM model parameters a and F.The study represents a laboratory and field determination of material properties, which could be used to model rutting if they were reproduced in other pavements. The predictions from the VESYS3AM system model matched field rutting performance data. Also, the layer rutting contributions were computed, and these compared favorably to MDD measurements.

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“…The MLS test site was selected for this study because it has been comprehensively characterized (4). The test section is an in-service pavement located on US-281 near Jacksboro in the Fort Worth District.…”

Section: Test Sitementioning

confidence: 99%

Determination of Bedrock Depth from Falling Weight Deflectometer Data

Chen

1999

Transportation Research Record: Journal of the Transportation R

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The accuracy of falling weight deflectometer (FWD) back-calculated moduli depends heavily on knowledge of bedrock depth. The bedrock depth can be obtained from coring, boring, and seismic refraction tests, but these operations are not practical. Determining the bedrock depth from FWD data is the easiest and least expensive way. This paper documents the effects of bedrock depth on FWD responses and makes comparisons between predicted bedrock depth and field measurements. Modified algorithms that better fit the field measurements are proposed. It was found that bedrock depth has a great influence on outer FWD sensor (r3 to r6) readings. Deeper bedrock resulted in a higher percentage of increase in r3 to r6 readings in response to increased load. When the r4 reading is less than 25.4 μm for any drop height, it is very likely that the bedrock is within 1.52 m of the surface. The time-deflection history patterns were drastically different between shallow and deep bedrock. When there is no free oscillation after the first deflection peak in a time-deflection history, shallow bedrock (within 1.52 m) is indicated. A modified equation (Equation 2) using the peak deflections provides an accuracy within 30 percent. It is recommended that these equations be used on a pavement where there is no severe surface distress. Another modified equation (Equation 6) using time-deflection history data yields an accuracy within 20 percent but cannot be used when there is no clear indication of free oscillation.

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Monitoring Pavement Response and Performance Using In-Situ Instrumentation

Cited by 6 publications

References 1 publication

Evaluation of Resilient Moduli of Pavement Layers at an Instrumented Section on I-35 in Oklahoma

Evaluation of Resilient Moduli of Pavement Layers at an Instrumented Section on I-35 in Oklahoma

Application of VESYS3AM in Characterization of Permanent Deformation

Determination of Bedrock Depth from Falling Weight Deflectometer Data

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