Comparing back-calculated and laboratory resilient moduli of bituminous paving mixtures

2004 ◽  
Vol 31 (6) ◽  
pp. 988-996 ◽  
Author(s):  
Ahmed Shalaby ◽  
Tara Liske ◽  
Amir Kavussi
Keyword(s):  
Laboratory Testing ◽  
Resilient Modulus ◽  
Field Tests ◽  
Falling Weight Deflectometer ◽  
Important Indicator ◽  
Indirect Tensile Test ◽  
Test Parameters ◽  
Back Calculation ◽  
Indirect Tensile ◽  
Falling Weight

The stiffness of bituminous mixes is an important indicator of mix performance and a required input for mechanistic pavement design. Resilient modulus is one of many stiffness indicators of mixes which can be determined using laboratory testing methods or non-destructive field tests such as falling weight deflectometer (FWD) tests through back calculation. In this paper, two Manitoba mixes known as Bituminous B (Bit B) and Bituminous C (Bit C) are analysed using laboratory testing and FWD back calculation. The experiment involved samples from eight paving sites. Each site included two side-by-side sections having a common Bit B surface course over either a Bit B or a Bit C binder course. Cored samples were tested following the guidelines of the long term pavement performance protocol P07 at 5, 25, and 40 °C. The modulus of each layer was also estimated from FWD deflection measurements. Findings include correlations between the various material and test parameters and a comparison between back calculated and laboratory stiffnesses.Key words: falling weight deflectometer, indirect tensile test, resilient modulus, asphalt concrete.

Relating Laboratory and Field Moduli of Texas Base Materials

1998 ◽  
Vol 1639 (1) ◽  
pp. 1-11 ◽  
Author(s):  
S. Nazarian ◽  
J. Rojas ◽  
R. Pezo ◽  
D. Yuan ◽  
I. Abdallah ◽  
...  
Keyword(s):  
Resilient Modulus ◽  
Design Method ◽  
Field Tests ◽  
Pavement Design ◽  
Falling Weight Deflectometer ◽  
Nondestructive Tests ◽  
Second Stage ◽  
Base Materials ◽  
Two Stages ◽  
Falling Weight

Resilient modulus of base is an important parameter in the AASHTO pavement design method. However, the manner to determine this parameter is not well defined. Recent efforts in combining the resilient moduli from laboratory testing with those obtained in the field using nondestructive testing devices are presented. Laboratory tests were carried out in two stages. In the first stage, virgin materials from the quarry compacted to optimum moisture content were tested. In the second stage, similar base materials were retrieved from in-service roads. Specimens were prepared and tested at the corresponding field densities and moisture contents. Nondestructive tests were performed with the Falling Weight Deflectometer and the Seismic Pavement Analyzer. Based on tests on 10 different base materials from different parts of Texas, it was concluded that it may be difficult to directly compare moduli from laboratory and field tests; however, they can be combined for effective pavement design.

EVALUATION OF PFWD AS POTENTIAL QUALITY CONTROL TOOL OF PAVEMENT LAYERS

2010 ◽  
Vol 16 (1) ◽  
pp. 123-129 ◽  
Author(s):  
Amir Kavussi ◽  
Shahaboddin Yasrobi
Keyword(s):  
Field Tests ◽  
Field Testing ◽  
California Bearing Ratio ◽  
Falling Weight Deflectometer ◽  
Drop Mass ◽  
Quality Control Tool ◽  
Plate Size ◽  
Weight Drop ◽  
Pavement Layers ◽  
Falling Weight

Portable Falling Weight Deflectometer (PFWD) that can be considered as simple equipment is mainly used to measure elastic moduli of pavement unbound layers. This paper evaluates the potential use of PFWD to reliably measure the elastic modulus of pavement layers. To achieve this, PFWD tests were conducted on highway sections selected from different projects in Tehran. The California Bearing Ratio (CBR) laboratory tests were also conducted on samples collected during field tests. PFWD testing parameters were varied while performing the field testing. These included drop weight, drop height, plate diameter and position of additional geophones. In addition, PFWD moduli were compared with those obtained from performing FWD testing on the same site. It was found that drop mass and loading plate size affect PFWD modulus significantly. In addition, the results indicated that good correlation exist between PFWD moduli and FWD and CBR results. Santrauka Nešiojamasis krintančio svorio deflektometras PFWD (angl. portable falling weight deflectometer) yra nesudetingas prietaisas, dažniausiai naudojamas kelio dangu nesurištu sluoksniu tamprumo moduliui nustatyti. Straipsnyje apžvelgta, kaip PFWD naudojamas kelio dangu sluoksniu tamprumo moduliams matuoti. Taikant PFWD išbandyti skirtinguose projektuose Teherane (Iranas) panaudoti kelio dangu skerspjūviai. Bandiniams papildomai atlikti Kalifornijos santykinio atsparumo rodiklio CBR (angl. California bearing ratio) nustatymo eksperimentiniai tyrimai. Atliekant lauko tyrimus naudoti skirtingi PFWD bandymu parametrai: krintantis svoris, kritimo aukštis, plokštes skersmuo ir papildomai išdestyti geofonai. PFWD nustatyti tamprumo moduliai palyginti su tamprumo moduliais, išmatuotais naudojant krintančio svorio deflektometra FWD (angl. falling weight deflectometer). Nustatyta, kad PFWD matavimu rezultatams didele itaka turi kritimo mase ir apkrovimo plokštes matmenys. Gauti eksperimentiniu tyrimu rezultatai parode, kad PFWD, FWD ir CBR matavimai gerai koreliuoja tarpusavyje.

Implementation of Cold In-Place Recycling with Expanded Asphalt Technology in Canada

2005 ◽  
Vol 1905 (1) ◽  
pp. 17-24 ◽  
Author(s):  
Becca Lane ◽  
Tom Kazmierowski
Keyword(s):  
Resilient Modulus ◽  
Efficient Manner ◽  
Pavement Rehabilitation ◽  
Asphalt Cement ◽  
Foamed Asphalt ◽  
Pavement Roughness ◽  
Asphalt Mix ◽  
Indirect Tensile ◽  
Emulsified Asphalt ◽  
Falling Weight

Cold in-place recycling (CIR) is a pavement rehabilitation method that processes an existing hot-mix pavement, sizes it, mixes in additional asphalt cement, and lays it back down without off-site hauling and processing. The added asphalt cement is typically emulsified asphalt. A recent development in CIR technology is the use of expanded (foamed) asphalt rather than emulsified asphalt to bind the mix. This combination of CIR and expanded asphalt technologies is termed cold in-place recycled expanded asphalt mix (CIREAM). The Ministry of Transportation Ontario (MTO) constructed a CIREAM trial section on Highway 7 in July 2003. The 5-km CIREAM trial section was constructed adjacent to an 8-km section on which conventional CIR was performed. CIREAM placement resulted in a smooth, hard, uniform surface that provided an excellent platform for paving operations. The CIREAM placement progressed in a continuous and efficient manner, with 5 km placed over a 3-day period. Indirect tensile strength testing was carried out on both materials during construction. Falling weight deflectometer (FWD) testing and evaluation of pavement roughness and rutting by the use of MTO's automatic road analyzer (ARAN) were carried out. Resilient modulus testing of core samples of the CIR material and CIREAM was also carried out. The results of the FWD, ARAN, and resilient modulus tests indicated that the CIR and CIREAM pavements were performing similarly. A field review 1 year after construction showed no discernible distortion, rutting, or cracking. On the basis of short-term results, CIREAM appears to be an acceptable in-place recycling and rehabilitation strategy that provides an economical alternative to conventional CIR, reduces curing time, and extends the construction season.

Visco-Elastic Back-Calculation of Traffic Speed Deflectometer Measurements

2019 ◽  
Vol 2673 (12) ◽  
pp. 439-448 ◽  
Author(s):  
Christoffer P. Nielsen
Keyword(s):  
Calculation Procedure ◽  
Falling Weight Deflectometer ◽  
Calculation Algorithm ◽  
Structural Evaluation ◽  
Driving Speed ◽  
Back Calculation ◽  
Traffic Speed ◽  
Falling Weight ◽  
Calculation Procedures ◽  
Project Level

The traffic speed deflectometer (TSD) has proven a valuable tool for network level structural evaluation. At the project level, however, the use of TSD data is still quite limited. An obstacle to the use of TSD at the project level is that the standard approaches to back-calculation of pavement properties are based on the falling weight deflectometer (FWD). The FWD experiment is similar, but not equivalent, to the TSD experiment, and therefore it is not straightforward to apply the traditional FWD back-calculation procedures to TSD data. In this paper, a TSD-specific back-calculation procedure is presented. The procedure is based on a layered linear visco-elastic pavement model and takes the driving speed of the vehicle into account. This is in contrast to most existing back-calculation procedures, which treat the problem as static and the pavement as purely elastic. The developed back-calculation procedure is tested on both simulated and real TSD data. The real TSD measurements exhibit significant effects of damping and visco-elasticity. The back-calculation algorithm is able to capture these effects and yields model fits in excellent agreement with the measured values.

A practical approach to falling-weight deflectometer (FWD) data reduction

2005 ◽  
Vol 42 (2) ◽  
pp. 641-645 ◽  
Author(s):  
Dieter Stolle ◽  
Peijun Guo
Keyword(s):  
Mechanical Properties ◽  
Shear Modulus ◽  
Falling Weight Deflectometer ◽  
Layer System ◽  
Surface Loading ◽  
Back Calculation ◽  
Pavement Response ◽  
Subgrade Modulus ◽  
Falling Weight

The authors present a simplified methodology for preprocessing falling-weight deflectometer (FWD) data, which identify a pseudo-static pavement response to surface loading. This allows one to employ static analysis to back-calculate the mechanical properties of the pavement–subgrade system. It is shown that the subgrade modulus can be identified, independent of the details of the pavement structure itself, at least for a two-layer system. The quality of the effective shear modulus is sensitive to the value of Poisson's ratio selected.Key words: pavement–subgrade system, subgrade modulus, back-calculation, FWD.

Assessment of Falling Weight Deflectometer Data for Stabilized Flexible Pavements

2000 ◽  
Vol 1709 (1) ◽  
pp. 19-25 ◽  
Author(s):  
Alexander K. Appea ◽  
Imad L. Al-Qadi
Keyword(s):  
Resilient Modulus ◽  
Ground Truth ◽  
Monitoring And Evaluation ◽  
Structural Condition ◽  
Base Layer ◽  
Falling Weight Deflectometer ◽  
Structural Capacity ◽  
Pavement Monitoring ◽  
Aggregate Base ◽  
Falling Weight

Backcalculation of pavement moduli through the utilization of the falling weight deflectometer (FWD) is used for pavement monitoring and evaluation. The performance and structural condition of nine flexible pavement test sections built in Bedford County, Virginia, have been monitored over the past 5 years using FWD. The nine sections include three groups with aggregate base layer thicknesses of 100, 150, and 200 mm, respectively. Sections 1, 4, and 7 are control, whereas Sections 2, 5, 8 and 3, 6, 9 are stabilized with geotextiles and geogrids, respectively. The FWD testing used five double-load drops ranging from 26.5 to 58.9 kN. The deflection basins obtained from the testing have been analyzed using the ELMOD backcalculation program to find the pavement structural capacity and to detect changes in the aggregate resilient modulus. The analysis shows a reduction in the backcalculated resilient modulus of the 100-mmthick base layer. The reduction was 33 percent over 5 years for the nonstabilized section compared with the geosynthetically stabilized section. The reduction in base layer resilient modulus may have resulted from subgrade fine migration into this layer as confirmed by excavation. The study confirms the effectiveness of using woven geotextile as a separator in a pavement system built over weak subgrade. This supports the continuous rutting measurements and ground truth excavation conducted in late 1997.

Relationship Between Backcalculated and Laboratory-Measured Resilient Moduli of Unbound Materials

2003 ◽  
Vol 1849 (1) ◽  
pp. 177-182 ◽  
Author(s):  
Gerardo W. Flintsch ◽  
Imad L. Al-Qadi ◽  
Youngjin Park ◽  
Thomas L. Brandon ◽  
Alexander Appea
Keyword(s):  
Resilient Modulus ◽  
Shift Factor ◽  
Falling Weight Deflectometer ◽  
Test Results ◽  
Structural Capacity ◽  
Bulk Stress ◽  
Stress Dependent ◽  
Falling Weight ◽  
Virginia Smart Road

The resilient moduli of an unbound granular subbase (used at the Virginia Smart Road) obtained from laboratory testing were compared with those backcalculated from in situ falling weight deflectometer deflection measurements. Testing was performed on the surface of the finished subgrade and granular subbase layer shortly after construction. The structural capacity of the constructed subgrade and the depth to a stiff layer were computed for 12 experimental sections. The in situ resilient modulus of the granular subbase layer (21-B) was then back-calculated from the deflections measured on top of that layer. The back-calculated layer moduli were clearly stress-dependent, showing an exponential behavior with the bulk stress in the center of the layer. Resilient modulus test results of laboratory-compacted specimens confirmed the stress dependence of the subbase material modulus. Three resilient modulus models were fitted to the data. Although all three models showed good coefficients of determination ( R2 > 90%), the K-θ model was selected because of its simplicity. The correlation between field-backcalculated and laboratory-measured resilient moduli was found to be strong. However, when the stress in the middle of the layer was used in the K-θ model, a shift in the resilient modulus, θ, was observed. This finding suggests that a simple shift factor could be used for the range of stress values considered.

scholarly journals Estimation of Flexible Pavement Structural Capacity Using Machine Learning Techniques

2020 ◽  
Author(s):  
Nader Karballaeezadeh ◽  
Hosein Ghasemzadeh Tehrani ◽  
Danial Mohammadzadeh S. ◽  
Shahaboddin Shamshirband
Keyword(s):  
Machine Learning ◽  
Random Forest ◽  
Ground Penetrating Radar ◽  
Flexible Pavement ◽  
Falling Weight Deflectometer ◽  
Machine Learning Methods ◽  
Back Calculation ◽  
Ground Penetrating ◽  
Falling Weight ◽  
Surface Deflections

The most common index for representing structural condition of the pavement is the structural number. The current procedure for determining structural numbers involves utilizing falling weight deflectometer and ground-penetrating radar tests, recording pavement surface deflections, and analyzing recorded deflections by back-calculation manners. This procedure has two drawbacks: 1. falling weight deflectometer and ground-penetrating radar are expensive tests, 2. back-calculation ways has some inherent shortcomings compared to exact methods as they adopt a trial and error approach. In this study, three machine learning methods entitled Gaussian process regression, m5p model tree, and random forest used for the prediction of structural numbers in flexible pavements. Dataset of this paper is related to 759 flexible pavement sections at Semnan and Khuzestan provinces in Iran and includes “structural number” as output and “surface deflections and surface temperature” as inputs. The accuracy of results was examined based on three criteria of R, MAE, and RMSE. Among the methods employed in this paper, random forest is the most accurate as it yields the best values for above criteria (R=0.841, MAE=0.592, and RMSE=0.760). The proposed method does not require to use ground penetrating radar test, which in turn reduce costs and work difficulty. Using machine learning methods instead of back-calculation improves the calculation process quality and accuracy.

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