Back-calculation of elastic modulus of soil and subgrade from portable falling weight deflectometer measurements

2012 ◽  
Vol 34 ◽  
pp. 1-7 ◽  
Author(s):  
C. Asli ◽  
Z.-Q. Feng ◽  
G. Porcher ◽  
J.-J. Rincent
Keyword(s):  
Elastic Modulus ◽  
Falling Weight Deflectometer ◽  
Back Calculation ◽  
Falling Weight

scholarly journals Measurements of the elastic modulus of pavement subgrade layers using the SASW and FWD test methods

2015 ◽  
Vol 10 (2) ◽  
pp. 174-181 ◽  
Author(s):  
Nur Izzi Md. Yusoff ◽  
Sentot Hardwiyono ◽  
Norfarah Nadia Ismail ◽  
Mohd Raihan Taha ◽  
Sri Atmaja P. Rosyidi ◽  
...  
Keyword(s):  
Spectral Analysis ◽  
Elastic Modulus ◽  
Surface Wave ◽  
Time Lag ◽  
Test Methods ◽  
Pavement Management ◽  
Falling Weight Deflectometer ◽  
Surface Wave Propagation ◽  
Evaluation And Monitoring ◽  
Falling Weight

In pavement management systems, deflection basin tests, such as the Falling Weight Deflectometer test, are common techniques that are widely used, while the surface wave test, i.e. the Spectral Analysis of Surface Wave test, is recently employed as an alternative technique in pavement evaluation and monitoring. In this paper, the performance of both dynamic non-destructive tests on pavement subgrade investigation is presented. Surface wave propagation between a set of receivers was transformed into the frequency domain using the Fast Fourier Transform technique and subsequently a phase spectrum was produced to measure the time lag between receivers. Using the phase difference method, an experimental dispersion curve was generated. Inversion analysis based on the 3-D stiffness matrix method was then performed to produce a shear wave velocity profile. The elastic modulus of pavement layers was calculated based on linear elastic theory. In the Falling Weight Deflectometer test, seven geophones were used to collect in situ deflection data. Based on a back-calculation procedure with the ELMOD software, the elastic modulus of each flexible pavement layer can be obtained. Both techniques are able to comprehensively investigate the elastic modulus of the subgrade layer in existing pavement non-destructively. The elastic modulus between the Spectral Analysis of Surface Wave method and the Falling Weight Deflectometer test on the subgrade layer is observed to be in a good agreement. A correlation of the elastic modulus of thesubgrade layer from both techniques is also presented.

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.

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.

Static and Dynamic Backcalculation Analyses of an Inverted Pavement Structure

2013 ◽  
Vol 723 ◽  
pp. 196-203 ◽  
Author(s):  
James Maina ◽  
Wynand JvdM Steyn ◽  
Emile B. van Wyk ◽  
Frans le Roux
Keyword(s):  
South African ◽  
Maintenance Strategy ◽  
Falling Weight Deflectometer ◽  
Non Destructive Testing ◽  
Destructive Testing ◽  
Back Calculation ◽  
The Difference ◽  
Falling Weight ◽  
Non Destructive ◽  
Crucial Part

A crucial part of any maintenance strategy is an intricate understanding of the material characteristics of the pavement, so that the current level of damage may be accurately assessed and an appropriate plan implemented. Advances in the precision to which these parameters can be determined, as well as improvements in how these results are interpreted under varying conditions of measurement and analysis, are essential in the effective execution of a maintenance strategy. Results from Falling Weight Deflectometer (FWD), which is a Non-Destructive Testing (NDT) device, can be used to predict elastic modulus of any layer by comparing measured deflection data to calculated values through an iterative process referred to as back-calculation. This paper presents a comparison between static and dynamic back-calculation procedures, specifically with regard to typical South African inverted pavements. The analysis indicates a dynamic analysis provides results of greater accuracy than a static analysis, although the effect of the difference requires further investigation.

scholarly journals The Application of Frequency-Temperature Superposition Principle for Back-Calculation of Falling Weight Deflectometer

2019 ◽  
Vol 10 (1) ◽  
pp. 132
Author(s):  
Jung-Chun Lai ◽  
Jung Liu ◽  
Chien-Wei Huang
Keyword(s):  
Evaluation Model ◽  
Superposition Principle ◽  
Test Site ◽  
Temperature Correction ◽  
Falling Weight Deflectometer ◽  
Temperature Superposition ◽  
Back Calculation ◽  
Falling Weight ◽  
Frequency Temperature

The falling weight deflectometer (FWD) is a widely used nondestructive test (NDT) device in pavement infrastructure. A FWD test measures the surface deflections subjected to an applied impact loading and the modulus of pavement layers can be determined by back-calculating the measured deflections. However, the modulus of asphalt layers is significantly influenced by temperature; hence, the temperature correction must be considered in back-calculation to evaluate the moduli of asphalt layers at a reference temperature. In addition, the in situ temperature at various pavement depths is difficult to measure. A model for evaluating the temperature at various depths must be established to estimate the in situ temperature of asphalt layers. This study collected the temperature data from a FWD test site to establish a temperature-evaluation model for various depths. The cored specimens from the test site were obtained to conduct dynamic modulus tests for asphalt layers. The FWD tests were applied at the FWD test site and the back-calculation was performed with temperature correction using the frequency-temperature superposition principle. The back-calculated moduli of asphalt layers were compared with the master curve of dynamic modulus to verify the application of the frequency-temperature superposition principle for FWD back-calculation. The results show that the proposed temperature-evaluation model can effectively evaluate the temperature at various depths of pavement. Moreover, the frequency-temperature superposition principle can be effectively employed to conduct temperature correction for FWD back-calculation.

Influence of inertia on falling weight deflectometer (FWD) test response

1995 ◽  
Vol 32 (6) ◽  
pp. 1044-1048 ◽  
Author(s):  
Dieter F.E. Stolle ◽  
Gabriel Sedran
Keyword(s):  
Displacement Field ◽  
Load Distribution ◽  
Structural Integrity ◽  
Inertial Forces ◽  
Falling Weight Deflectometer ◽  
Ritz Vector ◽  
First Order ◽  
Back Calculation ◽  
Falling Weight

This note addresses the appropriateness of adopting an elastostatic model for backcalculating in situ layer moduli from falling weight deflectometer (FWD) data. By approximating the elastodynamic displacement field using an elastostatic solution for a given load distribution, it is shown via Ritz vector analyses that elastostatic fields do not accurately represent the displacements associated with pavements subjected to FWD-type loading. Some improvement is, however, possible by including first-order corrections for inertial forces. The main conclusion stemming from the analyses is that elastostatic models should not be used to estimate in situ moduli. Key words : pavement, elastodynamic analysis, Ritz vectors, back-calculation, structural integrity.

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