Falling Weight Deflectometer Test Data Research Articles

Development of FWD based hybrid back-analysis technique for railway track condition assessment

Track substructure is a key component of the railway transportation system. Similar to the built environment of other surface transportation systems, track substructures are subjected to aging and deterioration. This, frequently leads to the failure and collapse of the transportation systems, resulting in the imposition of costly repairs and maintenance. At the same time, the emergence of high-speed trains and heavier axle loads, together with a need for sustainable designs, has put additional pressure on asset owners. It has been shown that frequent condition assessments of railway substructures can considerably reduce the overall annual maintenance costs. Furthermore, limited knowledge of the substructure condition leads to the employment of inefficient, time-consuming, and expensive maintenance actions. Therefore, development of time- and cost-efficient techniques to frequently monitor existing railway track substructures is vital. The falling weight deflectometer (FWD) is recognised as an effective non-destructive test used to survey ballasted railway substructures through a back-analysis process. This paper presents a novel hybrid back-analysis technique that includes an artificial neural network (ANN) and genetic algorithm (GA) to estimate the substructure layer moduli of railway tracks using FWD testing data. To this aim, firstly a dynamic finite element (FE) model was developed and validated against experimental data from the literature. This FE model then were employed to generate a reliable dataset to train the ANN. In the next step, GA was employed as an optimisation tool within the back-analysis technique/framework to optimise the layer moduli (the ANN’s input). A comparison study was performed to evaluate the performance of the developed technique. The results of this comparison revealed excellent performance and robustness of the developed technique.

Using FWD deflection basin parameters for network-level assessment of flexible pavements

ABSTRACT Decisions regarding the selection and implementation of appropriate pavement rehabilitation methods is usually based on pavement functional and structural condition data. Visual distress surveys and Falling Weight Deflectometer (FWD) testing are often carried out by agencies as parts of their pavement preservation programmes. Although backcalculation of individual layer moduli from FWD data is a common approach to assess a pavement’s structural condition, the accuracy of this approach is largely dependent on exact estimates of individual layer thicknesses. Coring operations to determine pavement layer thicknesses require significant time and resource commitments, and hence cannot always be accommodated within an agencies’ operational constraints. Accordingly, alternative analysis methods to assess the pavement’s structural condition from FWD data are often desired. An ongoing research study at Boise State University is focusing on combined usage of pavement structural and functional evaluation data for making pavement rehabilitation decisions. Considering the lack of pavement layer thickness information for all locations, this study is using Deflection Basin Parameters (DBPs) calculated from FWD test data to make inferences regarding the structural condition of individual pavement layers. This manuscript presents findings from this study, and establishes DBPs as reasonable alternatives to be used in network-level pavement condition evaluation practices. The adequacy of DBPs to assess the structural condition of individual pavement layers was first assessed through Finite-Element Modelling. A series of analyses were performed by assigning typical modulus values to individual pavement layers, and the corresponding DBPs were calculated. The calculated DBP values mostly fell within typical ranges specified in the literature for different layer conditions. Once the DBPs were established as adequate alternatives for making network-level pavement assessment decisions, four selected pavement sections in the state of Idaho were analyzed based on this method, and the results were compared against those obtained from visual distress assessment routines.

The effect of insulation layers on pavement strength during non-freeze–thaw season

This paper examines the effect of integrating insulation layers on pavement strength using falling weight deflectometer testing data conducted on an instrumented test road in Edmonton, Alberta, Canada. The insulated sections of this road consisted of a -metre-thick bottom ash layer and two polystyrene layers at thicknesses of 5 and 10 cm, while the adjacent conventional section functioned as the control section (CS). For the purpose of strength comparison, the effective modulus and structural number of insulated sections were compared to a conventional CS in a non-freeze–thaw season. The durations of pavement freezing, recovering and fully recovered (non-freeze–thaw) periods were established by monitoring the moisture variations in different pavement layers. The results indicated that using insulation layers generally reduces pavement strength, and this reduction is more pronounced in the insulated section with thicker polystyrene.

Field and Laboratory Determination of Subgrade Resilient Modulus and its Application in Pavement Design

This paper presents a comparison study of the experimental results from the falling weight deflectometer (FWD) test and laboratory resilient modulus test on granular subgrade materials and its application in flexible pavement design. Field and laboratory testing programs were conducted to develop a practical methodology for estimating resilient modulus (Mr) values of subgrade soils for use in the design of pavement structures. Soil characterization database was established for lab testing. A multiple regression model can be used to predict Mr value using several factors including soil properties, soil type and state of stresses for three popular American Association of State Highway and Transportation Officials (AASHTO) soil types (A-4, A-6, and A-7-6) in Indiana, and these prediction models developed were verified compared with laboratory Mr tests with high R2 value. In situ Mr seasonal variation based on abundant FWD test data in five field testing sites spread in Indiana was conducted in order to find the correlation between resilient modulus, temperature, and precipitation for the period from 2006 to 2012. The proposed method can accurately predict subgrade Mr of lab testing. However results from lab testing are significantly lower than recommended range by mechanistic-empirical pavement design guide (MEPDG) and backcalculation one using an adjust factor of 3. The design examples showed that the seasonal variation of temperature and precipitation as well as traffic can affect the design thickness by as much as 15 to 20 % in general. The findings of this study are expected to be helpful in the implementation of the pavement design in Indiana and elsewhere.

Evaluation of Seasonal Variation in Mechanistic Responses of Flexible Pavements through use of Falling Weight Deflectometer Data

Flexible pavements in cold regions with frequent freeze and thaw cycles are prone to damage at the start of thawing and during the thaw–recovery season every year. In an attempt to limit damage to the pavement, many highway agencies enforce a spring road ban (SRB) on secondary roads during the thawing period. The Alberta Ministry of Transportation in Canada performs an extensive falling weight deflectometer (FWD) test program during the spring to enhance SRB decision making. This study uses FWD test data from 2000 to 2006 for multiple highway sections in Alberta to investigate the seasonal variation in pavement stiffness and its effect on pavement mechanistic responses. FWD data were used to backcalculate the moduli for the pavement layers, which were then used in multilayer elastic models to predict the pavement critical responses in thawing versus recovery periods. Asphalt Institute models were used to relate the pavement critical responses to fatigue cracking life (Nf) and rutting life (Nd) in thawing versus recovery periods. Nf and Nd dropped by as much as 80% for fatigue cracking and 95% for rutting in the thawing period compared with the recovery period. Further analysis showed that a 50% reduction in the load applied during thawing can result in an approximately 90% increase in both Nd and Nf. The Mechanistic– Empirical Pavement Design Guide software was used to simulate SRB by reducing the maximum applied load by 50% in the thawing period. The results showed a 50% increase in pavement life in rutting and in top-down and bottom-up fatigue cracking.

Falling Weight Deflectometer Testing to Determine Relative Damage in Asphalt Pavement Unbound Aggregate Layers

Falling weight deflectometer (FWD) testing is a nondestructive pavement structural evaluation technique routinely performed on highway and airfield pavements to estimate pavement layer properties from measured deflection basins. This paper presents a methodology based on analyzing FWD test data between trafficked and nontrafficked lanes to determine the degradation and rutting potential of flexible pavement unbound aggregate layers in comparison to the subgrade damage. The validity of the approach is demonstrated by analyzing the heavy weight deflectometer (HWD) data obtained from the FAA's National Airport Pavement Test Facility (NAPTF) flexible airport pavement test sections built with substantially thick unbound aggregate base–subbase courses. The modified base damage index and base curvature index defined from HWD pavement deflection basins were used to determine relative base-to-subgrade damage, which clearly showed evidence of the increased base damage induced in the NAPTF airport pavement layers during trafficking partly due to the applied aircraft gear load wander. This was in accordance with both the individual pavement layer recovered and unrecovered (inelastic or residual) deformation trends identified from analyzing the multidepth deflectometer data collected during trafficking and the post-traffic forensic analysis results, which indicated that a majority of the permanent deformation occurred in the unbound aggregate layers and not in the subgrade. The methodology presented for the detailed analyses of the FWD (or HWD) test data between trafficked and nontrafficked lanes can be effectively used in flexible pavements to detect unbound aggregate layer deterioration and the pavement damage potential due to that deterioration.

Influence of Seed Layer Moduli on Finite Element Method–Based Modulus Backcalculation Results

The determination of pavement layer moduli from falling weight deflectometer test data is known as backcalculation analysis. Generally, backcalculation analysis is unstable–-greatly influenced by several causes of error. They may be categorized as modeling error in the forward analysis, deflection measurement error, or numerical computation error due to instability in the backcalculation procedure, for example. Because of these problems, the seed values selected for layer moduli greatly influence backcalculation results. To reduce the effects of measurement error, truncated singular-value decomposition is used for regularization. Variable scaling, often used in optimization algorithms, is implemented to improve numerical accuracy. A Ritz vector reduction method is used to solve a large system of dynamic equations in dynamic backcalculation efficiently, and various other means are introduced to decrease computational time. Recent updates of Dynamic Back Analysis for Layer Moduli software, first developed in 1993 and whose solver is based on axi-symmetric finite element method, are presented, as are examples of airfield pavement applications. Results are compared with results from Back Analysis for Layer Moduli static backcalculation software, whose solver was developed using multilayered linear elastic theory. Experience indicates that a dynamic backcalculation is superior to static back-calculation. The results from the two methods are presented and compared.

Influence of Seed Layer Moduli on Finite Element Method-Based Modulus Backcalculation Results

The determination of pavement layer moduli from falling weight deflec-tometer test data is known as backcalculation analysis. Generally, back-calculation analysis is unstable—greatly influenced by several causes of error. They may be categorized as modeling error in the forward analysis, deflection measurement error, or numerical computation error due to instability in the backcalculation procedure, for example. Because of these problems, the seed values selected for layer moduli greatly influence backcalculation results. To reduce the effects of measurement error, truncated singular-value decomposition is used for regularization. Variable scaling, often used in optimization algorithms, is implemented to improve numerical accuracy. A Ritz vector reduction method is used to solve a large system of dynamic equations in dynamic backcalculation efficiently, and various other means are introduced to decrease computational time. Recent updates of Dynamic Back Analysis for Layer Moduli software, first developed ...

Verification of falling weight deflectometer backanalysis using a dynamic finite elements simulation

Falling weight deflectometer (FWD) testing is probably the most widely used device for the non-destructive testing of pavements. In many cases, engineers use the FWD test data for the estimation of pavement material properties, assuming a quasi-static approach. Since the verification of such results is often necessary, a dynamic finite element (FE) approach can be used towards this goal. Analytically, data provided by static backanalysis is used as input for 2D and 3D dynamic FE modeling of the FWD test in order to calculate the expected deflection bowl. Comparison of the measured with the calculated deflection bowl may provide a strong indication for the validation of the backanalysed data. Investigation of the application of this approach using field data from new and existing asphalt pavements with two different FWDs and several backanalysis programs as well as data of laboratory tested cores is also presented and discussed.

Dynamic Time Domain Backcalculation of Layer Moduli, Damping, and Thicknesses in Flexible Pavements

A dynamic time domain method was developed to backcalculate the layer moduli, damping ratios, and thicknesses of asphalt pavements from dynamic falling weight deflectometer test data. The method uses the SAPSI program as a forward routine and a Newton-Raphson method for the backcalculation. The advantage of the time domain approach is that SAPSI can match selected features of the measured time histories directly, and inaccurate measurements at the ends of histories can be ignored. The peak deflections and the time lag between the peak of the load and the peak of the deflections at different sensors are matched. The Newton algorithm in MICHBACK is adopted to perform the backcalculation. The new algorithm is capable of backcalculating the moduli, damping ratios, and thicknesses of three-layer flexible pavements reasonably well. Backcalculations based on synthetic time histories generated using SAPSI show excellent stability and accuracy. Backcalculation using measured time histories yields less accurate results. Possible sources for the discrepancies when using field data are addressed.

Comparative Analysis of Using AASHTO and WESDEF Approaches in Back-calculation of Pavement Layer Moduli

This paper presents an evaluation of the falling weight deflectometer testing data using the AASHTO and WESDEF back-calculation procedures. General concepts of each procedure are highlighted, together with data utilized in the analysis. The back-calculated layer moduli and effective structural number (SNeff) of an existing flexible pavement were determined from both procedures and compared to see the difference between the procedures. The average subgrade modulus of resilience (MR) obtained from WESDEF was found to be about 0.7–0.9 of the value obtained from AASHTO with the factor (C) of 1.0. Modulus values obtained from California bearing ratio tests were in close agreement with AASHTO values only when the factor (C) was set to 0.33, the AASHTO recommended value. The analysis also suggests that a similar factor, about 0.5, for WESDEF should be used. WESDEF, without adjustment, produced higher SNeff values compared to AASHTO, with the difference being significant only at higher levels of reliability. This difference could reach 0.44 and 0.66 for reliability levels of 95 and 99%, respectively, and could result in a difference in the overlay thickness by up to 25 and 38 mm, respectively.

Investigation of Performance of Asphalt Pavement with Fly-Ash Stabilized Cold In-Place Recycled Base Course

Class C fly ash is a coal combustion product from lignite or subbituminous coal obtained as a result of the power generation process. In recent years, efforts have been made to incorporate self-cementing fly ash into cold in-place recycled (CIR) asphalt material to improve the structural capacity of asphalt pavement base layers. In this study, asphalt pavements in County Trunk Highway JK in Waukesha County, Wisconsin, were pulverized in place and mixed with fly ash and water to function as a base course. To evaluate the contribution of fly ash to the pavement’s structural performance, nondestructive deflection tests were performed with a KUAB 2m-FWD falling weight deflectometer (FWD) on the outer wheelpath right after construction. The MICHBACK program was used to backcalculate the material properties of pavement layers from FWD measurements of deflection. The average moduli of the materials in the hot-mix asphalt layer, fly ash–stabilized base course, and subgrade were backcalculated. The structural capacity and structural number were also obtained from FWD test data. The structural coefficient of 0.16 was obtained for the fly ash–stabilized base course in the highway. The results of FWD testing indicate that CIR stabilization with self-cementing fly ash is an economical method of recycling flexible pavements and eliminates the need for expensive new granular base courses for road reconstruction.

Lives of Mill-and-inlay Rehabilitation Strategies

The Kansas Department of Transportation and the Kansas Turnpike Authority routinely mill the surfaces of some asphalt concrete (AC) pavements before inlaying as part of the substantial maintenance program. In selecting this strategy, no "life" is assigned due to a lack of methodologies to estimate lives of such strategies. In this paper, the functional and structural lives of mill-and-inlay strategies were analyzed for seven different routes using Falling Weight Deflectometer test data and fatigue tests on AC beams sawn from the test sections. The results show that the "life" of a mill-and-inlay strategy is mostly controlled by serviceability. For high traffic pavements, an optimal mill-and-inlay depth based on fatigue can be found. Cost-effectiveness of this strategy is higher for pavements with high traffic volumes. The strategy did not appear to be susceptible to rutting nor did it appear to cause any damage to the existing pavement layers.

APPLICATION OF ARTIFICIAL NEURAL NETWORK TO BACKCALCULATION OF PAVEMENT STRUCTURE

Structural evaluation of pavement has been conducted from a set of surface deflections measured by a fallingweight deflectometer (FWD). However, because a backcalculation requires repetitive computation, layer modulican not be estimated instantaneously after FWD tests. This study aims to overcome this shortcoming.Selecting three layer pavement as an example structure, artificial neural network is trained to acquireknowledge on relationship among layer modulus, layer thickness and surface deflections. The systemconstructed in this manner is verified by applying the system to FWD test data and by comparing the systemgenerated layer moduli with those obtained from backcalculation.