Full Depth Reclamation Pavement Structural Evaluation Using Falling Weight Deflectometer
1 Samrat Ashok Technological Institute, Vidisha, Madhya Pradesh, India
Abstract. This report presents the results of a Falling Weight Deflectometer (FWD) evaluation conducted on a rural road section constructed using Full Depth Reclamation (FDR) technology under the PMGSY program in Raebareli District, Uttar Pradesh. The evaluated pavement, built between T08-Nasirabad (T01) and Babhanpur (T03) via Rajapur Garam (Package ID: UP58130), spans 7.20 km and was completed in July 2023 for a design traffic load of 2 million standard axles (MSA). The FDR base incorporated cement along with TerraSil and ZycoBond additives for enhanced stabilization. FWD tests were conducted both pre- and post-monsoon in 2024 to assess seasonal effects on pavement performance. The study used normalized deflection data and back-calculated moduli via KGP BACK software to evaluate structural capacity. Results indicated a slight increase in deflection post-monsoon, likely due to moisture ingress, but the pavement retained satisfactory structural integrity and surface condition. The findings validate the durability of the FDR system and emphasize the role of seasonal monitoring in pavement management.
Keywords: Falling Weight Deflectometer (FWD), Full Depth Reclamation (FDR).
1 Introduction
This report presents the findings of a Falling Weight Deflectometer (FWD) evaluation conducted on a UP FDR package UP58130. The FWD study aimed to assess the structural performance and resilience of the pavement under varying environmental conditions, including pre and post monsoon seasons [9]. The pavement under evaluation was designed for a traffic load of 2 million standard axles and utilized Full Depth Reclamation (FDR) techniques stabilized with TerraSil and ZycoBond additives, along with cement for enhanced durability. FWD testing is a globally accepted non-destructive technique (NDT) for evaluating pavement structural health. It provides critical data on deflection responses and enables back-calculation of the elastic moduli of pavement layers. This method offers a reliable and efficient means of determining the structural integrity of pavements while minimizing disruptions during field data collection.
The objectives of the FWD evaluation for this project were to:
• Measure the elastic moduli of the bituminous layer, FDR base, and subgrade.
• Evaluate the impact of seasonal variations, particularly an increase in moisture contents post-monsoon compared to pre-monsoon, on pavement performance.
• Validate the effectiveness of innovative stabilization techniques using TerraSil and ZycoBond additives, along with cement as a binder in enhancing pavement durability and load distribution. This analysis, conducted in accordance with the standards outlined in IRC: 115-2014 serves as a critical step in understanding the long-term performance of the pavement and its ability to withstand both traffic loads and environmental conditions.
2 Literature Review
Haifeng Wen & Bruce Ramme (2008) made study on “Performance evaluation of Asphalt Pavement with Fly ash stabilized FDR base: A case Study”. The study evaluated the performance of an asphalt pavement with Class C fly ash stabilized full-depth reclaimed (FDR) base. Over six years, strength increased initially due to pozzolanic reactions but declined later from freeze-thaw damage. Top-down and thermal cracking developed early. The M-E design under predicted cracking but accurately estimated rutting.
Ujjval J. Solanki, Pradip J. gundalia, Mansukh D. Barasara (2015). “A review on structural evaluation of flexible pavement using falling weight deflectometer”. The paper reviews structural evaluation of flexible pavements using the Falling Weight Deflectometer (FWD). It highlights FWD's effectiveness in assessing pavement layer moduli, detecting structural deficiencies, and aiding rehabilitation design. The study emphasizes its non-destructive, reliable, and practical approach for modern pavement analysis and maintenance decision-making.
J. Pothalaiah & B. Srikanth (2018). “Determination of structural strength of pavement using FWD and remaining life Analysis”. The paper investigates the use of Falling Weight Deflectometer (FWD) in evaluating pavement structural conditions. It demonstrates how deflection data helps assess layer strength, estimate remaining life, and guide maintenance. The study confirms FWD as a vital non-destructive tool for accurate pavement analysis, promoting cost-effective rehabilitation strategies.
3 Methodology
3.1 Equipment Details
The FWD testing was carried out using a KUAB made FWD machine. The machine is equipped to apply varying load levels, typically ranging from 50 kN to 350 kN, with the standard load used for analysis being 40 kN. This load simulates the impact of traffic on the pavement. The machine also records deflections at multiple sensor points, ensuring accurate data collection [5].
3.2 Sensor Arrangement and Spacing
The FWD machine uses a set of seven geophones, or sensors, placed at specific radial distances from the load plate. These distances ensure a comprehensive measurement of the deflection bowl, capturing both the immediate and far-field effects of the applied load. The sensors are critical for analyzing how the pavement responds to loading at various depths and distances from the load [5].
3.3 Data Collection Protocols
Testing Parameters
The primary testing parameter is the target load, which is normalized to a 40 kN standard load for consistency across all test sites and conditions. The deflection values measured by the sensors are then processed to assess the structural integrity of the pavement [8][9]. The sensor configuration, with sensors placed at varying radial distances, allows for detailed analysis of the deflection profiles. Additional parameters include the pavement's surface temperature and the seasonality of the testing period, as temperature and moisture levels can significantly influence the deflection response of the pavement [6].
Seasonal Conditions
Field testing was conducted during pre-monsoon and post-monsoon periods to capture the influence of seasonal variations on pavement performance.
· Pre-Monsoon Testing: Conducted on July 2nd, 2024, under the dry conditions typical of summer. Raebareli experiences a peak temperature of approximately 40°C in summer.
· Post-Monsoon Testing: Conducted on September 26th, 2024, after the rainy season, to reflect the impact of moisture absorption on pavement behavior. Raebareli experiences an annual average rainfall of approximately 1200 mm.
Temperature and moisture fluctuations between these periods notably influence deflection and modulus values, particularly for bituminous and subgrade layers. These seasonal variations were accounted for during data analysis to ensure accurate interpretation of pavement performance under differing environmental conditions.
The project site is located in Raebareli District, Uttar Pradesh, along the T08-Nasirabad (T01) to Babhanpur (T03) via Rajanpur Garam, with a package ID: UP58130. The road section was constructed by using in-situ technology by M/s Sri Bhawan Construction in July 2023 under the supervision of Zydex Industries Private Limited. This 7.20 km stretch, with a 5.50 m width, consists of 6.650 km of bituminous pavement and 0.550 km of cement concrete pavement. Falling Weight Deflectometer (FWD) evaluations were performed on the bituminous pavement section. For the FDR base, Cement 5.0%, TerraSil 1 kg/cum, and ZycoBond 1 kg/cum were used, mixed with optimal moisture content (OMC) using a recycler, followed by compaction, followed by motor grader, and curing. Additionally, prime coat was applied on the FWD surface, and then a Stress Absorbing Membrane Interlayer (SAMI) with a geosynthetic fabric was employed at the interface between the FDR base and the bituminous concrete layer to enhance structural performance and mitigate reflective cracking. No significant maintenance or rehabilitation treatments were carried out prior to this evaluation, as the pavement was newly constructed and subjected to one monsoon cycle. Pre-monsoon FWD testing was conducted on July 2nd, 2024. While post-monsoon testing occurred on September 26th, 2024. These evaluations aimed to assess the structural integrity and durability of the pavement under varying seasonal conditions, offering insights into the effectiveness of the stabilization method used [9]. The cross-section of the existing pavement illustrating the thicknesses of structural layers is shown in Fig. 1.
Fig. 1. Cross-section of the FDR Pavement (Package ID: UP58130)
A visual inspection of the road indicated that it is in good condition, with no significant signs of distress or deterioration observed on the surface. The pavement exhibits a smooth and even texture, free from visible cracks, potholes, or rutting. Road appear to be functioning effectively, with no water accumulation or signs of erosion along the shoulders. Overall, the road’s structural and functional performance suggests that it is adequately serving its intended purpose without the need for immediate maintenance or repairs. The visuals of the road pre and post monsoon are shown in Fig. 2.
Fig. 2. Pre-monsoon (02-July-2024) and Post-monsoon (26-September-2024)
Data Normalization and Processing.
To ensure that the FWD data is comparable across various conditions, normalization is applied to adjust the measured deflections to a standard load condition [6]. In this case, the data is normalized to a target load of 40 kN, which corresponds to the load typically applied by a dual-wheel set of an 80 kN standard axle. The procedure to normalize the FWD deflection data follows these steps:
Collection of Raw Deflection Data. The deflections were recorded at seven radial distances (D0 to D6) using the FWD machine. This includes the deflection response from the pavement layers to a loading pulse. The impact load used in this study was approximately 40KN. The pavement surface deflections were recorded by seven sensors located at 0, 0.2, 0.3, 0.45, 0.6, 0.9, and 1.2m from the center of loading plate [4].
Normalization. The deflection values, initially measured at different load levels, were adjusted to reflect the response of the pavement to the standard target load of 40 kN. This adjustment was performed according to the method prescribed in IRC: 115-2014, ensuring that all deflections were standardized to a comparable loading condition, enabling the assessment of the pavement's performance across varied field conditions [5][7].
5.1 Back-calculation of Layer Moduli
The back-calculation process involves deriving the modulus values of various pavement layers (bituminous layer, Full Depth Reclamation (FDR) base, and subgrade) from the normalized deflection data. This analysis is crucial for understanding the structural integrity of the pavement and its ability to withstand traffic loads over time [3].
Back-Calculation Tool. The KGP BACK software was used to perform the back-calculation of the moduli values from the normalized deflections. This software uses the deflection data and a set of assumed layer moduli (called seed values) to iteratively calculate the elastic moduli for each pavement layer [3].
Seed Modulus Values and Assumptions. For the bituminous layer, seed modulus values were chosen within the range of 500-3500 MPa. For the FDR base (which includes cement binder, TerraSil and ZycoBond additives), the seed modulus values were set between 100 & 10,000 MPa. For the subgrade layer, the seed modulus values ranged from 20 to 300 MPa [9]. These seed values were selected to provide a realistic initial estimate of the moduli for the iterative back-calculation process. The wide range of seed values is particularly important for addressing the gradation variability and improving the accuracy of the back-calculation, as KGP BACK software does not directly output the goodness-of-fit or quantify relative error during convergence [4].
Correction Factors Applied. Temperature Corrections for Bituminous Layers: Temperature correction ensures that the modulus values reflect the material's true performance at a standard reference temperature. However, no temperature correction is necessary for thin bituminous layers (less than 40 mm thick), as specified in IRC 115-2014.
Seasonal Corrections for Subgrade Layers. The modulus of subgrade layers is highly sensitive to moisture content, which fluctuates with seasonal changes. For the summer/pre-monsoon data, a seasonal correction was applied to the subgrade modulus to account for the lower strength of the subgrade when it is moist during the monsoon season. This is particularly important as the subgrade is generally at its weakest during this time. For the post-monsoon data, no seasonal correction was applied, as the moisture content had stabilized, reflecting typical subgrade conditions after the monsoon season. These correction factors were applied according to the recommendations in IRC 115-2014 to ensure that the back-calculated modulus values are accurate and reflective of the pavement's performance during different seasonal conditions.
Final Moduli Values. After applying these corrections and back-calculating the moduli for each layer, the final moduli values for the pre-monsoon and post-monsoon conditions were calculated. The average modulus values were derived for the bituminous layer, FDR base, and subgrade layers, providing insights into the structural behavior of the pavement under both dry and wet conditions.
6 Results and Discussions
6.1 Deflection Data Summary
The deflection bowl data for pre and post monsoon seasons are shown in Fig. 3 and 4, respectively. The average deflection values recorded at D0 before and after the monsoon were 0.406 mm and 0.477 mm, respectively, showing a slight increase due to moisture effects during the monsoon.
.png)
Fig. 3. Pre-monsoon deflection bowl data
Fig. 4. Post-monsoon deflection bowl data
6.2 Back-calculated Moduli for Pavement Layers
The back-calculated modulus values for the pavement layers (bituminous, FDR base, and subgrade) were determined using the normalized deflection data and processed with KGP BACK software [3]. The analysis included temperature corrections for the bituminous layer and seasonal corrections for the subgrade to reflect the moisture content variations due to the monsoon. The back-calculated layer moduli for each chainage are presented in Table 1 for the pre-monsoon condition and in Table 2 for the post-monsoon condition.
Table 1. Pre-monsoon corrected back-calculated moduli
Lane | Chainage | Pavement Temp. | Corrected Modulus (MPa) | |||
Bituminous Layer | FDR Base | Subgrade | ||||
RHS | 0 | 44 | 629 | 806.5 | 122.8 | |
LHS | 50 | 44.3 | 1165.7 | 371 | 151.3 | |
Centre | 265 | 43.8 | 3456 | 245.2 | 121.2 | |
RHS | 500 | 44.1 | 546.9 | 419.4 | 90.9 | |
LHS | 750 | 42.9 | 3089.4 | 1067.7 | 141.4 | |
RHS | 1000 | 45.4 | 1447.2 | 729 | 116.1 | |
LHS | 1250 | 45.1 | 3054.3 | 941.9 | 166.6 | |
LHS | 1500 | 41.8 | 3001.5 | 3690.3 | 119.2 | |
RHS | 1751 | 44.5 | 1673 | 893.5 | 125.9 | |
LHS | 2000 | 45 | 2907.6 | 1435.5 | 70.7 | |
Centre | 2250 | 43.5 | 1470.7 | 912.9 | 162.5 | |
RHS | 2750 | 44.6 | 3409.1 | 167.7 | 73.5 | |
LHS | 3000 | 43.4 | 699.4 | 1193.5 | 89.3 | |
Centre | 3250 | 43.4 | 3180.4 | 477.4 | 165.9 | |
RHS | 3500 | 44.8 | 816.7 | 390.3 | 127.5 | |
LHS | 3750 | 44.6 | 505.9 | 332.3 | 123.1 | |
Centre | 4000 | 44.9 | 617.3 | 564.5 | 77.7 | |
RHS | 4250 | 43.5 | 2350.4 | 612.9 | 200 | |
LHS | 4500 | 40.8 | 3417.9 | 3012.9 | 117.5 | |
Centre | 4750 | 40.7 | 3435.5 | 9951.6 | 200 | |
RHS | 5000 | 43.3 | 1250.7 | 806.5 | 139.6 | |
LHS | 5250 | 45 | 3277.1 | 806.5 | 134.4 | |
Centre | 5500 | 44.8 | 1397.4 | 709.7 | 131 | |
RHS | 5750 | 45.7 | 3045.5 | 312.9 | 122.9 | |
LHS | 6000 | 43.8 | 3283 | 1387.1 | 199.8 | |
Centre | 6250 | 42.8 | 3365.1 | 4271 | 151.6 | |
RHS | 6500 | 41 | 2714.1 | 3922.6 | 144.2 | |
Centre | 7000 | 44 | 3033.7 | 758.1 | 176.8 | |
LHS | 7157 | 45 | 3461.9 | 593.5 | 156.2 | |
Centre | 7142 | 44.6 | 3473.6 | 506.5 | 134.9 | |
Average | 2366 | 1575 | 135 | |||
15th Percentile | 3410 | 3047 | 166 | |||
Table 1. Modulus valve for bitumen layer observed moderate to high stiffness, possibly due to fresh or well compacted bituminous layer. Modulus value for FDR base within expected range, some low values may indicate moisture or gradation issues. While subgrade modulus value is acceptable.
Table 2. Post-monsoon corrected back-calculated moduli
Lane | Chainage | Pavement Temp. | Corrected Modulus (MPa) | ||||
Bituminous Layer | FDR Base | Subgrade | |||||
CENTRE | 0 | 34.2 | 756.6 | 4522 | 95.6 | ||
LHS | 51 | 34.2 | 754.4 | 4739.5 | 100 | ||
LHS | 250 | 34.2 | 772 | 4548.9 | 99.8 | ||
CENTRE | 500 | 34.1 | 750 | 4597.8 | 99.7 | ||
RHS | 750 | 34.2 | 752.2 | 6909.6 | 100 | ||
LHS | 1000 | 34.4 | 765.4 | 4531.8 | 100 | ||
CENTRE | 1250 | 34.4 | 868.8 | 6904.7 | 100 | ||
LHS | 1750 | 34.5 | 767.6 | 6161.8 | 100 | ||
CENTRE | 2000 | 34.4 | 774.2 | 4504.9 | 99.6 | ||
RHS | 2250 | 34.3 | 752.2 | 4512.2 | 72.9 | ||
RHS | 2252 | 34.4 | 750 | 4507.3 | 72.6 | ||
LHS | 2500 | 34.3 | 765.4 | 4534.2 | 75.9 | ||
CENTRE | 2750 | 34.1 | 750 | 4519.6 | 80.4 | ||
RHS | 3000 | 34.2 | 772 | 4514.7 | 95 | ||
LHS | 3250 | 34.2 | 756.6 | 4517.1 | 99.3 | ||
LHS | 3508 | 34.3 | 765.4 | 4519.6 | 98.4 | ||
RHS | 3750 | 34.4 | 752.2 | 4514.7 | 99.9 | ||
LHS | 4000 | 34.4 | 769.8 | 4500 | 92.9 | ||
LHS | 4002 | 34.3 | 772 | 4509.8 | 73.9 | ||
CENTRE | 4250 | 34.2 | 833.6 | 4509.8 | 100 | ||
CENTRE | 5000 | 34.3 | 805 | 4502.4 | 100 | ||
RHS | 5250 | 34.4 | 796.2 | 4607.5 | 100 | ||
CENTRE | 5500 | 34.5 | 750 | 4539.1 | 98 | ||
RHS | 5750 | 34.5 | 796.2 | 4575.8 | 100 | ||
RHS | 7000 | 34.5 | 2819.6 | 6941.3 | 100 | ||
CENTRE | 7200 | 34.1 | 785.2 | 4566 | 100 | ||
15th Percentile | 752 | 4509 | 79 | ||||
Average | 852 | 4877 | 94 | ||||
| |||||||
Table 2. Modulus valve for bitumen layer observed slightly lower than typical-likely due to temperature or aging. Modulus value for FDR base within expected range, indicate excellent consistency and stiffness, good stabilization. While subgrade modulus value is acceptable range, indicate moderately strong subgrade.
7 Conclusions
The significant role of TerraSil and ZycoBond in stabilizing the Full Depth Reclamation (FDR) base layer is effectively demonstrated through Falling Weight Deflectometer (FWD) evaluations. The analysis of pavement performance under seasonal conditions provided valuable insights into its structural behavior and resilience. FWD evaluations showed a marginal increase in deflections post-monsoon due to moisture-induced effects; however, the values remained well within acceptable limits. The structural integrity of the FDR stabilized base layer was confirmed by comparing the back-calculated moduli with the design moduli. Seasonal variations in deflections and moduli, particularly in cement-only stabilized bases, underscore the necessity of incorporating moisture-resistant stabilization techniques to ensure strength and durability in wet conditions.
8 ACKNOWLEDGEMENT
I take this opportunity to express my thanks to Dr. Rajeev Jain, Professor and Head, Department of Civil Engineering, for extending every possible help and support during the experimental work. I am especially thankful to Dr. Y.K. Jain, Director, SATI, Vidisha. Also, Dr. Ajay Ranka, Managing Director, Zydex Industries Pvt. Ltd., for their kind cooperation and rendering me all possible facilities.
9 References
1. Haifeng Wen & Bruce Ramme (2008) made study on “Performance evaluation of Asphalt Pavement with Fly ash stabilized FDR base: A case Study”
2. Ujjval J. Solanki, Pradip J. gundalia, Mansukh D. Barasara (2015). “A review on structural evaluation of flexible pavement using falling weight deflectometer”.
3. J. Pothalaiah, B. Srikanth.: Determination of structural strength of pavement using FWD and remaining life analysis, International Journal for Modern Trends in Science and technology, vol., Issue 06. June (2018).
4. Shubham karole (2024). “Stabilisation in pavement- design, performace & economy”. Indiairf.com
5. IRC: 115-2014 “Guidelines for strengthening of flexible road pavements using falling weight deflectometer (FWD) technique” Published by Indian Roads, Congress, New Delhi, India.
6. C. Kishore Kumar,D. S. N. V. Amar kumar,M. Amaranatha reddy &K. Sudhakar Reddy (2008). “Investigation of cold-in-place recycled mixes in India”. International Journal of Pavement Engineering, Vol. 9,
7. Aditya Singha , Akash Sharmab , Tanuj Chopra (2019). “Analysis Of The Flexible Pavement Using Falling Weight Deflectometer For Indian National Highway Road Network”. World Conference on Transport Research - WCTR 2019 Mumbai 26-31 May 2019.
8. Aswani K. Haridas, Naga Siva Pavani Peraka, Krishna Prapoorna Biligiri (2022). “Structural Behavior Prediction Model for Asphalt Pavements: A Deep Neural Network Approach”. ASME, Paper no. JTE20210804.
9. Zul Fahmi Bin Mohamed Jaafar (2019). “Computational Modeling and Simulations of Condition Deterioration to Enhance Asphalt Highway Pavement Design and Deterioration to Enhance Asphalt Highway Pavement Design and Asset Management”. University of Mississippi University of Mississippi.
Comments
Post a Comment