In an accelerated full-scale experiment on three asphalt pavements with different interlayer conditions (unreinforced reference, 100 kN-grid, 50 kN-grid), Le et al. (2023) showed that a damage ratio derived from Falling Weight Deflectometer (FWD) back-calculated asphalt moduli tracks fatigue evolution well, but the backcalculation treated the two asphalt layers as one fully bonded layer, so the resulting modulus is an apparent value in which true material stiffness loss from fatigue cracking cannot be separated from changes in interface bonding (partial bonding or debonding). The open problem is to characterize damage faithfully in pavements with imperfect interfaces: determining whether apparent stiffness reductions can be attributed to fatigue cracking versus interface debonding; destructive (coring, trenching) verification of the modeled cracking-versus-debonding patterns; extension of the ASTSs in-situ stiffness-evaluation procedure and its temperature correction beyond one structure, one material set and a narrow temperature window; assessment of whether the circa 50% stiffness-loss threshold for surface-cracking onset is general or structure- and interface-specific; and accounting for instrumentation-induced damage, which biases the measured response.

Background

Asphalt pavements are multilayer systems in which a bituminous base course is covered by one or more surface courses, typically with a tack coat ensuring that adjacent layers act compositely. The degree of bonding at these layer interfaces is a structural variable, not a detail: perfect bonding makes the layers behave as one thick beam, while partial bonding or full debonding (delamination) redistributes strains, raises tensile stresses near the interface, and can strongly accelerate cracking. Geosynthetic reinforcement grids (characterized here by their tensile stiffness, 100 kN/m and 50 kN/m glass grids) are often embedded at the interface to retard such cracking.

Accelerated pavement testing (APT) studies these mechanisms at full scale: a circular test track (the fatigue carousel of Université Gustave Eiffel, Nantes) applies millions of controlled heavy wheel loads to instrumented pavement sections, reproducing decades of traffic in months. Le et al. (2023) analyzed three such sections, identical except for the interface condition between the two asphalt layers (total about 11 cm): an unreinforced reference and two grid-reinforced variants. Pavement response was monitored by three complementary non-destructive observations: embedded asphalt strain gauges, Falling Weight Deflectometer (FWD) tests (a trailer-mounted device that drops a weight on the pavement and records the surface deflection basin with geophones), and photographic surface-crack mapping.

Because asphalt is linear viscoelastic (LVE) — its stiffness depends on both temperature and loading frequency, conventionally summarized by a laboratory master curve or by isotherm curves at fixed temperature — in-situ stiffness evaluation must account for the speed of passing loads. The paper introduced the ASTSs procedure (Asphalt layer Stiffness from measurements at different Traffic Speeds), which back-analyzes gauge strain signals measured at several traffic speeds, using a layered elastic calculation (ALIZE-LCPC software, based on Burmister's multilayer elastic theory), to determine in-situ asphalt stiffness isotherms without prior laboratory LVE characterization of the material.

Layer moduli themselves are routinely estimated from FWD data by backcalculation: an inverse analysis that adjusts layer moduli in a multilayer elastic model until computed and measured deflection basins match. Crucially, Le et al.'s backcalculation combined the two asphalt layers into a single equivalent layer, i.e. assumed a fully bonded interface in all three sections, and the authors emphasize that the resulting modulus is an apparent value reflecting field conditions, not the material modulus. From these apparent moduli (temperature-corrected to a reference state, an approximation the authors validated only for the 12–19 °C range of their FWD campaigns), they defined a damage ratio Di=1−Ei/E0D_i = 1 - E_i/E_0 relative to the initial condition, which successfully tracked the pavement from an initial stiffening phase (aging, post-compaction) through fatigue degradation, and compared it with the onset of visible surface cracking.

Two findings define the open problem. First, local strain-gauge responses were unusable as average-damage indicators because they mix fatigue cracking near the gauge, interface-bonding changes and the resulting strain redistribution; earlier layer-wise numerical simulations of damage scenarios on the same experiment (Chupin et al. 2020, using the M4-5n layer-wise model — a simplified plate-type pavement model) could propose, but not verify, how cracking and debonding developed. Second, surface cracking appeared at about 50% stiffness loss (damage ratio) in the instrumented subsections — consistent with the assumption built into the French pavement design method's fatigue criterion — but at lower, section-specific levels (about 37% and 18%) in the non-instrumented subsections, and the instrumented zones cracked more than the non-instrumented ones, indicating that the gauges themselves initiate damage. The cracking-versus-debonding attribution, the generalization of the stiffness-based indicators to other structures, materials and temperatures, and the status of the cracking threshold therefore all remain unresolved.

Problem Statement

How can fatigue damage evolution in asphalt pavements whose layer interfaces degrade be characterized faithfully from non-destructive monitoring? Le et al. (2023) established a stiffness-modulus-based damage indicator for full-scale pavements with different interface conditions, but its backcalculation assumed a single fully bonded asphalt layer, leaving apparent modulus reductions ambiguous between true material fatigue (cracking) and interface debonding; with a backcalculation that treats the asphalt layers as fully bonded and strain-gauge responses that mix the two mechanisms, the measured responses alone do not determine the influence of each mechanism (fatigue cracking or interface debonding). The central open problem is this attribution of apparent stiffness loss to cracking versus debonding. The associated open needs comprise: (1) determining whether apparent stiffness reductions can be attributed to fatigue cracking versus interface debonding; (2) destructive ground-truth verification: further detailed destructive investigations (coring, or cutting of trenches) for verification of the best modeled cracking/debonding pattern scenario from numerical damage-scenario simulations such as the M4-5n computations of Chupin et al. (2020); (3) generalization of the ASTSs in-situ stiffness-evaluation procedure and its temperature-correction approach, obtained for one asphalt thickness (about 11 cm) and a limited temperature range, with the correction a first approximation declared reasonable only for the 12–19 °C of the FWD campaigns, to other pavement structures, with different asphalt thicknesses, and to a larger temperature range; (4) determining whether the circa 50% stiffness-loss threshold for surface-cracking onset observed in instrumented subsections (with lower section-specific levels of about 37% and 18% observed without instrumentation) is broadly applicable across pavement types, interface systems and environmental conditions, or whether section-specific thresholds are required; and (5) accounting for instrumentation-induced damage: strain-gauge installation can create defects in the pavement layer and initiate cracking, and instrumented subsections cracked more than non-instrumented ones, so damage indicators measured at instrumented zones are biased by the instrumentation itself. Needs (2)–(5) are related extensions of that central attribution problem.

References

  1. Le, X. Q., Nguyen, M. L., Hornych, P., & Nguyen, Q. T. (2023). Analysis of LVE behaviour and fatigue damage evolution of asphalt pavements with different interface conditions in an accelerated full-scale experiment. International Journal of Pavement Engineering, 24(2), 2147522. https://doi.org/10.1080/10298436.2022.2147522
  2. Chupin, O., Piau, J.-M., Chabot, A., Nasser, H., Nguyen, M. L., & Lefeuvre, Y. (2020). Simulation of Damage Scenarios in a Bituminous Pavement Tested Under FABAC ALT Using M4-5n. In Accelerated Pavement Testing to Transport Infrastructure Innovation, Lecture Notes in Civil Engineering, vol. 96, pp. 389–398. Springer. https://doi.org/10.1007/978-3-030-55236-7_40
  3. Nguyen, M. L., Blanc, J., Trichet, S., Gouy, T., Coirier, G., Baudru, Y., Le, X. Q., Nguyen, M. D., Siroma, R. S., Hornych, P., & Blaineau, F. (2020). Rapid and Continuous Imaging for Crack Monitoring During APT Experiments. In Accelerated Pavement Testing to Transport Infrastructure Innovation, Lecture Notes in Civil Engineering, vol. 96, pp. 649–657. Springer. https://doi.org/10.1007/978-3-030-55236-7_67
  4. Nguyen, M. L., Chupin, O., Blanc, J., Piau, J.-M., Hornych, P., & Lefeuvre, Y. (2020). Investigation of Crack Propagation in Asphalt Pavement Based on APT Result and LEFM Analysis. Journal of Testing and Evaluation, 48(1), 161–177. https://doi.org/10.1520/JTE20180933
  5. Le, X.-Q., Nguyen, M. L., Hornych, P., Blanc, J., & Nguyen, Q. T. (2026). Evaluation of pavement performance using a probabilistic design approach with application based on accelerated pavement testing data. Road Materials and Pavement Design (online first). https://doi.org/10.1080/14680629.2026.2664603
  6. Wang, M., Chen, C., Yu, X., Zhou, X., Zhu, H., & Song, J. (2025). The influence of interlayer voids on the mechanical behavior of semi-rigid base asphalt pavement based on continuous-discrete coupled simulation. International Journal of Pavement Engineering, 26(1), 2582711. https://doi.org/10.1080/10298436.2025.2582711
  7. He, Y., Lv, S., Wang, Z., Ma, H., Lei, W., Pu, C., Meng, H., Xie, N., & Peng, X. (2023). Research on the Modulus Decay Model under a Three-Dimensional Stress State of Asphalt Mixture during Fatigue Damage. Buildings, 13(10), 2570. https://doi.org/10.3390/buildings13102570
  8. Deng, Y., Zhang, Y., & Shi, X. (2023). Feasibility of determining asphalt pavement condition from falling weight deflectometer test and finite element model updating. Philosophical Transactions of the Royal Society A, 381(2254), 20220168. https://doi.org/10.1098/rsta.2022.0168
  9. Park, B., Chun, S., & Kim, K. (2023). Effect of various interface bonding conditions on critical response characteristics for cracking potential of asphalt pavements. Road Materials and Pavement Design, 24(8), 2010–2026. https://doi.org/10.1080/14680629.2022.2117065
  10. Qiu, X., Yang, Q., & Hu, Y. J. (2010). Influence of Layer Interface Condition on Modulus Backcalculation Results of Semi-Rigid Asphalt Pavement. Advanced Materials Research, 168–170, 1277–1280. https://doi.org/10.4028/www.scientific.net/AMR.168-170.1277
  11. Sun, Q., Zhao, Y., Peng, X., & Li, B. (2026). Characterisation of interlayer contact behaviour in asphalt pavements via pavement system transfer function analysis. Nondestructive Testing and Evaluation (online first), 1–35. https://doi.org/10.1080/10589759.2026.2668636
  12. Liu, W., Yang, X., Pan, J., Wang, H., Wang, J., Jiang, R., & Zhao, Z. (2026). Automatic detection of large-scale pavement layer debonding via light-weight deep multi-view learning model and B-scan composite images. Nondestructive Testing and Evaluation (online first), 1–30. https://doi.org/10.1080/10589759.2026.2678564