Exploring capacitance-based stress and deformation sensing in asphalt for smart infrastructure
Nondestructive Testing and Evaluation, vol.41, no.6, pp.3541-3558, 2026 (SCI-Expanded, Scopus)
- Publication Type: Article / Article
- Volume: 41 Issue: 6
- Publication Date: 2026
- Doi Number: 10.1080/10589759.2025.2530089
- Journal Name: Nondestructive Testing and Evaluation
- Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aerospace Database, Applied Science & Technology Source, Aquatic Science & Fisheries Abstracts (ASFA), Communication Abstracts, Compendex, INSPEC, Metadex, Civil Engineering Abstracts
- Page Numbers: pp.3541-3558
- Keywords: asphalt, deformation monitoring, electromechanical characterisation, stress self-sensing, Structural health monitoring (SHM)
- Bursa Uludag University Affiliated: Yes
Abstract
This study investigates capacitance-based self-sensing for monitoringstress and deformation in asphalt materials. Cylindrical asphaltsamples equipped with aluminium foil electrodes undergo compressiveand tensile loading while capacitance is measured in real time. Theresults show that capacitance effectively tracks the mechanicalresponse of asphalt. Under cyclic compressive loading, thecapacitance changes reversibly, indicating that the material remainswithin the elastic deformation range without permanent damage. Stresssensitivity is observed in two regimes: 9.07 × 10-6 P-1at low stress (1.5–7.5 kPa) and 0.22 × 10-6 P-1 athigh stress (17.5–87.5 kPa), suggesting higher sensitivity atlower stress levels. In tensile tests, the specimens experiencesplitting tensile failure, with a clear decrease in capacitance asdeformation increases. The maximum deformation sensitivity, definedas the fractional decrease in capacitance per unit deformation,reaches 8.75 × 10-2mm-1 at a load of 5.6 kN—approximately one order of magnitude higher than thestress sensitivity. A strong correlation (R² = 0.96) betweendeformation and capacitance change confirms the robust sensingcapability. These findings demonstrate the potential of asphalt toserve as a self-sensing material for smart infrastructure andstructural health monitoring applications, without requiring theintegration of additional functional materials.