University of Twente Student Theses
Evaluating Sensor Technologies for Use in Asphalt Pavement Engineering
Asghari, K. (2025) Evaluating Sensor Technologies for Use in Asphalt Pavement Engineering.
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| Abstract: | The need for durable, sustainable pavements under increasing traffic loads focuses attention on the need for innovative monitoring and maintenance solutions for asphalt infrastructure. Traditional monitoring methods cannot provide the real-time, continuous data that will be needed to address modern challenges. Advanced sensor technologies discussed in this paper offer opportunities for revolutionizing asphalt pavement engineering. Carried out in cooperation with Heijmans, one of the leading construction firms, the research focuses on the use of state-of-the-art systems in monitoring pavement health: fiber optic sensors, self-sensing materials, and wireless sensor networks. A combination of systematic literature review and multi-criteria analysis was therefore conducted to evaluate the sensor technologies based on sensitivity, accuracy, cost, durability, sustainability, and readiness level. FBG and DOFS sensors were identified to be blessed with high accuracy and sensitivity during the monitoring process of stress, strain and temperature in real time. Of these, self-sensing asphalt with the inclusion of conductive additives like carbon nanotubes and fibers presented intrinsic capabilities for structural deformation and damage detection without external sensors. Wireless sensors such as SmartRock and Smart Aggregates provided localized monitoring of the stress conditions with data transmission; however, these require further field validation to demonstrate robustness for practical applications. Key findings are that integration into asphalt is challenging with regard to durability in extreme environmental/operational conditions and the cost barrier to large-scale deployment. Even within such limitations, the research identifies promising pathways to advance construction quality and prolong pavement lifespan. This will involve recommendations for optimization in sensor placement strategy, standardization of embedding techniques, and utilization of data analytics for predictive maintenance. It shows in the study the urgency for combined efforts between academia and industry to remove the existing obstacles and accelerate intelligent sensing systems applied in asphalt pavement engineering. This research contributes to the advancement of sustainable and smart infrastructure solutions, paving the way for improved road performance, reduced maintenance costs, and enhanced transportation safety. |
| Item Type: | Essay (Bachelor) |
| Faculty: | ET: Engineering Technology |
| Programme: | Civil Engineering BSc (56952) |
| Link to this item: | https://purl.utwente.nl/essays/105325 |
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