University of Twente Student Theses


Developing a data-infrastructure for automating the asphalt cooling process analysis

Mora Ordoñez, G.A. (2023) Developing a data-infrastructure for automating the asphalt cooling process analysis.

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Abstract:The construction process of asphalt pavement is divided into four phases: production, transportation, paving, and compaction. All these phases play a role in determining the quality and durability of the asphalt. However, the most crucial is the last phase -compaction- . Here the asphalt is compacted until a pre-determined density is reached. To ensure optimal compaction, operating within a specific temperature range known as the compaction window is essential. Therefore, it is important to acknowledge that the cooling behavior of asphalt during compaction will be influenced by several internal and/or external factors such as ambient temperature, wind speed, mix temperature at delivery, the temperature of subsurface, speed of pavers, roller capacity, type of mixture, and the temperature variation of the mix. Since the compaction phase is often reliant on experience-based decision-making and craftsmanship of on-site operators, a certain level of variability and uncertainty is introduced, which may affect the quality of asphalt. In this context, ASPARi developed the Process Quality Improvement (PQi) framework that aims to provide better guidance for construction operations to transit from the standard support systems. The focus of this research is the cooling curve station of the PQi framework which has some limitations to be addressed. Currently, the management of cooling curve data lacks adequate infrastructure, leading to ad hoc practices and fragmented processes. The proposed automated data infrastructure aims to overcome these limitations and provide a more organized and streamlined approach. Therefore, this project aims to enhance the quality of data management in the PQi framework. This was done by developing and providing ASPARi with an automated data infrastructure to analyse the asphalt cooling behavior and its curve. It includes strategies for data collection, such as identifying the parameters and information that must be collected before and during construction, determining suitable and standard equipment, and implementing appropriate distribution and labeling of sensors. Also, a new database to store the collected information. Moreover, a data preparation pipeline was designed using Extract, Transform, and Load (ETL) tools and various data cleansing methods to ensure the information's quality. Finally, a conceptual model was created. It estimates the asphalt cooling curve using the information from the database and polynomial regression. The final product was subjected to expert opinion for validation and verification. This allowed the assessment of the developed data architecture and contributed valuable insights and recommendations for future research. The overall acceptance of methods, theories, completeness, and strategies was good.
Item Type:Essay (Bachelor)
Faculty:ET: Engineering Technology
Programme:Civil Engineering BSc (56952)
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