Real-time data sensing and digital twin model development for pavement material mixing: enhancing workability and optimisation

International Journal of Pavement Engineering, vol. 25

Abstract

An essential aspect of pavement construction sustainability is its low-energy consumption and emissions. The study of pavement materials workability tests holds significant importance in terms of achieving well-mixed conditions with low-energy consumption. The complex components of the material and the uncertain kinematic behaviours of aggregates during mixing make this process challenging. And, few studies of the signal response of pavement materials have been found in the field of civil engineering. For this purpose, an accurate evaluation and monitoring approach for mixing are needed. In this paper, a wireless real-time sensing method is used to monitor the dynamic behaviour of aggregates during mixing. A 3D digital twin model, combining data-sensing techniques and numerical simulation, has been proposed for rapid identification of the mixing material. This model has been validated via a data-fusion algorithm. The application of this model makes a contribution to the data-intensive analysing jobs and decision-making tasks in pavement construction engineering.

Authors 6

1. Chonghui Wang

   Aston University

   Affiliation as printed

   College of Engineering and Physical Sciences, Aston University, Birmingham, UK

2. Xiaodong Zhou
   Affiliation as printed

   Rizhao Municipal Transport Bureau, Rizhao, People’s Republic of China

   Rizhao Municipal Transport Bureau, Rizhao, People's Republic of China

3. Yuqing Zhang corresponding

   Southeast University

   Affiliation as printed

   School of Transportation, Southeast University, Nanjing, People’s Republic of China

   School of Transportation, Southeast University, Nanjing, People's Republic of China

4. Hainian Wang

   Chang'an University

   Affiliation as printed

   School of Highway, Chang’an University, Xi’an, People’s Republic of China

   School of Highway, Chang'an University, Xi'an, People's Republic of China

5. Markus Oeser

   Federal Highway and Transport Research Institute

   Affiliation as printed

   Federal Highway Research Institute, Bergisch Gladbach, Germany

6. Pengfei Liu Aachen Institute of Highway Engineering

   RWTH Aachen University

   Affiliation as printed

   Institute of Highway Engineering, RWTH Aachen University, Aachen, Germany