@inproceedings{90266ccf45754336a4c89c0c2635f396,
title = "Damage progression identification in asphalt concrete pavements: A smart self-powered sensing approach",
abstract = "This paper develops a novel approach for damage detection in Asphalt Concrete (AC) pavements using a new class of self-powered Piezo-Floating-Gate (PFG) wireless sensors. The sensor operates using the energy harvested from the host structure via a piezoelectric transducer. The size of a unit is only limited by the size of the transducer and it operates in the nanowatt scale (∼80 nW). Different Finite Element (FE) models are developed to obtain the structural response of the structure. A three-point bending test is performed on an AC beam and damage is defined by making notches with different lengths at the bottom of the specimen. An experimental study is conducted to verify the numerical results. The results indicate that bottom-up cracking in AC pavements can be monitored by interpreting the data generated from the self-powered sensor.",
author = "K. Aono and S. Chakrabartty and H. Hasni and K. Chatti and N. Lajnef",
note = "Publisher Copyright: {\textcopyright} 2018 Taylor & Francis Group, London.; International Conference on Advances in Materials and Pavement Performance Prediction, AM3P 2018 ; Conference date: 16-04-2018 Through 18-04-2018",
year = "2018",
language = "English",
isbn = "9781138313095",
series = "Advances in Materials and Pavement Performance Prediction - Proceedings of the International AM3P Conference, 2018",
publisher = "CRC Press/Balkema",
pages = "71--74",
editor = "Eyad Masad and Ilaria Menapace and Amit Bhasin and Tom Scarpas and Anupam Kumar",
booktitle = "Advances in Materials and Pavement Performance Prediction - Proceedings of the International AM3P Conference, 2018",
}