Next Article in Journal
Estimation of Long-Term Surface Downward Longwave Radiation over the Global Land from 2000 to 2018
Next Article in Special Issue
Bridge Foundation River Scour and Infill Characterisation Using Water-Penetrating Radar
Previous Article in Journal
Comparing PlanetScope to Landsat-8 and Sentinel-2 for Sensing Water Quality in Reservoirs in Agricultural Watersheds
Previous Article in Special Issue
Quantification of the Mechanized Ballast Cleaning Process Efficiency Using GPR Technology
Article

Identifying Spatial and Temporal Variations in Concrete Bridges with Ground Penetrating Radar Attributes

1
Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ 08540, USA
2
Department of Civil and Environmental Engineering, New Mexico Institute of Mining and Technology, Socorro, NM 87801, USA
*
Author to whom correspondence should be addressed.
Academic Editors: Mercedes Solla, Vega Perez-Gracia and Simona Fontul
Remote Sens. 2021, 13(9), 1846; https://doi.org/10.3390/rs13091846
Received: 30 March 2021 / Revised: 26 April 2021 / Accepted: 30 April 2021 / Published: 9 May 2021
(This article belongs to the Special Issue Trends in GPR and Other NDTs for Transport Infrastructure Assessment)
Estimating variations in material properties over space and time is essential for the purposes of structural health monitoring (SHM), mandated inspection, and insurance of civil infrastructure. Properties such as compressive strength evolve over time and are reflective of the overall condition of the aging infrastructure. Concrete structures pose an additional challenge due to the inherent spatial variability of material properties over large length scales. In recent years, nondestructive approaches such as rebound hammer and ultrasonic velocity have been used to determine the in situ material properties of concrete with a focus on the compressive strength. However, these methods require personnel expertise, careful data collection, and high investment. This paper presents a novel approach using ground penetrating radar (GPR) to estimate the variability of in situ material properties over time and space for assessment of concrete bridges. The results show that attributes (or features) of the GPR data such as raw average amplitudes can be used to identify differences in compressive strength across the deck of a concrete bridge. Attributes such as instantaneous amplitudes and intensity of reflected waves are useful in predicting the material properties such as compressive strength, porosity, and density. For compressive strength, one alternative approach of the Maturity Index (MI) was used to estimate the present values and compare with GPR estimated values. The results show that GPR attributes could be successfully used for identifying spatial and temporal variation of concrete properties. Finally, discussions are presented regarding their suitability and limitations for field applications. View Full-Text
Keywords: structural health monitoring; ground penetrating radar; attribute analysis; in situ material property; machine learning; maturity method structural health monitoring; ground penetrating radar; attribute analysis; in situ material property; machine learning; maturity method
Show Figures

Graphical abstract

MDPI and ACS Style

Kumar, V.; Morris, I.M.; Lopez, S.A.; Glisic, B. Identifying Spatial and Temporal Variations in Concrete Bridges with Ground Penetrating Radar Attributes. Remote Sens. 2021, 13, 1846. https://doi.org/10.3390/rs13091846

AMA Style

Kumar V, Morris IM, Lopez SA, Glisic B. Identifying Spatial and Temporal Variations in Concrete Bridges with Ground Penetrating Radar Attributes. Remote Sensing. 2021; 13(9):1846. https://doi.org/10.3390/rs13091846

Chicago/Turabian Style

Kumar, Vivek, Isabel M. Morris, Santiago A. Lopez, and Branko Glisic. 2021. "Identifying Spatial and Temporal Variations in Concrete Bridges with Ground Penetrating Radar Attributes" Remote Sensing 13, no. 9: 1846. https://doi.org/10.3390/rs13091846

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop