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

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 th...

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Main Authors: Vivek Kumar, Isabel M. Morris, Santiago A. Lopez, Branko Glisic
Format: Article
Language:English
Published: MDPI AG 2021-05-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/13/9/1846
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author Vivek Kumar
Isabel M. Morris
Santiago A. Lopez
Branko Glisic
author_facet Vivek Kumar
Isabel M. Morris
Santiago A. Lopez
Branko Glisic
author_sort Vivek Kumar
collection DOAJ
description 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.
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spelling doaj.art-0f0b8266a0e34a0fab6682964cb35e3e2023-11-21T18:53:32ZengMDPI AGRemote Sensing2072-42922021-05-01139184610.3390/rs13091846Identifying Spatial and Temporal Variations in Concrete Bridges with Ground Penetrating Radar AttributesVivek Kumar0Isabel M. Morris1Santiago A. Lopez2Branko Glisic3Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ 08540, USADepartment of Civil and Environmental Engineering, New Mexico Institute of Mining and Technology, Socorro, NM 87801, USADepartment of Civil and Environmental Engineering, New Mexico Institute of Mining and Technology, Socorro, NM 87801, USADepartment of Civil and Environmental Engineering, Princeton University, Princeton, NJ 08540, USAEstimating 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.https://www.mdpi.com/2072-4292/13/9/1846structural health monitoringground penetrating radarattribute analysisin situ material propertymachine learningmaturity method
spellingShingle Vivek Kumar
Isabel M. Morris
Santiago A. Lopez
Branko Glisic
Identifying Spatial and Temporal Variations in Concrete Bridges with Ground Penetrating Radar Attributes
Remote Sensing
structural health monitoring
ground penetrating radar
attribute analysis
in situ material property
machine learning
maturity method
title Identifying Spatial and Temporal Variations in Concrete Bridges with Ground Penetrating Radar Attributes
title_full Identifying Spatial and Temporal Variations in Concrete Bridges with Ground Penetrating Radar Attributes
title_fullStr Identifying Spatial and Temporal Variations in Concrete Bridges with Ground Penetrating Radar Attributes
title_full_unstemmed Identifying Spatial and Temporal Variations in Concrete Bridges with Ground Penetrating Radar Attributes
title_short Identifying Spatial and Temporal Variations in Concrete Bridges with Ground Penetrating Radar Attributes
title_sort identifying spatial and temporal variations in concrete bridges with ground penetrating radar attributes
topic structural health monitoring
ground penetrating radar
attribute analysis
in situ material property
machine learning
maturity method
url https://www.mdpi.com/2072-4292/13/9/1846
work_keys_str_mv AT vivekkumar identifyingspatialandtemporalvariationsinconcretebridgeswithgroundpenetratingradarattributes
AT isabelmmorris identifyingspatialandtemporalvariationsinconcretebridgeswithgroundpenetratingradarattributes
AT santiagoalopez identifyingspatialandtemporalvariationsinconcretebridgeswithgroundpenetratingradarattributes
AT brankoglisic identifyingspatialandtemporalvariationsinconcretebridgeswithgroundpenetratingradarattributes