Graphic illustration for Electromagnetic Detection & Identification Of Concrete Cracking In Highway Bridges. Overview of the proposed research.

Overview of the proposed research.

PI: Tzuyang Yu (UMass Lowell)
Institution: University of Massachusetts Lowell (UML)
PI Email: Tzuyang_Yu@uml.edu
PI Phone: 978-934-2288

Background/Need:

Concrete highway bridges (reinforced and prestressed) are a major component in the U.S. transportation infrastructure. Their deterioration can occur in various damage mechanisms including:

  1. mechanical (e.g., abrasion, erosion, cavitation),
  2. physical (e.g., freeze-thaw);
  3. chemical (e.g., alkali-silica reaction (ASR), alkali-aggregate reaction (AAR), carbonation), and
  4. electrochemical (e.g., steel rebars corrosion).

As a result, concrete cracks and further damages are accelerated. One of the most critical challenges for the durability and life expansion of concrete highway bridges is crack identification. This is because the cracking of concrete structures can be attributed to one or many damage mechanisms. Detection and identification of surface and subsurface cracks in concrete bridges can provide state DOTs with critical information for repair and rehabilitation.

The problem we are trying to solve is the structural assessment of aging concrete bridges (reinforced and pre-stressed) in New England, targeting at concrete cracking and degradation (e.g., carbonation, alkali-silica reaction). The problem is important because that the integrity of concrete cover indicates not only mechanical strength of the cross section but also the level of protection for steel corrosion. Concrete cracking and steel corrosion can occur to any component in concrete bridges. We propose to:

  1. conduct field radar inspection (using ground penetrating radar (GPR) and synthetic aperture radar (SAR), and impact-echo) for 2D and 3D radar imaging and to
  2. develop a damage detection model for predicting the level of structural damage for concrete bridges. Fig. 1 provides an overview of the proposed research.

Objectives:

This project aims to:

  • Develop a data driven field inspection procedure for concrete cracking on concrete bridges
  • Develop a radar signature database of concrete cracking at various levels such that bridge engineers can use it for efficient assessment of concrete cracking in the field.
Experimental set up of SAR imaging

Updates:

December 30, 2019: We have conducted laboratory tests and found that various parameters extracted from synthetic aperture radar (SAR) images can be used to estimate the width, length, and depth of concrete cracks of regular geometry.

Concrete specimens with artificial cracks

The findings developed from Tasks 1 and 2 will help us to complete the development of an EM database and to better characterize actual concrete cracks in the field.

A 1.6 GHz GPR and concrete specimens with artificially cracks

March 31, 2020: The right figure shows the 1.6 GHz GPR and the B-scan GPR images of intact and artificially-cracked concrete panels. In the figure, it is clear that the presence of an artificial crack on the surface of concrete panels can be detected by the presence of reduced GPR amplitude at the crack location. It is also observed that the change of crack geometry has led to different scattering patterns of hyperbola in the GPR B-scan images, suggesting the promising use of GPR for quantifying crack geometry.

Processed GPR B-scan images and hyperbolic pattern of crack

The right figure (a) shows a series of processed GPR B-scan images for background subtraction, consisting of the following two steps:

  1. development of a representative background signature from the intact specimen CNI, and
  2. removal of background signature in the GPR images of specimens CNC, CNCD, and CNCW to reveal the hyperbolic pattern of a crack.

Figure (b) shows the hyperbolic patterns of surface cracks with different geometries.

GPR B-scan of crack obtained from the vertical crack on bridge

We also conducted field GPR tests on a concrete bridge with the result shown in the right figure. In the figure, our conclusions on the reduced GPR amplitude and an induced hyperbolic pattern representing the presence of a crack are confirmed.

  • Assoc. Professor TzuYang Yu, Ph.D., Department of Civil and Environmental Engineering

  • Ahmed AlZeyadi, Doctoral Candidate in Structural Engineering

  • Harsh Gandhi, Master's Student in Structural Engineering

  • Sanjana Vinayaka, Doctoral Student in Structural Engineering

Publications

  • Alzeyadi, A., T. Yu (2018), Characterization of Moisture Content in a Concrete Panel using Synthetic Aperture Radar Images, Journal of Aerospace Engineering, ASCE, 32 (1); doi.org/10.1061/(ASCE)AS.1943-5525.0000945
  • Alzeyadi, A., T. Yu (2018), Moisture determination of concrete panel using SAR imaging and the K-R-I transform, Construction and Building Materials 184; 351-360, doi:10.106/j.conbuildmat.2018.06.209
  • Alzeyadi, A., T. Yu (2018), Characterization of the range effect in synthetic aperture radar images of concrete specimens for width estimation, In: Proc SPIE Smart Structures/NDE, Mar. 4-8, Denver, CO, doi: 10.1117/12.2294540
  • Ingemi, C.M., J. OwusuTwumasi, T. Yu (2018), Electromagnetic characterization of white spruce at different moisture contents using synthetic aperture radar imaging, In: Proc SPIE Smart Structures/NDE, Mar. 4-8, Denver, CO, doi: 10.1117/12.2296343
  • Hu, J., A. Alzeyadi, T. Yu (2018), Characterization of dielectric constant of masonry wall using synthetic aperture radar imaging, In: Proc SPIE Smart Structures/NDE, vol. 10971, Mar. 4-8, Denver, CO, doi: 10.1117/12.2514068
  • Tang, Q., J. Hu, T. Yu (2019), Electromagnetic evaluation of brick specimens using synthetic aperture radar imaging, NDT&E International, 104; 98-107, doi:10.1016/j.ndteint.2019.04.006
  • Ingemi, C., T. Yu (2019), Detection of grain angle in wood specimens using synthetic aperture radar imaging, In: Proc SPIE Smart Structures/NDE, vol. 10971, Mar. 4-8, Denver, CO, doi: 10.1117/12.2513972
  • Ingemi, C., T. Yu (2019), Estimating the density of wood specimens using synthetic aperture radar imaging, In: Proc SPIE Smart Structures/NDE, vol. 10971, Mar. 4-8, Denver, CO, doi: 10.1117/12.2514354
  • Alzeyadi, A., J. Hu, T. Yu (2019), Electromagnetic sensing of a subsurface metallic object at different depths, In: Proc SPIE Smart Structures/NDE, vol. 10971, Mar. 4-8, Denver, CO, doi: 10.1117/12.2514460
  • Alzeyadi, A., J. Hu, T. Yu (2019), Detecting underground metallic objects of different sizes using synthetic aperture radar, In: Proc SPIE Smart Structures/NDE, vol. 10971, Mar. 4-8, Denver, CO, doi: 10.1117/12.2514480
  • Alzeyadi, A., T. Yu (2020), Subsurface characterization of moisture content and water-to-cement ratio of concrete specimens using remote synthetic aperture radar imaging, Journal of Applied Remote Sensing, 14 (2); 024520-1-17, doi: 10.1117/1.JRS.14.024520
  • Yu, T., S. Vinayaka (2020), Quantification of surface crack depth in concrete panels using 1.6 GHz GPR images, In: Proc SPIE Smart Structures/NDE, vol. 11380, April 27~May 8, doi: 10.1117/12.2558952
  • Alzeyadi, A., T. Yu (2020), Remote moisture quantification of concrete using SAR images and the K-R-I transform, In: Proc SPIE Smart Structures/NDE, vol. 1159207, March 22~26, doi: 10.1117/12.2582429
  • Alzeyadi, A., T. Yu (2021), Determination of critical contour area in SAR images of concrete for subsurface moisture sensing, In: Proc SPIE Smart Structures/NDE, vol. 1159114, March 22~26, doi: 10.1117/12.2582431
  • T. Yu, A. Sinha, J. Wei, R. Bates, T. Dhant, H. Gandhi (2021), Short-term mechanical strength prediction of ultra-high performance concrete using noncontact synthetic aperture radar imaging, In: Proc SPIE Smart Structures/NDE, vol. 1159207, March 22~26, doi: 10.1117/12.2584809