Accelerated Repair of Corroded Bridge Steel Members using Cold Spray Additive Manufacturing

Project Information

Link to Latest Report: Coming Soon


Corrosion is one of the leading causes of deterioration of steel members, causing a wide range of consequences such as section weakening, section losses, and sudden failures. Lack of action toward detecting corrosion, quantifying the impact of corrosion, and the application of repair/preservation techniques can burden both infrastructure owners and users, especially those in rural and remote areas. The research team proposes an approach to evaluate corrosion damage in structural components and repair through cold spray additive manufacturing (CSAM). The objectives of the proposed research project are to (1) correlate corrosion with 3D-point cloud data from LiDAR scanners to quantify the extent and impact of corrosion on bridge elements, (2) develop robust and accelerated repair and upgrade techniques through CSAM, and (3) develop a robust implementation plan for rapid detection, evaluation of corrosion, and accelerated repair in steel bridges that will benefit state DOTs. Accurate detection and evaluation of the extent and impact of corrosion on steel members will allow infrastructure owners to manage resources more efficiently. Tools to preserve, rehabilitate, and repair steel members and structures will result in significant savings in materials, labor, and other construction costs throughout the life cycle of a bridge. The proposed project addresses corrosion of steel infrastructure, which contributes to the 2022-2026 U.S. DOT strategic goal of “Economic Strength and Global Competitiveness” and its
key performance indicator assigned to FHWA to “Fix the 10 most economically significant bridges and repair of 10,000 most in need smaller bridges.” The project also contributes to the research category proposed by IBT/ABC-UTC including (1) Research Category B – Accelerated Repair and Upgrade of Existing Bridges and (2) Research Category C – Advanced Bridge Technologies, especially additive manufacturing.


The proposed project objectives include:

  • Develop 3D-point cloud protocol using LiDAR scanners to assess the section loss of corroded steel elements. This objective will be achieved by fabricating steel dogbone coupons in accordance with ASTM standards, subject them to different levels of corrosion (ASTM B117-19), and sandblast the corroded coupons for corrosion removal. The coupons (corroded and uncorroded) will be scanned and tested to develop correlation between section loss, 3D-point cloud data, and remaining tensile strength.
  • Develop CSAM techniques capable of successful repair of corroded steel elements. This objective will be achieved by studying parameters associated with CSAM such as mean particle velocities, particle sizes, operating temperature, and substrate condition, among others, to maximize bonding between the steel substrate and sprayed particles.
  • Verify successful repair technique through experimental testing.This objective will be achieved using experimental testing (tension testing, fatigue testing, and additional corrosion testing) to evaluate the effectiveness of proposed techniques for either repair or protection of steel subject to corrosive environments.


The proposed project includes several tasks

  • Task 1: Literature Search
    • A detailed literature review will be conducted. Topics like cold-spray technologies and
      application for corrosion repair will be covered.
  • Task 2: Fabrication of test specimens
    • Coupon tests will be used to characterize the correlation between visual signs of damage and the actual amount of corrosion on test plates, as well as characterize the effect of corrosion damage on the mechanical behavior of corroded material. The use of an ultrasonic thickness gage will be considered for measurements, particularly in early stages of corrosion. Lessons learned in this stage will be utilized when corroding laboratory-based structural members.
  • Task 3: 3D-point cloud protocol using LiDAR scanners to assess the section loss of corroded steel specimens
    • Once coupons are corroded, the research team will scan and image the plates, measure the plates for thickness and weight, and then cut dogbone-style tensile coupons using a waterjet. Tensile tests of the corroded and control dogbone coupons will establish correlations between the level of corrosion and changes in mechanical behavior, specifically quantified by yield strength, ultimate strength and strain to failure.
  • Task 4: CSAM techniques capable for repairing corroded steel.
    • Many control parameters for CSAM, such as temperature, pressure, thickness, and particle size
      (all of which affect the erosion-corrosion (E-C) resistance and physical/mechanical deposit properties) will be studied to ensure sufficient bond between the steel substrate and the sprayed particles. Unlike superficial coating approaches, the research seeks to rebuild the lost section due to corrosion by utilizing CSAM. Evaluation of the effectiveness of the proposed CSAM technique will be conducted in Task 5.
  • Task 5: Verification through experimental testing.
    • Specimens obtained from Task 2 (uncorroded and corroded steel coupons) and Task 4 (additively repaired coupons using CSAM techniques) will be tested. The laboratory testing will
      include (1) conducting tensile testing to develop stress-strain relationships of all developed coupons; (2) conducting high-cycle fatigue testing informed by AASHTO-LRFD requirements;
      and (3) exposing the additively repaired coupons to additional time in a corrosive environment to evaluate the corrosion protection given by the restorative treatment applied in Task 4.
  • Task 6: Final Report, final deliverables, and recommendation for next phase of study.
    • In this task, the research team will develop a final report in compliance with Section 508, journal article, and recommendation for next phase of study or future studies.

Research Team:
Principal Investigator: Islam M. Mantawy, Ph.D., P.E.
Co-Principal Investigator: Adriana Trias Blanco, Ph.D. , William Riddell, Ph.D. ,Mac Haas, Ph.D. ,Joseph Stanzione, Ph.D.