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This proposal outlines the utilization of canines for the detection of corrosion within bridges and other large concrete structures.
Canines have been reliably used for the detection of clandestine substances for several years. These substances typically include explosives and narcotics but have also included more unorthodox items such as microbes, diseases and mass storage devices. The broad range of substances detected by canines stems from the versatility of canines as a result of their high sensitivity and specificity towards identifying volatile organic compounds (VOCs), their relative ease of use and the rapid trainability of canines for the detection of new substances most recently we have demonstrated that canines can be reliably trained to detect COVID-19 in persons with over 97% accuracy which exceeds most current methods including PCR and is completed in seconds versus tens of minutes to days for current methods.
Corrosion is the natural chemical oxidation of a metal into a more stable state. This slow chemical reaction causes the property of the metal to change, making it more brittle, losing tensile strength typically referred to as metal fatigue. The more corroded the metal, the weaker it becomes creating a structural issue in large engineering installations. Monitoring of corrosion may be done in several ways, the most common being through magnetic flux and acoustic emission measurements, however these are not very precise, and the equipment and expertise needed for the detection is expensive. The chemical reactions that occur during metal corrosion may generate changes in the volatile organic compounds (VOCs) above and around the corroded material, thereby allowing a well-trained canine to detect these changes and produce an alert. This proposal outlines the steps to determine what these changes are around a corroded material at different stages and also whether or not these changes can be reliably detected by a well-trained canine, thereby indicating when corrosion has occurred despite the fact that the corroded metal is completely hidden by being encased in concrete or other media.
The United States contains an inventory of roadways and bridges that have an age of over 50 years. It has been reported that of the over 600,000 bridges in the United States, 7.5% of which are in poor condition5. Meaning that they suffer from heavy wear or corrosion that warrants significant repair. However, the identification of many of these
deficient areas on these large structures is difficult for several reasons, the most common being the tight access areas available for inspection. Several techniques have been developed to facilitate identification of invisible areas of deterioration, however all have significant drawbacks. This proposal will outline the use of canines to overcome these drawbacks to create an efficient and reliable detection method for corrosion.
It is expected that this proposal will identify the proper techniques required to effectively and rapidly train a canine to detect corrosion and apply this detection capability to actual concrete structures. Figures of merit such as accuracy of detection and comparisons to current schemes such as magnetic flux will also be reported.
This proposal will be divided into three consecutive tasks that will first investigate the volatile organic compounds (VOCs) produced from corroded materials, imprint, or train canines to detect corroded materials and their VOCs and finally, field test the imprinted canines to determine figures of merit. A fourth task will be implemented to disseminate findings, this task will be done in conjunction with previous tasks as data is generated:
Task 1: Identification of Volatile Organic Compounds from Corroded Steel
This first task will be to utilize analytical instruments to identify the volatile organic compounds associated with corrosion.
Task 2: Utilization of Target Corroded Steel for canine imprinting
The appropriate VOCs identified from Task 1 will be selected and utilized to imprint on a canine. The canine(s) selected for this task will be previously trained to detect a patented compound called a Universal Detector Calibrant (UDC), a developed and patented device from FIU within the Global Forensic and Justice Center (GFJC).
Task 3: Validation of corrosion detection using trained canines
This final task will test the ability of the trained canines from task 2 in detecting corrosion from encased concrete structures.
Task 4: Data Dissemination and Reporting
This task unlike the previous three, is expected to be done in parallel with other tasks as data is generated. The first opportunity will be the dissemination of the data from the VOCs identified, this will be significant and the first of its kind.
Principal Investigator: Dr. Kenneth G. Furton
Post Doctoral Fellow: Dr. Kelvin Frank