The sensor system (currently under development) will reduce life-cycle costs for construction and maintenance of concrete structures by making concrete materials more durable and resilient against ingress of saltwater and other aggressive ions.
The use of the sensor system in cylindrical concrete samples will improve concrete mix design and construction quality control to produce concrete materials that are less permeable to aggressive ions, which can corrode steel reinforcement and accelerate deterioration.
The sensor can also be embedded inside concrete structures for monitoring changes in chloride content and detection of aggressive ions in a timely manner to preserve and prolong service life.
The US Department of Transportation (DOT) Federal Highway Administration (FHWA) sponsored a Small Business Innovation Research (SBIR) project for development of a commercially viable concrete pore solution resistivity (PSR) sensor, conducted by the Callentis Consulting Group in collaboration with Penn State University. In line with the Performance Engineered Mixtures (PEM) initiative, a concrete’s Formation Factor is used to assess its transport properties and as an indicator of long-term durability and resilience against ingress of aggressive ions. The Formation Factor has been shown to be an important parameter in service-life models to predict permeability of concrete, and chloride ion penetration that can cause corrosion of concrete and its reinforcing steel. In AASHTO R101-22, the Formation Factor is defined as the ratio of the electrical resistivity of the bulk concrete mixture over the resistivity of the concrete pore solution. The AASHTO TP 119 and the equivalent ASTM C1876 standards were developed to measure the bulk concrete resistivity, and AASHTO T 358 to measure surface resistivity of the concrete mixture. However, there are no standard equipment or test methods for non-destructive measurement of the pore solution resistivity, and the only available methods involve labor-intensive laboratory extraction of the pore solution.
AASHTO TP 119:
AASHTO T 358:
In-situ measurement of the electrical resistivity of the pore solution along with the resistivity of bulk concrete allows for qualification of concrete mix designs before construction, quality control (QC) and quality acceptance (QA) of concrete batches placed during construction, and service-life prediction of vital concrete infrastructure such as bridges, pavements, and marine structures. Additionally, the PSR sensor can be embedded in structures and used for long-term health monitoring to evaluate changes in the chloride content inside concrete over time. Finally, the sensor’s output can be translated to concrete’s pH and used for evaluation and mitigation of the risk of alkali-silica reaction (ASR) in concrete containing reactive aggregates.
The technology under development in this project is a sensor system that allows in-situ measurement of concrete’s PSR with an accuracy of 15% or better compared to laboratory measurements. The sensor system includes the sensor assembly that is embedded inside concrete and a measuring device to interrogate the sensor. The sensor assembly includes the sensor matrix, attached insulated electronic components, and a placement mechanism. The sensor matrix is made of a custom-designed nano-porous body. The sensor placement mechanism is designed in a way that would be easily embedded in concrete cylinders or structures. The mobile measurement device is a low-cost consumer-level product. The overall sensor system and the simple data post-processing is designed for seamless application by field and lab technicians, ideally along with the bulk or surface resistivity measurements.
Technology Readiness Levels (TRL)
Phase I: Proof of Concept (July to December 2021) TRL-2 to TRL-3
The Phase I project explored candidate body (matrix) materials for the sensor, manufacturing techniques, optimum sensor geometry and packaging, and the best methods for reading and measuring the sensor output. Phase I also explored the costs, material availability, manufacturability, scale-up, marketability, technology transfer, and industry implementation of the proposed sensor system. Phase I output was a proof-of-concept report summarizing the above and offering two best prototype designs to be produced and tested in Phase II. The project team has also filed a patent for the developed technology.
Phase II: Technology Development (July 2022 to June 2024) TRL-3 to TRL-8
Phase II will include the development and demonstration of market-ready prototypes for user testing and commercialization. Phase II will perform further refinement of the technology, design, and fabrication of the sensor prototypes. Phase II will also include experimental verification of the technology, including third-party testing (by the FHWA and several State DOTs), precision and bias evaluation, and development of a user’s guide and draft standard test method to facilitate effective implementation of the PSR sensor.
The Callentis-PennState team have filed for a patent regarding the developed technology, which is pending. The displayed abstract schematic is showing a sensor embedded in a cylindrical concrete sample that can be used for qualification of concrete mix designs before construction, quality control (QC) and quality acceptance (QA) of concrete batches placed during construction. Another sensor system is designed for embedding inside concrete structures for long-term health monitoring to evaluate changes in the chloride content inside concrete over time.
Callentis Consulting Group is a small research, development, and consulting company, focused on integrating the latest proven technologies into existing business processes to create growth and opportunity. With extensive background in engineering and computational science, our team offers software and hardware development for a variety of science and technology applications, and diagnostic support for data-driven decision processes.
Meet the USDOT SBIR project leadership team.
Founder and President
Dr. Drach has over ten years of experience in numerical modeling techniques, applied statistics, data science, custom software and hardware development, and renewable energy engineering. He has published over 40 peer-reviewed articles, presented at over 20 international conferences, and gave 4 invited talks. He did his postdoctoral training in Computational Engineering and Sciences at the University of Texas at Austin. He holds a PhD in Mechanical Engineering from the University of New Hampshire.
Dr. Kostiantyn Vasylevskyi has over six years of experience in computational mechanics, micromechanics, finite element methods, and data science applications in engineering. He specializes in numerical modeling of composite materials used in aerospace and automotive industries, micromechanical analysis of heterogeneous solid materials, and process modeling of biomedical polymers production.
He has published over 15 peer-reviewed articles and presented at 5 international conferences. He holds a PhD in Mechanical Engineering from the University of New Hampshire.
Dr. Kargah-Ostadi has over ten years of experience in pavement engineering, transportation infrastructure asset management, applied statistics, data science, machine learning, and evolutionary computation. He has published over 15 peer-reviewed articles, and presented at over 20 conferences, workshops, and webinars. He holds a PhD in Civil Engineering and a doctoral minor in Computational Science from Penn State University. He is a registered Professional Engineer and a certified Project Management Professional.